The Effectiveness of Electronic Word-Of-Mouth in Attracting International Students to Enrol Into Private Universities in Malaysia

THE EFFECTIVENESS OF ELECTRONIC WORD-OF-MOUTH IN ATTRACTING INTERNATIONAL STUDENTS TO ENROL INTO PRIVATE UNIVERSITIES IN MALAYSIA

VIJAYESVARAN A/L ARUMUGAM

UNIVERSITI SAINS MALAYSIA 2018

THE EFFECTIVENESS OF ELECTRONIC WORD-OF-MOUTH IN ATTRACTING INTERNATIONAL STUDENTS TO ENROL INTO PRIVATE UNIVERSITIES IN MALAYSIA

VIJAYESVARAN A/L ARUMUGAM

Thesis submitted in fulfilment of the requirements

for the Degree of

Doctor of Philosophy

September 2018

ACKNOWLEDGEMENT

The research journey is like a beginning without an end. It takes one through a multitude of emotions – of hope, excitement, despair but finally of accomplishment. The successful completion of this thesis was made possible through the invaluable contribution of a number of people. To say ―thank you‖ to all of you is not even enough to express my gratitude. I would like to extend my greatest appreciation to all of them as I never could have carried on towards the end alone.

To my supervisor, Associate Professor Dr. Azizah Omar, I express my heartfelt gratefulness for her guidance and support that I believed I learned from the best. It is with immersed gratitude that I acknowledge her patience and help in the completion of my thesis. It was a great privilege and honour to work and study under her guidance. I also wish to extend my special thanks to Professor T. Ramayah for his constructive inputs in many areas of my research and in pointing out to me the best contributions that I can make through this research. My sincere thanks and appreciation also goes to all the other lectures and staffs of School of Management for their selfless kindness, warmth, and helps during my study in Universiti Sains

Malaysia.

I would not have been able to embark on this journey if not for the financial assistance from Ministry of Higher Education (MOHE); I am especially grateful to them for giving me this golden opportunity. To the respondents (international students) from private universities, I am indeed indebted to them for their support in the difficult task of data collection. Special thanks also to private universities who permitted me to collect data from their premises.

To all my friends in USM, thank you for your understanding and encouragement in my many, many moments of crisis and for the beautiful friendship;

Dr. Norzie, Dr. Wan Normila, Dr. Ying San, Dr. Iman, Samsudeen, Pravina, Nor

Bayaah, Charlie and others whose names I unintentionally left out, you are always on my mind. Thanks for your presence in my life.

Most importantly, I would like to thank my family for all their love and encouragement. I deeply thank my parents, Mr.Arumugam Rengasamy and

Mrs.Vijayal Johny Grey for their unconditional trust, timely encouragement, and endless patience. It was their love that raised me up again when I got weary. To my brothers, sisters, sisters in law and brothers in law, thanks for your concern and words of encouragement.

Last but not least, I would like to acknowledge the people who mean world to me; my wife and my daughter. To my ever supportive wife, Logavalli Balakrishnan, thank you for the undying love and support you have provided me and for believing in me that I can finish my thesis on time. You have been a valued companion throughout this journey, without your prayers, support, inspiration and motivation I would never have seen the end of this journey. I am just so grateful that I have you all this time. To my wonderful daughter, Shashmietha Vijayesvaran, thank you for bearing with me and my mood swings and being my greatest supporter.

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TABLE OF CONTENTS

ACKNOWLEDGEMENT ii TABLE OF CONTENTS iv LIST OF TABLES xi LIST OF FIGURES xiv LIST OF DIAGRAMS xvii LIST OF ABBREVIATIONS xviii ABSTRAK xx ABSTRACT xxiii

CHAPTER 1 – INTRODUCTION

1.0 Introduction 1 1.1 Background 1 1.2 Internet and Word-of-Mouth 3 1.3 Electronic Word-of-Mouth‘s Adoption Across Industries 7 1.4 Development of Higher Education Institution in Malaysia 11 1.5 Problem Statement 16 1.6 Research Objectives 22 1.7 Research Questions 23 1.8 Significance of the Study 24 1.8.1 Theoretical Contribution 24 1.8.2 Practical Contribution 26 1.9 Operationalisation of Key Terms 28 1.10 Organization of the Thesis 30 1.11 Chapter Summary 31

CHAPTER 2 – LITERATURE REVIEW

2.0 Introduction 32 2.1 International Students 32 2.2 International Students in Malaysia 35 2.3 Development of Private Higher Education Institutions in Malaysia 41 2.4 Theoretical Model of HEI Choice Process 45 2.5 International Students Enrolment Decision Making Process 53 2.6 The Information Search Process in Digital Environment 58 2.7 Transformation of Word-of-Mouth to Electronic Word-of-Mouth 60 2.7.1 Electronic Word-of-Mouth Channels 71 2.7.1(a) Facebook 71 2.7.1(b) Twitter 71 2.7.1(c) LinkedIn 72 2.7.1(d) YouTube 72 2.7.1(e) Google+ 73 2.7.1(f) Pinterest 74 2.7.1(g) Instagram 74 2.7.2 Effects of eWoM Across Industry 76 2.7.3 Effects of eWoM in Higher Education Industry 78 2.7.4 Electronic Word-of-Mouth and International Students Enrolment Decision 80 2.8 Information Orientation 82 2.9 Information Quality and Source Credibility 89 2.10 Information Usefulness 93 2.11 Underlying Theories 96 2.11.1 Theory Reasoned of Action (TRA) 96 2.11.2 Theory of Planned Behaviour (TPB) 98 2.11.3 Technology Acceptance Model (TAM) 100 2.11.4 Unified Theory of Acceptance and Use of Technology 107 2.11.5 Information Adoption Model 110 2.12 Conceptual Framework 114 2.13 Development of Hypotheses 118

2.13.1 Relationship between Country Image and Information Usefulness 118 2.13.2 Relationship between City Effect and Information Usefulness 119 2.13.3 Relationship between Higher Education Institution Image and Information Usefulness 121 2.13.4 Relationship Between Programme Evaluation and Information Usefulness 122 2.13.5 The Moderating Role of Information Quality 123 2.13.6 The Moderating Role of Source Credibility 126 2.13.7 The Mediating Role of Information Usefulness 128 2.14 Chapter Summary 131

CHAPTER 3 – RESEARCH METHODS

3.0 Introduction 132 3.1 Research Paradigm 132 3.1.1 Differences between Quantitative, Qualitative and Mixed Method Approach 135 3.1.2 Rationalisation for Paradigm Selection 137 3.2 Research Design 138 3.2.1 Population 141 3.2.2 Sampling Frame 142 3.2.3 Sampling Technique 147 3.2.4 Sampling Size 148 3.2.5 Unit of Analysis 149 3.3 Questionnaire Design 153 3.3.1 Construct Measurements 157 3.3.1(a) Screening Questions 157 3.3.1(b) Demographic Data 158 3.3.1(c) Country Image 159 3.3.1(d) City Effect 161 3.3.1(e) Institution Image 162 3.3.1(f) Programme Evaluation 165

3.3.1(g) Information Quality 168 3.3.1(h) Source Credibility 169 3.3.1(i) Information Usefulness 169 3.3.1(j) Enrolment Choice 171 3.4 Statistical Techniques 172 3.4.1 Measurement Model 175 3.4.1(a) Pre-Test 175 3.4.1(b) Pilot Test 176 3.4.1(b)(i) Validity 176 3.4.1(b)(ii) Reliability 177 3.4.2 Structural Model 177 3.4.2(a) Coefficient of Determination (R2) 178 3.4.2(b) Cross-Validated Redundancy (Q2) 178 3.4.2(c) Effect Size (f2) 178 3.4.2(d) Path Coefficients 179 3.5 Chapter Summary 180

CHAPTER 4 – FINDINGS

4.0 Introduction 181 4.1 Analysis of Survey Response 181 4.1.1 Goodness of Data 181 4.1.2 Response Rate 182 4.1.3 Test for Non-Response Bias 183 4.1.4 Profile of the Respondents 185 4.2 Missing Value Imputation 190 4.2.1 Common Method Variance 192 4.3 Goodness of Measure 192 4.3.1 Construct Validity 195 4.3.1(a)(i) Convergent Validity 200 4.3.1(a)(ii) Discriminant Validity 203 4.3.2 Reliability Analysis 206 4.4 Assessment of Structural Model 208 4.4.1 Mediating Effect 211

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4.4.1(a) Mediating Effect of Information Usefulness between Country Image and PrUni Enrolment Choice 211 4.4.1(b) Mediating Effect of Information Usefulness between City Effect and PrUni Enrolment Choice 213 4.4.1(c) Mediating Effect of Information Usefulness between Institution Image and PrUni Enrolment Choice 214 4.4.1(d) Mediating Effect of Information Usefulness between Programme Evaluation and PrUni Enrolment Choice 216 4.4.2 Moderating Effect 219 4.4.2(a) Information Quality as a Moderator in the Relationship between Country Image and Information Usefulness 220 4.4.2(b) Information Quality as a Moderator in the Relationship between City Effect and Information Usefulness 221 4.4.2(c) Information Quality as a Moderator in the Relationship between Institution Image and Information Usefulness 224 4.4.2(d) Information Quality as a Moderator in the Relationship between Programme Evaluation and Information Usefulness 226 4.4.2(e) Source Credibility as a Moderator in the Relationship between Country Image and Information Usefulness 229 4.4.2(f) Source Credibility as a Moderator in the Relationship between City Effect and Information Usefulness 231 4.4.2(g) Source Credibility as a Moderator in the Relationship between Institution Image and Information Usefulness 234

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4.4.2(h) Source Credibility as a Moderator in the Relationship between Programme Evaluation and Information Usefulness 235 4.4.3 Summary of Hypotheses Testing 240 4.4.4 Analysing Predictive Relevance (Q2) 242 4.4.5 Goodness of Fit (GoF) 243 4.5 Summary 246

CHAPTER 5 – DISCUSSION AND CONCLUSION

5.0 Introduction 247 5.1 Recapitulation of the Study Findings 247 5.2 Discussion of Findings 253 5.2.1 The Relationship between Country Image, City Effect, Institution Image, Programme Evaluation on Information Usefulness towards PrUni Enrolment Choice by International Students 254 5.2.1(a) The Mediating Effect of Information Usefulness between Country Image and PrUni Enrolment Choice 254 5.2.1(b) The Mediating Effect of Information Usefulness between City Effect and PrUni Enrolment Choice 256 5.2.1(c) The Mediating Effect of Information Usefulness between Institution Image and PrUni Enrolment Choice 258 5.2.1(d) The Mediating Effect of Information Usefulness between Programme Evaluation and PrUni Enrolment Choice 260 5.2.2 Information Usefulness on PrUni Enrolment Choice by International Students 262

5.2.3 The Moderating Effect of Information Quality and Source Credibility towards the Relationship between Country Image, City Effect, Institution Image, Programme Evaluation and Information Usefulness 264 5.2.3(a) Moderating Effect of Information Quality 264 5.2.3(b) Moderating Effect of Source Credibility 270 5.3 Implications of Research 276 5.3.1 Theoretical Implication 276 5.3.2 Managerial Implication 279 5.4 Methodological Contributions 286 5.5 Limitation of Study 286 5.6 Recommendation for Future Study 288 5.7 Conclusion 291

REFERENCES 294 APPENDICES LIST OF PUBLICATIONS

LIST OF TABLES

Page

Table 1.1 Target Markets for Malaysian Education 15

Table 1.2 Summary of Information Searched by International 19 Students in HEI Choice Decision Making

Table 1.3 The Operationalisation Definition of Variables Used 28 in This Study

Table 2.1 Top Ten Countries of Origin of Foreign Students 37 (1975-2005)

Table 2.2 Internationals Students Enrolment in Public and 39 Private Higher Education Institution

Table 2.3 Malaysian International Students‘ Country of Origin 39

Table 2.4 Contribution of Private Education Sector to GDP at 42 Constant Prices

Table 2.5 Categorization of Private Higher Education 44 Institution

Table 2.6 Most Important Research Findings in the Main 62 Periods of Development of Word-of-Mouth Communication

Table 2.7 Summary of Past Literature on Country Image 84

Table 2.8 Summary of Past Literature on City Effect 85

Table 2.9 Summary of Past Literature on Higher Education 86 Institution Image Table 2.10 Summary of Past Literature on Programme 88 Evaluation

Table 2.11 Summary of Past Literature on Components of 90 Information Quality

Table 2.12 Summary of Past Literature on Components of 93 Source Credibility

Table 2.13 Summary of Past Literature on Components of 95 Information Usefulness

Table 2.14 Summary of Selected Studies Related to TAM 104

Table 2.15 The Comparison between Various Information 112 Science Models and Theories

Table 3.1 Difference between Quantitative, Qualitative and 136 Mixed Method Approach

Table 3.2 Advantages and Disadvantages of Data Collection 140

Table 3.3 Population Size 142

Table 3.4 Target Population of Private Universities 143

Table 3.5 Approved List of Private Universities to Recruit 143 International Students

Table 3.6 PrUni Selected Units by States 150

Table 3.7 Summary of Constructs for Each Item 154

Table 3.8 Screening Questions 158

Table 3.9 Country Image 159

Table 3.10 City Effect 161

Table 3.11 Institution Image 162

Table 3.12 Programme Evaluation 165

Table 3.13 Information Quality 168

Table 3.14 Source Credibility 169

Table 3.15 Information Usefulness 170

Table 3.16 Enrolment Choice 171

Table 3.17 Comparison of PLS-SEM and CB-SEM 173

Table 3.18 Review on PLS-SEM in the Perspective of Business 174

Table 4.1 PrUni Permission for Data Collection 182

Table 4.2 Response Rate 183

Table 4.3 Differences in the Major Variables by Early and 184 Late Responses

Table 4.4 Respondent Demographic Profile 187

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Table 4.5 Top eWoM Platform 189

Table 4.6 Top Information Category 189

Table 4.7 Loading and Cross Loading 196

Table 4.8 Results of Measurement Model 201

Table 4.9 Discriminant Validity of Constructs 204

Table 4.10 Result of Reliability Test 206

Table 4.11 Variance Explained (R2) 208

Table 4.12 Path Coefficient (Without Moderating and 209 Mediating Variables)

Table 4.13 Hypotheses Testing for Country Image-Information 212 Usefulness Indirect Effect

Table 4.14 Hypotheses Testing for City Effect-Information 214 Usefulness Indirect Effect

Table 4.15 Hypotheses Testing for Institution Image- 216 Information Usefulness Indirect Effect

Table 4.16 Hypotheses Testing for Programme Evaluation 217 Information Usefulness Indirect Effect

Table 4.17 Summary of Hypotheses Testing for Indirect Effect 218

Table 4.18 Summary of Hypotheses Testing for Moderating 240 Effect

Table 4.19 Summary of Hypotheses Testing 241

Table 4.20 Prediction Relevance of the Model 243

Table 4.21 Goodness-of-Fit Index 244

Table 5.1 A Summary of Hypotheses 252

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LIST OF FIGURES

Page

Figure 1.1 Consumers Trust in Advertising by Channel 7 2007 vs 2009

Figure 2.1 Percentage Distribution of Value Added by Types, 43 2010

Figure 2.2 Economic Model of College Choice 46

Figure 2.3 Sociological Model of College Choice 48

Figure 2.4 Combined Student Choice Model 50

Figure 2.5 Three Phase Model of HE Choice 51

Figure 2.6 Student Choice Model 55

Figure 2.7 The Organic Inter-Consumer Influence Model 65

Figure 2.8 The Linear Marketer Influence Model 65

Figure 2.9 The Network Co-Production Model 65

Figure 2.10 Theoretical Relationship Between Information 89 Quality and Information Usefulness Proposed by Sussman and Siegal (2003)

Figure 2.11 Theoretical Relationship Source Quality and 91 Information Usefulness Proposed by Sussman and Siegal (2003)

Figure 2.12 Theory Reasoned of Action (TRA) 97

Figure 2.13 Theory of Planned Behaviour (TPB) 99

Figure 2.14 Technology Acceptance Model (Davis, 1989) 100

Figure 2.15 Technology Acceptance Model 101 (Venkatesh & Davis, 1996)

Figure 2.16 Technology Acceptance Model 2 103 (Venkatesh & Davis, 1996)

Figure 2.17 Technology Acceptance Model 3 (Venkatesh, 2000) 104

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Figure 2.18 Unified Theory of Acceptance and Use of 108 Technology (Venkatesh et al. 2003)

Figure 2.19 Information Adoption Model (Sussman & Siegal 110 2003)

Figure 2.20 Proposed Research Framework 117

Figure 2.21 The Integrated Generic Higher Education Student- 130 Choice Model

Figure 3.1 Stages in the Selection of Samples 141

Figure 4.1 Research Model (Inner and Outer Models) 194

Figure 4.2 The Measurement Model after Adjustment 205

Figure 4.3 Statistical Significant Path Coefficients 210

Figure 4.4 Mediating Model of Information Usefulness 212 between Country Image and PrUni Enrolment Choice

Figure 4.5 Mediating Model of Information Usefulness 213 between City Effect and PrUni Enrolment Choice

Figure 4.6 Mediating Model of Information Usefulness 215 between Institution Image and PrUni Enrolment Choice

Figure 4.7 Mediating Model of Information Usefulness 217 between Programme Evaluation and PrUni Enrolment Choice

Figure 4.8 Moderator Model 219

Figure 4.9 Result of the Moderation Effect of Information 221 Quality on the Relationship between Country Image and Information Usefulness

Figure 4.10 Result of the Moderation Effect of Information 223 Quality on the Relationship between City Effect and Information Usefulness

Figure 4.11 Moderation Effect of Information Usefulness 223 between City Effect and Information Usefulness

Figure 4.12 Result of the Moderation Effect of Information 225 Quality on the Relationship between Institution Image and Information Usefulness

Figure 4.13 Moderation Effect of Information Usefulness 226 between Institution Image and Information Usefulness

Figure 4.14 Result of the Moderation Effect of Information 228 Quality on the Relationship between Programme Evaluation and Information Usefulness

Figure 4.15 Moderation Effect of Information Usefulness 228 between Programme Evaluation and Information Usefulness

Figure 4.16 Result of the Moderation Effect of Source 230 Credibility on the Relationship between Country Image and Information Usefulness

Figure 4.17 Moderation Effect of Source Credibility between 231 Country Image and Information Usefulness

Figure 4.18 Result of the Moderation Effect of Source 233 Credibility on the Relationship between City Effect and Information Usefulness

Figure 4.19 Moderation Effect of Source Credibility between 233 City Effect and Information Usefulness

Figure 4.20 Result of the Moderation Effect of Source 235 Credibility on the Relationship between Institution Image and Information Usefulness

Figure 4.21 Result of the Moderation Effect of Source 237 Credibility on the Relationship between Programme Evaluation and Information Usefulness

Figure 4.22 Moderation Effect of Source Credibility between 237 Programme Evaluation and Information Usefulness

Figure 4.23 Theoretical Framework with significant effect 239

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LIST OF DIAGRAMS

Page

Diagram 3.1 Sampling Procedure 147

Diagram 3.2 Summary of Data Collection 152

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LIST OF ABBREVIATIONS

AVE Average Variance Extracted

BI Behavioural Intention

DTPB Decomposed Theory of Planned Behaviour

DV Dependent Variable

EAHEP Eu-Asia Higher Education Platform

eWoM Electronic Word of Mouth

f2 Effect Size

GDP Gross Domestic Product

GoF Goodness of Fit

HEI Higher Education Institution

IAM Information Adoption Model

ICT Information and Communication Technology

IV Independent Variable

LAN National Accreditation Board

LMIM Linear Marketer Influence Model

MDV Moderating Variable

MOHE Ministry of Higher Education

MSC Multimedia Super Corridor

MV Mediating Variable

NDP National Development Policy

NEP New Economic Policy

NOPM Network Co-Production Model

NVP National Vision Policy

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OICIM Organic Inter-Consumer Influence Model

PBC Perceived Behavioural Control

PEOU Perceived Ease of Use

PHEIA Private Higher Educational Institution Act

PLS Partial Least Squares

PrHEI Private Higher Education Institution

PrUni Private University (Local and Foreign Based Branch Campuses)

PU Perceived Usefulness

PuHEI Public Higher Education Institution

Q2 Cross-Validated Redundancy

R2 Coefficient of Determination

SEM Structural Equation Model

TAM Technology Acceptance Model

UNESCO United Nations Educational, Scientific and Cultural Organization

WOM Word of Mouth

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KEBERKESANAN ELECTRONIC WORD-OF-MOUTH (eWoM) DALAM

MENARIK MINAT PELAJAR ANTARABANGSA UNTUK

MENDAFTARKAN DIRI DI UNIVERSITI SWASTA (US) DI MALAYSIA

ABSTRAK

Dalam persekitaran yang penuh persaingan kini, pelajar antarabangsa sangat bergantung kepada maklumat yang diperolehi daripada eWoM untuk mendaftar diri di Institut Pengajian Tinggi Swasta (IPTS). Beberapa pihak telah berhujah dan berpendapat kualiti dan kredibiliti sumber maklumat dari eWoM boleh mendorong pelajar antarabangsa untuk mendaftar dan mengikuti pengajian di IPTS di Malaysia.

Mobiliti pelajar antarabangsa dan globalisasi telah mencetuskan persaingan dalam kalangan universiti di seluruh dunia untuk bersaing demi mendapatkan pelajar dengan mempromosikan universiti masing-masing dan kursus yang ditawarkan dengan menggunakan pelbagai kaedah promosi. Pada masa yang sama, pelajar antarabangsa mencari pelbagai maklumat berkaitan dengan Insititut Pengajian Tinggi

Swasta (IPTS) melalui eWoM sebelum membuat keputusan. Sebelum eWoM, sumber maklumat konvensional seperti media cetak, media penyiaran, pameran pendidikan dan laman web universiti merupakan asas kepada kaedah pemasaran institusi pengajian tinggi. Pembangunan WEB 2.0 membolehkan pelajar antarabangsa untuk berkomunikasi, mencari dan mengumpul maklumat seperti imej negara, keberkesanan bandar IPT, imej institusi pengajian dan program yang ditawarkan oleh IPT melalui eWoM. Penerimaan platform eWoM seperti Facebook,

LinkedIn, Twitter, Google+, YouTube, kini merupakan sumber maklumat alternatif bagi pelajar antarabangsa untuk mendapatkan maklumat sebelum mendaftarkan diri ke IPT. Dalam konteks ini, mengkaji dan memahami keberkesanan eWoM dalam

xx konteks pelajar antarabangsa boleh meningkatkan kadar bilangan pelajar antarabangsa yang berdaftar di Universiti Swasta (US) di Malaysia. Oleh itu, tujuan kajian ini adalah untuk mengkaji orientasi maklumat yang dicari oleh pelajar antarabangsa seperti imej negara, keberkesanan bandar, imej institusi pengajian, penilaian program serta semua maklumat yang bermanfaat ke arah menarik pelajar antarabangsa mendaftar diri dalam US pilihan mereka. Kajian ini juga memberi tumpuan untuk memahami hubungan kualiti maklumat dan kredibility sumber maklumat sebagai pembolehubah penyederhana di antara orientasi maklumat dan keberkesanan penggunan maklumat. Saiz sampel terdiri daripada 359 orang pelajar antarabangsa dari US yang dipilih dan maklumat tersebut dikumpulkan dan dianalisis menggunakan Structural Equation Modeling (SEM). Kajian mendapati bahawa tiga daripada empat orientasi maklumat iaitu kesan bandar, imej institusi pengajian dan penilaian program mempunyai kesan langsung yang signifikan terhadap keberkesanan penggunaan maklumat. Selain itu, keberkesanan penggunaan maklumat didapati menjadi pengantara yang menghubungkan antara orientasi maklumat iaitu kesan bandar, imej institusi dan penilaian program ke arah keputusan pelajar antarabangsa untuk mendaftar di US. Kesan pembolehubah penyederhana kualiti maklumat dan kesan pembolehubah penyederhana kredibiliti sumber juga telah diuji. Berdasarkan kajian, kualiti maklumat mempunyai kesan penyederhana yang kecil ke arah hubungan di antara kesan bandar, imej institusi dan penilaian program kearah keberkesanan penggunaan maklumat. Begitu juga dengan sumber kredibiliti yang mempunyai kesan penyederhana kecil di antara imej negara, kesan bandar dan penilaian program kearah keberkesanan penggunaan maklumat.

Berdasarkan kepada dapatan kajian, implikasi teori dan praktikal kajian juga telah disediakan. Secara keseluruhan, kajian ini menyumbang kepada pemahaman tentang

xxi keputusan untuk mengikuti pelajaran di US di kalangan pelajar antarabangsa yang menggunakan eWoM sebagai satu platform untuk mencari maklumat. Di samping itu, kajian ini juga memberi input kepada universiti swasta untuk merumuskan strategi pemasaran, supaya US boleh mengambil bahagian dalam eWoM dan pengambilan pelajar antarabangsa.

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THE EFFECTIVENESS OF ELECTRONIC WORD-OF-MOUTH IN

ATTRACTING INTERNATIONAL STUDENTS TO ENROL INTO PRIVATE

UNIVERSITIES IN MALAYSIA

ABSTRACT

In this current competitive environment, it is important for international students to accentuate on information from eWoM to enrol in PrHEI. It has been argued that the quality of information orientation and the credibility of the information orientation source from eWoM can guide international students to enrol in Malaysian PrHEIs. International student mobility and globalisation has triggered universities around the world to compete for students by promoting their universities and courses using a variation of promotion methods. Simultaneously, international students go through a university search, decision-making and selection process using a variety of information sources such as eWoM. Prior to the eWoM, conventional information sources such as print media, broadcast media, education fairs and university websites have been fundamental on HEI marketing methods. The development of WEB 2.0 allows international students to communicate and gather information such as country image, city effect, institution image and programme offered by a HEI via eWoM platform. The acceptance of eWoM platform such as

Facebook, LinkedIn, Twitter, Google+, YouTube, now presents an alternative university information source for international student to search in for information and use the information prior to their HEI enrolment. In this manner, investigating and understanding the effectiveness of eWoM in the context of international students could increase the enrolment of international students in Malaysian PrU. As such, the

xxiii purpose of this study was to examine the information orientation searched by international students such as country image, city effect, institution image, programme evaluation and the usefulness of the information towards enrolment of the international students in their choice of PrU. This study also focused to understand the moderating effect of information quality and source credibility between information orientation and information usefulness. The sample size comprises 359 international students from selected PrU were collected and analysed using Structural Equation Modelling (SEM). The study found that three out of four information orientation namely city effect, institution image and programme evaluation had a significant direct effect towards information usefulness. Moreover, information usefulness was found to mediate the relationship between information orientation namely city effect, institution image and programme evaluation towards

PrU enrolment by international students. The moderating effects of information quality and source credibility also have been tested. Based on the study information quality has small moderating effect toward relationship between city effect, institution image and programme evaluation. Similarly source credibility has small moderating effect toward the relationship between country image, city effect and programme evaluation. Overall this study contributes to the understanding of private university decision making amongst international students using eWoM as an information platform. In addition, this study also provides inputs for private universities to formulate marketing strategies for eWoM participation and recruitment of international students.

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CHAPTER 1

INTRODUCTION

1.0 Introduction

This chapter encompasses the background of this study, problem statement, research questions, and research objectives, operationalisation of key terms, significances of the study and organization of the remaining chapters.

1.1 Background

The introduction of information technology and communications technology has transformed the mode individuals and organizations function, communicate, manage, and carry out business. In the early years of 1960s, television, radio, magazines and newspaper are the foremost used communication platforms.

Furthermore, there is growing disintegration within the numerous communication platforms (Rosen, 2009). According to Egli & Gremaud (2008), the consumers have not kept pace with the increasing fragmentation within various communication platforms which disseminates information. This expansion is correspondingly nurtured by the element that marketing information sent by various communication platforms are currently utilized by the corresponding target viewers to merely a reduced range (Godes et al., 2009).

According to Sankatsing (2007), the emerging range of communication platform and the homogenisation of the existing product or services have had a negative influence on the current communication platform. Therefore, traditional marketing communication platforms are progressively facing credibility concerns

1 since there are market oriented context which frequently disseminate faulty information related to a product or service to the consumers.

These developments presume that the traditional communication approach has become ever more unpopular amongst consumers. According to Egli & Gremaud

(2008) consumers often feel pressurised toward those incalculable promoting advertising and read this overflow of information either selectively or not at all, additionally consumers does not show the interest or spend time to deal with different advertising messages and gradually disregard them. Comparatively, a consumer gives more priority to interactive communication in their buying selection based on recommendations from their social environment. Thus, word-of-mouth

(WOM) turns out to be an effective marketing communication channel (Egli &

Gremaud, 2008). Word-of-mouth is pioneered by George Silverman, a psychologist in the early 1970s. George Silverman created what he called "teleconferenced peer influence groups" to engage physicians in dialogues about new pharmaceutical products. George Silverman discovered that few physicians who were having respectable knowledge with a drug would influence a whole crowd of doubters. They would even sway a dissatisfied group of ex-prescribers who have had negative experiences (Silverman, 2009).

Definitions of word-of-mouth (WOM) can be found in various articles and journals. Gafni & Deri, (2012) describes WOM as the intentional involvement of communications between consumers by professional marketers. Kozinets et al.,

(2010), claims that WOM is an interactive communication method among observed non-commercial communicator and a receiver relating to product or service. In the

Journal of Marketing Research, WOM is described as informal communication focussed at new consumers associated with possession, utilization, or features of

2 specific products and service. Justin &Paul (2006) provided a more specific and restricted definition of WOM as verbal, communication among a sender and a receiver which has a substantial influence on consumer decision making. In addition

WOM is considering having greater beneficial than the old-fashioned marketing methods, for instance WOM communication believe to be credible and reliable than the marketers originated communications. Therefore, WOM is seen to be more credible than the marketer originated communications since it is viewed as a communication that is accepted over the neutral individuals of ‗people like me‘

(Allsop, 2007). The development of Internet has changed the way of WOM functions. The advance of internet has transformed WOM – face-to-face communication to eWoM – face-to-screen communication.

1.2 Internet and Word of Mouth

In the recent decades, the Internet plays a pivotal role in communication through building it to share information with easiness between individuals. Internet has changed the approach individuals share their positive and negative thoughts. The reason the Internet is so attractive and efficient for individuals, and consequently a vehicle for WOM, lies in the concept of the Internet itself. This new medium called internet has a great level of interaction which often exists to only a limited extent, especially in traditional marketing communication (Esch, Langner & Ullrich, 2009).

According to Sankatsing (2007), some of the most significant characteristics of the

Internet are it is always available, 24 hour access to the utmost current information, its worldwide exposure, unrestricted volume and basis of facts on goods, trademarks or competitors facts and figures, its simplifying the ordering procedures, personalization and secured payment methods, as well as the medium‘s capability to

3 aim particular marketing segments. Thus, internet became an interactive medium in promoting and retaining old and new consumers. Hence, it became even more important with the introduction of Web 2.0 to the computer users.

Web 2.0 is described as World Wide Web site that emphasizes user-generated content, usability, and interoperability (O‘Reilly & Marx, 2011). The term was propagated by Tim O'Reilly and Dale Dougherty in late 2004, though it was coined by Darcy DiNucci in 1999 (O‘Reilly & Marx, 2011). According to O‘Reilly & Marx

(2011) Web 2.0 websites exhibit five important characteristics, first, it delivers information and application entirely through a web browser; second, it develops structural design of individuals that inspires consumers to increase value to the method as they utilize it. A deserving illustration will be a webpage that tracks prominent news and blog entries by permitting its consumers on vote with respect to them; third, consumers can without much of stretch offer information with each other through interpersonal social network pages. Most Web 2.0 sites enable online consumers to assemble a system of different consumers for the reasons for sharing the internet resources; fourth, consumers can compose and characterize information to address their own issues. Many Web 2.0 sites bolster the utilization of a folksonomy, a method for utilizing open-finished names to arrange information;

Fifth, Web 2.0 gives online consumers a rich, intelligent and easy to understand interface.

The advancement of Web 2.0 offers potential consumers various chances to pick up information from different channels (for instance, websites, valuation entrances, gatherings, groups) or to take part in the consumer created content (Alby,

2008). In spite of the fact that Web 2.0 proposes another form of the World Wide

Web, it doesn't allude to a refresh to any specialized detail, but instead to total

4 changes in the way Web pages were made and utilized. A Web 2.0 webpage may enable consumers to communicate and team up with each other in an online networking dialogue as creators of user-generated content in a virtual group, rather than Web sites where individuals are restricted to the inactive review of content.

Example of Web 2.0 includes social networking sites, blogs, wikis, folksonomies, video sharing sites, and Web applications.

The appearance of the Internet and Web 2.0 interactive abilities has presented another type of verbal exchange termed electronic word-of-mouth (eWoM), where eWoM occurs throughout the web and permits consumers, to communicate with each other and offer their thoughts about different products via social networking sites, blogs, web journals, content-sharing sites and different types of online networking.

Kaptein (2012), specified eWoM as an approach that influences the substantial power of individuals to motivate other individuals in their online social network via computer assisted communication medium. Electronic word-of-mouth also identified as any information shared by prospective, current or former consumers which the information is presented in numerous levels of consumers by the Internet (Hennig-

Thurau, Gwinner, Walsh & Gremler, 2004), Goldsmith (2006), characterized eWoM as a casual communications focused on online users who use internet for searching information related to their interest of product or service and or the sellers. All the three eWoM definitions above highlighted that eWoM is an informal communication between consumers-to-consumers in online environment. This consumer-to- consumer communication has turned out to be progressively compelling in consumers' purchasing decision and has moved the power of impact from advertisers to consumers, as the present consumers are never just receive information from market oriented communication but instead become more dynamic in searching for

5 information related to consumers' feelings and offer their own information to other consumers‘ (Chu & Kim 2011).

The growing importance of eWoM in the realization of purchasing processes can be seen from the early 2000. According to an internet-based survey which was conducted in 2007 and 2009 principally shows 80% consumer belief in the references of other consumers and 70% in consumer thoughts circulated online in

2009 (Figure 1.1). Media such as newspaper (61%), television (61%) and radio

(55%) were stated; nonetheless they track considerably behind inter-personal communication. Figure 1.1 clearly point out that online users are getting recommendations from other consumers before purchasing a product or service.

These recommendations come from eWoM platforms such as social media, blogs and videos. Figure 1.1 also clearly indicates that eWoM is the most trusted medium by consumers to search for information associated with products or services across the industries. This survey is conducted over 25,000 internet users through few nations.

90 80 70 60 50 40 30 20 10 2007 0 2009

Figure 1.1: Consumer Trust in Advertising by Channel 2007 vs. 2009 (The Nielsen Company, 2009)

1.3 Electronic Word of Mouth’s Adoption Across Industries

As the Internet turns into an essential vehicle for eWoM communication, eWoM has conveyed significant changes to consumer-to-consumer communication.

Generally, WOM communication is regularly verbal, casual and restricted by transient or physical space (Stern 1994). Despite what might be expected, eWoM varies from WOM in the accompanying ways: First, eWoM tackles the boundless reach of the Internet for people to impart insights on a one-to-world platform (Litvin et al., 2008). By empowering consumers to retrieve mass electronic verbal information from others in a minimal effort and timely manner, eWoM is more diffusible than conventional WOM. Second, eWoM can originate from differing sources including acquaintances and total strangers (Lim & Van Der Heide, 2015), though traditional WOM essentially originates from family and companions. This difference in closeness of the eWoM sources additionally builds the extent of eWoM that consumers may get. At last, eWoM is highly accessible because most content on

7 the Internet are archived for an indefinite long period of time (Cheung & Thadani,

2012). In this manner; consumers can without much of problem to recover countless positive and negative eWoM information concerning a specific item. The importance of eWoM and the influence of its attributes related to consumers' online purchase behaviour have brought about a generous research stream.

A vast amount of studies validates that eWoM has a substantial effect on online consumers‘ purchase decisions. Specifically, content of eWoM and origin of eWoM have been generally contemplated. In particular, the direction of eWoM

(positive versus negative) has been appeared to have huge effect on consumers. Past research recommended that positive eWoM information would build consumers‘ purchasing decisions, while negative eWoM information would decrease consumers‘ purchasing choices, for example Chatterjee (2001) created an imaginary web shopping centre, and utilizing a non-existent consumer as responded for the study to examine the impact of eWoM. Outcome of the study shows that negative consumer review relatively has impact on consumer's confidence and purchase intent in the web shopping centre. Furthermore, in appropriate circumstances, for users who wish to purchase at a lower cost, the impact of negative eWoM is more powerful. It seems that eWoM users are considerably sensitive in receiving negative information from eWoM and this is especially true of low-cost products or services. Chatterjee (2001), highlighted that for those business dependent on cost benefit should manage the negative information in eWoM as they do not have the brand influence. Chatterjee

(2001), in his study indicated that the information disseminated in eWoM can be of negative or positive impact on companies based on the capacity of online companies, but failed to highlight what motivates the online user to read these positive and negative information disseminated by eWoM (Chatterjee, 2001). Henning-Thurau

(2004), addressed the motivation for online users to read positive and negative information in their study. Hennig-Thurau et al. (2004) stated the most imperative inspirations for reading online reviews were: decreased of risk, bringing down of search time, realizing the different techniques in buying an item, reduction of purchase regret, looking to new merchandise, and upsurge social reputation and position. In addition, Gruen, Osmonbekov & Czaplewski (2006), highlighted that reduction of decision making time and better purchase decision making were shown to be the most significant factors motivating the customer to read eWoM. Hennig-

Thurau et al., (2004) in his research clearly indicates the motive of a consumer using eWoM is for better purchase decision, but failed to identify why online users exchange information and adopt eWoM information. Gruen et al., (2006); Bickart &

Shindler (2001); and Chevalier & Mayzlin (2006) in their studies highlighted on why online users exchange information and adopt eWoM information.

Gruen et al., (2006) considered eWoM as a sort of learning on the most proficient method to trade information among the consumers, and that the advancement of the awareness on how eWoM was followed by inspiration and capability. Moreover, when eWoM is overseen legitimately, it was demonstrated that it effectively affects the consumer appraisal of the business and on expectations to repurchase. Bickart & Shindler (2001), allowed consumers to gather data on 5 item classifications for a time of 12 weeks. The outcomes demonstrated that consumers essentially pay more thought to the information given by different consumers generally than those of the business people or advertisers since they have used the item. In short the information they offer is more appealing and critical to the potential consumers. Chevalier & Mazlin (2006) studied Amazon; Barnes and

Nobles actual sales in relation to eWoM online book assessments. The results

9 demonstrated that more positive eWoM is sent on online book shops than offline, with Amazon having much more positive eWoM in both amount and quality than

Barnes and Noble. Generally, all the 3 studies indicate that online consumers interchange and adopt information in eWoM because consumers pay extra consideration for the information disseminated by other consumers in eWoM.

Electronic word-of-mouth turns out to be a significant platform for consumers to accumulate information prior to their purchase. Electronic word-of-mouth is most likely to impact on the buying selections for product or service which is complex, costly and exceptionally desired items. According to Riegner (2007), consumers will put extra efforts in searching for information and compare all the alternatives before buying items that are expensive and complex. Riegner (2007) likewise recommends that it is a necessity for consumers to tangibly assess an item that might restrict the possibility for eWoM to impact the buy of the item. Electronic word-of-mouth has additionally been found to influence high-risk purchase decision, for example, travel

(Libai, Balton, Bugel, Ruyter, Gotz, Risselada & Stephen, 2010). The fact that the tourism product is an intangible items, including complex options associated with high expenditures, encourage consumers to look for more important information via a wide variety of platforms (Libai et al., 2010). These results recommend that eWoM could have a comparable result on one more category of complex, expensive service buying — international students‘ higher education institution enrolment choice decision. Hence, eWoM plays a vital role for international students to search for information before enrolling into the HEI of their choice.

1.4 Development of Higher Education Institutions in Malaysia

Requirement for vastly highly skilled labour force to cater for a knowledge economy has changed the prospect of Malaysian Higher Education Institutions

(HEI). The beginning of globalization joined with technological insurgency, particularly within the Information and Communication Technology segment has provided an ascent towards Malaysian knowledge economy which requires knowledge workforce (Vicziany & Puteh, 2004). To meet the knowledge manpower,

Malaysian upper secondary was generalized in year 1991. As indicated by Htherto, all students had just 9 years of basic education and subsequently they needed to proceed for their Lower School Certificate Examination. Only half of the students who sit for the examination were advanced to the next phase in their education. From now on, and into the foreseeable future, all students are qualified to continue till the

11th year and sit for the School Certificate Examination. Thus, expended the interest for students to continue to HEIs, however in usual terms; not all the students who applied for public university (PuHEI) were successful in getting a place to study.

According to Marimuthu, Jasbir Singh, Chew Sing Buan & Noraini Salleh (1999) it was estimated that, there were shortages of 150,000 spots for students to continue in

HEIs in the year 1992. Therefore, the government pursued private body to participate in developing private higher education institutions (PrHEI) to support the PuHEIs.

One more aspect that contributed concerning the advancement of PrHEIs is the expansion in the expenses associated with Malaysian students studying abroad.

The year 1985 saw a gauge of 68,000 Malaysian students studying abroad

(Marimuthu 2008), largely in the United Kingdom, Australia, United States of

America, Canada and New Zealand. Though in the year 2000, quantity of Malaysian students studying in abroad has declined to an aggregate of 50,000 students, 30% of

11 who were sponsored by government or government linked agencies (Marimuthu,

2008). While in the year 2006, there were only 11,900 students sponsored by the

Malaysian government due to the full-cost payment for abroad students which introduced by the Thatcher government in UK, trailed by Australia and other

Commonwealth countries (Marimuthu, 2008). The decline in the quantity of abroad students and public request pressured Malaysian government to take serious consideration in developing PrHEIs. These situations contributed to the expansion of

Malaysian PrHEIs. The development of PrHEIs has also contributed to the growth of

GDP of Malaysia. PrHEIs sector contributed 60% from the overall GDP growth of private education sector towards the GDP of Malaysia in year 2012. The strategic growth of PrHEIs has led to series of new rules and regulations to enable a methodical growth of PrHEIs in Malaysia.

The National Accreditation Board (LAN) was presented in the year 1996 to uphold the quality of PrHEIs programmes and as accreditation agency within the nation. Likewise, the National Council on Higher Education Act, 1996 was built up to define arrangement for both PuHEIs and PrHEIs. Following the National Council on Higher Education Act, Private Higher Education Institutions Act was presented in

1996, allowing the development of PrHEIs (local and foreign branch campuses) and granting PrHEIs to conduct their programme in English language with the approval of the Ministry of Higher Education (MOHE).

University and University Colleges Act 1971 was then altered in year 1996 to empower the universities to be corporatized and to modernize the administration of the universities keeping in mind the end goal to address the issues of the general public and the industry. In 1997, National Higher Education Funding Board Act was presented where the foundation of the HEIs subsidizing panel was to give education

12 aid to both PuHEIs and PrHEIs students. The introduction and implementation of new rules and regulations enabled a systematic growth of PrHEIs. The growth is evident in the number of PrHEIs from the year 2000 to June, 2016. In June 2016, there were 480 PrHEIs in Malaysia; 44 PrHEIs with university status, 29 PrHEIs with university college status, 9 foreign university branch campuses and 398 PrHEIs with college status (MOHE, 2016).

Development of PrHEIs can also be viewed from student‘s enrolment perspective to PuHEI or PrHEI. This view is explained by Zahir & Mushtaq (2008), in their study. According to Zahir & Mushtaq (2008), Malaysian higher education system has five phases. The first phase was initiated in the year 1970 with the aim to

‗export‘ local students abroad to gain tertiary education, the second phase started in the mid-1980s with the Malaysian government‘s emphasis on strategic alliance,

―import substitution‖, among local PrHEIs and their overseas institutions. The introduction of ―split-degree‖, which programmes comprised credit exchange and official twinning programmes with selected overseas institutions were developed in the particular phase. The third phase (mid-1990s) of the cycle went past twinning programmes as overseas institutions created "administration contracts" and

"permitting" relationship with home-grown Malaysian universities that provides whole programme compare to part of undergraduate programmes. During the fourth phase (late-1990s), Malaysia opened the door for foreign entity to directly invest to open branch campuses and endorsed PrHEIs to fund their degrees by providing approval for establishments of the ―university college‖ (Zahir & Mushtaq, 2008).

The fifth phase (2000 to present-day) not only focused on the steps of both government and private entity in building the domestic options for Malaysian students, yet not withstanding in the end to "import" students from abroad,

13 overwhelmingly, from the neighbouring nations to study in Malaysian local PrHEIs and branch universities which offer complete degree programmes. Malaysia‘s current international students‘ percentage stands at approximately 2% to 3% of total global market share and Zahir & Mushtaq (2008), specifies that WOM is seen as one of the main tool to attract international students to Malaysian HEIs, especially to PrHEIs

(Table 1.1).

The UNESCO (2014), Institute of Statistics characterizes international students as students who have spanned a national or territorial border for the reason of higher learning and are joined outside their country of origin. Alternatively, the

Organization for Economic Cooperation and Development (OECD) - (2003) defines international students as individuals admitted by a country other than their own, commonly under distinct permits or visas, for the particular purpose of following a specific higher learning of study in an accredited institution of the receiving country.

Therefore, international students can be concluded as those who have crossed borders for the purpose of higher education in a different country from their country of origin (UNESCO, 2014).

Table 1.1 Target Markets for Malaysian Education

Malaysian Education Evolution

Evolution 1: Export of Evolution 2: Import Evolution 3: Evolution 4: Evolution 5: local Malaysian students substitution “Twinning Licensing by Foreign direct International to foreign educational programs”. foreign institutions. investment by students is imported Components institutions Partial study done Entire program overseas. to Malaysia abroad completed in Licensing by Malaysia Malaysian public universities granting the degree Critical impacts on the  Overseas institutional  Affordable oversea  Monetary  Involvement of  The prestige of “buying centre” for prestige/position higher education burdens. many organizations an institution is example on users,  Peer knowledge at which could support  Improved to uphold education growing through influencers, and overseas institution. by family. consciousness in level. WOM. deciders  Government has national pride  Home-grown  Cheaper control on the and Asian morals institutions are alternative for policies and being accepted by oversea higher financial issues. their reputation. education  Emphasize on local institutions culture. Source: Zahir & Mushtaq (2008)

1.5 Problem Statement

Previously, consumers searching for information were constrained to rely upon marketer generated sources, third party statements and discussions with loved one such as family and friends. Though, by the introduction and development of Web

2.0 that empowers consumers to take part actively in sharing information among consumers and allows consumers to interact between each other and exchange information prior to their purchasing decision (King, Racherla & Bush, 2014). The

Web 2.0 revolution introduces consumers to the utmost capable voice they have used so far – eWoM (King, Racherla &Bush, 2014). With the capacity to effortlessly request and offer all kind of information, such as from which doctor to consult to what type of laundry detergent to buy, consumers are putting less trust in experts and are increasingly basing their purchasing decisions on the recommendations of their peers obtained mainly through the Web and web-based social networking, otherwise called eWoM (King, Racherla & Bush, 2014). This supported by Bronner & Hoog

(2012), where the scholars indicated that eWoM is considered as the most trusted platform to gain information.

Electronic word-of-mouth has been extensively explored by scholars. The earlier studies of eWoM focused on the search goods or products (Cheol Oark &Thae

Min Lee, 2009). Bronner & Hoog, (2012) and King et al., (2014), categorized searched products by the product qualities which all the details of the product could be attained prior to purchase. Clemons et al., (2006) addressed that the characteristics of the search product discussed in eWoM subsequently will affect the consumers‘ perception about a product. There was few research conducted on experience goods or service industry. Cheol Oark & Thae Min Lee (2009) explained that experience goods are those items which grouped under goods that are difficult to give full details

16 before the acquisitions. Thus it makes the information exploration far more expensive compared to the search products. In fact, PrHEIs are grouped under experience goods. The intangible nature of PrHEIs has made it difficult for early scholars to investigate the relations between information orientation search via eWoM and the criteria of HEI enrolment choice destination by international students.

Most prior study related to HEI and information search by international students are focused on official marketing medium of a particular HEI. Official marketing medium plays a big role as an investment in the future. Official marketing medium includes all of the available tools to the marketer for 'marketing communication'. Official marketing medium can be in mass media like TV, radio, newspapers, internet, and mobile phones, in which the advertiser pays an advertising agency to place the advertisement (Kathryn DiAna., 2014). According to Mortimer

(1997), Hesketh & Knight (1999) and Gatfield, Barker & Graham (1999), there was a substantial information inconsistency throughout decision aspects by students and the information that had been given by HEI in their official marketing medium.

Mortimer (1997); Hesketh & Knight (1999); and Gatfield et al., (1999) have each conducted their own research on the effect of official marketing medium in United

Kingdom and Australia. In all the three research, there was a significant gap identified. The gap demonstrates that the official marketing medium produced to prospective students regularly neglected to give adequate academic programme and other related information in detail. This is supported by Casttleman (2015),

Fagerstrøm& Ghinea, (2013) and Ismail & Leow (2008) in their research. Casttleman

(2015), Fagerstrøm& Ghinea, (2013) and Ismail & Leow (2008) highlighted that there are gap between information required by international students and the information provided by HEI official marketing medium. The official marketing

17 medium also normally fails to provide relevant, accurate, timely and comprehensive information about a particular HEI, country and cultural value (Gatfield et al., 1999).

Adding to Mortimer (1997); Hesketh & Knight (1999); and Gatfield et al.,

(1999), Gurevitch, Coleman & Blumler (2009) highlighted that, in recent years, many newspapers and television channels lost their audiences, since traditional print and broadcast media as promotional tool have faced major challenges in providing informative information. Furthermore, Kathryn DiAna (2014) stressed that HEI admissions departments which provide students with traditional marketing materials such as view books, brochures, or general print pieces fail to attract students to enrol in their HEI. Hence HEI fail in their efforts in pooling their efforts to present a clear image of offering a brand (Gurevitch et al., 2009). Thus, international students are looking for more formless information from their peers before the decision was taken

(Hesketh &Knight, 1999). International students must be convinced that ―what they see is what they get‖ before HEI decision is made. Therefore, eWoM is seen as the next step for international students to search for information prior to enrolling into the HEI of their choice.

The procedures of international students selecting HEI is developing due to the rapid expansion of HEI on the global platform and the continued Web 2.0 revolution that affects online user‘s behaviour, decision making, beliefs and perceptions which led to online consumer empowerment (Flew, 2011). Thus, international students had their own way to search for information via eWoM before the enrolling decision was taken. International students will seek information in relation to HEIs and their contributions from a range of sources including eWoM as a mean of reducing the perceived risk associated in enrolling into the wrong HEI (Flew, 2011). Other than the information about universities and their programme offerings, international

18 students also search for information on quality teaching (Mazzoral & Soutar, 2002), institution‘s reputation, employment opportunities (Mazzoral & Soutar, 2002), accessibility of up-to-date amenities and an international student body effectiveness.

Jenkins (2011) explains that course admission marks and simplicity of admission to be important elements to Australian students. Table 1.2 presents a summary of the information orientation searched by international students which have an influence on international students‘ HEI enrolment choice.

Table 1.2

Summary of Information Searched by International Students in HEI Choice Decision Making

Researchers Information Country of study

Maringe and Carter, 2007 Lack of access to better Australia local United Kingdom education

Maringe, 2006 Financial factors Australia Bodycott, 2009 United Kingdom . Hong Kong

Mazzarol and Soutar, 2002; Cultural factors Australia Counsell, 2011; United Kingdom Bodycott, 2009 Hong Kong

Chen, 2007 Environmental and social Canada factors

Bodycott, 2009; Foreign university‘s Hong Kong quality and United Kingdom better facilities

Bodycott, 2009; Chen, 2007 Security and safety Australia United Kingdom Canada Hong Kong

Mazzarol and Soutar, 2002; Teaching credentials, Australia Maringe, 2006 qualification United Kingdom and reputation

Table 1.2 (Continued)

Researchers Information Country of study

Bodycott, 2009; Higher education Australia Cubillo et al, 2006 institution‘s Hong Kong status for excellence United Kingdom Spain

Mazzarol and Soutar, 2002; Accessibility of a broad United Kingdom variety of Australia courses and programs

Maringe and Carter, 2007; University environment United Kingdom Bodycott, 2009 Hong Kong

Source: Lee & Morrish (2012)

HEIs enrolment decision procedure becomes an important research area among PuHEIs and PrHEIs scholars. This can be seen from the development of HEI choice model by Hossler & Gallagher in 1987 and keeps on being investigated today against eWoM, for example Counsell (2011), who watched that 46% of potential international students communicated and searched for information in eWoM prior to their HEI choice decision. Adding to Counsell (2011), Morris (2012), acknowledged that international students used eWoM in gaining information related to higher education institutions which guides them in selecting the right institution.

Accordingly, a research by Kuzma & Wright (2013) has indicated that, today eWoM tools are making it possible to communicate directly with almost any audience.

Further Kuzma & Wright (2013) indicated that the tools for communicating with the target audiences and marketing have significantly changed from traditional media to a new phenomenon known as ―eWoM‖. As a result, HEIs are beginning to embrace eWoM and realizing the potential power and implications for using it as a component of their overall marketing mix (Fagerstrøm & Ghinea, 2013).

Thus, the problem statement of this study is, whereas eWoM seems to have much opportunity and promise, it is still to be experimentally determined if and what information searched in eWoM plays a role in international students‘ decision of HEI enrolment choice. Thus, this study focuses on the affiliation among international students' information orientation search in eWoM and the usefulness of the information orientation towards PrHEI enrolment choice (focused on Private

Universities (PrUni) – local and foreign based branch campus) by international students.

1.6 Research Objectives

Current study is focusing on understanding on the relationship between international student‘s eWoM usage in searching for information and their PrUni choice of enrolment. Thus, the following research objectives are developed:

1. Examine the effect of country image (cultural proximity, academic reputation

and socioeconomic level) and information usefulness towards PrUni

enrolment choice.

2. Examine the effect of city effect (city dimension and cost of living) and

information usefulness towards PrUni enrolment choice.

3. Examine the effect of institution image (quality of professors, institution

recognition and facilities on campus) and information usefulness towards

PrUni enrolment choice.

4. Examine the effect of programme evaluation (programmes recognition,

programmes suitability, programmes specialization and cost or finance) and

information usefulness towards PrUni enrolment choice.

5. Examine the mediating effect of information usefulness between the

information orientations and PrUni enrolment choice.

6. Examine the moderating effect of information quality on the relationship

between information orientation (country image, city effect, institution image

and programme evaluation) and information usefulness.

7. Examine the moderating effect of source credibility on the relationship

between information orientation (country image, city effect, institution image

and programme evaluation) and information usefulness.

1.7 Research Questions

In direction to accomplish the above objectives, the subsequent research questions were developed for this study:

1. What is the relationship between country image (cultural proximity, academic

reputation and socioeconomic level) and information usefulness towards

PrUni enrolment choice?

2. What is the relationship between city effect (city dimension and cost of

living) and information usefulness towards PrUni enrolment choice?

3. What is the relationship between institution image (quality of professors,

institution recognition and facilities on campus) and information usefulness

towards PrUni enrolment choice?

4. What is the relationship between programme evaluation (programmes

recognition, programmes suitability, programmes specialization and cost or

finance) and information usefulness towards PrUni enrolment choice?

5. Does information usefulness mediate the relationship between the

information orientations and PrUni enrolment choice?

6. Do information qualities moderate the relationship between information

orientation and information usefulness?

7. Does source credibility moderate the relationship between information

orientation and information usefulness?

1.8 Significance of the Study

This section discusses on the significant of theoretical and practical contribution in the relation to information orientation searched in eWoM by international students on their PrUni enrolment choice. Specifically, the contributions are as follows:

1.8.1 Theoretical Contribution

Based on the discoveries of this investigation, three possible theoretical contributions have been identified. Firstly, this investigation authenticates and approves a research model by extending the information adoption model (IAM) of

Sussman & Siegal (2003) by integrating and HEI choice combined model of Hossler

& Gallagher (1987). Hossler & Gallagher (1987) highlighted that the information search phase as critical and important stage in HEI enrolment choice by international students. Student‘s search for more informal information orientation as formal information from HEI‘s marketing platform does not really help them to decide on the HEI of their choice. This information orientation such as country image, city effect, and institution image and programme evaluation is explored and studied further to enrich the academic literature in understanding HEI enrolment choice by international students particularly PrUni enrolment by international students.

IAM is used to understand the effectiveness of information quality and source credibility in perceiving information usefulness towards HEI enrolment choice by international students. Thus, a new model will be developed that will integrate the

IAM and HEI choice combined model of in understanding the relationship between information orientation, information quality, source credibility, information usefulness and PrUni enrolment choice by international students.

Furthermore, this investigation will add to the developing body of literature writing by distinguishing and featuring the impact of information orientation searched by potential international students via eWoM in the procedure of HEI enrolment choice. Even though many studies have discovered and examined the HEI choice decision by students, only few researches focused one eWoM effect in international students‘ PrUni choice decision. Therefore, this study will add to eWoM literature by focusing on the effectiveness of information orientation searched in eWoM among international students and its relation towards HEI enrolment choice which focus on PrUnis in Malaysia.

Thirdly, there are inadequate studies and investigation on international students‘ enrolment choice, particularly PrUni in developing countries such as

Malaysia (Maringe, 2007); Malaysia‘s current international students‘ percentage is approximately 2% of the total global market share (UNESCO, 2014). From this 2%,

1.3% international students are enrolled in PrHEI. This clearly shows the importance of PrHEI in attracting international students. Therefore, this study will assist academicians to attempt more in depth research on the growing pattern of international students in PrHEIs specifically in PrUni. Furthermore, this study would also assist academicians and researchers to understand further on the relation between international students and information orientation search behaviour of international students in eWoM.

1.8.2 Practical Contribution

Through the findings of this study, few possible practical contributions are identified. The first contribution would be the outcome of this investigation which would present a better insight of the observable fact of eWoM in relations to PrUni enrolment choice by international students. Hence PrHEI, particularly PrUni is able to observe and learn the information orientation considered by international students prior to their PrUni enrolment choice destination. This will definitely help PrUni to improvise their traditional marketing strategies which failed to give the much needed information by international students (Fagerstrøm & Ghinea, 2013 and Gatfield et al., 1999). This investigation is likewise ready to help HEI by exploring the most commonly utilized eWoM platforms and also the best approaches to communicate with international students. It is not only adequate for HEI to only build up communication interchanges with their prospective students; but also to attract the participation of the students for effective communication. Hence, this study provides the much needed information for PrUni to understand the relationship between eWoM, international students and PrUni enrolment choice.

An immense number of international students leave their nation to study in overseas universities. Besides relying upon conventional data sources, they also rely upon eWoM for instructive and other related information. Subsequently, this investigation will profit international students in relation to understand the significance of information orientation, information quality and source credibility on information usefulness towards PrUni enrolment choice. By addressing this, international students will have a clear picture on the role of eWoM in their PrUni enrolment choice process.

The next contribution of the study falls on the hope of the study in assisting the Malaysia Ministry of Higher Education (MOHE) in achieving its target of

250,000 international student‘s enrolment in Malaysia (MOHE, 2015) as highlighted in Malaysia Education Blueprint 2015-2025 (Higher Education). By understanding the importance of the relation of eWoM and international students‘ HEI enrolment choice, HEI either PuHEI or PrHEI may utilize the inputs from the study and revisit their marketing strategy. Hence, improving the international student‘s enrolment into

Malaysian HEI and achieve the target of 250,000 international students by year 2025.

1.9 Operationalisation of Key Terms

The operational definitions of each variable used in the studies are as described below (Table 1.3).

Table 1.3

The Operational Definition of Variables Used in This Study

Variables Definitions

Electronic Word of Mouth Electronic Word-of-Mouth (eWoM) can be well-defined (eWoM) as an informal communications focussed at consumers via Internet technology related to the usage or features of particular products and services, or their sellers. This comprises communication among producers and consumers as well as those amongst consumers themselves (Goldsmith, 2006)

Information Quality Information quality refers to the persuasive strength of arguments embedded in an informational message (Bhattacherjee & Sanford, 2006).

Source credibility Source credibility refers to a message recipient‘s perception of the credibility of a message source, reflecting nothing about the message itself (Chaiken, 1980). Source credibility discusses about how much of the information receiver trusts in the sender. (Gunther, 1992).

Information usefulness Information usefulness is defined as the extent to which the readers perceive the received information as valuable thus can help them make a better purchasing decision (Cheung et al., 2008; Sussman & Siegal, 2003).

Information adoption Information adoption is a process in which people purposefully engage in using information which leads people to a decision. (Sussman & Siegal, 2003)

International Students International students are those who have crossed borders for the purpose of study. International students are those who are not residents of their country of study or those who received their prior education in another country (The UNESCO Institute for Statistics, the OECD and Eurostat, 2016).

Country Image Country image represents all that a consumer attaches to a country and its inhabitants (and not to its products). (Brijs et.al., 2011)

Table 1.3 (Continued)

Variables Definitions

City Effect The city represents the environment in which the service will be produced and consumed. Environment is more towards the study ―climate‖ of the country which takes into consideration of its physical climate and lifestyle (Mazzarol & Soutar, 2002).

Institution Image Institution image comprise of the reputation of the institution, lecturer‘s proficiency, teaching quality, and the campus environment. Hence institution image is considered as the perception of student on overall HEI (Qureshi, 1995).

Programme Evaluation Programme Evaluation is the systematic collection and analysis of information about programme activities, characteristics, and outcomes to make judgements about the programme, improve programme effectiveness and/or inform decisions about future programming (Patton, M.Q., 2008).

Higher Education Higher education institution is defined as all categories of Institution education (academic, training, technical, inventive, pedagogical, and long distance learning) delivered by HEI, technological institutes, teacher training colleges, which are generally planned for students having finished a secondary education, and whose educational aim is the achievement of a title or a grade in their undergraduate or postgraduate level (UNESCO, 2014). Public Higher Education A public university is a university that is owned, operated and Institution (PuHEI) is predominantly funded by public means through a national or sub-national government (UNESCO, 2014).

Private Higher Education Private HEIs are commonly owned and run by non-state Institution (PrHEI) personnel such as individuals, families, companies or corporations, religious organizations, and foundations. Private HEIs typically receive little or no state funding, and rather rely heavily on tuition and fees. (UNESCO, 2014).

Branch Campus of Foreign Foreign direct investment from abroad, which set up branch University campuses in Malaysia and offer foreign education (Zahir & Mushtaq, 2008)

Private University (PrUni) A private university is an independent academic institution endeavours to achieve the objectives of higher education and scientific research. In order to achieve such objectives in accordance with the higher education policy, it may design its study and research programs, curricula and plans, hold exams, and grant scientific and honorary degrees and certificates. (EACEA, 2017)

1.10 Organization of the Thesis

Chapter 1 discusses the overview of the communication platform which focuses on the development of eWoM. This chapter also presents the importance of eWoM and potential international students‘ HEI choice decision making. Following this, the research problems, research objective, research questions, and significance of the research and organization of the research thesis was discussed.

Chapter 2 is generally divided into three key sections. The first section will review the available literatures that are relevant to the main domain of this study which provides overview of the internationally mobile students, Malaysian private higher education institution scenario and eWoM environment. The second section will review the higher education institution choice model with decision making process. This is followed by the understanding about underlying theories and development of research framework.

Chapter 3 highlights the research approaches used in this study and followed by discussion on research design and methods along with the statistical instruments used for this study. Chapter 4 discusses the statistical analysis based on the questionnaires.

Chapter 5 summarize the outcome and result based on the investigation completed in previous chapters, consequently the implication of the findings, limitation of the study and proposition for future research is also discussed.

1.11 Chapter Summary

This chapter begins with the discussions on the overview of the communication platform which in particularly focuses on the Internet and eWoM. This chapter also presents the importance of eWoM across the industries and particularly on international students‘ HEI enrolment choice.

Finally, the chapter discusses the background and motivation of the study, research problems, research objective, research questions, and significance of the research and the organization of the thesis. The following chapter explores literature related to the study variables and underlying theories.

CHAPTER 2

LITERATURE REVIEW

2.0 Introduction

This chapter defines and evaluate the existing literatures that are relevant to the main domain of this study which provides an overview of the global internationally mobile students. This is followed by international students‘ mobility in Malaysia. Next, this chapter discusses on the evolution of WOM to eWoM.

Studies related to eWoM are also discussed in this section. All the above topics are discussed comprehensively in relation to HEIs and international student information search in eWoM. Subsequently the literatures also synthesized to support the entire research hypotheses. The main aim of this chapter is to understand the concept of information orientation searched by international students in HEI enrolment choice decision. Finally, development of conceptual framework and hypotheses are discussed.

2.1 International Students

The rapid expansion of higher education on the global platform is clearly evident with the enrolment of 97 million international students in HEI in the year

2000 (UNESCO, 2014). The need for skilled human resource and knowledge workforce has been the pillar for the rapid growth of international students around the global (UNESCO, 2014). Thus more and more country has invested money and time heavily to increase the number of HEIs and further increase student‘s enrolment for domestic and international students. The increase of student‘s enrolment has changed the HEIs philosophy of many countries, for example countries such as South

Korea, China and Singapore who has been considered as elite providers of higher

32 education which has limited access to enrol to more welcoming higher education system (UNESCO, 2014).

The financially sound middle class parents, and the need for skilled and knowledge work force has indirectly open up the door of opportunity for students to choose HEI from other countries. United States, United Kingdom and Australia were few destinations which become the favourite of traditional English speaking countries around the mid-1990. However, in the mid-1990s, few new countries start to take advantage of the demand in providing higher education. Countries like

Malaysia, Singapore and Republic of Korea begin to position their countries as excellent education hubs (UNESCO, 2014). International student‘s enrolment has extended to East Asia in the early 2010, thus open up opportunity for countries like

Hong Kong SAR, China, Singapore and Malaysia to expend their HEIs development.

Hence, these countries competed among each other to be the education destination of choice. The development of East Asia has invited Australia, United Kingdom and

United States to establish branch campuses or extend their mutual contracts with

HEIs in Asia (UNESCO, 2014).

According to Verbik & Lasanowski (2007), there will be a great demand for international students‘ placement around the globe, and it has estimated to be around

5.8 million in the year of 2020. According to statistics countries that are under the

Organization for Economic Co-operation and Development (OECD) has been to preferred destination by international students. More than 90% of international students enrol in OECD. 70% of the international students, who are enrolled in

OECD, choose United States, United Kingdom, Germany, France and Australia as the main destination for continuing their higher education (Verbik & Lasanowski,

2007).

According to Lasanowski (2009), there are three countries that have the major share of international student‘s market; they are United States, United Kingdom, and

Australia. UNESCO (2014), identified United States, United Kingdom, and Australia as the ―major players‖ of international student‘s market as they combined to have

45% of 2.7 million international students who are studying in their respective countries HEIs. Countries like Germany, France and China has classified as ―middle power‖ and has 25% of 2.7 million international students. Most of the students are from their neighbouring countries. Thus to increase the market share of the middle power countries, these countries are moving forward with new strategy by beginning to teach in English language which allows international students from English spoken country to enrol in their HEIs (Ndanusa Mohammed Manzuma-Ndaaba et.

El., 2016). Countries that are identified as ―Shape shifters – Canada, New Zealand and Japan‖ have 10% of the total global international student‘s market. These countries have changed their marketing efforts and government policies to attract international students to their HEIs.

In contrast to this, Singapore, Malaysia and Republic of Korea are placed as the ―emerging contenders‖ in the international student market. These countries have

5% of the world‘s international students mainly from Asian countries (Lesleyanne

Hawthorne 2008). Lasanowski (2009), notes that Malaysia ―stand to benefit by marketing the value of their education to an increasingly wide audience‖ as the country is rich in multicultural environment. Hence Malaysian government and private entity are working together in addressing new strategy and policies which allow Malaysia to become regional education leaders beyond the Asian region (Siti

Falidah Padlee, Razak & Rohaizat, 2010).

2.2 International Students in Malaysia

According to Zahir & Mushtaq (2008), Malaysian higher education system has five phases. The first phase was initiated in the year 1970 with the aim to ‗export‘ local students abroad to gain tertiary education and followed by strategic alliance in

1980s with the introduction of twinning programmes by selected foreign institutions in local institutions. In the third phase (1990s) local colleges are allowed to conduct whole rather than partial degree programmes from overseas HEIs through

―licensing‖ empowerment (Zahir & Mushtaq, 2008). Subsequently in late 1990

Malaysia allows overseas institutions to start branch campuses in Malaysia through

―foreign direct investment‖. Additionally, this also leads to HEI to award oversea degrees which the degree programme conducted in approved university colleges. The present day saw the government and private initiatives to develop more HEI in

Malaysia to cater for local market but as well as try to capture oversea market (Zahir

& Mushtaq, 2008). Malaysia‘s current international students‘ percentage stands at approximately 2% to 3% of the total global market share (UNESCO, 2014). The five phases of education cycle clearly indicate that HEIs in Malaysia are shifting and expanding not only in the PuHEIs but also in the PrHEIs.

As a result of the education paradigm shift over the last 50 years, the enrolment of domestically and internationally students has increased greatly. Malaysia also experienced this situation particularly with the launch of New Economics Policy

(NEP) in the year 1970 (UNESCO, 2014). The launch of NEP in the year 1970 resulted in Malaysia government allocating a larger portion of Malaysian expenditure for the growth of higher education in Malaysia. As a result of the NEP launch in

1970, Malaysian student number in foreign higher education institution has decreased. Back in 1975 around 16, 162 Malaysian students has enrolled in oversea

HEIs, comparatively in 1985 the number of Malaysian students increased to 40,493

(Table 2.1) and ranked Malaysia as the third largest country in sending Malaysian students to abroad HEIs to continue their higher education (UNESCO, 2014).

The economic crisis in year 1986 and 1997 however had their impacts on the

Malaysian economy. Thus, many students in overseas find difficulties in pursuing their education as the education turn out to be expensive and unaffordable.

Sponsored students are asked to return to Malaysia and continue their studies in

Malaysian HEIs (Marimuthu et al., 1999). Thus, student‘s enrolment in PuHEIs has increased. The increase in student‘s number and limited place in PuHEIs has brought government to work together with private sector in developing new HEIs policy and strategy.

Private Higher Educational Institution Act (PHEIA) in 1996 has allowed government to invite private sectors to actively involved in the higher education development for the country (Marimuthu et al., 1999). As a result of the PHEIA, the

Malaysian government approved the private sectors to establish private colleges and universities to support the demand for higher education in Malaysia. PHEIA also allowed foreign universities to establish their branch campuses which will provide higher education for domestic and international students. The progression of

Malaysia tertiary education with the introduction of PrHEIs, Malaysian students studying in foreign university has reduced and at the same time international student‘s enrolment in PuHEIs and PrHEIs has increased gradually.

Table 2.1 Top Ten Countries of Origin of Foreign Students, 1975 – 2015

No 1975 1985 1995 2005 2015

Country No Country No Country No Country No Country No 1 Islamic Rep. of Iran 33,021 China 42,481 China 115,871 China 343,126 China 328,457

2 USA 29,414 Islamic Rep. of Iran 41,083 Rep.of Korea 69,736 India 123,559 India 165,918

3 Greece 23,363 Malaysia 40,463 Japan 62,324 Rep. of 95,885 Rep. of 61,007 Korea Korea

4 Hong Kong SAR, 21,059 Greece 34,086 Germany 45,432 Japan 60,424 Saudi Arabia 61,287 China

5 China 17,201 Morocco 33,094 Greece 43,941 Germany 56,410 Canada 26,973

6 UK 16,866 Jordan 24,285 Malaysia 41,159 France 53,350 Vietnam 21,403

7 Nigeria 16,348 Hong Kong SAR, 23,657 India 39,626 Turkey 52,048 Taiwan 21,127 China

8 Malaysia 16,162 Rep. of Korea 22,468 Turkey 37,629 Morocco 51,503 Japan 19,060

9 India 14,805 Germany 22,424 Italy 36,515 Greece 49,631 Mexico 16,733

10 Canada 12,664 USA 19,707 Hong Kong SAR, 35,141 USA 41,181 Brazil 13,370 China

Source: UNESCO, 2016

Table 2.1 indicates that by the year 2015 Malaysia is not in the list of top ten countries that send their students to overseas HEIs and the trend continues up until

2015. Comparatively Malaysia is focused in developing PuHEIs and PrHEIs to facilitate the enrolment of international students from all around the world

(UNESCO, 2016). As a result of the upsurge of HEIs, Malaysia developed to be the higher education hub in Asian region and as an exporter of international students.

Hence Malaysia focused in developing PuHEIs and PrHEIs to attract international students in the coming years (UNESCO, 2016).

Table 2.2 present the overall enrolment of international students in Malaysian

PuHEIs and PrHEIs from the year 2009 to 2013. Table 2.2 clearly indicates that the international students enrolled in Malaysian PuHEIs and PrHEIs have increased from

27,872 international students to 83,633. It is an increase of 200% from the year 2002 to 2013. According to UNESCO (2014), Iran tops the list with 9,311 international students studying in Malaysian PuHEIs and PrHEIs. This is followed by international students from Indonesia, China, Nigeria and Yemen (Table 2.3).

Table 2.2 also indicates that PrHEIs has a strong position in attracting international students compared to PuHEIs. The international student number enrolled in PrHEIs increased from 58,294 in the year 2009 to 62,705 students in

2010. In contrast, the enrolment of international students in year 2011 had dropped to 45,246 students compared to year 2010. In year 2012, the enrolment of international students in PrHEIs had increased to 57,306 and slightly dropped again in 2013 to 53,971. As overall, in the last decade, international students who enrolled in PrHEIs have increased tremendously, as shown in the Table 2.2.

Table 2.2

International Students Enrolment in PuHEI and PrHEIs

HEI/Year PuHEIs PrHEIs Total

2002 5,045 22,827 27,872 2003 5,239 25,158 30,397 2004 5,735 25,939 31,674 2005 6,622 33,903 40,525 2006 7,941 36,449 44,390 2007 14,324 33,604 47,928 2009 22,456 58,294 80,750 2010 24,214 62,705 86,919 2011 25,855 45,246 71,101 2012 26,232 57,306 83,538 2013 29.662 53,971 83,633

Source: Ministry of Higher Education (2015)

Table 2.3

Malaysian International Students Country of Origin

Country of Origin 1 Iran, Islamic Rep. 9,311 2 Indonesia 7,989 3 China 6,484 4 Nigeria 4,975 5 Yemen 3,235 6 Sudan (pre-secession) 1,820 7 Iraq 1,748 8 Pakistan 1,649 9 Bangladesh 1,536 10 United Kingdom 1,532 11 Saudi Arabia 1,231

Table 2.3(Continued)

Country of Origin 12 India 1,170 13 Somalia 1,039 14 Thailand 1,025 15 Libya 1,000 16 Botswana 933 17 Maldives 885 18 Singapore 791 19 Sri Lanka 772 20 Jordan 727 21 Palestine 682 22 Kazakhstan 681 23 Tanzania 528 24 Zimbabwe 475 25 Brazil 462 26 Uganda 438 27 Kenya 435 28 Egypt 432 29 Korea, Rep. 424 30 Myanmar 364 31 Norway 351 32 Vietnam 346 33 Syrian Arab Republic 315 34 Mauritius 310 35 Brunei Darussalam 309 36 Philippines 267 37 Malawi 262 38 Oman 259 39 Algeria 225 40 Cambodia 210 41 Mongolia 193 42 Ghana 185 43 Uzbekistan 172

Table 2.3 (Continued)

Country of Origin 44 Afghanistan 168 45 Guinea 168 46 Bahrain 167 47 Turkey 153 48 Chad 146 49 Morocco 132 50 Zambia 131

Source: UNESCO (2014)

2.3 Development of PrHEI in Malaysia

The development of PrHEIs has also contributed to the GDP growth of

Malaysian private education sector. Table 2.4 indicates the overall contribution of private education sector towards the GDP of Malaysia from the year 2005 until 2011.

The percentage share of GDP by private education sector increased by 0.2% from

0.5% in year 2005 to 0.7% in year 2011. Figure 2.1 further explains the contribution of each type of private education sector to GDP Malaysia in detail. The 10 types of educational services identified are pre-primary education, primary education, general school secondary education, college and university education, technical and vocational education, sports and recreation education, cultural education, tuition centres, driving school and other education (Department of Statistics, Malaysia,

2012). Figure 2.1 presents the percentage distribution of value added by the type of private education sectors in 2010. College and University education contributed

RM3.8 billion from overall private education sector contribution. Comparatively general school secondary education contributed RM583.7 million and other education around RM571.5 million. Table 2.4 and Figure 2.1 clearly show that college and university education play an essential role in Malaysian GDP.

Series of new rules and regulations were implemented to enable a systematic growth of PrHEIs. To assure the quality of education provided by PrHEIs, The

National Accreditation Board (LAN) was introduced in year 1996 within the country.

Followed the development of LAN, National Council on Higher Education Act, 1996 is introduced for formulating policy for both PuHEIs and PrHEIs. In the same year

Private Higher Education Institutions Act 1996 is introduced. This act draws the guideline for standard operating procedures for PrHEIs operations and procedures in establishing branch campuses with the monitoring of MOE.

Table 2.4 Contribution of Private Education Sector to GDP at Constant Prices

Economic Year RM Annual Percentage Percentage Share to Activity Million Change GDP

2005 2,925 n.a. 0.5

Private 2006 3,220 10.1 0.5 Education Sector 2007 3,784 17.5 0.6

2008 4,476 18.3 0.6

2009 4,864 8.7 0.7

2010 5,200 6.9 0.7

2011 5,591 7.5 0.7

2012 6,021 7.7 0.7

Source: Department of Statistics, Malaysia (2012)

70 College & University Education 60 Other Education 50 General School Secondry 40 Education Pre-Primary Education 30 Tuition Centres 20 Cultural Education 10 Driving Schools 0

Figure 2.1: Percentage Distribution of Value Added by Type, 2010 (Department of

Statistics, Malaysia. 2012)

To cater the demand of higher education and to accommodate the need of the community and industry, universities management need to be modernize. Thus, in

1996 University and University Colleges Act 1971 were amended accordingly.

National Higher Education Funding Board Act was introduced in 1997. This act draws standard operating procedures in relation to financial aids for both PuHEIs and

PrHEIs. The introduction and implementation of new rules and regulations enabled a systematic growth of PrHEIs. The growth is evident in the number of PrHEIs from the year 2000 to May 2015 (Table 2.5). In June 2016, there were 480 PrHEIs in

Malaysia; 44 PrHEIs were with university status, 29 PrHEIs with university college status, 9 foreign university branch campuses and 398 PrHEIs with college status

(MOHE 2016).

Table 2.5

Categorization of Private Higher Education Institutions

No Status Units 1 University 44

2 College University 29

3 Foreign University Branch campus 9

4 College 398

Total 480

Source: Ministry of Higher Education Malaysia (2016)

As a result of PrHEIs‘ rapid expansion, the competition between PrHEIs in attracting international students turns into an intense scenario. Thus, PrHEI will use all available marketing platforms to advertise about their university which give them the upper hand in attracting international students. In contrast these methods overburdened international students with abundance of information from different platform by PrHEIs. According to Gatfield et al., (1999), international students are burdened with information from various marketing strategies which failed to provide the information needed and sometimes overload the international students with unsuitable information. Mortimer (1997); Hesketh & Knight (1999); and Gatfield et al., (1999) have each conducted their own research on the dissemination of HEI‘s marketing information by print medium effect in United Kingdom and Australia. In all the three research, there was a significant gap identified. The gap indicates that international students did not receive adequate information related to ―academic, practical aspects of the programme and other information such as country image, city effect social life and institution image‖ (Hesketh et al., 1999, Ismail & Leow, 2008).

Hence, international students find alternatives to find more formal and informal

44 information through other sources such as eWoM before they enrol into the HEI of their choice. As for this research, the focus will be on international student‘s enrolment decision in Malaysian PrHEIs of their choice.

2.4 Theoretical Model of HEI Choice Process

There are number of theoretical models which explain the fundamentals on student‘s intention to enrol in their choice of HEIs. In spite of the fact that these models may have been originated many years ago, proceeding the Internet age, they are as yet legitimate with regards to and as a premise to investigate the advancement of elements affecting the students HEIs choice decision. For example, the qualities portrayed in Hossler & Gallagher (1987) Model of College Choice were additionally specified in the recent studies by Chen & Zimitat (2006), Mazzarol & Soutar (2002) and Pimpa (2003). Three models can explain the conceptual approach of the HEIs choice process; they are economic models; sociological models and combined models.

Econometric model or economic model specifies that students exclude and evaluate the alternatives to post-secondary education based on the following criteria: geographic location, economic factors and academic factors. This model looks into the relation between HEI enrolments choices and search for non-academic options, for instance econometric model focused on HEI choice and the relation towards job specifications and individual choice (Jackson, 1982). Thus, students will choose HEI that can give them better options after their higher education, such as job, salary and social status (Hossler & Stage, 1992). This model assumes that ―as students consider colleges, they can detail the advantages and disadvantages of each, associate a utility or a value with the attributes of each, make reasonable assumptions about the

45 outcomes of one decision over another, and then choose more or less rationally in order to maximize benefits and reduce costs‖ (Figure 2.2).

Figure 2.2: Economic Model of HEI Choice

Although economic models detail out on the student HEI choice process, it has few weak points. This model believes that students have the complete knowledge which guides them to a rational HEI choice decision, but this is not true all the time

(Hossler & Gallagher, 1999). Additionally, economic models did not highlight the importance of the institution itself (Chen & Zimitat, 2006). Sociological model addresses the weakness of economic model, by understanding the influence of an institution on HEI enrolment choice process.

The sociological model identifies a diversity of individual and social aspects that lead to educational aspirations. Sociology is a science which tries to clarify sequences of action and their effects in relations to social action (Weber, 1946).

Sociological scholars would discuss that a student‘s university decision is associated

46 with characteristics that an individual owns. The characteristic an individual owns can influence the category of HEI an individual attends (Hearn, 1991).

Characteristics related with student's HEI decision are more often than not socioeconomic status (Hearn, 1991) and race or ethnicity (Perna, 2000, Perna & Titus,

2005). Perna & Titus (2005) theorized that education prompts social generation and social stratification in a way that advantages the exclusive classes. Students that have elevated amounts of social capital are compensated with larger amounts of scholarly accomplishment. Thus, when they enter the workforce, they can acquire higher paying occupation and reputable positions in the society. As a matter of course, those students who are members of the working class are not rewarded for their cultural capital but are groomed for working class jobs.

Sociological model would also emphasize that the cultural value and consumptions form that one inherits influence the educational outcomes. According to Perna & Titus (2005), cultural capital would comprise inherited substances such as art, education and language. Sociological model correspondingly believe that student‘s HEI choice is influenced by relations between and among individuals

(Perna & Titus, 2005). The commitments, desires and dependability of social structures found beneficial capital assets for an individual (Lin & Vogt 1996). The significance of analysing the impact of sociological model on instructive results is featured by the way that individuals, particularly HEI bound individuals are affected by those found in their prompt environment, and characteristic in the structures of the relationship between and among community. Such association and participation in communities can have both positive and negative outcomes for the individual and the community (Hearn, 1991).

Figure 2.3: Sociological Model of HEI Choice

Sociological models (Figure 2.3) were explored to understand the desire and aim of an individual who is in the process of deciding HEI. Earlier research using social models are focused towards educational and status achievement of an individuals. According to Jackson (1982), sociological model is utilized to understand the social and individual factors that being influence in an individual HEI and job selection. Relatively sociological model is used to investigate the HEI choice

(Hossler & Gallagher, 1987). The model has given a clear understanding on the influence of parents, friends and academic performance (Sewell & Shah, 1968) as indicators of enrolment in universities. Econometric and sociological model has their weaknesses whereby econometric model focuses on cost benefit meanwhile sociological focuses more on people influence. This has led to the development of combined model of HEI choice by Jackson (1982), and Hossler & Gallagher (1987).

Indicators from economic and social models are utilized in developing the combined model. Several established combined model that examined the aspects that define

48 students‘ enrolling into the HEI of their choice, and this model can be explained by

Jackson (1982), combined model and Hossler & Gallagher (1987) combined model.

Jackson (1982) developed a model that combined both the sociological and economic influences of the choice process – combined model of HEI choice. His model separated the choice process into three phases: preference, exclusion and evaluation. Within these phases, family background and social context influence elements that ultimately lead to the HEI decision. The interrelation of these factors can be a bit confusing and is best seen in a visual flow as shown in Figure 2.4. He recognizes the first stage in the model as one that focuses more on sociological influences such as family, friends, personal aspirations and academic achievement.

Within the first phase, ―the strongest correlate of high school students‘ aspirations

(educational or occupational) is their academic achievement‖ (Jackson, 1982).

However, Jackson shows that these factors are only preferences and have no direct influence on choice but influence other areas that ultimately lead to a decision.

The second phase of the model tends to introduce the economic influences of

HEI choice. This includes the financial aid offered by the institution and the expenditure of overall cost which include fees, living cost and other related costs.

Included in this phase is the geographic location of the institution as it can be directly tied with cost factors. This stage of exclusion begins the use of resources provided by the institution that may help inform the students about their choices. Students exclude HEIs as unfeasible based on partial information when more information would lead them to do otherwise, and quite reasonably they do not consider HEIs unknown to them or about which they can obtain no information (Jackson, 1982).

This is the point in the choice process where the accuracy and availability of information from an institution is vital to avoid being excluded from consideration.

In looking at the current use of technology in this phase, Cox, Enns & Clara (2002) indicates that prospective students are further expected to use a website to exclude an institution than to include it.

Finally, the third phase of Jackson‘s model is where students evaluate their options and ultimately make a final decision. In this phase, each student develops their own rating scheme to which they use to rank institutions and ultimately make a decision that makes the most sense. Jackson (1982) notes that although students create their rating scheme in this final phase, the opinions developed from the creation of their HEI set in the exclusion phase are seldom changed by the rating scheme, giving those decisions direct influence on the ultimate choice decision.

Jackson model did not explain how the initial institutional processes are shaped; nevertheless, it is student centred model. Hossler & Gallagher (1987) addresses the weakness of Jackson (1982), combined model with the introduction of three stage college choice model.

Figure 2.4; Combined Student HEI Choice Model

Hossler & Gallagher (1987) developed a three phase college choice model.

The model first phase is identified as predisposition; second phase as search and the third phase is choice. The model explains the effectiveness of individual factors and

HEI factors that define HEI choice decision. The factors such as students‘ unique individualities, education status, social significance, information search pattern in relation towards HEI choice decision are considered as individual factors.

Subsequently HEI features and brand are considered as organizational factors.

Combined model explains the anticipated result from each 3 phases as shown in

Figure 2.5.

Influential factors Model Individual Factors Organizational Student Outcomes Dimensions Factors

Predisposition  Student  School  Search for (Phase One) Characteristics characteristics  College  Significant others options  Educational  Other activities options

 Student preliminary  College and  Decision Search college values University search  Other (Phase Two)  Student exploration activities options actions

 Selection set  University  Choice Choice courtship (Phase Three) activities

Figure 2.5: Three-Phase Model of HEI Choice (Hossler & Gallagher, 1987)

The first phase of predisposition is similar to Jackson‘s (1982) stage of preferences in which it involves in understanding the students‘ preference and aim in pursuing higher education. In this phase, students will consider the individual factors and organizational factors before looking for HEI choices or any other choice available for the students (Hossler & Gallagher, 1987). Several factors that have been found to affect students‘ decision towards HEI include socioeconomic status,

51 students‘ academic accomplishment, parents‘ education levels, ethnicity, gender, encouragement from high school counsellors and teachers, support from peers, and parental expectations and encouragement (Hossler & Stage, 1992). This is followed by students actively look for information about HEI and comparatively HEI search for students‘ information. Hossler & Gallagher (1987), characterize this phase with the initial interaction with the institutions in directive to collect additional information.

The search phase also identified as the stage when students reduce the number of institutions from every school to only those that meet a set of preferences established. This helps to create the desired outcome of a choice set. Factors that may be considered by students at this second phase include cost of attendance, availability and offers of financial assistance, and academic reputation. It is important to note that in the search phase, there is still a possible outcome of other options to HEI, showing that the search process could still influence whether a student wishes to pursue HEI.

The final phase of the model is the choice process of the student. This is when the student evaluates all the information prior to their choice decision.

According to Hossler & Gallagher (1987), in this phase HEI will begin to communicate with the students in which highlighting all the activities and features of the HEI, thus influence the students HEI choice decision. The major difference between Jackson (1982), model and Hossler & Gallagher (1987), model is the understanding the relationship between individual factors and organization factors which lead to student enrolment. Jackson model is student centred model which fail to identify the importance of HEI internal and external environment. Comparatively

Hossler & Gallagher (1987) combined model identifies the individual and

52 environment factors and their affiliation which determine international students HEI enrolment decision in detail. Thus, Hossler & Gallagher (1987) combined model is adopted and adapted for this study in understanding the information orientation searched by international students in their HEIs enrolment choice, as Hossler &

Gallagher (1987) combined model discusses the overall perspective of college choice decision by students.

2.5 International Students Enrolment Decision Making Process

According to Griffin (2007), the process of selecting one possibility from a set of possibilities is defined as decision making. Griffin (2007), further defined decision making as a process that require understanding the environment which the decision need to be made, evaluable all the options available, choose the best option and decide on the action. These processes can be associated with HEI choice decision by students. Adding to Griffin (2007), definition, Marinage & Carter (2007), defines students HEI decision making as a process which involves many complex stages. According to Hanson & Litten (1989) selecting one better option between collections of options is the main aim of the decision making. Thus, from the above statement decision making can be concluded as complex processes which evaluate all the possible options via few stages prior to the decision action.

Decision-making is a necessary component of everyday human life. Some decisions, like what to eat for lunch are simple, but others, like whether to go to HEI are more complex. People make decisions based on a number of factors, some that are logical and others that seem irrational (Castleman et al., 2015). Economists have traditionally assumed people make financial decisions, including the decision to attend HEI based on thorough cost-benefit analyses. But in practice, this is simply

53 not true (Castleman et al., 2015). A cost-benefit analysis requires access and awareness of complete information. It also assumes that people are rational decision makers. In terms of the decision to attend HEI, the cost-benefit theory assumes students and their families are rational decision makers and it would posit that the vast majority of students choose post-secondary options that maximize short and long term benefits related to the costs of HEI (Castleman et al., 2015).

Not only most students does nothing related to complete information with regards to HEI including HEI costs, HEI geographical information, detail programme evaluation and HEI image in general, but they might be overloaded with marketing information which has no value to students in deciding their choice of HEI enrolment. Therefore, student‘s especially international students will search for information from other source such as in eWoM apart from formal information that is provided by the HEI marketing channels. International students critically review the information in eWoM before the HEI enrolment choice is finalised. Hence, HEI enrolment choice is related to the information orientation searched via eWoM by international students and how useful the information to be adopted in the process of

HEI enrolment choice decision.

According to Litten & Brodigan (1982), HEI student decision choice involves complicated sequence of actions in every phase; with individual students behave differently in every phase. Litten & Brodigan (1982) identified 5 phases that determine the HEI Choice decision by students. The phases discussed by the scholar are needs and motives, information gathering, evaluating alternatives, decision and post-choice evaluation (Figure 2.6). The first phase is within the students‘ interest – need or motive, if the need is identified by the student than the students start to explore for information about the potential HEI (Phang, 2013). After that,

54 assessments among many HEIs options are evaluated critically. Once the HEI option is decided, students may take the next step which is to enrol in the particular HEI.

Needs and Motives

Information Gathering

Evaluating Alternatives

Decision and Enrolment

Post-Purchase Evaluation

Figure 2.6: Student Choice Model (Litten & Brodigan, 1982)

The student choice decision-making process generally begins with an understanding of a need. According to Van Aart (2011), need is caused by the inconsistent state between the actual and desired state of an individual and individuals believed that there are some missing part which required to be addressed.

Similarly, higher education is something that students need to address. For instance, the realization of future job and social status will create the need for students to pursue higher education. The need to pursue HEI could be vary from one student to another student, for example few students need the HEI to have successful life

(Brown & Reingen, 1987; Pimpa, 2003; Thompson, 2007; Phang, 2013), comparatively to others who is enrolled for personal reasons and wanting to be with their friends (Constantinides et al., 2012; Counsell 2011, Phang, 2013).

In the next phase, student begins to search for adequate HEI information which is related to the need. The process of searching information may start from the

55 experience and knowledge of the students itself that probably fulfil their needs which

Pimpa (2003), defined as internal search and students centred. The internal search and the amount of the information searched is correlated with the students‘ involvement in searching for the information needed (Phang, 2013) and it is subject on their level of association in the decision. According to Phang (2013), the involvement of students in searching information is related to social and economic background of the students, for instance students who are cautious on the social economic issues will actively participate in the process of information search. The significance of the involvement will be reflected in the information collection procedures and decision making process. This involvement can be seen in HEI enrolment choice decision as the decision will shape the future of the student (Kotler

& Fox, 1995; Hesketh & Knight, 1999, and Drummond, 2004). In the event of inadequate internal information, students will source for information from external sources such as eWoM. The evolution of eWoM has made it easy for students to search for information they need. International students can search for information in depth before HEI decision choice is made.

Thus, this research focuses on the categories of information orientation searched by potential students in enrolling in the HEIs of their choice. As soon as students have sufficient information, students will list the HEIs following the criteria which are established by the students (Kotler & Fox 1995). Students will evaluate all the HEIs options prior to one final HEI is selected. At this level, students might visit the HEIs they are considering and this is associated to physical proof where a student wishes to inspect some tangible parts of the offer. The significance of each criteria will be varies from one student to another student, for example students from Middle

East will prefer the HEI which uses English language as communication medium,

56 comparatively there might have few others does not like this and prefer to have their mother tongue as the communication medium. Thus it is hard to find the exact same selection criteria over two or more students (Blackwell, Miniard & Engel, 2001).

According to Galotti (1995), students do overall evaluation and define various aspects and order them in a hierarchy of importance prior to their decision to enrol.

The next phase examine discusses on the reason why student chose a particular HEI (Gorard, 1997; White, 2007). It is a critical stage in the whole HEI choice decision. Students evaluate all the HEI aspects and information gathered periodically, hence students make a right HEI enrolment decision based on their needs identified earlier. Internal information and organization information play a crucial role in this phase as students might evaluate and re-evaluate all the aspects if student has ‗a feeling‘ of perceived risk about their decision as there is usually a high level of involvement and risk in such HEI enrolment decisions (Kotler & Fox, 1995;

Brassington, 2006). The last phase on this student choice model is evaluating the service provider which in this research is HEI. The evaluation will reflect on all the promises raised by the HEI in the earlier phase of the process (Brassington, 2006).

Students will evaluate the HEI education standards, experience in campus and the value of the degree (Lovelock & Wirtz, 2004). Thus, creating a scenario that leads to student‘s dissatisfaction with negative comments or towards student‘s satisfaction with positive comments about HEI (Kotler & Armstrong, 2008).

From the above discussion, it can be concluded that information search process is the utmost important process in HEI enrolment choice. Over the years, the

HEI enrolment choice decision has been influenced by numerous features at the search stage. One of the features is the communication platform (Kotler &

Armstrong, 2008). Traditional communication methods have been dominant in past

HEI enrolment choice process. Currently, with the advent of Web 2.0, another communication platform is presented, which is – eWoM for international students to search for information.

2.6 The Information Search Process in a Digital Environment

Based on the above literature review, information search by international students seem to be an important stage in HEI enrolment decision. The information search process is considered as an important process regardless of search venue or printed or digital medium is used to search for the information. Bonnema & Van der

Waldt (2008) highlighted the importance of the Internet in the search stage for students in the digital environment. Internet has allowed students to search and find information as fast as they could and also gather reliable and credible information from variety of source (Bonnema & Van der Waldt, 2008).

The Internet has a high degree of interactivity which often exists to only a limited extent, especially in traditional marketing communication. Internet became even more powerful in interactive communication with the introduction of Web 2.0.

The development of Web 2.0 give opportunities for individuals to retrieve and gather information from various platforms, for example web sites, blogs and social network which allows individuals to participate actively in two-way communication – eWoM.

Electronic word-of-mouth allows individuals to search information from user generated content (Alby, 2008; Huber, 2008; Bauer, Große-Leege & Rösger, 2007) which are more trustworthy and useful compared to market generated content. Thus changed the interpersonal communication method (sender – message – receiver) and

58 introduce the new communication method, a forwarder or transmitter (Brown,

Broderik & Lee, 2007).

To understand further on the effect of eWoM, Komjuniti agency carried out a ten-week study in 2008 on three brands which comprise of 1400 consumers. Out of

1400 consumers, 400 consumers are those who are actively involved in Internet brand communities. Comparatively 1000 consumers are those who do not actively involved in Internet such as social media and these consumers are identified as control group (Komjuniti agency, 2009). The result from this study further proved the significance of eWoM, where consumers involved in the Internet actively exchange their opinions, suggestion and thoughts about brand of product with seventeen other internet consumers on average. By contrast, only two members of the control group spoke about the three brands advertised by traditional marketing methods. The study also highlights the positive effect eWoM by viewing the sales of a particular product. Traditional advertising and its influence in sales could be identified with the higher sales in the first two week of the advertising.

Comparatively there was a 29% upsurge in the sales of the products advertised through eWoM. The subsequent weeks, the result demonstrated a 14% increase in sales based on eWoM, though the sales increase aided by traditional advertising was a moderately low 2%. This study further confirmed that, consumers who had acquired products through eWoM have the tendency to repurchase and develop brand loyalty (Komjuniti agency, 2009).

In addition to Komjuniti agency study in 2008, Deloitte – accountancy and consulting firm investigated on the readiness of organization to involve in eWoM.

The findings were reported in ‗Tribalisation of Business 2009‘, which clearly highlighted that 94% of the approximately 400 companies surveyed are ready to

59 invest resources in eWoM and to enter into a discussion with consumers, partners and employees for effective organization operation. Comparatively 6% organization plan to decrease their investment in developing eWoM. Thus, from the above discussion it could be concluded that, eWoM activities are widely recognized as an important instrument in marketing strategies for an organization (Huber, 2008).

To understand further on the differences between social media and eWoM, the following definition from Kaplan & Haenlein (2010) and Chan & Guillet (2011) was discussed. According to Kaplan and Haenlein (2010) defined it as ―a group of

Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated

Content‖. There are six types of SM: blogs and micro-blogs, virtual worlds, collaborative projects, content community sites, sites dedicated to feedback and social networking sites (Chan & Guillet, 2011). These means are used as platforms for engaging in relationships, exchanging views, provoking debates, questioning and sharing information (Chan & Guillet, 2011). Comparatively eWoM is defined as

―any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet‖. Thus it can be concluded that social media is a platform for online users to engage in a relationship whereas eWoM is any information that is shared among the online users in social media.

2.7 Transformation of Word-of-Mouth to Electronic Word-of-Mouth

The term of WOM is pioneered by George Silverman, a psychologist in the early 1970s. George Silverman created what he called "teleconferenced peer influence groups" in order to engage physicians in dialogue about new

60 pharmaceutical products. George Silverman discovered that one or two physicians who were having good experiences with a drug would sway an entire group of doubters. They would even sway a dissatisfied group of ex-prescribers who have had negative experiences (Silverman, 2009). Definitions of WOM can be found on various articles and journals. According to Kozinets et al., (2010) WOM is explained as intentional involvement of marketers in communicating with consumers. In addition, the scholar also claims that WOM is interactive communication among two different individuals relating to a product or service of common interest. In the

Journal of Marketing Research, WOM is focused on communicating information about a specific product or service characteristics and the retailer within the social group of an individual (Westbrook, 1987). Justin & Paul (2006) gives a more specific and restricted definition of word-of-mouth as oral, person to person communication between a receiver and a communicator whom the receiver perceives as non- commercial, concerning a brand, a product or a service.

According to Arndt (1967), WOM is up close and personal face-to-face communication about a brand, product or service between individuals who are seen as not having any associations with a business entity. As of late, American

Word-of-Mouth Marketing Association (WOMMA), established in 2005, defined

WOM as the action of consumers in sharing their opinion and suggestion to other consumers (WOMMA, 2008). WOMMA additionally defines WOM as a platform for consumers which allow them to discuss about companies‘ products and services, and making it less demanding for that discussion to occur. Consequently, Word-of- mouth isn't tied in with generating discussions between consumers yet rather to urge these discussions and to anchor them in the overall marketing strategy (WOMMA,

2008, and Sernovitz, 2007). All the definitions above underline on the three

61 significant elements that every single other definition are attempting to clarify. The three elements are; first, interpersonal communications second is commercial content and the third element is non-commercial motivations which are the key elements of

WOM (WOMMA, 2008). WOM has been viewed as an essential element in the purchasing behaviour of consumers for quite a long time. As of late, many organizations have found WOM viability of by means of studies like those referred in the accompanying literature review (Table 2.6). This brief literature on WOM communication will demonstrate the immense improvement, significance and effect of WOM on marketing technique which guides the organization for effective business.

Table 2.6

Most Important Research Findings in the Main Periods of Development of Word-of- Mouth Communication

First Author Year Subject of Paper Brooks 1957 Word-of-mouth advertising in selling new products

Dichter 1966 How word-of-mouth advertising works

Arndt 1967 Role of product-related conversations in the diffusion of a new product

Arndt 1968 Selective processes in word of mouth

Bickart 2002 Expanding the scope of word of mouth: Consumer-to-consumer information on the internet

Wirtz 2002 The effects of Incentives, deal proneness, satisfaction and tie strength on word-of-mouth behaviour

Dellarocas 2003 The digitization of word of mouth: Promise and challenges of online feedback mechanisms

Godes 2009 Using online conversations to study word-of-mouth communication

Brown 2007 Word-of-mouth communication within online communities: conceptualizing the online social network

Cong & 2017 A Literature Review of the Influence of Electronic Word-of-Mouth Zheng on Consumer Purchase Intention Source: Sernovitz (2007)

In the 1960‘s, most of the research were concentrated in understanding the correlation of WOM on marketing and advertising (Brooks, 1957). The first empirical study that focuses on significance of WOM in marketing was led by Arndt in 1967. Arndt (1967) investigated the correlation of significance of WOM and consumer purchase behaviour on new food product. Dichter (1966), conducted in- depth interviews with 255 consumers in 24 regions in The United States and investigated the aspects of consumer psychology with respect to WOM. Likewise, in the mid-1980s Richins (1987), further explored the relationship between customer satisfaction and WOM, with focusing on the negative WOM and the correlation of negative WOM used and consumer dissatisfaction (Richins, 1987). The findings of

Richins (1987) are similar to the earlier scholars who investigated the correlation between WOM and purchase decision. Richins (1987) highlighted that, the negative and positive WOM will influence the purchasing decision of a consumer.

In the early-2000, the effectiveness of communication and WOM was the main focus of research. Scholars are interested in investigating the positive WOM and the relation towards customers‘ behaviour. For example, Gremler (2001) investigated the relationship between generating positive WOM and customer-employee relationship. Gremler (2001) confirmed that there will be a significant positive WOM if the communication between employees and consumers are interactive which develop a friendly bond between them. In Gremler‘s study, the propositions were examined using information collected from bank consumers. A significant outcome in Gremler‘s investigation is that the presence of interactive relationships among staffs and consumers is considerably associated with consumer‘s WOM behaviour.

According to Cong & Zheng (2017) electronic word-of-mouth information has gradually become an important factor of affecting consumer purchase intention.

Cong & Zheng (2017) further explained that, there are three independent variables which include sender characteristics, information characteristics and receiver characteristics of electronic word-of-mouth, trust as the intermediary variable, involvement as the moderator variable, the article carries on the literature carding of the influence electronic word-of-mouth on consumer purchase intentions, which provide the importance of eWoM development. From table 2.4, we can perceive the importance and the evolution of WOM from the early 1950‘s till early 2000. In addition, figures 2.7, 2.8 and 2.9 clearly presented the evolution of eWoM for further understanding.

Figure 2.7: The Organic Inter-Consumer Influence Model

Figure 2.8: The Linear Marketer Influence Model

Figure 2.9: The Network Co-Production Model

Source: Kozinets et al (2010)

The organic inter-consumer influence model (OICIM) is the simplest understanding of consumer word-of-mouth (Figure 2.7). OICIM if focused in developing an interchange platform for exchanging information related to product

65 and brand. In OICIM WOM take place between consumers and an organization without any motivation, influence or expecting outcome. Thus WOM in OICIM is considered as ―organic.‖ Gatignon & Robertson (1986), views that WOM will take place by it if marketers developed a proper marketing strategy to disseminate product or service information

The linear marketer influence model (LMIM) discussed about the consumers who are influential in the spreading WOM among the community (Feick & Price,

1987; King & Summers, 1976). Therefore, organization needs to get close to these persuasive, respected and trustworthy WOM spreading consumers or opinion leaders as identified by few scholars to create a positive view (Figure 2.8). LMIM allows organization to market their product indirectly through these opinion leaders rather than the salesman (Dichter 1966). Consumers believe that the information disseminated by opinion leaders as ―realistic information‖ and communicate marketing information without any changes from any consumers. Consumers receive the information as accurate as possible (Brooks, 1957; Katz & Lazarsfeld, 1955).

Marketing has evolved from one-way communication to two way interactive communications, in which consumers, consumer networks, groups and communities are identified as an important element in WOM communication (Cova & Cova,

2002; Hoffman & Novak, 1996; Muniz & O‘Guinn, 2001). WOM communications are thus co-produced in consumer networks – The network co-production model

(NOPM) (Figure 2.9). There are two important elements in NOPM, first is marketers‘ developed new strategy in identifying the target market and marketing strategy to influence the consumers or opinion leaders. Next element is to understand the importance of co-production value in consumer network and adopt towards

66 organization success. NOPM effectiveness is further investigated by scholars in line with the development of Internet and Web 2.0

The Internet has provided consumers a new platform to communicate with each other and more importantly, the way we shop. Thus traditional WOM communication has evolved to electronic word-of-mouth (eWoM) communication.

Prior to the introduction of eWoM, consumers highly reliant on marketer generated information or advice from family and friends through face to face communication.

This scenario changed, when eWoM become more common method in searching and gathering reliable information by the consumers from network that they trust. Thus, eWoM developed a platform for consumers to socially communicate with one another, discuss on products or service related information which allows the consumers to make informed purchase decision.

According to Kaptein (2012), eWoM is specified as an approach that influences the substantial power of individuals to motivate other individuals in their online social network via computer assisted communication medium.

Hennig-Thurau et al., (2004), defined eWoM as any positive or negative information made by prospective, actual or previous consumers related to a product or service which is made accessible to a multitude of individuals and organizations through the

Internet. Goldsmith (2006), characterized eWoM as a casual communications focused on online users who use internet for searching information related to their interest of product or service and the sellers. All the three eWoM definitions above highlights that eWoM is an informal communication between consumer-to-consumer in online environment.

The power of eWoM influencing online consumer‘s decision clearly shows the dynamic and unique character of eWoM. Kozinets et al. (2010) identifies six major characteristics that define the unique nature of eWoM. The first character identified by Kozinets et al (2010) is enhanced volume of information disseminated by eWoM.

According to Liu (2006), the greater the volume of eWoM, the more likely a consumer will be aware about a product or service. Consequently, greater awareness tends to generate greater sales. Hence, eWoM conversations are asynchronous and are competent to influence a vast number of people in a short time. Consequently, both communicators and consumers have considerably more options available for spreading and consuming opinions to greater awareness (Petrescu et al., 2011). The second character discussed by Kozinets et al. (2010) is platform dispersion. Godes et al. (2004) describe eWoM as a platform for which product-related discussions are taking place across a wide-ranging society. The Internet and Web 2.0 has created a strong dispersion platform in eWoM such as online discussion forums, electronic bulletin board systems, newsgroups, blogs, review sites and social networking sites

(Goldsmith, 2006). Dispersion has two specific implications: first – the nature of the eWoM platform could have a significant impact on purchase decision (for instance, which products are discussed and how often); and second – from the measurement perspective, it is difficult to narrow down which platform to target and measure. As a result, online users have vast amount of platform to acquire relevant information.

The third unique character of eWoM addressed by Kozinets et al. (2016) is eWoM persistence. Persistence means that existing eWoM significantly influences future eWoM (Dellarocas & Narayan 2007). Electronic word of mouth is persistent and remains in public repositories (Dellarocas & Narayan 2007). This information is available ‗on-demand‘ to other consumers who are seeking opinions about products

68 and services (Hennig-Thurau et al., 2010). Thus, eWoM is endogenous (Godes &

Mayzlin, 2004). It not only influences consumer purchase behaviour, but is also the outcome of consumer purchases (Duan, Gu, & Whinston, 2008). The fourth unique eWoM character is anonymity and deception. Online users are exposed to information from anonymous resource which can be accurate or misleading information. This comprises information among organization to consumer and between individual consumers. The fifth eWoM unique character is eWoM valence.

Valence refers to the positive or negative rating assigned by consumers (typically on

1–5 or 1–7 Likert scales) when they review products and with an assigned numerical rating, there is less issue with interpreting the valence of a sender's opinion in eWoM

(Chevalier & Mayzlin, 2006). According to Li et al., (2008), there are significant association between positive or negative rating and product sales and the external influence propensity of online reviews. Chevalier & Mayzlin (2006), find evidence of confirmatory bias that drives consumers to look for affirmative evidence supporting an already-made product choice. As a result of valence rating, eWoM information becomes more salient for online users.

The final unique character addressed by Kozinets et al., (2010) is the community engagement in eWoM environment. Consumer engagement is the important element in gaining consumer loyalty, increase profit and to develop a sustainable competitive advantage. This eWoM platforms support collections of people in forming specialized, non-geographically bound consumer communities

(Kozinets et al., 2010). These platforms provide forums for consumers to discuss about a products or services and learn from other consumers on how to better use the products or services.

Kozinets et al. (2010) stressed that there were distinctive examples in the way consumers may comment on or exchange their thoughts through eWoM. Consumers may very well basically record their feelings, recommendations and remarks on products or services through the range of eWoM platforms such as blogs, micro- blogs, chat boards, chat rooms and many social network websites which are identified as eWoM platforms (Cheung & Thadani, 2012). According to Cheung &

Thadani (2012), Web 2.0 advancement has given the eWoM a wide range of platform for consumer to communicate with effortlessly and fast.

Electronic word-of-mouth platforms are categorized in two approaches first is one-to-one approach which indicates that the information is sent starting with one individual then onto the next. A classic example is when one individual send information via text to another individual or a group of individuals using eWoM platforms. For example, when a consumer suggests or comment on a product or service in eWoM platforms such as chat rooms, websites or product review websites it reaches many individuals that are actively participating in the group. The second approach is many-to-many, where information is shared and talked by many people on blogs, virtual communities, online communities and newsgroups. Next sub heading will further discuss the most utilized eWoM platforms by online consumers.

2.7.1 Electronic Word-of-Mouth (eWoM) Platforms

According to marketingchart.com (2015), Facebook, Twitter, LinkedIn, You

Tube, Google+, Pinterest and Instagram are the mostly used eWoM platforms as communication platform around the world.

2.7.1 (a) Facebook (https://www.facebook.com)

A trend in today‘s world would be social media, and one of the most famous networking site that allows us to share opinions, create profiles, upload photos and videos and on top all just keeping in touch with friends and be at par with the social trend is none other than the ever famous Facebook. Public with common interest could create private and specific groups to enhance their likings on subject matters such as fashion, cooking, grooming, sports and much more. One of the most feasible features on Facebook would be the ‗Wall‘, the god of virtual wall. A vast range of messages and postings in the form of text, audio and video can be published on the wall. The wall is another platform for users to post their status updates for the rest of the world‘s population to be notified on their daily activities. As of August 2015,

Facebook has over 1.59 billion monthly active users.

2.7.1 (b) Twitter (http://tweeternet.com)

Apart from Facebook, Twitter is another free social media application that offers consumer to broadcast their tweets or short posts online. It is a platform where it allows consumers to share posts and follow tweets from others by using different platforms and devices. A tweet can be shared by an end users very own mobile phone, a desktop or even at the website. On twitter a person‘s tweet is configured as public and this enables everyone on the social platform to view their tweets unlike

Facebook where the end user sets the restrictions. A hashtag is required to create tweets into conversational thread or connect them to a general topic. The hashtag or better said Meta – tag is a keyword expression. In general, a tweet can only contain

140 – characters due to the constraints of twitter‘s SMS system. This is because a tweet can be sent and viewed at live time similar to instant messaging (IM), just that

IM disappears but tweets don‘t.

2.7.1 (c) LinkedIn (http://whatis.techtarget.com/definition/LinkedIn)

A professional site, LinkedIn is to build one‘s professional identity and keep a brace with colleagues and classmates as well to expand search capabilities in various areas to expand and built one professional skills. The main features on the application would be the main page where a user creates his/her profile based on their employment history, education and personal achievements. The basic membership for LinkedIn is free and all networks on this platform are called

‗connections‘. The free membership is restricted to users to connect with someone they know professionally or has worked or gone to school with. This application however requires the end user to have connection to be able to have pre – existing relationship.

2.7.1 (d) YouTube (https://www.youtube.com)

A website like YouTube is designed for digital users to share video clips online as at times videos files are too large to be sent via an email thus sharing and uploading it on YouTube is viable. The benefit of sharing it online like YouTube is the user can just share the link or known as URL to their receiver to be viewed. This website enables the user or receiver to rate, share, comments and like the videos that

72 are published on the website. When YouTube was initially created the main purpose of it was to allow people to share and post original videos, but as time and technology progresses it has become a platform for users to store favourite clips, songs, jokes and also a marketing tool for companies to promote their products and services. In the new era of technology advancement, the term ‗viral video‘ is so common that anyone who wants to blast an information or make a movie famous, video clip or even product uses this method to share and increase views.

2.7.1 (e) Google+ (https://plus.google.com)

Google social networking project is identified as Google+. The Google+ configuration group looked to imitate the way individuals communicate more closely than the other social networking services, for example, Facebook and Twitter. The project‘s slogan is ―Real-life sharing rethought for the web.‖ The key highlights of

Google+ are Circles and Hangouts. Circles resemble classes for associations, to share updates specifically with various groups. Examples of such groups may incorporate family, friends, and office colleagues and individuals that you share a specific interest with. Circles might be discrete or have cover, for instance, somebody you work with who's likewise in your book club will get updates for both groups. Users outside a circle can see a list of member names but not the name of the circle. The second highlight of Google+ is Hangouts which allows user to share video chat for up to 10 people at any given time. In addition, Google+ also incorporates other

Google applications, such as, Gmail, Google Maps and Google Calendar for user ease.

2.7.1 (f) Pinterest (http://www.webopedia.com/TERM/P/pinterest.html)

Pinterest gives individuals a chance to sort and share pictures and videos from their very own media accumulation or from the websites they visit. The site's name is a blend of the words ―pin‖ and ―interest.‖ Pinterest classifications incorporate design, craftsmanship, DIY and specialties, fashion, food and drink, home stylistic layout, science and travel. Pinterest utilizes an arrangement of

"boards" which is an accumulation of photographs on any subject you choose to pin about. On the Pinterest website, the word pin is used to mean any image added to

Pinterest, while the word board means a set of pins. Pinterest includes brief descriptions of a photo; however, the fundamental concentration of the site is visual.

Clicking on an image will take you to the original source. For instance, if you click on a picture of a sports shoe, you may be taken to a site where you can buy them.

Users can browse or search for image content and follow the boards of other users and can ―like‖ or repin other users‘ pins. User also will receive notification when another Pinterest user "repins" from your board.

2.7.1 (g) Instagram (https://www.instagram.com)

Instagram name is originated from combined words of ―instant‖ and

―telegram‖. This online networking webpage challenges the supposition that taking fascinating photographs require a major massive camera and a couple of years of art school education. Instagram encourages the sharing of pictures and photographs on various stages. Instagram image filters and transforms normal images into professional like images. In addition, transferring and sharing photographs on Flickr,

Facebook, Twitter and Foursquare become quick and efficient. Many ‗selfies‘ or self-portrait shots are shared on Instagram. In addition, Instagram allows Instagram

74 users to follow other users‘ photo and can the user can be followed back by those users or other users as well.

Instagram also allows users to search and find friends that are connected to the user in different social network platform like Facebook or Twitter by using the

―Profile‖ icon on Instagram. When a user decides to follow a user, that user's

Instagram photos will appear in the user feed, which can be found under the "Feed" icon on the lower menu. In addition, Instagram user also could ―Like‖ any photo in

Instagram platform to appreciate the photography or the user also can leave a comment. Instagram isn't only a photograph application, but a great platform to share photo and receive feedback and comments from those user following the user. User also can browse through the "Explore" tab to find new users to follow and creative photos to look at.

2.7.2 Effects of eWoM Across Industry

In recent years‘ research on eWoM has increased significantly. For instance,

Dellrocas (2007) investigated the online communication methods in eBay and found out that this online communication permits the communication between consumer and seller effectively. Thus, creating a reliable and trusted communication platform for consumers to communicate within the communication platform (Fong & Burton

2006). Furthermore, Dellarocas‘ (2007), explained that eWoM facilitate an organization to build strong brand name, effective customer relationship management system and guide an organization in developing a new product for the existing market. Comparatively Hagel & Armstrong (1997), stated that eWoM develop to be a good foundation for consumers and marketers to exchange information about product or services. Thus, indirectly engage consumers and marketers effectively eWoM communities. Correspondingly Senecal & Nantel

(2004) examined the influence of eWoM on consumer product choice and found out that, those who seek advice in eWoM has the tendency to choose a product twice as often compare to those who did not seek any information in eWoM. Hence highlighting the significance of eWoM in consumers‘ product choice decision, which yet again point out the significance power of eWoM on consumers‘ product-related decision.

There are many research across several industries examine the eWoM significance towards consumer decisions, for example travel and vacation. According to Litvin, Goldsmith & Pan, (2008), the intangible nature of tourism product makes it difficult for consumers to decide on travel products, such as hotels, foods, accommodation and others prior to the consumptions. Therefore, consumers seek help from other consumers who has experienced on the related products from eWoM.

In addition, consumers also can gather genuine, useful, reliable information from those consumers who have travel experience (Litvin, Goldsmith, & Pan, 2008). Apart from the travel product, eWoM also has positive outcomes in sales of books, video games, electronic gadgets and products (Aggarwal & Prasad 1998; Cheung &

Thadani, 2012; Dellarocas, 2003; Godes & Mayzlin, 2009; Hu, Li & Zhang, 2008;

Riegner, 2007; Zhou, Lee, O‘Neil & Chen 2009).

According to Dellarocas, Awad, & Zhang (2007) eWoM‘s influence has also been examined in predicting the revenue for motion pictures. Furthermore, the scholars stated that the influence of eWoM has reacted positively compared to the traditional advertising and professional critic reviews and other salient variables.

Thus, online movie reviews in eWoM influenced consumer decisions on whether or not to watch a movie. The above literature clearly indicates the importance of eWoM in tangible and intangible products or services. According to Riegner (2007), eWoM not only influences purchasing decision in tangible or intangible products or services, but eWoM has a greater influence in more complex products or services.

According to Riegner (2007), eWoM is destined to impact purchasing choices for things that are more complex, expensive and highly coveted such as technology; consumer electronics; travel; education and less inclined to impact low-association products, products for the most part bought in stores that buyers want to see, feel or attempt on, for example, garments and furniture, and items that are close to home or private in nature, for example, monetary administrations (Riegner, 2007). As per

Riegner (2007), the costlier and profitable a thing is, the additional time a buyer will spend inquiring about on the thing and considering the perspectives of others before buying it. Riegner (2007) likewise proposes that the need to physically assess an item

(seeing it and touching it) might restrict the potential for eWoM to impact the purchase of the product.

Electronic word-of-mouth has also been found to have a strong influence on high-risk purchasing decisions such as travel (Hernández-Méndez, Muñoz-Leiva &

Sánchez-Fernández, 2013). The fact that travel products are intangible goods involving complex decisions associated with high costs leads consumers to seek a greater amount of information through a wide range of sources (Henning Thurou,

2010; Cheung, 2012; Patterson, 2006). These findings suggest that eWoM may have a similar effect on another type of complex, high-risk service purchase — the Higher

Education Institution (HEI) choice by international students.

2.7.3 Effect of eWoM in Higher Education Institution

According to Coladarci & Kornfield (2007), and Edwards et al., (2009) there are very few research that examined the eWoM significance in educational context.

The majority of eWoM in the context of education research are focused in understanding the effects of eWoM‘s on student learning, students‘ motives for using eWoM, lecturer performance, programme potential and lessons assessments

(Edwards et al., 2007; Edwards et al., 2009; Felton, Mitchell & Stinson, 2004;

Kindred & Mohammed, 2005). Although eWoM‘s precise function in the HEI choice has yet to be investigated, scholars have investigated the role of social media in the

HEI choice procedure, largely addressing on how HEIs could utilize social media to market HEI programmes (Anderson, K. J., 2005; Barnes & Lescault, 2012).

Subsequently there are few studies observed the relationship between HEI choice process and social media. According to Constantinides & Zinck Stagno (2012), students consider social media has least important, least influential and least reliable

78 in their HEI choice comparatively to the information from students‘ parents, friends, school counsellors, HEI Websites, HEI brochures and other sources of information

(Constantinides & Zinck Stagno, 2012).

Although social media such as product review sites, social networking sites, blogs, and online forums – eWoM platforms did not influence the HEI choice, but these outcomes should not be interpreted to mean that students will also set low value on eWoM information that has been exchanged between individuals and HEI choice decision. Especially in light of findings that eWoM has the strongest influence on decision-making for complex, high involvement purchases which suggests eWoM may have a similar effect on HEI enrolment choice (Hernández-Méndez, Muñoz-

Leiva, & Sánchez-Fernández, 2013; Riegner, 2007). Jang, Prasad, & Ratchford

(2012), found that consumers use product or service reviews more in the searching stage, the stage in which consumers access products for incorporation in the thought set than in the decision phase, the phase in which the information from searching phase is additionally assessed and a purchase decision is made. Furthermore, Hossler

& Gallagher (1987) identified that, the searching phase as the most influence phase in their combined model of the HEI choice process. The above discoveries recommend that eWoM may have a more significant impact during the searching phase of the HEI choice process when students are setting up their ―choice set‖ of institutions they apply to (Hossler & Gallagher, 1987). This finding likewise propose that HEI bound students would probably to search for information in the Internet, especially in eWoM throughout the HEI choice process phase to the choice phase.

According to Thompson (2007) students who are currently entering HEI are effectively connected by digital platform – Internet. In addition, these students also are identified as ―the Social-Networking Generation‖ (Thompson, 2007) due to their

79 extensive involvement in eWoM through social media. According to Junco & Cole-

Avent (2008), 72% of HEI students stated that they would be interested in instant messaging with an admissions counsellor, 64% were interested in reading blogs written by faculty members and 63% were interested in reading online profiles or blogs written by current students at the institution, and these are the most common information searched in eWoM by the international students prior to their HEI enrolment choice. This clearly illustrates the importance of information search in eWoM by international students.

2.7.4 Electronic Word-of-Mouth (eWoM) and International Students

Enrolment Decision.

The intangible nature of HEIs has made it difficult for early scholars to investigate the relationship between eWoM and the HEI enrolment choice destination by international students. Currently, HEIs are using printed medium to disseminate marketing information. According to Mortimer (1997); Hesketh et al.,

(1999) and Gatfield et al., (1999), there were significant gap between information searched by international students and the information provided by universities in their printed medium. The gap indicates that the printed documents from the HEI often fail to provide adequate academic and practical aspects of the programme information to the international students (Hesketh & Knight, 1999). The print documents also normally fail to provide relevant, accurate, timely and comprehensive information about a particular university (Gatfield et al., 1999).

Apart from academic and programme information, international students are seeking other information before making the decision on their choice of HEI.

According to Jang, Prasad, & Ratchford (2012), location of the HEI and employment

80 opportunities after graduating from the particular HEI are considered as additional information searched by international students. According to Mazzarol & Soutar

(2002), information such as HEI location, institutional character and facilities are searched by international students. According to Ching Huei, Craig & Zimitat

(2006), culture and beliefs of higher quality of foreign higher education system are additional information searched by international students. Apart from this, information about geographic nearness of the HEI destination, teaching credentials, qualification and reputation of HEI as well as the availability of various courses are among other information searched by international students (Mazzarol & Soutar,

2002). Levitz (2012), reported that HEI bound students value academic information, financial aid or tuition cost, admission process, campus visit, campus life and athletics programmes prior to their HEI decision.

Thus, international students turn to eWoM to search for information that is related to HEIs of their choice (Morris, 2012). The 2012 Social Admissions Report

(SRA) research outcome shows that 2/3 of secondary students use eWoM to find HEI and enrolment information. Social Admissions Report (2012) study also revealed that

72% out of 7000 potential college students search and gather HEI information by the use of eWoM. Among the eWoM communication platforms, Facebook is the most used eWoM platform and followed by YouTube and Twitter, while other eWoM sites trailed distantly in the Social Admissions Report (2012). The information quality and source credibility that students obtained from eWoM influenced international student‘s HEI selection. Hence, this research will focus on the information orientation relation towards international student‘s HEI choice decision.

This research will also look further on the moderating factor of information quality and source credibility of the information received by international students via

81 eWoM towards the usefulness of the information and enrolment choice of international students. The following sections will discuss in detail the entire studied variable for this research.

2.8 Information Orientation

There are four information orientations focused on this study, they are country image, city effect, higher education institution image and programme evaluation.

First information orientation – country image, positively influence the consumer decision in purchasing a product or service. According to Srikatanyoo & Gnoth

(2002), country image is identified as an influential variable that uniquely identify a product or a service. Additionally, Qureshi (1995) stated that the country image has great influence in consumer purchasing intention as well as to gain trust on the brand and quality of a product or service. Country image also play a greater role in influencing purchasing intention on unproven brand product and service. In fact, the country image is presumed to be the first foundation that consumers consider in product assessment since the attitude of consumers towards the products or services are correlated to their stereotypes about the country of origin. According to Peng,

Lawley & Perry (2000) country image is related to the consumers‘ view towards a product or service of a specific country. From the above discussion, it is clear that country image is crucial element in consumer purchasing decision.

Thus far, the researches on country image are focused towards product – tangible items (Peng et al., 2000). Comparatively there are limited country image researches focused on service items (Javalgi et al., 2001). According to Peng et al.,

(2000) country image may have a unique association for service items. Current available research shows that the relationship between country image and services

82 seems to be similar to the one between country image and products. Consequently,

Peng et al., (2000) explained that consumer choice of service is influenced by country image. In addition, the scholar also highlighted that, consumers are comfort in acquiring service from developed countries compared to developing countries, except when lower prices are considered. Subsequently country image may have influence the HEI choice decision by international students as international students prefer to continue their higher education in reputable country. Information such as host country culture, socioeconomic and academic reputation is the most searched information (International Student Survey 2014 Overview Report). This is further supported by Freeman (1999), Chapman (1981) and Cabrera and La Nasa (2000).

Freeman (1999) highlighted culture and social barriers as an important factor;

Chapman (1981) confirmed on the importance of the HEI location and Cabrera and

La Nasa (2000) further strengthen on the importance of Cultural and social capital development. Thus, this study will be focusing on these important factors compared to politic and history of the HEI host country.

Mazzarol & Soutar (2002) investigated the influence of country image and

HEI choice by students. The research further strengthens the argument of Peng

(2012), which the results indicates a strong country image significance on international students HEI enrolment decision. Thus, international students tend to first search the information about country and then the institution‘s information

(Srikatanyoo & Gnoth, 2002). Table 2.7 summarises past literature on country image related to HEI choice decision by prospective international students.

Table 2.7

Summary of Past Literature on Country Image

Researchers Information Country of study

Mazzarol &Soutar, 2002 Country Image Australia The United Kingdom

Hanapi, Zahiruddin & Country Malaysia Mohd Shah (2003)

Felix Maringe Steve Carter Country The United Kingdom (2007)

Joseph Sia Kee Ming (2010) Location of HEI Malaysia

Melisa et al., (2015) Location of HEI Malaysia

Anil Tan (2015) Country The United States of America

Source: Literature review (author)

The second information orientation that will be discussed is city effect. City effect comprise of the environment in which the service is produced. Since the education service is a complex service jointly produced with a wide group of services, the physical environment will be made up of the institution facilities and the city as a whole. Thus city effect perception will influence the decision of an international student. For example, Salamanca in Spain is well known as a city that linked closely in learning Spanish language and culture. Thus, every summer many international students visit Salamanca to learn Spanish. In addition, the beauty, history of the city and the stunning monuments create an interactive environment in

Salamanca for students to learn and communicate Spanish with other students

(Srikatanyoo & Gnoth, 2002)

According to Price et al., (2003) city effect dimension such as the strategic location of the city and good social facilities in the city will significantly influence

84 the HEI choice decision by international students. Similarly, Chen & Zimitat (2012), in their research highlighted that international students are searching and gathering information about city safety and security. Apart from those stated above, city location (Bodycott, 2009) and city cost living are other information that prospective students are searching before they make decision on the HEI of their choice. Table

2.8 summarises past literature on city effect on HEI choice decision by international students. Table 2.8 also clearly indicates the importance of the city effect in HEI enrolment choice by international students. City safety and security followed by city cost of living are the most important determinants in the city effect.

Table 2.8

Summary of Past Literature on City Effect

Researchers Information Country of study

Price et al. (2003) City social facilities The United Kingdom

José María Cubillo et City security and safety NA al.(2006) Chen(2007) City Safety Canada

Bodycott(2009) City location Hong Kong

Rodney Arambewela John City cost living Australia Hall (2009)

Ian Phau Tekle Shanka City Choice Mauritius Neema Dhayan (2010)

Melisa et al.(2015) City location Malaysia

Source: Literature review (author)

Higher education institution image is the third information orientation analysed in this study. A positive image of an HEI is able to intensely impact the decision of international students to attend a particular HEI (Qureshi, 1995; Mazzarol

& Souther, 2002). According to Qureshi (1995), the institution image comprises of the reputation of the institution, lecturer‘s proficiency, teaching quality, and the campus environment. Hence institution image is considered as the perception of international student on overall HEI. The understanding of institution image is formed from WOM, previous understanding and promotion events of the HEI

(Kotler & Armstrong, 2008). Hence, frequently the awareness of the HEI‘s superiority goes beyond its genuine superiority. Subsequently international students are more critical and analytical when selecting their HEI (Kotler & Armstrong 2008).

In line to the upward competency in HEI, HEIs need to uphold and develop an exclusive brand status in the direction of competitive benefit. The physical surroundings of HEI is also considered an important dimension in HEI image which contribute to the decision making process. According to Price et al., (2003) a well- developed and high standard facility will influence student in deciding on which HEI to enrol in. In addition, Price et al., (2003) examined a group of individuals to understand the significance of facilities and locations. Results showed that factors such as supporting services: library services; accessibility to computers and computer labs; quality of library services; availability of quiet areas; availability of areas for self-study (Price et al., 2003) are the few dimensions that comprise in HEI image that determine international students HEI choice decision. Table 2.9 summarises past literature on higher education institution image.

Table 2.9

Summary of Past Literature on Higher Education Institution Image

Researchers Information Country of study

Price et al.,(2003) HEI facilities The United Kingdom

José María Cubillo et Programme suitability NA al.(2006)

Table 2.9 (Continued)

Researchers Information Country of study

Ching-Huei Chen Craig Academic research Taiwan Zimitat (2006)

Joseph Mbawuni & Gyasi Quality of professors Ghana Nimako (2015)

Juan Antonio Moreno- Quality of professors Spain Murcia et al., (2015)

Source: Literature review (author)

International students are more information savvy and as a result of this, these students will search not only for formal information provided by a particular HEI, but also for informal information such as institution image, academic reputation, lecturers quality and proficiency, campus environment (Soutar & Turner, 2002) from a neutral person. Information of HEI image is hard to come by to international students as printed medium and traditional marketing fail to provide complete information. Therefore, eWoM provides an option to international students to search for related information of higher education from neutral party before making informed HEI enrolment choice.

Programme evaluation is the final information orientation to be discussed.

According to Peng et al., (2000) programme evaluation is considered as consumers‘ attitude towards a targeted programme. In addition, Hooley & Lynch (1981), programme suitability is the main factor for international students in deciding on

HEI. International students will compare programmes offered with those being promoted by competing institutions in order to check their suitability (Krampf &

Heinlein, 1981). Programme evaluation comprise of variety of programme, quality of programme, recognition of international body, financial matters, financial aid and

87 entry requirements (Qureshi, 1995). Table 2.10 summarises past literature on programme evaluation.

Information provided by HEI in traditional method does not provide the information needed by the prospective international students. Therefore, prospective international students are participating in eWoM to search and gather information about a particular programme (Binsardi & Ekwulugo, 2003). According to José

María Cubillo et al. (2006) programme evaluation is a significant variable in HEI decision making process. With the advance of eWoM, international students are evaluating about a HEI programme more frequently before HEI enrolment choice is finalised.

Table 2.10

Summary of Past Literature on Programme Evaluation

Researchers Information Country of study

José María Cubillo et al., (2006) Programme specialization NA

Keling, S. B. A. Krishnan, Programme specialization Malaysia A. Nurtjahja, O. (2007)

Siti Falidah Padlee et al., Programme suitability Malaysia (2010)

Joseph Mbawuni and Gyasi Programme suitability Ghana Nimako (2015)

Anil Tan (2015) Programme cost The United States of America

Joseph Mbawuni and Gyasi Programme finance Ghana Nimako (2015)

Source: Literature review (author)

All the four information orientation discussed above contributes towards HEI choice decision by international students.

2.9 Information Quality and Source Credibility

There are many researches that discussed argument quality in the context of eWoM, and it is directly related to the information itself. Argument quality also sometimes referred to as information quality (Sepideh Ebrahimi, 2014). According to Sussman & Siegal (2003), the quality of the information confined inside the information will define the significance of informational effect. Adding to Sussman

& Siegal (2003), Bhattacherjee & Sanford (2006), further explained that information quality as the influential power of information that included in a communication which leads to information usefulness for online consumers. From the above review, information quality is identified similar to the strength of information that is useful and able to influence an online consumer‘s decision. Figure 2.10 clearly indicates the direct association of information quality and information usefulness.

Information Information Quality Usefulness

Figure 2.10: Theoretical Relationship between information Quality and Information Usefulness Proposed by Sussman & Siegal (2003)

Information quality is becoming a decisive factor in eWoM platform.

Therefore, it is essential to apprehend the efficiency of information quality in the eWoM platform as information published in eWoM is now in the hands of almost any person. Thus the quality of information from eWoM is considered debatable as anyone from anywhere can disseminate the information (Cheung et al., 2008). This created a scenario where online users will be piled up with good quality information as well as ambiguous information. Hence, the qualities of information in the eWoM

89 are important factor for the online users to use and make decision. Information quality in eWoM can be determined by few constructs. According to Doll &

Torkzadeh (1988), accuracy, format and timelines are the dimensions that normally are evaluated under information quality. DeLone & McLean (2003), pointed out that accuracy, relevance, understandability, completeness, current; dynamism and personalization are the dimensions of information quality used in the recent eWoM studies. According to McKinney, Yoon & Zahedi (2002), in web satisfaction model, understandability, reliability and usefulness of information are the three key dimensions related to information quality. Table 2.11 summarises past literature on dimensions of information quality.

Table 2.11

Summary of Past Literature on Components of Information Quality

Author (s) / Information quality year Accuracy Relevance Timeline Comprehensiveness Format Understandability

Doll & √ √ √ Torkzadeh (1988)

DeLone √ √ √ √ √ (2003)

McKinney √ √ (2002)

Sussman √ √ √ √ &Siegal (2003)

Cheung et al., √ √ √ √ (2008)

The symbol ‗√‘ represents the feature considered by specific author (s) in their past literature

Therefore, it is important for this study to analyse the information quality and how it moderates the information orientation towards information usefulness and HEI enrolment choice by international students.

Source credibility is another variable that moderates and determines the information usefulness (Sussman & Siegal, 2003). Source credibility does not reflect about the information itself, but it focused on the information source credibility

(Chaiken 1980). According to Petty & Cacioppo (1986), source credibility is the level of an information source is perceived to be believable and trustworthy by information recipients. Ling & Liu (2008) explained source credibility as the extent of receiver believes on the information send by a third party. It is an approach concerning the information source that influences the receiver‘s level of confidence about what the source claims. Therefore, it is appropriate to conclude that source credibility significantly influences the information usefulness. Thus, the more credible the source is, the more consumers use the information from the source

(Ling & Liu, 2008). Figure 2.11 shows the underpinned theoretical association among source credibility and information usefulness proposed by Sussman & Siegal

(2003).

Source Information Credibility Usefulness

Figure 2.11: Theoretical Relationship between Source Credibility and Information Usefulness Proposed by Sussman & Siegal (2003)

Various scholars in particular communication area such as Hovland, Janis, &

Kelley, (1953); Kiousis (2001); Jones, Sinclair, & Courneya (2003) have found that

91 higher credibility of a spokesperson leads to more persuasive power in persuading an online consumer. According to Hovland &Weiss (1951) and Hovland et al., (1953), the role of source credibility in informational influence has been found to most significantly change a recipient‘s opinion in the direction of the source when the information is disseminated by a high-credibility origin compared to information disseminated by a low-credibility origin. According to Ko et al., (2005) the degree of consumer perception on the information usefulness and reliability is significantly relate to how credible the information source is. Walther et al., (2012) highlighted that, receiver‘s decision of the source credibility as a significant initial phase in the information persuasion procedure; it regulates how considerable an individual consequently learns from and accepts the received information. Thus, if individuals think the received information is from a credible source, an individual has an assurance to embrace the eWoM information and use them for purchase decisions.

Based on the past literature, source expertise and source trustworthiness are the two major dimensions that comprise in source credibility (Sussman & Siegal, 2003 and

Hu & Zhang, 2008). Table 2.12 summarises past literature on components of source credibility.

In the perspective of HEIs, source credibility plays an important role.

According to Cheung & Lee (2007) individuals often have a strong confidence on eWoM information credibility. In addition, Cheung & Thadani (2012) explained that consumers‘ judgement and choice is positively relates to the information source credibility. Hence, sources credibility will be a determining factor for potential users to use or not to use the information. Even though international students can acquire information orientations from a variety of source, it is imperative to recognize the source credibility of the information source. Hence, information from credible source

92 will guide the international students to use the information prior to their HEI enrolment choice.

Table 2.12

Summary of Past Literature on Components of Source Credibility

Author (s) / year Source credibility Source expertise Source Presence of trustworthiness advertisement

Cheung et al. (2008) √ √

Cheung et al. (2009) √ √

Chu & Kamal (2008) √

Zhang &Watts (2008) √ √

Au-Yeung Ying Lun √ √ √ (2010)

Wu (2014) √ √

The symbol ‗√‘ represents the feature considered by specific author (s) in their past literature

2.10 Information Usefulness

Davis (1989) introduced the construct ―perceived usefulness‖ in Technology

Acceptance Model (TAM). Perceived usefulness is related on the usage of new technology and the implication of new technology on work performance. Sussman &

Siegal (2003), believe that this construct significantly influences in information communication context. Thus, Sussman & Siegal (2003), refer perceived usefulness as information usefulness in Information Adoption Model (IAM). Sussman & Siegal

(2003), defined information usefulness as how individuals perceive the usefulness of

93 received information in eWoM, thus influence individuals on their purchasing decision.

Numerous researches has been conducted in understanding information usefulness throughout the information readers‘ information processing, and confirms that the information quality and source credibility influence the readers‘ perception of information usefulness towards particular information. In addition to Sussman &

Siegal (2003), Zhang & Watts (2008) further confirms the importance of eWoM in his exploratory research on effect of information in eWoM. According to Choo

(2002), information usefulness is seen as an intuitive social strategy of request that may result in understanding of information in detail which leads to decision making by consumers. While Choo (2002) discusses this form in the context of organizational decision-making, a few viewpoints are similarly relevant to individual decision making. Therefore, information usefulness will determine the adoption of information by users. Similarly, in eWoM environment, information usefulness plays a crucial part in influencing online consumers to adopt information.

Electronic word-of-mouth builds a platform for consumers to articulate new information, opinions and suggestion about a product or service. Consumers would evaluate these information, opinions and suggestion towards a better decision in purchasing a product or service. Information usefulness is the factor that drives all other information behaviours, since it represents the ultimate purpose for which information is needed and sought. Without giving a serious attention in understanding information usefulness, attention such as information seeking, information retrieval, information adoption or action to be taken is incomplete. Table

2.13 summarises past literature on components of information usefulness. The

94 previous literature shows that valuable, informative, helpful and instructive information are the determining construct for information usefulness in eWoM.

Table 2.13

Summary of Past Literature on Components of Information Usefulness

Author (s) / year Information usefulness Valuable Informative Helpful Instructive

Davis (1989) √ √ √

Sussman & Siegal √ √ √ √ (2003)

Cheung et al., √ √ √ √ (2008)

Cheung et al., √ √ (2009)

Cheung & √ √ Thadani (2012) The symbol ‗√‘ represents the feature considered by specific author (s) in their past literature

Information usefulness is a fundamental predictor of international students‘

HEI enrolment choice. Hence, international students will use the information orientation from eWoM when it is valuable, informative, helpful and instructive.

Hence, information usefulness will lead to information adoption and HEI enrolment decision.

2.11 Underlying Theories

Theory Reasoned of Action (TRA) Fishbein & Ajzen (1975), Theory of

Planned Behaviour (Ajzen, 1985), Technology Acceptance Model (TAM) Davis

(1989), Unified Theory Acceptance and Use of Technology (UTAUT) Venkatesh et al., (2003) and Information Adoption Model (IAM) Sussman & Siegal (2003), are few underlying theories that are used to understand the new technology phenomena such as eWoM. Over time, theories such as TRA, TPB, TAM, UTAUT and IAM has been adopted and adapted in various discipline such as sociology and marketing.

These theories are currently being improvised, developed and validated by researches from information science in order to understand and foresee the technology adoption and application (Venkatesh et al., 2003). Therefore, TRA, TPB, TAM, UTAUT and

IAM will be reviewed to assist in the development of rightful research framework for the current study.

2.11.1 Theory Reasoned of Action (TRA)

Theory Reasoned of Action is the earliest model used to explain technology acceptance. TRA was developed in the social psychology field. Fishbein & Ajzen

(1975) suggested that a person‘s actual behaviour could be determined by considering his or her prior intention along with the belief that the person would have for the given behaviour. They referred to the intention that a person has prior to an actual behaviour as the behavioural intention of the person. Behavioural intention is defined as a measuring tool of one‘s intention to perform an actual behaviour.

According to TRA, the most important determinant of an individual‘s behaviour is behavioural intention. An individual‘s intention to perform behaviour is a combination of attitude towards performance of the behaviour, and subjective norms.

Attitude, subjective norm and behavioural intention are the significant variables that construct the basis of TRA. According to Fishbein and Ajzen (1975), attitude is defined as: ―An individual‘ positive or negative feelings (evaluating affect) about performing the target behaviour.‖: Subjective norm is defined as: ―The person‘s perception that most people who are important to him think he should or should not perform the behaviour in question‖: and Behavioural intention is defined as: ―An individual‘s subjective probability that he or she will perform a specified behaviour.‖The theory can be explained by model in Figure 2.12

The person‘s belief that the behaviour leads to Attitudes towards the certain outcomes and his/her evaluations of Behaviour these outcomes

Behavioural Actual Intention Behaviour

The person‘s beliefs that specific individuals or groups think he/she Subjective Norms should or should not perform the behaviour and his/her motivation to comply with he specific referents

Figure 2.12: Theory Reasoned of Action (Fishbein & Ajzen, 1975)

Ajzen (1985) noted that the theory was limited by what is called correspondence. In order for the theory to predict specific behaviour, attitude and intention must agree on action, target, context, and time frame (Sheppard, Hartwick

& Warshaw 1988). The greatest limitation of the theory stems from the assumption that behaviour is under volitional control. That is, the theory only applies to behaviour that is consciously thought out previously. Irrational decisions, habitual

97 actions or any behaviour that is not consciously considered cannot be explained by this theory. Theory of Planned Behaviour (TPB) was developed to extend TRA theory.

2.11.2 Theory of Planned Behaviour (TPB)

The Theory of Planned Behaviour (Ajzen, 1985, 1991) is an extension of the

Theory Reasoned of Action (Ajzen and Fishbein, 1980; Fishbein and Ajzen 1975).

Even though both model have the core as behaviour, Theory Reasoned of Action

(TRA) missed some important aspects. TRA is restricting itself to volitional behaviours. Behaviours requiring skills, resources or opportunities not freely available are not considered to be within the domain of applicability of the TRA or are likely to be poorly predicted by the TRA. Theory of Planned Behaviour was developed to predict non-volitional behaviours by incorporating perceptions of control over performance of the behaviour as an additional predictor (Ajzen ,1991).

The behavioural intention in TPB directly influenced by attitude, subjective norm and perceived behavioural control. Perceived behavioural control also has direct influence towards actual use (Figure 2.13). According to Ajzen (1991) the behavioural intention only has a small amount of variance in actual behaviour, though both behavioural intention and perceived behavioural control are important predictors of actual behaviour.

There are eight variables that construct TPB. They are actual behaviour, behavioural intention, attitude, subjective norm, perceived behaviour control, attitudinal belief, normative belief and control belief. Attitudinal belief, normative belief and control belief are also known as salient belief. These salient believes are

98 considered as the determining factor of a person‘s behavioural intention and actual behaviour.

According to Ajzen (1991), attitudinal belief is defined as: ―the probability which is assumed to influence attitudes towards the behaviour.‖: Normative belief is defined as: ―are concerned with the likelihood that important referent individuals or groups approve or disapprove of performing a given behaviour.‖: Control belief is defined as: ―a set that deals with the presence or absence of requisite resources and opportunities.‖: and perceived behavioural control as ―people‘s perception of the ease or difficulty of performing the behaviour of interest.‖ The theory can be explained by model in Figure 2.13.

Attitudes towards the Behaviour

Subjective Norms Behavioural Actual Intention Behaviour

Perceived Behavioural Control

Figure 2.13: Theory of Planned Behaviour (Ajzen, 1985)

Models such as TRA and TPB are not without criticism. For example, Eagle &

Chaiken (1993) acknowledged evidence of other variables such as habit, perceived moral obligation and self-identity, that may predict intentions and behaviour in the context of TRA model, yet TPB did not address such variables. The TPB, as a replacement for the volitional control limitation of TRA suggests behaviours are

99 deliberate and planned, yet TPB does not reveal how do people plan and how does planning mechanism is related to TPB. The development of computer technology has limited the usage of TRA and TPB by scholars, hence TAM model was developed

(Davis, 1989) to understand user behaviour in computer mediated environment. The next theory presents a discussion of Davis (1989) work.

2.11.3 Technology Acceptance Model (TAM)

Technology Acceptance Model (TAM) Davis (1989) had been the mostly used and accepted model to clarify the technology acceptance by users. Theory of

Reasoned Action (TRA) Fishbein & Ajzen (1975) had been the basis of the TAM.

TRA is extensively used to determine the factors which influence a person‘s actual behaviour. TAM uses TRA as theoretical basis for specifying the relation between two key variables; (1) Perceived Usefulness (PU) and Perceived Ease of Use

(PEOU), and (2) Attitude (A), Behavioural Intentions (BI) and actual computer usage behaviour. The aim of TAM is to deliver clarification of the elements of computer adoption among users (Figure 2.14).

Perceived Usefulness

Behavioural External Variables Attitude Actual Usage Intention

Perceived Ease of Use

Figure 2.14: Technology Acceptance Model (Davis, 1989)

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Perceived usefulness and perceived ease of use are the two significant variables that construct the basis of TAM. Perceived Usefulness (PU) is identified as the significant to whom a person trusts that using a specific system would improve his or her work performance within an organizational context, and Perceived Ease of Use

(PEOU) is defined as the degree to which a person believes that using a particular system would be free of effort. The initial model TAM suggested by Davis (1989), explained that PU and PEOU forecast attitude has relations with behavioural intention and the actual usage (Figure 2.14). TAM has evolved ever since it was introduced. Later development from Venkatesh & Davis (2000), suggest that perceived PU and PEOU influence the behavioural intention of an individual, thus eliminating the need for the attitude variable which is shown in Figure 2.15. At the same time, the attitude variable had eliminated any unexplained direct influence observed from the system characteristics to the attitude variable (Venkatesh & Davis,

2000).

Perceived Usefulness

Behavioural External Variables Actual Usage Intention

Perceived Ease of Use

Figure 2.15: Technology Acceptance Model (Venkatesh & Davis, 1996)

According to Davis (1996) system characteristic‘s, training, user participation in designing system, computer self-efficacy and the procedures in implementing the

101 procedures are the external variables that encompass in TAM model. However, as

TAM continued to evolve, new variables were introduced as external variables affecting PU, PEOU, BI and actual usage or behaviour. Among the most frequently referenced are: system quality, compatibility, computer anxiety, enjoyment, computing support and experience (Lee, Kozar & Larsen, 2003).

Over the time, TAM has become a powerful model in understanding the acceptance level of new technologies by individuals‘. However, the model still has several shortcomings. According to Sun & Zhang (2006), TAM has two major shortcomings; the first is the explanatory power of the model, and the second is the unpredictable relationship between constructs. According to Legris, Ingham &

Collerette (2003), generalizations of findings is one of the shortcomings in TAM, as the sample choices are from university students or professional users. Taylor & Todd

(1995) and Venkatesh et al., (2003) further explained that TAM present limited guidance in understanding the TAM usage through design and implementation which is another shortcoming of TAM. According to Davis (1989), TAM clearly explained the importance of information usefulness and ease of use of a system, but failed to address the aspects of enhancement such as flexibility, incorporation, completeness of information, and information currency. The failure of TAM in addressing these aspects, thus TAM2 is developed.

TAM2 is the extended version of the original TAM. TAM2 is developed to describe perceived usefulness and usage of intentions in relations of social stimulus and cognitive influential process. According to Venkatesh & Davis (2000), TAM2 performed well in both voluntary and mandatory environments with exceptions that subjective norm had no effecting voluntary settings. Figure 2.16 shows the proposed model referred to as TAM2. The new model includes additional theoretical

102 constructs covering social influence processes (subjective norm, voluntariness and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability and perceived ease of use).

Experience Voluntariness

Subjective Norm

Image Perceived Usefulness Job Relevance

Intention to Usage Output Quality Use Behaviour

Result Perceived Ease Demonstrability of Use

Figure 2.16: Technology Acceptance Model 2 (Venkatesh & Davis, 1996)

Venkatesh (2000) explored further on antecedent of perceived ease of use in

TAM2 and introduce to TAM3 (Figure 2.17). Venkatesh & Davis (2000) identifies and adds two main groups for perceived ease of use: anchor and adjustments.

Anchors were considered as common principles related to computers and computer procedure, whereas modifications were considered as opinions which is designed based on through knowledge.

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Figure 2.17: Technology Acceptance Model 3 (Venkatesh & Davis, 2000)

Various scholars use TAM, TAM2 and TAM3 especially in testing the acceptance of new technology use. Table 2.14 summarizes several of the main significant research associated to TAM, TAM 2 and TAM 3.

Table 2.14 Summary of Selected Studies Related to TAM

Author Technology Respondents Objective of the Outcomes examined study

Davis (1989) e-mail & file 112 employee Development of Two 6 item editor; graphic 40 evening valid measurement scales with systems MBA scale for PU & high reliability students PEOU for the PU & PEOU

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Table 2.14 (Continued)

Author Technology Respondents Objective of the Outcomes examined study

Davis et Word 107 MBA Comparing TRA to Both models al. (1989) processor students TAM in predicting postulated intentions to use and that BI is the the role of attitude in major mediating the effect determinant of of beliefs on usage behaviour. intentions Attitude has no mediating effect between PU or PEOU and BI.

Davis et al. Word 200 + 40 Testing enjoyment as Usefulness & (1992) processing MBA a determinant of enjoyment program+ students computer use explained 62% Graphic and 75% system of variance in usage intentions and were found to mediate the effects on usage intention of PEOU & output quality.

Davis & WordPerfect+ 182 + 214 + Testing for any The 3 Venkatesh Lotus 312 discernible effect on experiments (1996) university the psychometric showed that students properties of TAM‘s TAM measures measurement in the group format best predict and explain user acceptance of IT.

Agrawal & Software 230 Investigated the role Validated the Prasad applications in technology of personal relationship (1999) PC literate differences with Between employees regard to technology individual acceptance differences and technology acceptances mediated by the TAM beliefs.

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Table 2.14 (Continued)

Author Technology Respondents Objective of the Outcomes examined study

Venkatesh Online help 70 employees Determinants of Anchor elements (2000) system 160 employee PEOU based n were used to Multi media 52 employees anchoring (self- form PEOU system efficacy, about a new Windows 95 facilitating system and with conditions, computer increased anxiety, and experience computer adjustments play playfulness) and an important adjustment role in perspective determining moderated by system specific experience PEOU

Venkatesh Data & 246 Investigating SN, Women are & Morris information employees experience & gender influenced by (2003) retrieval from 5 differences in the PEOU & SN in system different context of individual making their organizations adoption & usage of adoption technology at the decisions while work place men consider PU only.

Wixom & Data 456 The model explicitly Results Todd (2005) warehouse employees distinguish the supported the predefined from seven system based beliefs application of reporting organizations and attitudes information software from different (satisfaction & system industries perspective) satisfaction as from behavioural external beliefs and attitudes variables to (technology traditional TAM Acceptance perspective).

Source: (Venkatesh & Davis, 2000)

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2.11.4 Unified Theory of Acceptance and Use of Technology (UTAUT)

Venkatesh et al., (2003) proposed a model known as the unified theory of

Acceptance and Use of Technology (UTAUT). Eight well-known theories in user behaviour were incorporated in developing UTAUT (Figure 2.18). The models that were synthesized in the development of the UTAUT model are: (a) theory of reasoned action (TRA), (b) technology acceptance model (TAM), (c) motivational model (MM), (d) theory of planned behaviour (TPB), (e) combined TAM and TPB

(C-TAM-TPB), (f) model of PC utilization (MPCU), (g) innovation diffusion theory

(IDT), and (h) social cognitive theory (SCT).

According to Venkatesh et al., (2003), UTAUT was developed to understand four major objectives, first is to review the literature on user acceptance; second, to compare the eight models; third to integrate the eight models to develop the UTAUT model, and empirically to test the UTAUT model. In addition to the four major objectives, Venkatesh et al., (2003) also identified 32 constructs in UTAUT. The

UTAUT study design was a longitudinal field study across four organizations and among employees being introduced to a new technology. Additionally, UTAUT also is examined across different technologies, industries, organizations and business functions (Venkatesh et al., 2003).

The survey results indicated that each of the eight models had one or more significant constructs (Venkatesh et al., 2003). The researchers found seven of the constructs appeared to be consistent determinants of intention to use or actual usage.

Venkatesh et al., (2003) eliminated the following three constructs: (a) attitude towards technology, (b) self-efficacy and (c) anxiety. The researchers theorized that the three constructs are not direct determinants of intention. The remaining four

107 constructs were used in the UTAUT model. The constructs measured in the UTAUT model are: (a) performance expectancy, (b) effort expectancy, (c) social influence, and (d) facilitating conditions. Each of the construct is defined below. Four moderating factors will influence these independent variables in different ways according to Venkatesh et al., (2003). The factors are: (a) gender, (b) age, (c) experience, and (d) voluntariness of use.

Figure 2.18: Unified Theory of Acceptance and Use of Technology (UTAUT) - Venkatesh et al., (2003)

Performance expectancy was defined by Venkatesh et al., (2003) as the degree to which an individual believes that using the system will help him or her to attain gains in job performance. Based on the literature, the influence of performance expectancy on behavioural intention is hypothesized to be moderated by gender and age; such an effect would be stronger for men, particularly younger workers. Effort expectancy was defined by Venkatesh et al., (2003) as the degree of ease associated

108 with the use of the system. Based on the literature, the influence of effort expectancy on behavioural intentions is hypothesized to be moderated by gender, age, and experience; such an effect would be stronger for young women and older workers at early stages of experience.

Social influence is the degree to which an individual perceives important, others believe he or she should use the new system (Venkatesh et al., 2003). The literature explained that in mandatory contexts, the effect is attributed to compliance and appears to be important only in the early stages of individual experience and when rewards/punishment are applicable; in contrast, social influence in voluntary contexts operates by influencing perceptions about the technology.

Equally, based on the literature, the influence of social influences on behavioural intentions is hypothesized to be moderated by gender, age, voluntariness and experience; such an effect would be stronger for women, particularly in mandatory settings in the early stages of experience. Facilitating conditions are the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system (Venkatesh et al., 2003). Based on the literature, when both performance expectancy and effort expectancy constructs are present, facilitating conditions become insignificant; and consistent with theory planned behaviour, facilitating conditions are also direct antecedents of usage. This effect is expected to increase with experience and technology as users find multiple avenues for help and support. Hence, the influence of facilitating conditions on usage is hypothesized to be moderated by age and experience; such an effect would be stronger for older workers, particularly with increased experience.

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2.11.5 Information Adoption Model (IAM)

The Information Adoption Model (IAM) is the phase where internalization of knowledge process occurs, in which explicit information is strategically processed into internalized knowledge and implication (Nonaka, 1994). Thus to understand the internalization of knowledge process, Sussman & Siegal (2003) adapted Elaboration

Likelihood Model (ELM) and developed IAM. This model is developed to recognize on how individuals are influenced to adopt information posted in computer-mediated communication platforms. IAM comprise of two main constructs, first information quality (argument quality) and second source credibility which significantly influence usefulness towards information adoption (Figure 2.19).

Information Quality (Argument Quality) Information Information Usefulness Adoption

Source Credibility

Figure 2.19: Information Adoption Model (Sussman & Siegal 2003)

Rieh (2002), Zhang & Watts (2003), Davy (2006), Hong (2006), and Cheung

& Lee (2007), examined and validate the significance of information quality and source credibility in their information communication research. Information quality has extensively investigated in the perspective of information system. With the ability to publish, information now is in the hands of almost anyone and the quality of some online information will inevitably be diminished. Hence acquiring quality information is vital in online information exchange.

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According to Bhattacherjee & Sanford (2006), information quality can be identified as the influential strength of information embedded within the information.

Subsequently Nagesh et al., (2002) stated that, the information quality as the perceived value of user produced by an online communication system. Within the end-user computing context, the quality of information is basically evaluated in terms of the information content, accuracy, format, and timeliness (Doll &

Torkzadeh, 1988). The introduction of internet and proliferation of Internet shopping has extended the research dimension of information quality dimensions. DeLone &

McLean (2003), pointed out that accuracy, relevance, understandability, completeness, currency, dynamism; personalization and variety are the information quality measures used in recent e-commerce studies. In McKinney et al. (2002) web satisfaction model, understandability, reliability and usefulness of information are the three key dimensions related to information quality.

Source credibility refers to the perception of user on the credibility of an information source of a message (Chaiken, 1980). According to Petty & Cacioppo

(1986), source credibility is defined as the degree which an information source is perceived to be believable, competent and trustworthy by information recipients. The function of source credibility in disseminating information is vital in eWoM platform. Online consumer perceived to accept information from high credible source comparatively from information source that has low credibility (Hovland,

1951; Hovland et al., 1953). Hence, information provided by highly credible sources is perceived to be useful and reliable, and thereby facilitates knowledge transfer

(Ko et al., 2005).

The discussion of each model has clearly explained the evolution of behavioural models in the context of technology and technology communication.

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TAM was evolved from adoption to validation and to extension, starting from 1989 to 2000. Original TAM extended to TAM2 and to TAM3 which later extended to

UTAUT to explain further on the acceptance of new technology. TAM and UTAUT mostly discussed on the use of new technology but failed to explain on how information is disseminated within the technology. This limitation helped Sussman &

Siegel (2003), to develop IAM. IAM is used to understand how information movement in online environment by understanding the information quality and source credibility. Table 2.15 summarizes the core constructs of the models and their definitions.

Table 2.15 The Comparison between Various Information Science Models and Theories

Technology Acceptance Core Construct Definitions Model (TAM) Perceived usefulness The degree to which a person TAM is tailored to IS believes that using a particular contexts, and was designed system would enhance his or to predict information her job performance technology acceptance and (Davis, 1989) usage on the job. Unlike TRA, the final Perceived ease of use The degree to which a person conceptualization of TAM believes that using a particular excludes the attitude system would be free of effort construct in order to better (Davis, 1989) explain intention parsimoniously. TAM2 Subjective Norm Adapted from TRA/TPB. extended TAM by including the person‘s perception that subjective norm as additional most people who are important predictor of intention in the to him think he should or case of mandatory settings should not perform the (Venkatesh and Davis 2000). behaviour in question TAM3 extended to add more (Fishbein & Ajzen, 1975) robust to the model. TAM has been widely applied to a Behavioural Intention An individual‘s subjective diverse set of technologies probability that he or she will and users. perform a specified behaviour (Fishbein & Ajzen, 1975)

Actual Behaviour Actual performance of a specified behaviour of an individual (Fishbein & Ajzen, 1975)

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Table 2.15 (Continued)

UTAUT Core Construct Definitions UTAUT was created based Performance Expectancy The degree to which an on the conceptual and individual believes that using empirical similarities across the system will help him or eight models and through her to attain gains in job consolidation and performance (Venkatesh et al., improvements of existing IT 2003) acceptance model (Rosen, P., 2005) Effort Expectancy The degree of ease associated with the use of system (Venkatesh et al., 2003)

Social Influence The degree to which an individual perceive that important others believe he or she should use the system (Venkatesh et al., 2003)

Facilitating Conditions The degree to which an individual believes that an organizational and technical infrastructure exists to support us of the system (Venkatesh et al., 2003)

Behavioural Intention An individual‘s subjective probability that he or she will perform a specified behaviour (Fishbein & Ajzen, 1975)

Use Behaviour Actual performance of a specified behaviour of an individual (Fishbein & Ajzen, 1975) Information Adoption Core Construct Definitions Model The Information Adoption Information Quality Persuasive strength of Model (IAM) is the phase information embedded in the where internalization of disseminated information knowledge process occurs, in (Bhattacherjee & Sanford, which explicit information is 2006) strategically processed into Source Credibility Receiver‘s perception of the internalized knowledge and credibility of information implication (Nonaka, 1994). source, reflecting nothing about the information itself (Sussman & Siegal, 2003) Information Usefulness Adapted from TAM Information Adoption Actual use of the information (Sussman & Siegal, 2003) Source: Compilation of Author

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2.12 Conceptual Framework

Based on the evaluation of the theoretical finding from previous literatures concerning the study variables as well as the recommendations of previous researches, the research model as illustrated in Figure 2.20 was constructed to explore the relationships expected in this study. This research utilizes the combined model of college choice (Hossler & Gallagher, 1987) and Information Adoption

Model (Sussman & Siegal, 2003) to support the theoretical basis for testing the relationship among type of information orientation, information quality, source credibility, information usefulness, and actual HEI choice decision.

The research framework conceptualizes the information orientation searched via eWoM by international students. Therefore, Hossler & Gallagher‘s (1987) model is utilized for the current study. Hossler & Gallagher‘s (1987) college choice model was utilized vastly by earlier scholars in understanding the student decision making proceeding the Internet age. Thus this research intends to understand on how Hossler

& Gallagher‘s (1987) college choice model could be relevant in current internet age.

This model focuses on aspiration, search and choice phases as discussed earlier. This model has been selected as the focus of this model was to understand the information orientation search by students before HEI choice decision is completed. Cubillo,

Sanchez, & Cervino (2006) developed a number of information orientation searched by international students, which are the important factors in the HEI enrolment choice process of international students, such as personal factors, country image, city effect, and HEI image and program. Therefore, this study will focus on search phase as Hossler & Gallagher‘s (1987) combined model with focusing on information orientation suggested by Cubillo, Sanchez, & Cervino, (2006).

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Since this study is focused on eWoM, it is critical in synthesizing the significance of information quality and source credibility of information received and shared among the information users – international students. Hence, information adoption model is utilized to understand the moderating effect of information quality and source credibility (Sussman & Siegal, 2003). Most of the earlier studies focused on the direct relationship between information quality and source credibility towards information adoption. There is limited study in understanding the moderating effect of information quality and source credibility (Chuan, Xin, Laurie, & Choon, 2013).

Thus understanding the moderating effect of information quality and source credibility further will strengthen the argument on the relationship of information orientation and information usefulness. This is an important determinant before international students use information and enrol into HEI of their choice. Therefore, when information perceived useful for the international students, it will lead to the information adoption and HEI enrolment choice by them. Hence, the core development of the theoretical framework is based on IAM. Thus, this research intends to clear the aforementioned gaps and examine the importance of information orientation such as country image and city image. HEI image and programme evaluation information are searched via eWoM by international students prior to their

PrUni enrolment decision. In addition, these studies will also address the importance of the moderating effect of information quality and source credibility between information orientation and information usefulness. There are several gaps in the literature that this study intends to fulfil by understanding the conceptual framework.

The gaps are:

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1. Limited researches have attempted to identify the information orientation

search via eWoM such as country image and city image. Institution image

and programme evaluation in understanding PrUni enrolment choice process.

2. Limited researches have attempted to identify the moderating effect of

information quality and source credibility between information orientation

and information usefulness.

3. Very limited studies focused on international students and information

orientation searched behaviour in eWoM.

4. Limited studies in Malaysia that focused on eWoM and HEI enrolment

choice, concentrating on PrUnis.

5. Limited studies in understanding the importance of the different eWoM

channels in HEI marketing strategy particularly in PrUni.

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Information Orientation COUNTRY IMAGE

 Cultural proximity H1  Academic reputation  Socioeconomic level INFORMATION QUALITY CITY EFFECT

 City dimension  Cost of living H2 H5

INSTITUTION IMAGE INFORMATION INFORMATION ADOPTION (PrUni ENROLMENT)  Quality of professors USEFULNESS  Institution recognition H3 H7  Facilities on campus

PROGRAMMES H6 EVALUATION

 Programmes recognition  Programmes suitability SOURCE CREDIBILITY  Programmes specialization H4  Cost and finance

Figure 2.20: Proposed Research Framework

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2.13 Development of Hypotheses

Based on the conceptual framework above, several research hypotheses are developed. These research hypotheses will guide in investigating the research objectives of this study.

2.13.1 Relationship between Country Image and Information Usefulness

The country image of a HEI is considered as important information by international students throughout the search point of the HEI choice process.

Bodycott (2009) found that country image information is given the priority by international students throughout the HEI choice process. According to the six- market research conducted by Litten & Brodigan (1982), students and parents has listed country image as one of the important attributes in HEI choice process. Among the major factors that serve to influence international students‘ selection of a host country is the perceived quality of education in the host country (Bodycott, 2009). In addition, Hossler & Gallahger (1987) highlighted that cultural, socioeconomics and academic reputation of the host country is given priority by international students comparatively to the politics of the host country.

Students are more likely to consider pursuing higher education in a country and location about which they have knowledge and familiarity, and where their friends and relatives live or have studied (Bodycott, 2009). Preferences of family members may also influence students‘ choices of host country (Pimpa, 2005). Other factors that may affect an international student‘s selection of a host country include the availability of scholarship assistance, the perceived lifestyle and environment, the language, the geographic location of the host country and the perceived level of

118 crime and racial discrimination in the host country (Mazzarol & Soutar, 2002). Other than availability of scholarship assistance, the perceived lifestyle and environment, the language, the geographic location of the host country is another important dimension discussed by American Freshman: National Norms Fall 2013. According to the American Freshman National Norms Fall 2013, academic reputation is referred as a predictor of future university trends which the host country designs to achieve in near future. For example, Countries such as Singapore, Malaysia and

Republic of Korea are destined to be education hubs in Asia (UNESCO, 2014).

Therefore, country image will play a crucial part in HEI enrolment choice by international students particularly in PrUni. Hence, international students will be searching for information related to the above country image in various communication platforms. One of the most important communication platforms used by these students is eWoM. International students will search and use the country image information gathered via eWoM before PrUni choice decision is made as the information is hard to come by in formal marketing tool of PrUni. Thus, the following hypothesis is proposed.

HI: Country image has a direct positive relationship on information

usefulness towards PrUni enrolment choice.

2.13.2 Relationship between City Effect and Information Usefulness

The geographical location of the HEI within the country – city effect plays a pivotal role in international students‘ HEI choice decision. According to Kusumawati et al., (2010) city effect is found to be a critical attribute in deciding on HEI by international students in Australia. Additionally, Jackson (1982) has highlighted that;

119 international students will consider HEI that are closer to their home. Kusumawati et al., (2010), research on postgraduate student‘s intention in continuing their studies has indicated that city effect has a huge influence in their decision. The city represents the environment in which the service will be produced and consumed.

Environment is more towards the study ―climate‖ of the country which takes into consideration of its physical climate and lifestyle (Mazzarol & Soutar, 2002). Since the HEI service is a complex service jointly produced with a wide group of services, the physical environment will be made up of the HEI facilities and the city as a whole.

For instance, Salamanca in Spain is well known as a city that linked closely in learning Spanish language and culture. Thus, during every summer season, many international students visit Salamanca to learn Spanish. Adding to the beauty, history of the city and the stunning monuments create an interactive environment in

Salamanca for students to learn and communicate in Spanish with other students

(Srikatanyoo et al. 2002). Casttleman (2015) identifies city effect as one of the significant factor that influence international students‘ HEI choice. Hence searching and gathering city effect information turns out to be an important process in HEI choice process. International students will also search for information about the city effect in eWoM before using the information to enrol into PrUni of their choice.

Hence, the following hypothesis is proposed.

H2: City effect has a direct positive relationship on information usefulness

towards PrUni enrolment choice.

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2.13.3 Relationship between Higher Education Institution Image and

Information Usefulness

The image of an institution (Choudaha & Kono 2012) appears to be significant factors in international students‘ decisions to attend a particular HEI.

Institutional image comprise everything from the best professors and research talent to philanthropic donations and star students (American Freshman: National Norms

Fall 2013). International students HEI choice decision is significantly influenced by institutional image and exceptionally persuasive in the HEI search and selection process. In addition, Krishnan et al., (2007), stated that the most influential factors that decide international students HEI choice are the image of the institution, quality of the professors and the facilities in the HEI.

According to Choudaha & Kono (2012), HEI that fulfil the needs of international students and committed in satisfying the needs will be highly preferred by international students. Commitment of the HEI in fulfilling the needs of international students, will allow them to gain a positive experience and serve as a living proof to the HEI‘s commitment to quality education and student care (Kotler

& Armstrong, 2008). According to Kotler & Fox (1995), HEI image is concluded as international student‘s views, ideas and impressions of a particular HEI. These views, ideas and impressions of a particular HEI image are formed from the HEI students (past and present) who actively share information via eWoM and WOM

(Kotler & Fox, 1995). Hence, the following hypothesis is proposed.

H3: Institution image has a direct positive relationship on information

usefulness towards PrUni choice decision.

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2.13.4 Relationship between Programme Evaluation and Information Usefulness

The availability of in-demand courses and programmes and the presence of a wide range of choices is the most important factor that can influence international students‘ HEI choice. However, this may be balanced by cost factors, especially when the student and his parents cannot afford a very expensive tuition and school fees. Maringe & Carter (2007) research suggests that when choosing programmes or courses including which schools or HEI to attend; international students put much stress on value for money. Part of their HEI choice process includes career prospects, better return on investment and a brighter future.

According to Ford, Joseph & Joseph (1999), range of programmes of study, flexibility of degree programme, and range of degree options are the most important factors for students to choose HEI. In addition, Yusof, Ahmad, Tajudin & Ravindran

(2008) highlighted that programme availability as an important element for students to choose a particular HEI especially PrUni in Malaysia. Furthermore, student‘s satisfaction will increase based on the programme recognition locally and globally, thus influence the international students HEI choice (Ismail & Leow 2008). Hence, the following hypothesis is proposed.

H4: Programme evaluation has a direct positive relationship on

information usefulness towards PrUni enrolment choice.

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2.13.5 The Moderating Role of Information Quality

According to Bhattacherjee & Sanford (2006), information quality can be identified as the influential strength of information embedded within the information.

This is the value of the output produced by a system as perceived by the user

(Negash et al., 2002). According to Olshavsky (1985), perceived information quality that is received by a consumer in a computer mediated environment will significantly influence consumers purchasing decisions. According to Noar, Benac, & Harris

(2007), it is notable that the purchasing decision is likely to be moderated by numerous variables and that a very limited studies on the purchasing decisions has included a manipulation of argument quality, a variable that is likely to moderate the effects of purchasing decisions (Petty, Cacioppo & Goldman, 1981). Research from

Dimmock, Jackscon, Clear & Law (2013) validates findings from other research that tailored messages are most likely to be significant under conditions of strong moderated argument quality.

According to Petty, Wheeler & Bizer (2009) matching a message to an individual can lead to a bias in message processing (e.g., reacting more positively to ambiguous arguments). It might also enable the message recipient to see the merits of arguments more easily or grant people more confidence in the thoughts they generate. Individuals who feel that a message relates to them are more likely to attend to and process information in the message, leaving them more susceptible to the influence of argument quality (Petty et al., 2000). In the case of weak messages, the heightened personal relevance resulting from the tailored content, and the central processing that is subsequently encouraged, may actually be undesirable because it increases elaboration about the weak arguments. With strong messages, however, the central processing resulting from personalized content is desirable because increased

123 attention is given to strong arguments. Evidence for these effects has been provided by Updegraff, Sherman, Luyster, & Mann (2007), who found that the effect of a tailored health message (about dental flossing) was moderated by argument quality, hence tailored messages were perceived more positively when the message contained strong arguments, but were perceived more negatively when the message contained weak arguments. Also, Petty et al. (1981) found that persuasion about a campus policy among college students was influenced mostly by argument quality in a high relevance condition. Spurred on by the original work of Sussman & Siegal (2003), information quality has four constructs which are relevance, timeline, accuracy and comprehensiveness as determinant of information quality. Relevance of information is a significant component in eWoM environment. Most of the eWoM users will search for information that is relevant to their desires at a particular period of time.

As stated by Madu & Madu (2002), internet users rarely read information in detail, but rather scan the pages to find the information they need. Generally, in eWoM, the users are conscious of their time, thus having the most relevant information in eWoM environment is essential (Cheung et al., 2008). Similarly, prospective international students will seek for relevant information related to HEIs in eWoM environment which is useful for the international students.

The second construct discussed by Sussman & Siegal (2003) is timeline.

Timeline of information concerns whether the information is current, timely and up- to-date. According to Madu & Madu (2002), when the information is not up-to-date, eWoM would not significantly influence a consumer and therefore, present no added value to consumers in using the information. Timeline of information disseminated in eWoM environment has positive relation with information used for particular individual. Besides relevance of information and timeline of information, Sussman &

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Siegal (2003) also identified that accurate information and comprehensiveness of information in the eWoM environment will determine quality of the information.

According to Wixom & Todd (2005), information accuracy is a measure of the reliability and credibility of information held within the eWoM environment.

Accurate information will lead to the international students using the information searched in the eWoM environment. Comprehensiveness of information refers to the detailed information shared in eWoM environment. Sullivan (1999) suggested that the more detailed the information, the wider the breadth of user categories and user- orientation, and thus, resulting in a greater likelihood of user acquisition of information. Therefore, in the current study, the four commonly used dimensions of information quality: relevance, timeliness, accuracy and comprehensiveness are tested to understand the moderating effect of information quality. Since message arguments are directed at users‘ rational judgement rather than their affect, information quality is expected to influence perceived usefulness rather than attitude.

Hence, the following hypotheses are proposed.

H5a: Information quality moderates the relationship between country

image and information usefulness.

H5b: Information quality moderates the relationship between city effect and

information usefulness.

H5c: Information quality moderates the relationship between institution

image and information usefulness.

H5d: Information quality moderates the relationship between programme

and information usefulness.

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2.13.6 The Moderating Role of Source Credibility

According to Chaiken (1980), source credibility is referred as the credibility of the information source received by consumer. Source credibility is defined as the extent to which an information source is perceived to be believable, competent and trustworthy by information receiver (Petty & Cacioppo, 1986). In addition, Ohanian

(1990), explained source credibility as how the information receivers‘ perceived confidence towards the foundation of information. According to Wu (2013), the strong point of ties among sender and receiver in eWoM environment is a foundation to evaluate the significance of source credibility. Brown & Reingen (1987) discovered that the stage of bond strength has different impact on the receiver‘s decision making and effectiveness of the information circulated in the eWoM situation.

Previous research by Cheung, Luo & Sia (2009), Cheung, Sia & Kuan (2012) finds that source credibility can directly form or change a reader's attitude, and that information provided by a highly credible source will produce a greater effect on perceived information credibility. Thus, the readers are more inclined to adopt the viewpoint of the information. In contrast, other research suggests that the role of source credibility in information processing is more complex. Sussman & Siegal

(2003) believe that source credibility will bias the information processing by changing the information readers' propensity to support or suspect the content of the information. This viewpoint is similar to Pornpitakpan (2004), who notes that source credibility interacts with several variables, such as informational factors, to jointly affect attitudes of information readers. From this perspective, some investigations further test source credibility's moderating effect in different contexts. For instance,

Moore (1986) detected a significant interaction between source credibility and

126 argument strength on advertising readers' attitude; Chuan, Xin, Laurie & Choon

(2013) highlighted that source credibility significantly moderates two informational factors' effects on readers' perception of recommendation credibility, each in a different direction in a leading online consumer discussion forum in China. These findings are consistent with attribution inference which suggests that when source credibility is low, a reader will discount the value of the information content they receive Grewal d., Gotlieb., (1994); in so doing, they determine that the recommendation is not as credible as one provided by a highly credible source. As a result, the recommendation claims made by a low-credibility source are less likely to change the information readers' attitude.

Wu (2013) classifies source expertise and source trustworthiness as the two main elements to examine the credibility of information. In the eWoM environment, users have practically boundless flexibility to distribute and express their emotions towards specific items without disclosing their real personality. Thus, user need to decide the expertise and trustworthiness of the information source prior to adopting or rejecting the information presented to them in eWoM. High credible information source in eWoM will directly influence the perception of the usefulness of the information. Consequently, prospective international students will positively react and use the information in the eWoM environment if the prospective international students believe the source of the information. Therefore, in the current study, the two measurements of source credibility, which is source expertise and source trustworthiness, are tested to understand the moderating effect of source credibility.

Hence, the following hypotheses are proposed.

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H6a: Source credibility moderates the relationship between country image

and information usefulness.

H6b: Source credibility moderates the relationship between city effect and

information usefulness.

H6c: Source credibility moderates the relationship between institution

image and information usefulness.

H6d: Source credibility moderates the relationship between programme

evaluation and information usefulness.

2.13.7 The Mediating Role of Information Usefulness

Davis (1989, 1993), introduced perceived usefulness as one of the antecedent in TAM. According to Davis (1989, 1993), Perceived Usefulness (PU) is identified as the significant to which a person trusts that using a specific system would improve his or her work performance within an organizational context. Sussman & Siegal

(2003) believe that the perceived usefulness construct can be applied to information communication context, namely, information usefulness. According to Cheung et al.,

(2008), information usefulness is defined as the degree to which the readers‘ perceived usefulness of the information which can improve an individual‘s purchasing decision. Therefore, information usefulness plays an essential role during the information readers‘ information processing in the eWoM environment.

A study conducted by Sussman & Siegal (2003) confirms that information quality and source credibility can significantly affect the readers‘ perception of information usefulness towards a particular e-mail message. This finding has also

128 been approved by some subsequent research (Zhang & Watts, 2008) which is conducted to explore the effect of a piece of eWoM information in online communities. Information usefulness is a crucial determinant of action taken.

Information usefulness will affect the behaviour of individual to use the information from a particular eWoM for a particular reason (Pitta & Fowler, 2005). Therefore, the information usefulness plays a crucial role in influencing the international students‘ HEI enrolment choice.

Hanson & Litten (1989) introduced five-step process that a student passes through to select and enrol in a particular HEI. The first step is students having aspirations to enrol in HEIs; second step, students starting the information search process; third step, students gathering information related to HEIs; fourth step, students sending applications to the selected HEIs; and finally, students enrolling in a particular HEI. Figure 2.21 shows the integrated generic higher education student- choice model (Demetri, Alkis & Yiould, 2007).

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Figure 2.21: The Integrated Generic Higher Education Student-Choice Model

The above studies have indicated that useful information searching and information gathering are an important element for prospective international students in their HEI choice decision. Therefore, information that is useful leads to the PrUni choice decision by prospective international students. Hence, the following hypothesis is proposed.

H7: Information usefulness mediates the relationship between country

image, city effect, institution image, programme evaluation and PrUni

enrolment choice by international students.

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2.14 Chapter Summary

This chapter explains the concepts, construct and relationship under investigation in this study as well as the theoretical foundation of the study. HEI choice models and decision making process are reviewed in depth. This chapter also describes the importance of eWoM and its relation to prospective international students‘ HEI choice decision. The importance of information orientation in eWoM and the effect of information quality and source credibility are reviewed towards information usefulness and HEI enrolment choice, particularly PrUni enrolment choice by international students. Based on the discussion, conceptual framework and hypotheses of the study are developed.

The next chapter describes the methodology for testing the relationship of the studied variables. Research design, sampling strategy, research instruments, data collections procedures and methods to be used in data analysis will be discussed in the following chapter.

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CHAPTER 3

RESEARCH METHODS

3.0 Introduction

This chapter presents the details of the research methodology used in this study. The topics discussed cover research design, area of study, sampling design, population and sample size, questionnaire design and pilot study. The data collection procedures and development of research instruments used to achieve the objective of this study are discussed in this chapter. Also, the various types of statistical analyses have been applied to test the proposed hypotheses.

3.1 Research Paradigm

Creswell (2014) defines paradigm as universal theoretical opinions and rules, and approaches for individual application and acceptance. A paradigm is therefore a complete trust scheme, global interpretation or framework that guides researchers to conduct research in structured method in a research ground. At present, there are several competing paradigms in the field of social sciences. Several scholars argued that research procedures are structured based on two general paradigms, which are quantitative and qualitative paradigm. On the other hand, this general paradigm view is seen as over simplification that highlights data rather than foundational philosophies and assumptions. The precise figure of paradigms and the terms related with a specific paradigm differ from one author to another. Creswell (2014) described post-positivism, constructivism, transformative and pragmatism as the four paradigms accepted generally as research paradigm.

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According to Creswell (2014), post-positivism replicates a deterministic perspective in which effects possibly decide the consequences. Therefore, the issues contemplated by post-positivists imitate a need to look at causes that impact results, for example, issues analysed in experimentations. It is likewise reductionist in that the determined is to shrink the philosophies into a small, separate arrangement of theories to examine, for example, the factors that constitute theories and research questions (Creswell, 2014). The information that progresses through a post-positivist view is constructed on cautious thought and dimension of the un-biased realism that occurs in real world. Consequently, creating numeric methods of explanations and examining the actions of people become principal for a post-positivist. Hence, positivism exploration is normally linked with quantitative approaches of data collection and analysis (Creswell, 2014).

Constructivism or social constructivism concentrates on the development of implication and the development of social and psychological worlds through individual and psychological procedures (Sweetman, Badiee & Creswell, 2010).

Constructivism trusts that individuals look for comprehension that related to the daily routine activities in the environment of an individual that lives in. Experience of an individual will develop subjective implications that significantly coordinate towards certain goal of an individual. The aim of research then, is to rely as much as could on the individuals' perspectives of the circumstance being considered. Thus, the research investigation questions ends up noticeably comprehensive and broad so that the individuals can develop the importance of a circumstance, a meaning classically forged in a communication with different individuals. The researcher with open ended questions has better understanding on what an individual speak or do in their life. Compare to positivism, constructivism paradigm collect data and hypothetical

133 awareness are collected from the data before hypotheses are created. More exactly, a hypothesis will be created in light of the example of the data gathered (Creswell et al., 2014). The constructivism investigation is probably depending on qualitative data collection method (Sweetman et al., 2010).

Transformative perspective was investigated by researchers in 1980s and 1990s from individuals that detected the post-positivist expectations of executing structural laws and theories that are not suitable for marginalized individuals or groups. This post-positivist also did not sufficiently address subjects of social equity of the marginalized individuals. Transformative researchers believe that governmental issues and political motivation to be considered in the examination of an individual.

Subsequently, the examination should to include a plan or strategy that improves the lives of the individuals. In addition, particular subjects should have been attended to, that is related to significant social issues of the day, issues, for example, strengthening, inequality, mistreatment, power, dominance and separation. The

"voice" of the individuals turns into a united opinion for change and transformation.

This transformative research may mean giving a voice to these individuals, raising their awareness or propelling a plan for change to enhance the lives of the individuals. Thus, hypothetical perspectives might be incorporated with the philosophical desires that construct a picture of the issues being explored, the individuals to be examined and the progressions that are required.

Pragmatism originates from the effort of Peirce, James, Mead, and Dewey

(Creswell, 2014). There are many procedures of pragmatism. For large portions of them, knowledge claims emerge out of actions, circumstances and outcomes as opposed rather than antecedent conditions (as in post-positivism). There is a concern with applications-what works and answers for issues. Rather than strategies being

134 critical, the issue is the most essential where, researchers use all ways to comprehend the issues (Creswell, 2014). According to Creswell (2014), pragmatism is best used for mixed method studies.

3.1.1 Differences between Quantitative, Qualitative and Mixed Method

Approach

Quantitative, qualitative and mix method approach discusses to the methodologies, analysis and reporting styles of a study. According to Cohen (2006), quantitative method attempts to quantity and assesses the phenomena of the research and produces substantial outcomes for generalization and reference for other researchers. Quantitative approaches comprise complex tests with numerous variables and actions. Quantitative approaches also consist of detailed SEM that integrates causal paths and the understanding of the collective power of numerous variables (Creswell, 2014).

Correspondingly, qualitative method highlights on the procedure and the results which specifies a comparable and dissimilarities among the phenomena under study. In qualitative research, the statistics and categories of methods also became more evidently noticeable in the year 1990 and throughout to the 21st century.

Qualitative research originates from the research scope of anthropology, sociology, the humanities and evaluation research. Inversely, mixed method combines or incorporates quantitative and qualitative research and facts in a research study.

Qualitative data inclines to be open-ended without pre-arranged responses whereas quantitative data commonly comprises close-ended response such as those found in questionnaires (Creswell, 2014). Table 3.1 further explains the differences among quantitative, qualitative and mix method research approach.

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Table 3.1

Difference between Quantitative, Qualitative and Mixed Method Approach

Components Quantitative Qualitative Mixed Method

Philosophical Post positivist Constructivist / Pragmatic knowledge Assumptions knowledge claims transformative claims knowledge claims

Practices of Research  Test and verify  Position himself  Collects both theories or herself quantitative and  Identifies  Collect qualitative data variables of study Participants  Develops a rationale  Relate variables meanings for mixing to hypotheses  Focus on a single  Integrates the data at  Use standards of concept or different stages of validity and phenomena inquiry reliability  Brings personal  Employs the  Observe and values into the practices of both measure study quantitative and information  Studies the qualitative research numerically context or settings  Uses unbiased of the participants approaches  Validate the  Employ accuracy of statistical findings procedures  Make interpretation of the data  Collaborate with the participants

Strategy Surveys and Case Study, Sequential, concurrent Engaged Investigations Grounded theory and transformative studies,

Methods Closed ended Open ended Both open and closed Employed questions, Numeric questions, Evolving ended questions, equally data and determined methods and evolving and pre- methods Manuscript arranged methods

Source: Creswell, 2014

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3.1.2 Rationalisation for Paradigm Selection

According to Creswell (2014), the important criteria in selecting the best approach is based on research issues. Fundamentally, if the issue is to recognize the elements that impact the result or distinguishing the best indicator of the result, at that point quantitative approach is the best answer. As per Kumar (2005), if the guideline inspiration driving the investigation is to gauge the qualification in the phenomena or certain issues and information are collected using quantitative factors and the examination is prepared at the level of difference on the specific phenomena; thus the research could be classified as quantitative study. Essentially, Creswell

(2014) guaranteed that the greater part of the exact investigations did in the field of managerial and behavioural sciences utilize quantitative methodology. This study is focused on behavioural action of international students searching information orientation in eWoM for HEI enrolment choice. Hence, this study is utilizing quantitative method to understand the relationship between information orientations, information quality, source credibility, information usefulness and HEI enrolment choice by international students in the eWoM platform.

Therefore, quantitative method guides this study to quantify the effect of all the independent variables, moderator, mediator on the dependent variable – outcome.

Based on the underlying theories a theoretical framework is developed and research hypotheses were established to understand the effect of the variables. According to

Pekrun, Goetz, Titz & Berry (2002) to have an effective dynamic test of hypotheses, particularly to understand the impact and causes of variables, quantitative measure is preferred compared to other measures. In addition, Creswell (2014) explained further that quantitative method is best to use when data is gathered for generalization of the entire population and to view the new evolving patterns. Moreover, Kappel &

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Wickens (2003) supported that quantitative strategy is an effective technique to utilize when the point of the investigator is to make speculation set up on the example, to broader groups. Accordingly, as the purpose of this study is to empirically investigate the relations among the fundamental variables based on the hypotheses developed, hence quantitative method is considered to be more relevant compared to other methods.

3.2 Research Design

The current study is directed to examine the relationship among information orientations searched by international students via eWoM towards HEI enrolment choice. This study will also investigate if information usefulness may enhance the relationship between international students‘ information orientation searched in the direction of the HEI enrolment choice by international students. Apart from the investigation of the relationship between information orientation, information usefulness and HEI choice decision, likewise this study investigates information quality and source credibility moderating effect towards information usefulness. The conceptual framework (Figure 2.18) considers information orientation searched by international students as independent variable (IV), information usefulness as mediating variable (MV), information quality and source credibility as moderating variable (MDV) and HEI enrolment choice as dependent variable (DV). A proper research design will be selected to investigate the relationship between IV, MV,

MDV and DV of this research.

As indicated by Sekaran (2003), research design includes a progression of rational decision-making with respect to the motivation behind the current investigation (exploratory, descriptive, hypotheses testing), its area (the examination

138 setting), the sort of investigation, the degree of researcher intervention, time line and the level to which the information will be examined (unit of investigation). With respect to this, decisions have to be made agreeing to the sampling design, how information is to be gathered, how variables will be measured and examined to test the hypotheses. De Vaus (2001) states that the purpose of a research design is to confirm that the proof obtained empowers scholars to answer the underlying question as unambiguously as possible. Therefore, research design of a study is related to the data collection method used for a particular research.

Data gathering procedures are an essential step of research design. Data is collected to examine the hypotheses derived from the conceptual framework presented. To identify the hypotheses and nature of certain relationship among the variables, this research has opted for the use of cross-sectional study. According to

Sekaran (2003), a cross-sectional study is performed over a period of time for instance over few days, weeks or months. This study opts for cross-sectional study as the data for this study is collected at one point of time from the gathered samples to regulate the relationship among variables.

Data could be gathered in diversified methods, in dissimilar situations – field or lab – and from numerous bases. According to Sekaran (2003), data collection methods include various techniques of interviews – face-to-face interviews, telephone interviews, computer assisted interviews, interviews over electronic media, self-administered questionnaires and ad-hoc mail surveys, or electronically administrated questionnaire. Sekaran (2003) has also stated that each data collection method has its own advantages and disadvantages (Table 3.2).

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Table 3.2 Advantages and Disadvantages of Data Collection

Mode of data collection Advantages Disadvantages

Personally  Ability to rapport &  Organizations may be motivate respondent reluctant to give administered  Doubts can be clarified company time for the survey with groups of questionnaires  Less expensive when administered to a group employees assembled Sekaran (2003) of respondents from the purpose  High response rate ensured  Respondent anonymity is high

Mail  Anonymity is high  Response rate is almost  Wide geographic regions always low Questionnaires can be reached  A 30 per cent rate is quite acceptable Sekaran (2003)  Respondent can take more time to respond at  Cannot clarify questions convenience  Follow-up procedures  Can be administered for nonresponses are electronically, if desired necessary

Electronic  Easy to administer; Can  Computer literacy is a reach globally; Very must Questionnaires inexpensive  Respondents must have  Fast delivery; access to the facility Sekaran (2003) Respondents can answer  Respondent must be at their convenience like willing to complete the the mail questionnaire survey

Source: Sekaran (2003)

Table 3.2 clearly indicates that a personally administered questionnaire has a greater advantage compared to the mail and electronic questionnaire in collecting data. Therefore, the data collection approach adopted within this study will be utilizing the method of personally administrated questionnaire. Once the questionnaire is prepared, it is important for a researcher to select the right sample for the study. Figure 3.1 presents the stages involved in selecting sample for a

140 research. Determining the right sample size is very important especially while carrying out a research, as the focus will be more on the reliability and validity of the data. A reliable and valid sample enables the researcher to generalize the findings of the population under investigation.

Describe the target population

Select sampling frame

Regulate if probability or non-probability

sampling technique will be chosen

Plan techniques for selecting sampling items

Decide sample size

Select definite sampling items

Figure 3.1: Stages in the Selection of Sample

3.2.1 Population

Population targeted for this study would be the International students who are enrolled in PrHEIs in Malaysia. In the year 2016, there were 480 PrHEIs in

Malaysia, in which 44 PrHEIs with university status, 29 PrHEIs with university- colleges status, 9 foreign university branch campuses and 398 PrHEIs with college status. According to the data from MOHE in 2016, there were 88, 665 international students enrolled in Malaysian PrHEIs (Table 3.3). To be precise, 61.4% of the

International students enrolled in PrHEIs with University status (local and branch

141 campus of foreign University) in year 2016. In the same year, 22.4% of the

International students enrolled in PrHEIs with University College status (Table 3.3).

The size of the population clearly indicates that PrHEIs with University status (local and branch campus of foreign University) is the main central point for international students to enrol themselves for a selected education programme. Thus this study focuses on international students from Private Universities – PrUni (local and foreign branch campuses) in Malaysia.

Table 3.3 Population Size

No Types of Private HEI Student Percentage (%) Enrolment 1 Private HEI with University status and 54,440 61.4 Private HEI with University status (branch campus of foreign University)

2 Private HEI with University College status 14,364 16.2

3 Private HEI with College status 19,861 22.4

Total 88,665 100.0 Source: Ministry of Higher Education (2016)

3.2.2 Sampling Frame

Once the target population size is determined, the sampling frame will be identified. Sampling frame is a list of components from which a sample could be identified. A sampling frame defines the members of the population who are eligible to be included in a given sample – in the sense of drawing a boundary or frame around those cases that are acceptable for inclusion in the sample. Sample frame is very common in survey sampling, where it is then associated with a countable listing of all the data sources in the population that are accessible for sampling. The sampling frame is also recognized as working population. Population targeted for

142 this study is the Private University. Private University in Malaysia is divided into 2 categories, the first category is PrUnis with University status (local based) and the second category is PrUnis with University status (foreign based). According to

MOHE (2016), currently there are 42 PrUnis with University status (local based) and the 9 PrUnis with University status (foreign based) (Table 3.4). Meanwhile, Table

3.5 details out the list of target population of PrUnis by states, for this research.

Table 3.4

Target population of Private Universities

No Private University Status Units 1 University (Local based) 42 2 Branch University (Foreign based) 9 Total 51

Source: Ministry of Higher Education Malaysia (2016)

Table 3.5

Approved List of PrUnis to Recruit International Student (2016)

Pahang No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 1 DRB-HICOM University of 1 2010 6 2020 Automotive Malaysia Kedah No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 2 AIMST University 1 2001 15 2019

3 University Antarabangsa 1 2010 6 2016 AlBukhary Kuala Lumpur No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 4 Asia e University 1 2007 9 2018

5 Asia Pacific University of 1 1993 23 2017 Technology and Innovation

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Table 3.5 (Continued)

Kuala Lumpur No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 6 Asean Metropolitan University 1 1997 19 2017 7 GlobalNxt University 1 2012 4 2017 8 HELP University 1 1986 30 2016 9 International Centre for 1 2005 11 2017 Education in Islamic Finance 10 International Medical University 1 1992 24 2021 11 International University of 1 2013 3 2018 Malaya-Wales 12 Mahsa University 1 2005 11 2018 13 Open University Malaysia 1 2000 16 2016 14 UCSI University 1 1986 30 2018 15 University of Kuala Lumpur 1 2002 14 2017 16 University Tun Abdul Razak 1 1987 28 2016 Negeri Sembilan No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 17 INTI International University 1 1998 18 2020 18 Manipal International University 1 2011 5 2020 19 Nilai University 1 1997 19 2017 Putrajaya No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 20 Heriot-Watt University 2 2013 3 2017 Malaysia 21 University Tenaga Nasional 1 1999 17 2019 Penang No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 22 Wawasan Open University 1 2006 10 2016 Perak No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 23 Petronas University of 1 1997 19 2020 Technology 24 Quest International University 1 2008 8 2020 Perak 25 University Tunku Abdul 1 2002 14 2019 Rahman Sarawak Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 26 Curtin University Sarawak 2 1999 17 2017 27 Swinburne University of 2 2000 16 2019 Technology

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Table 3.5 (Continued)

Selangor No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 28 Al-Madinah International 1 2006 10 2017 University 29 Binary University of 1 1984 32 2017 Management and Entrepreneurship 30 Infrastructure University Kuala 1 1999 17 2017 Lumpur 31 Lim Kok Wing University of 1 1992 24 2017 Creative Technology 32 Malaysian Institute for Supply 1 2011 5 2017 Chain Innovation 33 Malaysia University of Science 1 2000 16 2017 and Technology 34 Management and Science 1 2002 15 2017 University 35 Monash University 2 1998 14 2020 36 Multimedia University 1 1994 22 2019 37 Perdana University 1 2011 5 2021 38 Putra Business School, 1 1997 19 2017 Graduate School of Management 39 SEGI University 1 1977 39 2017 40 Sunway University 1 1987 29 2021 41 Taylor‘s University 1 1969 47 2020 42 Tun Abdul Razak University 1 1998 18 2018 43 UNITAR International 1 2011 5 2020 University 44 University of Nottingham 2 2000 16 2020 Malaysia Campus 45 University of Selangor 1 1999 17 2021 46 University Malaysia of 1 2012 4 2018 Computer Science and Engineering 47 Xiamen University Malaysia 2 2015 1 2020 Campus

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Table 3.5 (Continued)

Johor No Name of Institution Status Year Operation Certificate of Founded Year(s) Registration 48 Newcastle University Medicine 2 2009 7 2019 Malaysia 49 University of Southampton 2 2012 4 2016 Malaysia Campus 50 Raffles University Iskandar, 1 2012 4 2016 Malaysia 51 University of Reading Malaysia 2 2013 3 2018

Code Classification

1 Local founded University

2 Foreign founded University

Source: Ministry of Higher Education Malaysia (2016)

There are 54,440 international students enrolled in both local and foreign PrUni in the year 2016 (Table 3.3). Private University, both local and foreign branch campuses were selected as the first phase of the sample frame. The second phase of sample frame was to identify and differentiate between local and international students enrolled in PrUnis within University status, as this study focuses on international students as respondents. The last stage of the sample frame used within this study was to identify the first year international students who use eWoM search information orientation as well as use the information to enrol in the PrUnis.

Diagram 3.1 shows the sampling frame used in this study.

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Private University Target population identification

Private University– Private University – Local Branch campus

Identification of students

Local Students International students Sampling Procedure

Use traditional method Use eWoM to gather to gather information information and adopt and adopt to enrol in to enrol in the the University University

Diagram 3.1: Sampling Procedure

3.2.3 Sampling Technique

According to the data published by MOHE in 2016, approximately 88,665 international students were enrolled in Malaysian PrHEIs (Table 3.3), from the above total 54,440 enrolled in both local and foreign PrUni in the year 2016 (Table 3.3).

Therefore, the sampling technique that will be used in this study is the purposive sampling. According to Sekaran (2003), purposive sampling is a non-probability sampling technique in which a knowledgeable individual selects the sample addressed on some appropriate features required for the sample. In addition,

147 purposive sampling is applied when there are inadequate number of individuals have the information that is being pursued. Purposive sampling was decided to be the most suitable technique for this study as it focuses on the international students who have used the eWoM for information prior to enrolling in the local PrHEIs with university status. These international students are in their best position to provide the information required for this study. This is due to the condition that they have related knowledge as they have gone through the process of gathering information via eWoM and implemented this for their PrUni enrolment choice. The respondents will be international students who are enrolled in the 51 local PrUnis with university status in Malaysia, as listed in table 3.4 (MOHE 2016).

3.2.4 Sample Size

In order to have a reliable survey, the sample size should be reasonable to justify the significance of the study. Malhotra & Birks (2000) suggested that for descriptive survey which investigates problem-solving research, the sample size should be around 300 to 500. According to Banasiewicz (2005), sample size of 150 to 500 is appropriated to investigate problem-solving research. Based on Malhotra &

Birks (2000) and Banasiewicz‘s (2005) studies, the recommendation for maximum and minimum samples that can be collected are 500 cases for bigger subset and 200 cases for smaller subset.

In terms of SEM guidelines, Harris & Schaubrock (1990) recommended a minimum sample of 200 to assure strong SEM modelling. Bacon et al. (1999) proposed 200 – 400 cases to investigate the adequate of the models that hold 10 – 15 observed variables, with 300 samples being a good starting point to suit the SEM

148 analysis. Hence, the study follows Banasiewicz (2005) focus as general guideline and

Bacon et al (1999) as a specific guideline in determining the sample size for this study. These two studies have been adapted and referred because, Banasiewicz

(2005) consist of studies on problem solving wherelse Bacon (1999) focused more on SEM modelling and the finalised sample size of 381 is between the suggested minimum of 200 sample size by Banasiewicz (2005) and the maximum number of

400 sample size suggested by Bacon (1999). Thus the sample size of 381 is considered to be appropriate for this problem solving study.

3.2.5 Units of Analysis

The unit of analysis is the key elements that are investigated in a study. Unit of analysis explains on the sample that is been actuality investigated; for example, what or who is the sample for the research is investigated. Common units of analysis in social science studies are inclusive of individuals (most common), groups, social organizations and social artefacts. The unit of analysis for this study is international students – individuals, who utilised eWoM in searching for information and used it to enrol in PrUnis in Malaysia. Therefore, for this study, two stages of selection process were carried before finalising the unit of analysis. The first stage is to determine the HEI selection process and second stage on determining the international students‘ selection process.

First stage of this study was to determine the HEIs selected for the study. This study is focused on PrUni (local and foreign branch campus). Therefore, international students from the 51 PrUnis (Table 3.4) are eligible to participate in this study. Another determinant considered in PrUnis‘ selection is based on the approved

149 list of PrUnis to recruit international student by MOHE (2016). This study is focused on PrUnis which have the approval to recruit international students, and has three years till the license to recruit international students expires. Hence, PrUnis with their licence expiring in year 2018, 2019, 2020 and 2021 were selected. Therefore, international students from 27 out of 51 PrUnis will be focused in collecting the sample for this study (Table 3.6).

Table 3.6 PrUni Selected Units by States

State University (local University (Foreign Total founded) founded) Pahang 1 1 Kedah 1 1 Kuala Lumpur 5 5 Negeri Sembilan 2 2 Putrajaya 1 1 Perak 3 3 Sarawak 1 1 Selangor 8 3 11 Johor 2 2 Total 21 6 27 Source: MOHE (2016)

Another important criterion is that the international students should have utilized eWoM as a tool in gathering information and have used the information to enrol in the PrUnis. Therefore, international students from the PrUnis will be selected for this study. Once the international students‘ identification is decided, the next process will be to differentiate between international students who used eWoM to search information orientation and those who used traditional method. There are 2 screening questions in Section A that is used to differentiate the respondents as per

150 the study requirements. Once the PrUnis and international students‘ criteria selection is decided, the next process will be distributing questionnaires to the respondents. In total of 27 private universities selected, and 20 questionnaires been distributed equally to each private university. The target of collecting back a minimum of 15 answered questionnaires was achieved throughout the duration of 3 months. Overall a total of 381 questionnaires have been collected within the stipulated time frame.

The final process is to analyse the data that have been collected using Partial Lease

Square (PLS). The last stage of the data collection method is to report the findings

(Diagram 2).

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PrUnis that as approval to enrol internationals students Private University (year 2018, 2019, 2020 and 2021 are selected)

Private University Private University

(Local) (Branch campus)

Identification of students

Process Local Students International students end in first year

Use traditional method Use eWoM to gather Process to gather information information and adopt and adopt to enrol in end to enrol in the the University University

Questionnaire Distributions

Purposive sampling - PLS Data Collection

SEM - PLS Data Analysis

Report Findings

Diagram 3.2: Summary of Data Collection

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3.3 Questionnaire Design

This study has implemented a structured questionnaire survey (Table 3.7). The questionnaires were administrated directly by the researcher, where by the researcher monitored and administrated the data collection procedures from the specified private universities. The questionnaires were divided into ten broad sections.

Questions in section ―A‖ are used to screen out respondents who are not fit to participate in the rest of the questions. Section ―B‖ has 9 questions to understand the customers‘ demographic characteristics which were adopted from Juan Antonio

Moreno-Murcia et al., (2015).

Section C, D, E and F measure the information orientation searched by international students towards information usefulness. Section C, D, E and F were adapted from Joseph Mbawuni & Gyasi Nimako (2015), Siti Falidah Padlee et al.,

(2010), Krishnan, Nurtjahja & Keling S.B.A (2007), Juan Antonio Moreno-Murcia et al., (2015), Anil Tan (2015), Daniel Lohmann (2015) and Anna Round (2005).

Section G which measures the moderating effect of information quality was adapted from Sussman & Siegal (2003) with a total of 4 questions. Consequently, section H requires respondents to express their trust on the information searched via eWoM towards information usefulness and the items for this section were adapted from

Sussman & Siegal (2003) and Cheung et al., (2008). Section ―I‖ surveys the respondents‘ responses concerning the information usefulness. These items were adapted from Davis (1989). Inside the eWoM environment, new ideas and views about products or services may be communicated among online consumers. The perception of this information (ideas and views) is believed to influence on consumers‘ decision. The more useful the information is the higher the chance for a consumer to purchase a product or service.

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Comparatively, Section ―J‖ observes the respondents‘ HEI enrolment choice decision by international students. HEI choice decision is a procedure in which individuals purposefully involve in using the information in the eWoM environment.

Thus, HEI enrolment choice has the possibility to lead an international student to enrol in HEI particularly PrUni in Malaysia. Therefore, the questions for PrUni enrolment choice is adapted Sussman & Siegal (2003) for this study.

Table 3.7

Summary of Constructs for Each Item

Section Measure No of Scale Items A Screening Question 2

B Demographic Data 9

Country Image – Cultural Proximity 4 7 point Likert scale

1=strongly disagree 7=strongly agree C Country Image – Academic 4 7 point Likert scale Reputation 1=strongly disagree 7=strongly agree

Country Image – Socio Economic 4 7 point Likert scale level 1=strongly disagree 7=strongly agree

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Table 3.7 (Continued)

Section Measure No of Items Scale

City Effect – City 4 7 point Likert scale Dimension 1=strongly disagree 7=strongly agree

D City Effect – Cost and 4 7 point Likert scale Living 1=strongly disagree 7=strongly agree

Institution Image – 6 7 point Likert scale Quality of Professors 1=strongly disagree 7=strongly agree

Institution Image – 6 7 point Likert scale E Institution Recognition 1=strongly disagree 7=strongly agree

Institution Image – 6 7 point Likert scale Facilities in Campus 1=strongly disagree 7=strongly agree

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Table 3.7 (Continued)

Section Measure No of Items Scale

Programme Evaluation – 6 7 point Likert scale Programme Recognition 1=strongly disagree 7=strongly agree

Programme Evaluation – 4 7 point Likert scale Programme Suitability 1=strongly disagree 7=strongly agree F Programme Evaluation – 6 7 point Likert scale Programme Specialization 1=strongly disagree 7=strongly agree

Programme Evaluation – 4 7 point Likert scale Programme Cost and Finance 1=strongly disagree 7=strongly agree

G Information Quality : 4 7 point Likert scale Relevance 1=strongly disagree 7=strongly agree

H Source credibility : Source 4 7 point Likert scale Expertise 1=strongly disagree 7=strongly agree

I Information Usefulness 4 7 point Likert scale

1=strongly disagree 7=strongly agree

J HEI Enrolment choice 5 7 point Likert scale

1=strongly disagree 7=strongly agree

Responses to statements in the questionnaire were measured using the 7 point

Likert Scale ranging from 1= Strongly Disagree to 7=Strongly Agree, together with

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Semantic Differential Scale. This study adopts the 7 point Likert scale comparatively to 5 point Likert scale. According to Sekaran & Bougie (2010), 7-point scale increases the reliability of an investigation scale and outcome compare to the 5-point scale. In addition, Joseph Mbawuni & Gyasi Nimako (2015) expressed that 7-point scale gives balance better reliability scale and discriminative demand on the respondents. In order to ensure validity and reliability, most items were adopted and adapted from past literature. A cover letter including details on the reason for the investigation, criteria of the respondents and privacy affirmation on their responses towards this study will be attached to the questionnaire.

3.3.1 Construct Measurements

The constructs measured in this study were adapted and adopted from previous studies indicated in the tables below.

3.3.1(a) Screening Questions

Two screening questions were developed by the author to determine the respondents are international students from semester 1 or semester 2 and to determine the usage of eWoM by international students prior to their enrolment choice. International students from semester 1 and semester 2 are selected to fulfil the requirement in collecting 15 respondents from each selected private universities as not all the 1st semester international students are eligible to answer the questionnaire. This section will help to clear about the criteria of respondents to participate in the study. Having clear process will help to obtain accurate results on testing this study‘s research hypothesis. Table 3.8 specify all the items of screening questions.

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Table 3.8

Screening Questions

Screening Question – 2 items Author

1. Are you a first year (Semester 1, Self-Construct Semester 2) student?

Yes

(If “Yes”, answer the following questions) Self-Construct

2. Have you ever used the electronic Word- of-Mouth – eWoM (e.g. Facebook, Twitter, LinkedIn, You Tube, Google+, Pinterest or Instagram) to search for higher education institution information?

Yes

(If “Yes”, answer the following questions, if “No” process ends. Thank you for your time and participation)

3.3.1(b) Demographic Data

Section B constructs are adopted and adapted from Juan Antonio Moreno et al. (2015). The respondents were asked to answer questions pertaining to their background. Demographic data was collected for analysis purposes. In order to ensure validity, most items were adopted from past literature. There are 9 questions in the section. The questions cover the topics such as age, gender, nationality, PrUni enrolled, programme enrolled and usage of eWoM. Apart from this, in Question 5, the respondents are required to indicate the PrUnis they are enrolled in. This specific

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PrUni was named “X” later in the questionnaire and the respondents have to answer the questions based on the PrHEI they are enrolled in (Question 5).

3.3.1(c) Country Image

There are 3 sections for the country image where the first section is cultural proximity, second is academic reputation and third is socioeconomic level. There are a total of 12 items in this construct, and the items are adapted from Siti Falidah

Padlee et al., (2010), Daniel Lohmann (2015) and Anil Tan (2015). Table 3.9 specify all the items of country image.

Table 3.9

Source and Measurement Items for Country Image

No Original Source Country Image Author (Cultural Proximity)

1 There are cultural similarity to The country of X has similar Siti Falidah my home country culture to my home country. Padlee et al. (2010)

2 Low discrimination The country of X has Daniel Lohmann perceived lower level of (2015) racial discrimination.

3 Religious affiliation are similar The country of X has Siti Falidah to my home country religious affiliation of Padlee et al. institutions. (2010)

4 Safe (low crime) environment Daniel Lohmann The country of X has (2015) perceived lower level of crime.

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Table 3.9 (Continued)

No Original Source Country Image Author (Academic Reputation)

1 This institution has a high The quality of X is better Anil Tan (2015) reputation in my home country than my home country

2 There are many choices of The country of X have Anil Tan (2015) schools and academic programs many choices of quality in the United States than in my institution than in my home home country country

3 Availability of wide choices of Anil Tan (2015) academic programs that fit my The country of X have goals many choices of quality academic programmes than in my home country . 4 The country of education Daniel Lohmann institutions image and reputation The country of X has (2015) is positive destined them as education hub of Asia No Original Source Country Image Author (Socioeconomic level)

1 The quality of lifestyle is higher The quality of X country Anil Tan (2015) than home country lifestyle is higher than my home country 2 Availability of employment The country of X has the Anil Tan (2015) opportunities while studying option for international students to be employed while studying (part time jobs)

3 I would like to live and work in The country of X has the Anil Tan (2015) the United States after option for international graduation students to be employed after graduation 4 The country of X has the Siti Falidah Availability of affordable good medical facilities with Padlee et al. medical facilities. affordable fees. (2010)

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3.3.1(d) City Effect

Items from Joseph Mbawuni & Gyasi Nimako (2015), Anil Tan (2015),

Krishnan et al., (2007) and Daniel Lohmann (2015) are adapted for the city effect construct. This construct is divided into two sections and the total items for this section are 8. Table 3.10 specify all the items of city effect.

Table 3.10

Source and Measurement Items for City Effect

No Original Source City Effect (City Dimension) Author

1 Because the school‘s The city where X is located Joseph Mbawuni & location allows me to allows me to attend classes Gyasi Nimako combine work and college conveniently. (2015) conveniently

2 It is safer place for me to The city where X located is safe Anil Tan (2015) study than my other options for me to study. in the United States

3 Availability of employment The city where X is located Anil Tan (2015) opportunities while studying allows me to find part time job easily.

4 The location of the X friendly city atmosphere Krishnan et al., institution (i.e. in the urban, allows me to have peaceful life (2007) sub-urban or rural location) No Original Source City Effect (Cost and Living) Author

1 The cost of accommodation - The rental of house is affordable Krishnan et al., Accommodations for in the city where X is located. (2007) students are easy available

2 Cost of living are financially The food prices are reasonable in Daniel Lohmann feasible for students the city where X is located. (2015)

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Table 3.10 (Continued)

No Original Source City Effect (Cost and Living) Author

3 Because the college is Public transports are inexpensive Joseph Mbawuni & located in Kumasi where I in the city where X is located. Gyasi Nimako can easily attend classes (2015)

4 Safe, healthy and social Recreational activities are free Krishnan et al., environment provided the city where X is located. (2007)

3.3.1(e) Institution Image

In this study, 22 items were adapted from Joseph Mbawuni & Gyasi Nimako

(2015), Juan Antonio Moreno et al., (2015) and Anil Tan (2015) in measuring the institution‘s image. This section is divided into 3 sub-sections with 18 total items.

These items were selected because they suited the research purpose of current study.

Table 3.11 specify all the items of institution image.

Table 3.11

Source and Measurement Items for Institution Image

No Original Source Institution Image (Quality of Author Professor)

1 Because of the quality of X lecturers teaching quality is Joseph Mbawuni teaching they provide good & Gyasi Nimako (2015)

2 He/she provides clear X lecturers are competent in Juan Antonio information about objectives, their subject areas Moreno et al. bibliography, tutorials, (2015) contents, and assessment methods in the subject's curriculum

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Table 3.11 (Continued)

No Original Source Institution Image (Quality of Author Professor)

3 Because of the quality of the X lecturers profile is impressive Joseph Mbawuni profile of the teaching staff & Gyasi Nimako (2015)

4 He/she maintains an objective X lecturers maintains a Juan Antonio and respectful position with respectful position with the Moreno et al. the students international students. (2015)

He/she efficiently X lecturers efficiently Juan Antonio 5 incorporates and employs incorporates ICTs (Information Moreno et al. ICTs (Information and and Communication (2015) Communication Technologies) as teaching Technologies) medium.

6 He/she applies the assessment X lecturers are fair in assessing Juan Antonio criteria of the activities as international students Moreno et al. established in the subject's (2015) curriculum

No Original Source Institution Image (Institution Author Recognition)

1 Because I believed UEW has X has reputation for quality Juan Antonio reputation for quality academic standards Moreno et al. academic standards (2015)

2 Because the university has X program is recognized Juan Antonio good image worldwide Moreno et al. (2015)

3 This institution has strong X has close link with the Anil Tan (2015) international student support industries in Malaysia which services help international students to attach for industrial training.

4 Because the university has X is affiliated with international Juan Antonio good Reputation professional bodies Moreno et al. (2015)

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Table 3.11 (Continued)

No Original Source Institution Image (Institution Author Recognition)

Higher benefits of having X‘s graduates have the Anil Tan (2015) 5 foreign degree than having reputation of being recruited by national degree in home major corporations upon country completion of their studies

6 Employment opportunities are Employment opportunities are Anil Tan (2015) much greater with a foreign much greater with a degree degree upon return to home from X upon return to home country country

No Original Source Institution Image (Facilities Author on campus)

1 Because the college has good X has good facilities (for Juan Antonio lecture facilities example, lecture hall, library, Moreno et al. sport recreation and etc.) (2015)

2 He/she efficiently X has robust internet connection Juan Antonio incorporates and employs facilities (wired and wireless Moreno et al. ICTs (Information and connections) (2015) Communication Technologies)

3 This institution has strong X has strong international Anil Tan (2015) international student support student support Services services

4 Generally, I like to study in X overall layout is attractive Juan Antonio new school environments Moreno et al. (2015)

5 It is safer place for me to X is well-guarded by university Anil Tan (2015) study than my other options in personal the United States

6 Because the college has great X uphold conducive Juan Antonio resources for learning environment Moreno et al. (2015)

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3.3.1(f) Programme Evaluation

20 items from Krishnan et al., (2007), Daniel Lohmann (2015), Anil Tan

(2015), Siti Falidah Padlee et al. (2010), Anna Round (2005) and Joseph Mbawuni &

Gyasi Nimako (2015) were adapted for programme evaluation. This section is divided into four sub-sections with a total of 20 items, as listed in Table 3.12 below.

Table 3.12

Source and Measurement Items for Programme Evaluation

No Original Source Programme Evaluation Author (Programme Recognition)

1 Accreditation provided to the X courses are accredited by the Krishnan et al., institution's courses or Malaysian government. (2007) programs by the Malaysian government

2 Accreditation provided to the X courses are accredited by Krishnan et al., institution's courses or international bodies (2007) programs by the international bodies

3 Accreditation provided to the X courses are accredited by Krishnan et al., institution's courses or professional bodies (2007) programs by the professional bodies

4 The quality of the higher X courses are accredited by Daniel Lohmann education is high home country. (2015)

5 The good reputation of X courses are recognized by Anil Tan (2015) academic programs home country.

6 Links to other institutions are X courses are recognized among Daniel Lohmann given other overseas higher education (2015) institutions

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Table 3.12 (Continued)

No Original Source Programme Evaluation Author (Programme Suitability)

1 Course duration is suitable X course duration is suitable for Siti Falidah Padlee me et al. (2010)

2 University timetables should X course timetable is flexible to Anna Round be more convenient for rearrange. (2005) students

3 The flexibility of the The flexibility of the minimum Krishnan et al., minimum entry requirements entry requirements in X, (2007) appealed to me

4 My home institution has The flexibility in credit transfer Anil Tan (2015) sister school/dual degree or in X, attracted to me. other exchange programs with this institution

No Original Source Programme Evaluation Author (Programme Specialization)

1 Availability of wide choices The availability of specialized Anil Tan (2015) of academic programs that fit major courses in X attracted me my goals

2 Institution's twinning X twinning arrangement or Krishnan et al., arrangement, links or strategic alliance with well- (2007) strategic alliance with well- known overseas institution‘s known overseas institutions appealed to me .

3 Suitability of institution's X course content is suitable for Krishnan et al., course content me. (2007)

4 Suitability of institution's X course structure is suitable for Krishnan et al., course structure me. (2007)

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Table 3.12 (Continued)

No Original Source Programme Evaluation Author (Programme Specialization)

5 Well defined method of X course content is well defined. Krishnan et al., assessment of institution's (2007) course content

6 Well defined method of X course structure is well Krishnan et al., assessment of institution's defined (2007) course structure

No Original Source Programme Evaluation Author (Programme Specialization)

1 Tuition is cheaper in this X tuition fee is cheaper compare Anil Tan (2015) institution than other to my home country institution. institutions

2 Because the cost of the X provides flexible fee payment Joseph Mbawuni & programme is considerably mode. Gyasi Nimako affordable (2015)

3 This institution offers X offers scholarships (full Anil Tan (2015) scholarships opportunities scholarship or partial scholarship) for international students.

4 This institution offers X offers financial aid for Anil Tan (2015) financial aid opportunities international students (tuition fee waiver upon getting good grades

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3.3.1 (g) Information Quality

Information quality has been debated in the perspective of information system and it is directly related to the information itself. According to Sussman &

Siegal (2003), the quality of the information confined within the information will decide the degree of informational impact. Adding on to Sussman & Siegal (2003),

Bhattacherjee & Sanford (2006), further explained that the significant strength of information embedded in an informational communication which leads to information usefulness for online consumers is defined as information quality.

Information quality is determined by the relevance, up-to-date, accuracy and comprehensiveness of the information itself. Therefore, these four items have been adapted for this study from Sussman & Siegal (2003) IAM. The items are listed in

Table 3.13.

Table 3.13

Source and Measurement Items for Information Quality

No Original Source Source Credibility Author

1 The information from online I receive relevant information of Sussman & Siegal reviews was of sufficient X 2003 depth (degree of detail)

2 The information from online I receive up-to-date information Sussman & Siegal reviews was current for my of X 2003 needs

3 The information from online I receive accurate information of Sussman & Siegal reviews was accurate X 2003

4 The information from online I receive comprehensive Sussman & Siegal reviews was of sufficient information of X 2003 breadth (spanning different subject areas)

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3.3.1(h) Source Credibility

Source credibility is another variable that determines the usefulness of information (Sussman & Siegal, 2003). Source credibility is defined as the extent to which an information source is perceived to be believable, competent and trustworthy by information receiver and reflecting nothing about the information itself (Petty & Cacioppo, 1986 and Chaiken, 1980). There were four items adapted from Sussman & Siegal (2003) and Cheung et al. (2008). They are listed in Table

3.14.

Table 3.14

Source and Measurement Items for Source Credibility

No Original Source Source Credibility Author

1 The reviewers were I receive information of X from Cheung et al. experienced an expert source (2008)

2 The reviewers were I receive information of X Sussman & Siegal trustworthy trustworthy source (2003)

3 The reviewers were credible I receive information of X from Sussman & Siegal a credible source (2003)

4 The reviewers were reliable I receive related information of Sussman & Siegal X from a reliable source (2003)

3.3.1(i) Information Usefulness

The variable ―perceived usefulness‖ was introduced by Davis (1989) in

TAM, where it shows on perceived usefulness is related on the usage of new technology and the implication of new technology on work performance (Davis,

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1993). Sussman & Siegal (2003) investigated further on perceived usefulness and highlighted that perceived usefulness variable could be applied to information communication perspective namely as information usefulness. According to Cheung et al., (2008) information usefulness is the degree to which the consumers perceive the received information as important, therefore could assist consumers in purchasing decision (Cheung et al., 2008). Therefore, this study adapted items from Davis

(1989) as listed in Table 3.15 below.

Table 3.15

Source and Measurement Items for Information Usefulness

No Original Source HEI Enrolment Choice Author

1 The information in online reviews X Information is valuable Davis (1989) was valuable for me.

2 The information in online reviews X Information is Davis (1989) was sufficient informative for me

3 The information in online reviews X Information is helpful Davis (1989) was helpful for me

4 The information in online reviews X Information is Davis (1989) was useful instructive for me.

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3.3.1(j) Enrolment Choice

Enrolment choice may be considered as the outcome from using the information received via eWoM. According to Cheung et al. (2008) and Zhou &

Sung (2008), information usefulness indicates a direct positive effect on actual behaviour of individuals. Therefore, enrolment choice is a procedure in which individuals are purposefully engaged in utilizing the information. This study has adapted items from to Sussman & Siegal (2003) that are in Table 3.16.

Table 3.16

Source and Measurement Items for Enrolment Choice

No Original Source HEI Enrolment Choice Author

1 Review made it easier for me to Information orientation of Sussman & make purchase decision. (e.g., X from eWoM made it Siegal (2003) purchase or not purchase). easier for me to make enrolment choice.

2 Online reviews have enhanced my Information orientation Sussman & effectiveness in making purchase from eWoM guides me to Siegal (2003) decision enrol in X

3 Online reviews have motivated me The information orientation Sussman & to make a purchase decision of X from eWoM motivates Siegal (2003) me to enrol in X

4 The last time I read online reviews Information orientation Sussman & I adopted consumers‘ from eWoM has enhanced Siegal (2003) recommendations and purchased my effectiveness in making (or not purchased) the enrolment choice. recommended product/service

5 The last time I read online reviews Overall, i am satisfied to Sussman & I purchased (or not purchased) the use the information from Siegal (2003 recommended product/service eWoM

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3.4 Statistical Techniques

This study applies the Structural Equation Modelling (SEM) method to examine the proposed associations among the variables in the model. This method is considered sufficient for the type of exploration carried out by this study as it allows answering questions that encompass multiple regression analysis of factors among a single measured dependent variable and a group of measured independent variable

(Ullman, 2007). According to Hair, Blake, Babin & Tatham (2006), SEM is used to test theoretical models. A structural equation model usually comprises of two types of models:

 The measurement model that represents the theory and which specifies how

measured variables come together to represent latent factors, and

 The structural model which represents the theory specifying how constructs

are related to other constructs in the model.

Thus, SEM is a sufficient instrument for testing the hypotheses and succeeding the objectives of this research. The main objective is to examine the significant effectiveness of information orientation used by international students to enrol in

Malaysian PrUnis which include information quality and source credibility as moderating variables. This study also intends to examine the mediating effect of information usefulness on HEI, particularly PrUni enrolment choice by international students. In order to investigate all the objectives of this study, Partial Least Squares

(PLS-SEM) has been utilised. Hair, Sarstedt, Pieper & Ringle (2012) and Ringle,

Sarstedt & Straub (2012) found that the use of PLS-SEM in the marketing and management information systems fields has accelerated over time.

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Recently, PLS-SEM application has expanded in marketing research and practice with the recognition that PLS-SEM‘s distinctive methodological features make it a possible alternative to the more popular Covariance Based (CB-SEM) approaches (Henseler & Chin, 2010). Table 3.17 shows the similarity and differences between the two applications.

Table 3.17

Comparison of PLS-SEM and CB-SEM

Source: Paul Benjamin Lowry and James Gaskin (2014)

A variety of PLS-SEM enhancements have been developed in recent years, including (1) confirmatory tetrad analysis for PLS-SEM to empirically test a construct‘s measurement mode (Gudergan, Ringle, Wende & Will, 2008); (2) impact-performance matrix analysis (Slack, 1994; Völckner, Sattler, Hening-Thurau

& Ringle, 2010); (3) response-based segmentation techniques, such as finite mixture partial least squares (FIMIX-PLS; Hahn, Jenkinson, Herman & Huber 2002;

Sarstedt, Becker, Ringle & Schwaiger, 2011); (4) guidelines for analysing

173 moderating effects (Henseler & Chin 2010; Henseler & Fassott 2010); (5) non-linear effects (Rigdon, Ringle & Sastedt, 2010); and (6) hierarchical component models

(Lohmöller, 1989; Wetzels et al., 2009). These enhancements expand PLS-SEM‘s general usefulness as a research tool in marketing and the social sciences. Table 3.18 clearly indicates the expansion of PLS-SEM usage in marketing discipline.

Table 3.18

Review on PLS-SEM Studies in the Perspective of Business

Business Discipline Authors Time period Number of studies Marketing Hair et al. (2012) 1981-2010 204

Strategic Management Hair et al. (2012) 1981-2010 37

Management Information Ringle et al. (2012) 1992-2011 65 Systems

Productions and Peng & Lai (2012) 2000-2011 42 Operations Management

Accounting Lee et al. (2011) 2005-2011 20

Source: Adapted from Hair, Huit, Ringle &Sarstedt (2014)

Originally developed by Wold (1974, 1982), PLS is a SEM technique based on an iterative approach that maximizes the explained variance of endogenous constructs (Fornell & Bookstein, 1982). Unlike CB-SEM which aims to confirm theories by determining how well a model can estimate a covariance matrix for the sample data, PLS-SEM operates in similarity to a multiple regression analysis (Hair,

Ringle & Sarstedt, 2011).

According to Chin & Newsted (1999), PLS-SEM can be an adequate alternative to CB-SEM if (1) the phenomenon to be investigated is relatively new and measurement models is to be newly developed; (2) the structural equation model is

174 complex with a large number of latent variables and indicator variables; (3) relationship between the indicators and latent variables have to be modelled in different modes (i.e., formative and reflective measurement models); (4) the conditions related to sample size, independence, or normal distribution are not met and (5) prediction is important than parameters estimation. These characteristics make PLS-SEM valuable for this study purposes.

3.4.1 Measurement Model

Measurement models are carried out to analyse the theoretical constructs which are correctly measured by the variables. Both forms of Pre-test and pilot test were carried out in this research.

3.4.1(a) Pre Test

Pre-testing is an important tool to identify the effectiveness and suitability of the instrument designed for the research. The instrument which is designed for the research should be easy to understand without compromising the objective of the research. According to Pheleps, Lewis, Mobilio, Perry & Raman (2004), pre-testing is performed in direction to identify the suitability of the questionnaire design

(format, content, understandability and terminology), easiness and speed of completion. For pre-testing, a number of 30 (Thomas, Delphine, Patricia & Ange`le

Gayet-Ageron, 2014) international students who used eWoM in their decision to enrol into private university are randomly selected to answer the questionnaire. The pre-test outcome for this clearly indicates that the questionnaires design of this research is easy to understand by the respondents without compromising objective of the research.

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3.4.1(b) Pilot Test

Pilot test is conducted in order to test the reliability and validity of research instrument. This pilot test is conducted with a full version of questionnaire using respondent‘s background similar to the real study. Students from private HEIs

(University and University-Colleges) are selected as respondents. This pilot test also allows researcher to detect questions that would and could probably be interpreted differently by the respondents (Krosnick, 1999). Aiman-Smith & Markham (2004) suggested a rule of thumb in direction to decide the quantity of cases in pilot testing which are usually between 150 to 200 respondents. Aiman-Smith & Markham (2004) also suggested that at least 10% of the sample size should be used to conduct pilot test. Aiman-Smith & Markham (2004) suggestion of 10% of the sample size is used to conduct pilot test has been adapted and referred. Hence 38 samples were collected from two different private universities which are not in the 27 selected private universities for this study. The respondents selected were eligible international students who are in their first year of their programme and those who used eWoM prior to their private university enrolment choice. To check the internal consistency or reliability of the items, Cronbach‘s alpha must be above 0.70 (Aiman-Smith & Markham, 2004).

The closer the reliability gets to 1.0, the better, however reliabilities of less than 0.60 are considered poor (Cavana, Relahage & Sekaran, 2003). The essential changes were made before execution of the actual survey.

3.4.1 (b) (i) Validity

Validity is examined by perceiving a construct‘s convergent validity for formative measurement models. Convergent validity is supported when each item has outer loadings above 0.70 and while each construct‘s average variance extracted

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(AVE) is 0.50 or higher. The AVE is the grand mean value of the squared loadings of a set of indicators (Hair et al., 2014) and is equivalent to the communality of a construct. AVE of 0.50 demonstrates that the construct explains more than half of the variance of its indicators.

3.4.1 (b) (ii) Reliability

The composite reliability provides a more appropriate measure of internal consistency reliability for at least two reasons. Firstly, unlike Cronbach‘s α, composite reliability does not assume that all indicator loadings are equal in the population, which is in line with the working principle of the PLS-SEM algorithm that prioritizes the indicators based on their individual reliabilities during model estimation. Secondly, Cronbach‘s α is also sensitive to the number of items in the scale and generally tends to underestimate internal consistency reliability. By using composite reliability, PLS-SEM is able to accommodate different indicator reliabilities (i.e. differences in the indicator loadings), while also avoiding the underestimation associated with Cronbach‘s α.

3.4.2 Structural Model

Structural model is used to provide evidence which supports the hypotheses of the theoretical model of a study. According to Chin (2010), the structural model is assessed according to the meaningfulness and significance of the hypothesized relationship between the constructs which involves factors of Coefficient of determination (R2), Effect size (f2), Cross-validated redundancy (Q2), Path coefficients and Goodness of fit (GoF).

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3.4.2 (a) Coefficient of Determination (R2)

R2 is a measure of the model‘s predictive accuracy. Alternative way to view R2 is that it represents the exogenous variable‘s joined effect on the endogenous variable(s). This effect ranges from 0 to 1 with 1 indicating complete predictive accuracy. R2 with 0.75, 0.50, and 0.25 respectively, describes substantial, moderate or weak levels of predictive accuracy (Hair et al., 2011; Henseler et al., 2014).

3.4.2(b) Cross-Validated Redundancy (Q2)

Q2 is a means for measuring the inner model‘s predictive significance. The smaller the difference among predicted and original values, the better the Q2 and thus the model‘s predictive accuracy. Specifically, a Q2 value which is greater than zero for a specific endogenous construct specifies the path model‘s predictive relevance for this particular construct (Hair et al., 2014).

3.4.2(c) Effect Size (f2)

The effect size for individual path model can be determined by computing

Cohen‘s f2. The f 2 is computed by noting the change in R2 when a specific construct is removed from the model. To calculate f2, the scholar must estimate two PLS path models. The first path model should be the full model as specified by the hypotheses, yielding the R2 of the full model (R2 included). The second model should be similar except that a particular exogenous construct is removed from the model, yielding the

R2 of the reduced model (R2 excluded). Based on the f2 value, the effect size of the omitted construct for a particular endogenous construct can be determined, such that

0.02, 0.15, and 0.35 represent small, medium and large effects respectively (Cohen,

2006). That is, if an exogenous construct strongly contributes to clarifying an

178 endogenous construct, the difference between R2 included and R2 excluded will be high, leading to a high f2 value.

3.4.2 (d) Path Coefficients

Path coefficients represent the hypothesized associations linking the constructs.

Path coefficient values are standardized on a range from – 1 to + 1, with coefficients closer to + 1 representing strong positive associations and coefficients closer to – 1 representing strong negative associations. Although values close to + 1 or – 1 are almost always statistically significant, a standard error must be obtained using bootstrapping to test for significance (Helm, Eggett & Garnefeld, 2010). As specified by Hair et al. (2014), numerous studies oversee this phase and purely rely on the significance of effects. If this essential phase is omitted, scholars may emphasis on association that, although significant, may be too small to merit managerial consideration.

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3.5 Chapter Summary

This chapter explains the research methodology which includes research design, population, sample size, research instruments data collection procedures and statistical techniques. The unit analyses are to follow three basic rules indicating the first rule where the private universities (PrUnis) selected for this study were sub grouped into two categories: (a) university status – local and (b) university status – branch campus of Foreign University. Secondly, the prospective participants should be international participants and thirdly, the participants should be in the first or second semester of their study.

Structured questionnaire will be utilized to gather the information, and the questionnaires are divided into ten broad sections. Questions in section ―A‖ are used to screen out respondents who are not fit to participate in the rest of the questions.

Section ―B‖ has 9 questions in to understand the customers‘ demographic characteristics. Section ―C, D, E, F, G, H, I and J‖ addresses the issues related to the information adoption via eWoM with regards. Section ―C, D, E, F, G, H, I and J‖ questions are designed established on the 7 point Likert Scale. Overall number of constructs measured is 84 constructs. Partial Least Squared (PLS) is used to analyse and test the hypotheses for this study; the structural model provides evidence supporting the theoretical model in the study which includes predictive power, effect size, bootstrap procedure, and predictive relevance.

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CHAPTER 4

FINDINGS

4.0 Introduction

This chapter discusses on the data analysis and hypotheses testing of the study. The Partial Least Squared (PLS) technique, a covariance based Structural

Equation Modelling (SEM) was used to examine the data collected from the survey.

First, the response rate of the respondents was acquired, followed by the profiling of the respondents‘ demographic data. The profile of the respondents was obtained using the descriptive statistics using the Statistical Package for the Social Sciences

(SPSS) software, version 22. In addition to this, evaluation on the goodness of the measure was performed using validity and reliability tests. Finally, the structural model assessment was performed and the summary of hypotheses testing was concluded together with the model fit assessment.

4.1 Analysis of Survey Response

In this section, the results of data collection and demographic data were analysed and presented. This section focuses on the goodness of data, response rate and profile of respondents.

4.1.1 Goodness of Data

The primary data of this study was collected through an instrument in the form of a questionnaire. It aimed 27 PrUnis around Malaysia as shown in Table 3.6 of Chapter 3. The data collection was conducted over a period of three months, from

September 2016 until end of November 2016. Prior to performing the data analysis,

181 data from thirty-nine respondents for pilot study were excluded. From an overall of

400 questionnaires distributed, 359 questionnaires were usable.

4.1.2 Response Rate

Table 4.1 below summarizes the PrUni which allowed data collection for this study. The questionnaires were distributed and collected in the early month of

September 2016 and it ended in the month of November 2016. Official letters requesting for permission to enter and collect data were emailed in the early month of August 2016 to the respective PrUnis. A total of 27 PrUnis (21 locally funded

PrUnis and 6 foreign funded PrUnis) were selected to collect the data as per discussion in chapter 3. From the 27 selected PrUnis, only 18 PrUnis (15 locally funded PrUnis and 3 foreign funded PrUnis) granted permission to collect data from their premises and students. Hence, the minimum number of answered questionnaire to be collected from each 18 PrUni had increased from 15 to 21 questionnaires to achieve the desired 381 sample size.

Table 4.1 PrUni Permission for Data Collection

Description No of samples Percentage Total Number of PrUnis selected 27 100%

PrUnis – Permitted data collection 18 67%

PrUnis – Decline Permission for data 7 26% collection

No answer from PrUnis 2 7%

Table 4.2 below indicates the response rate of current study. A total of 400 questionnaires were circulated to the respective PrUnis. Out of the 381 (95%) questionnaires collected, only 359 (94%) were usable while 22 questionnaires (0.6%)

182 were incomplete. Thus, making them disqualified for use and 19 questionnaires returned without participation. Therefore, 359 valid responses were utilized for data analysis after data was cleaned.

Table 4.2 Response Rate Description No of samples Percentage Total Number of 400 100% Distributed Questionnaires

Overall Response 381 95%

Effective Response Rate 359 94% (Usable)

Questionnaires Returned 22 0.6% (Unusable)

Unreturned Questionnaires 19 0.5%

4.1.3 Test for Non-Response Bias

To guarantee that the outcome of non-response bias is minimal and non- existence, an assessment between early and late responses in terms of major variables of the study were carried out. An independent samples t-test was performed to compare the results of major variables for early and late responses. Table 4.3 summarizes the mean and standard deviation of the major variables of the study for overall sample, early and late responses. Non-response bias is a critical concern for this study and a non-response bias test was carried out with the late respondents being utilized as proxy for non-respondents (Mooi & Sarstedt, 2011). In respect of this recommendation, independent sample test using the Levene's Test for Equality of Variances has been employed to see whether the early and late respondent groups show any differences. If significant value is greater than 0.05, it means there are no

183 significant variances among the 2 groups. In order to accomplish this purpose, the first group of 344 usable questionnaires returned in the month of September and

October 2016 was considered as early respondents and the second group of 15 questionnaires received in end November 2016 was considered as late respondents.

Results from the Independent Samples t-test are shown in Table 4.3 below. The outcomes reveal there are no substantial variances statistically at the 0.05 level for any of the characteristics of the two groups, namely early respondents and late respondents. Based on the result, current study assumes non-response bias is not a critical concern for the current study.

Table 4.3

Differences in the Major Variables by Early and Late Responses

Group Statistics Levene's Test for Equality of t-test for Group N Mean Variances Equality of Variable Means F Sig Sig. (2-tailed) Early 344 4.4419 2.044 0.154 0.813 CP Late 15 4.5000 0.767 Early 344 4.5501 1.760 0.186 0.265 AP Late 15 4.8667 0.131 Early 344 4.3837 1.458 0.228 0.950 SL Late 15 4.3667 0.931 Early 344 4.7129 0.144 0.704 0.153 CD Late 15 4.3667 0.161 Early 344 4.5036 0.005 0.944 0.511 CL Late 15 4.6833 0.549 Early 344 4.9821 2.112 0.147 0.192 QP Late 15 5.3333 0.095 Early 344 4.8416 0.984 0.322 0.912 IR Late 15 4.8667 0.905 Early 344 4.8929 0.872 0.351 0.770 FC Late 15 4.8222 0.764 Early 344 4.9322 0.255 0.614 0.739 PR Late 15 5.0111 0.758

184

Table 4.3 (Continued)

Group Statistics Levene's Test for Equality t-test for Group N Mean of Variances Equality of Variable Means F Sig Sig. (2- tailed) Early 344 4.8016 2.332 0.128 0.746 PS Late 15 4.8833 0.675 Early 344 4.9506 0.601 0.439 0.064 PZ Late 15 5.3778 0.051 Early 344 4.1781 0.081 0.777 0.861 CF Late 15 4.2333 0.876 Early 344 4.8452 0.110 0.740 0.866 IQ Late 15 4.8000 0.869 Early 344 4.7398 3.228 0.073 0.980 SC Late 15 4.7333 0.971 Early 344 4.9113 0.224 0.636 0.355 IU Late 15 5.1500 0.349 Early 344 4.7895 0.741 0.390 0.876 EC Late 15 4.8267 0.846

4.1.4 Profile of the Respondents

Before examining the data, it is wise to explore the demographic profile of the respondents who directly involved in the survey. This study focused on a limited set of respondent‘s demographic items which comprise of country of origin, gender, age, university programme courses, eWoM platform and information category, all of which were anticipated to be vital in the explanation of the outcomes.

The description of the respondents in this research is shown in Table 4.4. Out of the 359 usable data, 54% are male respondents and 46% are female respondents.

From this 359 usable data, respondents from China contributed 16.4%; Indonesia

8.9%; Bangladesh 8.1%; Pakistan 6.4%; Yemen 5.9%; Nigeria 5.3%; Iran 4.5%;

185

India 4.2 %; UAE 3.1% and respondents from other countries contributing lesser than 3.0% to the study. Respondents covered the range of age categories from 15 to

35 years old and above, with the majority of 53.8% of the respondents included in the survey sample are between the age group of 20-24 years old who are mostly from

Bachelor Degree programme (245 students), followed by the age group of 15-19 years old at 35.9% which consist students from foundation programme (36 students),

Diploma programme (42 students) and a small portion of Bachelor Degree programme (51 students) and the third largest age group being 25-29 years old at

9.2%. In terms of respondents‘ course selection, 68.2% of the respondents were from

Bachelor Degree course. This is followed by 11.8% of respondents from Diploma course. Respondents from Master and Foundation programme, contribute 10% respectively from the total respondents for this study. The majority of respondents represent PrUni – local origin, which contribute 85%, while the respondents from

PrUni – foreign origin contribute 15% for this study.

Other than respondents‘ demographic data, this study also analyses respondents‘ choice of eWoM channels and the information category search by respondents in eWoM platform. Table 4.5 shows the most preferred eWoM channels used by respondents in searching for information about PrUnis is Facebook. It was followed by Instagram (52) and Google+ (34). Table 4.6 shows the respondents‘ most searched PrUni information category. It clearly indicates that university image

(110) and course information (104) are the most searched information by respondents in eWoM platform. This is followed by quality of lecturer (49) and course recognition (46).

186

Table 4.4 Respondent Demographic Profile

Frequencies Percentage (%) Country of Origin Australia 2 0.6 Bangladesh 29 8.1 Botswana 1 0.3 Botswana 1 0.3 Brunei 8 2.2 China 59 16.4 Egypt 4 1.1 Germany 2 0.6 Ghana 1 0.3 India 15 4.2 Indonesia 32 8.9 Iran 16 4.5 Iraq 4 1.1 Italy 1 0.3 Jamaica 1 0.3 Japan 3 0.8

Jordan 2 0.6 Kazakhstan 6 1.7 Kenya 2 0.6 Libya 2 0.6 Maldives 8 2.2 Mauritius 7 1.9 Morocco 1 0.3 Myanmar 1 0.3 New Zealand 1 0.3 Nigeria 19 5.3 Pakistan 23 6.4 Palestine 2 0.6 Philippines 2 1.2

187

Table 4.4 (Continued)

Frequencies Percentage (%) Country of Origin Portugal 1 0.3 Republic of Korea 8 2.3 Russia 1 0.3 Saudi Arabia 6 1.7 Singapore 6 1.7 Somalia 1 0.3 South Africa 6 1.7 Spain 3 0.8 Sri Lanka 7 1.9 Sudan 6 1.7 Syria 5 1.4 Thailand 5 1.4 Timor Leste 3 0.8 Turkmenistan 2 0.6 UAE 11 3.1 Uganda 1 0.3 United States of America 1 0.3 Uzbekistan 4 1.1 Vietnam 2 0.6 Yemen 21 5.9 Zimbabwe 2 0.6 Gender Male 194 54.0 Female 165 46.0 Age 15 - 19 129 35.9 20 - 24 193 53.8 25 - 29 33 9.2 30 - 35 2 0.6 36 and above 2 0.6

University Private University - Local 305 85.0 Category Origin Private University - Foreign 54 15.0 Origin

188

Table 4.4 (Continued)

Frequencies Percentage (%) University Course Foundation 36 10.0 Diploma 42 11.8 Bachelor Degree 245 68.2 Master Degree 36 10.0

Table 4.5

Top eWoM Platform eWoM Ranking (Frequencies) Platform Rank 1 Rank 2 Rank 3 Rank 4 Rank 5

Facebook 196 57 44 34 24

Instagram 52 73 59 61 66

Google+ 34 48 69 84 64

YouTube 33 68 96 75 46

Twitter 30 65 69 69 79

LinkedIn 8 37 16 18 41

Pinterest 6 11 9 18 39

Table 4.6

Top Information Category

Information Ranking (Frequencies) Categories

Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 University Image 110 37 39 41 41

Course Information 104 93 48 26 26

189

Table 4.6 (Continued)

Information Ranking (Frequencies) Categories

Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Quality Lecturers 49 36 53 54 49

Course Recognition 46 80 73 38 34

Course Options 19 52 66 69 39

City of the 12 29 30 67 68 University Located

Video of University 10 21 32 36 47 Facilities

Cultural Proximity 7 9 18 28 51

4.2 Missing Value Imputation

Among the fundamental steps in any study is to assess the study‘s data prior to analysing the effect of research framework on the particular phenomenon and thus, data screening was necessary. The essential for conducting data screening process was stressed in research methodology because the erroneous and poor quality of data distribution may distort analysis techniques and results (Tabachnick & Fidell, 2013;

Pallant, 2011; Kline, 2011). Although PLS-SEM was used in this study to evaluate the model quality such as measurement model, structural model and the hypotheses testing which has less sensitivity about data normality, data screening was still employed so that the nature of the distribution of data could be known. The main purpose of these screening procedures is to detect and decide on what to do with any extreme data encountered.

According to Cordeiro, Machas & Neves (2010), missing values emerge from the non-response of the respondents on the survey which might because of different

190 reasons. In addition, Cordeiro et al., (2010) clarified that these missing values can turn into a major issue during the investigation as it can diminish the statistical power and create unfairness outcomes from the inadequate data. Expectation Maximization

(EM) is used to overcome missing value problem. According to Byrne (2010), EM was claimed to be dominant in producing results close to the true results. There are four key procedures to be followed in using EM technique as discussed by

Kristensen & Eskildsen, (2010). The four key procedures are; first, replacing missing values by estimated values; two, estimating parameters of the variables distribution; three, re-estimating missing value assuming that the new parameter estimates are true; and four re-estimating parameters in an iterative procedure until convergence which needs to be followed in using EM technique to overcome the missing value.

However, in the present study, no missing value was found. This is because the issue of missing value has been addressed when data is collected, where by the researcher monitored and administrated the data collection procedures from the specified private universities. Each question should be answered by the respondents to proceed to the following pages. Besides that, only completed surveys are recorded to ensure that the issue of missing value does not arise.

191

4.2.1 Common Method Variance

Data collected over a cross-sectional survey technique could possibly lead to common method variance issue. Common method variance arises from having common rates, common measurement context, common item context or the common characteristics of the items (Podsakoff & Organ, 1986). In addition, the scholar also explained that common method bias is an issue which need to be addressed if a single latent factor would account for the majority of the explained variance. Harman single factor test was carried out to decide the presence of common method variance.

The fundamental premise of the Harman‘s single factor is where all items, apparently measuring a variety of different constructs were subjected to a single factor analysis.

The un-rotated factor analysis was performed on all measurement items, extracting seventeen factors with eigenvalues greater than 1.0, which accounted for 68.45% of the total variance. Factor one accounts for only 29.41% of the variance, thus common method variance was not a serious problem in this study. Karahanna,

Agarwal & Angst (2006) found that common method variance is not a serious threat in their study as Harman single factor test reveals a total variance of 71.6% where the first factor accounts for 39.3% (Appendix B).

4.3 Goodness of Measure

The present study uses SmartPLS software, version 3.0 to perform data analysis, according to Hair, Piper & Ringle (2012) this software is widely used to perform PLS-SEM method in marketing research. A PLS-SEM path model is examined and deduced in two phases, namely measurement model and structural model. First, the measurement model is similarly recognized as the outer model and

192 tested to ensure validity and reliability between constructs and indicators.

Measurement properties of multi-item constructs, including convergent validity, discriminant validity and reliability were examined by conducting confirmatory factor analysis (CFA). Multicollinearity testing was also part of the measurement model for formative measurement adapted in second order construct. Second, the structural model also known as inner model, was analysed to determine the relationship between constructs by means of R square (R2), effect size (f2) and predictive relevance of the model (Q2). Bootstrapping of 5,000 sub samples iteration as recommended by Hair et al., (2014) was utilized to examine the study hypotheses.

Figure 4.1 shows the full research model with inner and outer models of the current study.

193

CP1

CP2

CP3

Cultural Proximity CP4

Country Image AP1

AP2

AP3 Academic Reputation AP4

Information SL1 Quality IQ1 SL2 IQ2 SL3 Socioeconomic Level IQ3 SL4

IQ4 CD1

CD2 City Effect Source Credibility SC1 CD3

City Dimension SC2 CD4

SC3 CL1 SC4

CL2

CL3

Cost of Living CL4 PrUni Enrollment EC5

QP1 IU1 EC4

QP2 IU2 EC3

QP3 IU3 EC2 QP4 Information Usefulness IU4 Quality of Professor EC1 QP5

QP6

IR1 Institution Programme IR2 Image Evaluation

IR3

IR4 Institution Recognition IR5 Programme Programme Cost and Programme Finance Recognition Suitability Specialization IR6

FC1 PR1

PZ1 FC2 PR2 PS1 CF1 PZ2 FC3 PR3 PS2 CF2 PZ3 FC4 PR4 PS3 CF3 Facilities on Campus PZ4 FC5 PR5 CF4 PS4 PZ5 FC6 PR6 PZ6

Figure 4.1: Research Model (Inner and Outer) Models)

194

4.3.1 Construct Validity

Construct validity testifies the extent to which a set of measured variables actually represent the theoretical latent construct those variables are designed to measure (Hair et al., 2014). It comprises of two important components; convergent and discriminant. Before assessing the convergent and discriminant validity, the respective loadings and cross loadings of the factors are assessed if there is any problem with any particular items. The cut off value of 0.5 is used as suggested by

Hair et al. (2014) whereby values greater than 0.5 are generally considered for practical significance. Accordingly, two items were removed from further analysis because the loading from other constructs are higher than item CP4 (0.535) and CD3

(0.524). As a result, the items for Cultural Proximity (CP4) and City Dimension

(CD3) were deleted. The analysis was re-run and the new loadings and cross loadings were obtained as depicted in Table 4.7. It was observed that all the items measuring a particular construct loaded highly on that construct and loaded lower on the other construct, thus confirming construct validity.

195

Table 4.7 Loading and Cross Loading

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr

CP1 0.819 0.293 0.386 0.285 0.174 0.268 0.281 0.175 0.331 0.186 0.233 0.176 0.221 0.193 0.225 0.185 CP2 0.771 0.184 0.314 0.199 0.105 0.186 0.213 0.192 0.077 0.080 0.106 0.162 0.179 0.196 0.158 0.191

CP3 0.588 0.305 0.156 0.235 0.183 0.230 0.345 0.201 0.245 0.119 0.127 0.226 0.232 0.193 0.179 0.256

AP1 0.338 0.789 0.460 0.284 0.290 0.321 0.383 0.398 0.271 0.280 0.283 0.250 0.304 0.272 0.234 0.274 AP2 0.319 0.877 0.400 0.385 0.201 0.330 0.387 0.404 0.310 0.262 0.309 0.164 0.326 0.313 0.347 0.330 AP3 0.263 0.851 0.392 0.361 0.146 0.293 0.396 0.398 0.395 0.215 0.305 0.144 0.265 0.231 0.275 0.299

AP4 0.198 0.715 0.355 0.342 0.274 0.411 0.380 0.366 0.303 0.335 0.371 0.228 0.291 0.242 0.308 0.288

SL1 0.243 0.499 0.613 0.252 0.178 0.307 0.281 0.362 0.181 0.265 0.208 0.142 0.224 0.195 0.162 0.228 SL2 0.410 0.294 0.772 0.229 0.325 0.269 0.321 0.266 0.188 0.223 0.197 0.302 0.251 0.183 0.108 0.139 SL3 0.315 0.365 0.843 0.279 0.390 0.409 0.500 0.404 0.312 0.372 0.327 0.309 0.314 0.243 0.234 0.200

SL4 0.207 0.272 0.673 0.264 0.346 0.327 0.356 0.352 0.219 0.240 0.285 0.322 0.257 0.235 0.176 0.186

CD1 0.299 0.377 0.312 0.733 0.241 0.393 0.416 0.360 0.421 0.375 0.375 0.237 0.399 0.307 0.393 0.368 CD2 0.263 0.361 0.298 0.849 0.215 0.369 0.317 0.381 0.409 0.258 0.355 0.123 0.341 0.258 0.344 0.325

CD4 0.213 0.263 0.222 0.781 0.237 0.319 0.312 0.361 0.293 0.202 0.336 0.137 0.290 0.226 0.354 0.252

CL1 0.160 0.213 0.332 0.273 0.781 0.383 0.374 0.293 0.238 0.374 0.292 0.322 0.341 0.253 0.273 0.255 CL2 0.116 0.212 0.284 0.284 0.817 0.353 0.341 0.317 0.203 0.291 0.338 0.242 0.248 0.204 0.266 0.183 CL3 0.194 0.220 0.288 0.166 0.726 0.299 0.351 0.287 0.179 0.227 0.266 0.235 0.217 0.209 0.253 0.203

CL4 0.154 0.189 0.385 0.119 0.650 0.315 0.322 0.259 0.114 0.260 0.208 0.287 0.246 0.178 0.160 0.154

QP1 0.186 0.377 0.345 0.372 0.356 0.859 0.505 0.433 0.433 0.576 0.553 0.255 0.501 0.392 0.467 0.401 QP2 0.259 0.391 0.335 0.391 0.313 0.855 0.475 0.418 0.461 0.515 0.527 0.282 0.494 0.452 0.434 0.394 QP3 0.287 0.366 0.421 0.368 0.390 0.845 0.522 0.420 0.400 0.536 0.538 0.368 0.446 0.468 0.404 0.373

196

Table 4.7 (Continued)

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr

QP4 0.215 0.259 0.463 0.346 0.402 0.812 0.431 0.400 0.344 0.521 0.533 0.336 0.401 0.378 0.375 0.341 QP5 0.300 0.328 0.290 0.403 0.363 0.712 0.479 0.453 0.470 0.421 0.472 0.272 0.432 0.395 0.407 0.436 QP6 0.273 0.293 0.356 0.348 0.392 0.793 0.444 0.393 0.348 0.477 0.469 0.352 0.443 0.292 0.362 0.377

IR1 0.234 0.389 0.251 0.405 0.271 0.498 0.732 0.443 0.495 0.373 0.471 0.185 0.480 0.399 0.404 0.372 IR2 0.214 0.382 0.229 0.329 0.234 0.338 0.679 0.379 0.454 0.189 0.360 0.107 0.345 0.296 0.302 0.241 IR3 0.174 0.287 0.493 0.242 0.458 0.494 0.752 0.424 0.410 0.465 0.473 0.318 0.437 0.386 0.311 0.288 IR4 0.366 0.304 0.459 0.291 0.406 0.490 0.774 0.501 0.452 0.429 0.401 0.326 0.422 0.396 0.282 0.314 IR5 0.372 0.407 0.432 0.398 0.343 0.435 0.772 0.498 0.441 0.376 0.419 0.222 0.426 0.434 0.363 0.389

IR6 0.248 0.339 0.325 0.269 0.308 0.284 0.686 0.424 0.431 0.235 0.281 0.154 0.356 0.271 0.189 0.203

FC1 0.279 0.369 0.374 0.354 0.271 0.348 0.555 0.754 0.418 0.316 0.311 0.236 0.435 0.346 0.351 0.347 FC2 0.141 0.322 0.405 0.344 0.348 0.399 0.400 0.704 0.293 0.430 0.421 0.255 0.465 0.302 0.384 0.343 FC3 0.229 0.331 0.514 0.274 0.380 0.390 0.467 0.708 0.312 0.385 0.297 0.431 0.382 0.275 0.267 0.277 FC4 0.145 0.391 0.286 0.329 0.198 0.357 0.365 0.767 0.389 0.331 0.370 0.228 0.426 0.323 0.343 0.347 FC5 0.183 0.429 0.309 0.362 0.299 0.378 0.487 0.793 0.425 0.314 0.358 0.251 0.429 0.366 0.376 0.388

FC6 0.141 0.319 0.248 0.416 0.240 0.433 0.437 0.744 0.496 0.392 0.436 0.240 0.394 0.303 0.351 0.374

PR1 0.255 0.335 0.202 0.456 0.241 0.419 0.508 0.469 0.777 0.392 0.505 0.205 0.437 0.432 0.424 0.404 PR2 0.297 0.354 0.316 0.458 0.253 0.399 0.556 0.521 0.820 0.396 0.504 0.267 0.432 0.387 0.412 0.370 PR3 0.236 0.264 0.272 0.404 0.299 0.486 0.544 0.412 0.827 0.467 0.512 0.271 0.451 0.452 0.395 0.310 PR4 0.193 0.269 0.140 0.326 0.099 0.308 0.391 0.328 0.740 0.285 0.452 0.105 0.312 0.309 0.289 0.308 PR5 0.222 0.267 0.255 0.280 0.154 0.387 0.396 0.330 0.785 0.381 0.480 0.182 0.354 0.297 0.277 0.373

PR6 0.213 0.372 0.269 0.296 0.111 0.357 0.453 0.394 0.762 0.375 0.437 0.184 0.385 0.342 0.290 0.251

197

Table 4.7 (Continued)

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr

PS1 0.191 0.291 0.295 0.291 0.319 0.552 0.443 0.415 0.492 0.824 0.615 0.302 0.495 0.400 0.413 0.452 PS2 0.111 0.302 0.283 0.233 0.250 0.424 0.371 0.386 0.364 0.748 0.417 0.186 0.362 0.281 0.293 0.302 PS3 0.159 0.275 0.301 0.351 0.332 0.525 0.360 0.403 0.404 0.852 0.561 0.315 0.452 0.405 0.416 0.451 PS4 0.082 0.167 0.322 0.205 0.312 0.436 0.319 0.299 0.245 0.689 0.489 0.386 0.334 0.339 0.325 0.286

PZ1 0.244 0.361 0.232 0.394 0.201 0.446 0.490 0.385 0.559 0.509 0.717 0.251 0.450 0.433 0.430 0.417 PZ2 0.168 0.287 0.230 0.377 0.166 0.431 0.418 0.342 0.505 0.431 0.734 0.215 0.431 0.361 0.424 0.381 PZ3 0.207 0.352 0.261 0.400 0.310 0.516 0.436 0.435 0.503 0.544 0.833 0.182 0.458 0.465 0.496 0.422 PZ4 0.148 0.269 0.270 0.365 0.279 0.474 0.420 0.369 0.451 0.497 0.807 0.230 0.458 0.442 0.467 0.407 PZ5 0.179 0.289 0.326 0.277 0.372 0.534 0.397 0.384 0.439 0.601 0.820 0.297 0.415 0.406 0.463 0.404

PZ6 0.086 0.260 0.316 0.305 0.422 0.571 0.430 0.381 0.429 0.573 0.779 0.295 0.442 0.387 0.468 0.361

CF1 0.171 0.092 0.181 0.136 0.294 0.260 0.198 0.192 0.123 0.185 0.209 0.701 0.228 0.204 0.182 0.136 CF2 0.188 0.127 0.195 0.224 0.249 0.293 0.207 0.280 0.196 0.291 0.235 0.737 0.343 0.271 0.250 0.298 CF3 0.242 0.303 0.379 0.154 0.291 0.333 0.292 0.358 0.256 0.391 0.291 0.856 0.384 0.245 0.233 0.269

CF4 0.152 0.179 0.340 0.132 0.292 0.287 0.235 0.275 0.213 0.274 0.224 0.790 0.384 0.177 0.186 0.202

IQ1 0.280 0.306 0.271 0.412 0.216 0.464 0.500 0.455 0.519 0.433 0.535 0.362 0.823 0.549 0.558 0.509 IQ2 0.289 0.350 0.286 0.323 0.273 0.450 0.551 0.521 0.466 0.414 0.460 0.383 0.859 0.577 0.499 0.513 IQ3 0.201 0.270 0.372 0.339 0.391 0.518 0.423 0.447 0.324 0.492 0.478 0.410 0.848 0.500 0.467 0.457

IQ4 0.184 0.313 0.301 0.389 0.332 0.464 0.437 0.495 0.393 0.472 0.441 0.343 0.864 0.508 0.540 0.445

SC1 0.230 0.289 0.306 0.272 0.296 0.447 0.466 0.363 0.433 0.383 0.397 0.262 0.505 0.800 0.427 0.492 SC2 0.199 0.300 0.284 0.259 0.298 0.413 0.458 0.385 0.390 0.411 0.470 0.306 0.544 0.868 0.499 0.471 SC3 0.249 0.235 0.210 0.278 0.223 0.402 0.428 0.352 0.408 0.390 0.463 0.209 0.553 0.880 0.526 0.521 SC4 0.205 0.289 0.205 0.320 0.159 0.400 0.357 0.355 0.381 0.376 0.464 0.214 0.527 0.834 0.522 0.451

198

Table 4.7 (Continued)

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr

IU1 0.237 0.352 0.243 0.396 0.319 0.486 0.428 0.419 0.420 0.430 0.531 0.234 0.542 0.501 0.836 0.453 IU2 0.220 0.262 0.193 0.382 0.249 0.386 0.368 0.384 0.426 0.349 0.479 0.206 0.522 0.535 0.870 0.435 IU3 0.229 0.286 0.200 0.379 0.288 0.428 0.341 0.390 0.342 0.425 0.506 0.246 0.481 0.487 0.867 0.468 IU4 0.186 0.318 0.163 0.410 0.244 0.409 0.307 0.384 0.330 0.391 0.478 0.254 0.535 0.473 0.832 0.482

EC2 0.258 0.266 0.248 0.307 0.224 0.374 0.368 0.361 0.409 0.364 0.385 0.254 0.493 0.501 0.389 0.803 EC3 0.202 0.320 0.240 0.246 0.248 0.374 0.338 0.323 0.344 0.404 0.411 0.262 0.416 0.413 0.345 0.791 EC4 0.178 0.259 0.102 0.293 0.111 0.298 0.237 0.290 0.323 0.330 0.349 0.222 0.373 0.392 0.371 0.783

EC5 0.187 0.284 0.196 0.399 0.204 0.404 0.325 0.429 0.326 0.340 0.431 0.154 0.416 0.411 0.462 0.742 Notes: CP – Cultural Proximity; AP – Academic Reputation; SL – Socioeconomic Level; CD – City Dimension; CL – Cost of Living; QP – Quality of Professor; IR – Institution Recognition; FC – Facility on Campus; PR – Programme Recognition; PS – Programme Suitability; PZ – Programme Specialization; CF – Cost of Finance; IQ – Information Quality; SC – Source Credibility; EC – Enrolment Choice

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4.3.1 (a) (i) Convergent Validity

Convergent validity is the degree to which the items that are indicators of a specific construct should converge or share a high proportion of variance in common

(Hair et al., 2014). Hair et al., (2014) suggested several ways to estimate the convergent validity among items measured such as factor loadings, average variance extracted (AVE) and composite reliability (CR). The loadings for all items exceed the recommended value of 0.50 or higher (Hair et al., 2014). Average variance extracted (AVE) which is a mean variance extracted for the items loading on a construct were all above the recommended value of 0.5 or higher (Hair et al., 2014), which means that more than one-half of the variances observed in the items were accounted for by their hypothesized factors (Liao, 2011).

The AVE for this study is in the range of 0.534 and 0.725. Composite

Reliability which indicates the degree to which the latent variables can be explained by the observed variables (Tseng & Tsai, 2011) is in the range of 0.774 and 0.922 which exceeds the cut off value of 0.7 (Hair et al., 2014). Thus, this study ensured the existence of convergent validity. Table 4.8 summarizes the results of the measurement model which shows that the constructs are all valid measures of their respective constructs. According to Gotz, Liehr-Gobbers & Krafft (2010), the composite reliability is similar to Cronbach‘s alpha, a measure of a reflective construct‘s construct reliability, yet it includes the actual factor loading in which the alpha uses equal weighting. As such, Table 4.8 did not include Cronbach‘s alpha value.

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Table 4.8 Results of Measurement Model

Model Construct Construct Loadings AVE Composite Item Reliability Cultural Proximity CP1 0.819 0.537 0.774 CP2 0.771 CP3 0.588 Academic AP! 0.789 0.657 0.884 Reputation AP2 0.877 AP3 0.851 AP4 0.715 Socioeconomic SL1 0.613 0.534 0.818 Level SL2 0.772 SL3 0.843 SL4 0.673 City Dimension CD1 0.733 0.623 0.832 CD2 0.849 CD4 0.781 Cost of Living CL1 0.781 0.557 0.833 CL2 0.817 CL3 0.726 CL4 0.650 Quality of QP1 0.859 0.663 0.922 Professors QP2 0.855 QP3 0.845 QP4 0.812 QP5 0.712 QP6 0.793 Institution IR1 0.732 0.538 0.875 Recognition IR2 0.679 IR3 0.752 IR4 0.774 IR5 0.772 IR6 0.686 Facilities on FC1 0.754 0.556 0.882 Campus FC2 0.704 FC3 0.708 FC4 0.767 FC5 0.793 FC6 0.744 Programme PR1 0.777 0.617 0.906 Recognition PR2 0.820 PR3 0.827 PR4 0.740 PR5 0.785 PR6 0.762

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Table 4.8 (Continued)

Model Construct Construct Loadings AVE Composite Item Reliability Programme PS1 0.824 0.610 0.861 Suitability PS2 0.748 PS3 0.852 PS4 0.689 Programme PZ1 0.717 0.613 0.905 Specialization PZ2 0.734 PZ3 0.833 PZ4 0.807 PZ5 0.820 PZ6 0.779 Cost And Finance CF1 0.701 0.598 0.855 CF2 0.737 CF3 0.856 CF4 0.790 Information Quality IQ1 0.823 0.720 0.911 IQ2 0.859 IQ3 0.848 IQ4 0.864 Source Credibility SC1 0.800 0.716 0.910 SC2 0.868 SC3 0.880 SC4 0.834 Information IU1 0.836 0.725 0.913 Usefulness IU2 0.870 IU3 0.867 IU4 0.832 PrUni Enrolment EC1 0.769 0.605 0.884 Choice EC2 0.803 EC3 0.791 EC4 0.783 EC5 0.742 Note: Although all items surpassed the suggested value of 0.5 by Hair et al (2014), items CP4 (0.535) and CD3 (0.524) were deleted in establishing discriminant validity.

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4.3.1 (a) (ii) Discriminant Validity

Discriminant validity is the extent to which a construct is truly distinct from other constructs (Hair et al., 2014). It is indicated by inevitable low correlation between the measure of interest and other measures that are supposedly not measuring the same variable or concept. To address discriminant validity, the square root of the AVE is compared against the correlations of the other constructs (Fornell

& Larcker, 1981). As shown in Table 4.9, the calculated square root of the AVE exceeds the inter-correlations of the construct with the other constructs in the model which ensures adequate discriminant validity. In total, the measurement model of the study demonstrated adequate convergent and discriminant validity (Figure 2).

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Table 4.9 Discriminant Validity of Constructs

AP CD CF CL CP FC EC IQ IU IR PR PZ PS QP SL SC Academic Recognition 0.810 City Dimension 0.422 0.789 Cost and Finance 0.240 0.208 0.773 Cost of Living 0.278 0.292 0.362 0.746 Cultural Proximity 0.356 0.329 0.253 0.210 0.734 Facilities on Campus 0.483 0.466 0.366 0.388 0.255 0.746 PrUni Enrolment Choice 0.368 0.398 0.300 0.268 0.282 0.465 0.778 Information Quality 0.366 0.434 0.440 0.354 0.287 0.566 0.568 0.849 Information Usefulness 0.358 0.460 0.276 0.323 0.258 0.463 0.540 0.611 0.851 Institution Recognition 0.476 0.439 0.306 0.464 0.378 0.609 0.417 0.564 0.425 0.734 Programme Recognition 0.394 0.474 0.262 0.251 0.305 0.524 0.429 0.506 0.446 0.608 0.786 Programme Specialization 0.388 0.450 0.313 0.375 0.219 0.490 0.510 0.565 0.586 0.552 0.614 0.783 Programme Suitability 0.333 0.350 0.380 0.390 0.179 0.484 0.487 0.533 0.468 0.480 0.491 0.674 0.781 Quality of Professor 0.414 0.456 0.381 0.454 0.313 0.515 0.475 0.558 0.503 0.586 0.504 0.634 0.625 0.814 Socioeconomic Level 0.497 0.351 0.365 0.426 0.400 0.476 0.259 0.360 0.235 0.504 0.311 0.349 0.382 0.452 0.731 Source Credibility 0.328 0.333 0.290 0.284 0.263 0.429 0.570 0.629 0.586 0.502 0.474 0.532 0.460 0.488 0.293 0.846 Notes: Diagonal elements (in bold) represent the squared root of the average variance extracted (AVE) between the constructs and their measures. Off-diagonal elements represent the correlations between construct. In discriminant validity, diagonal elements should be larger than off-diagonal elements in the same row and column.

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CP1 (0.819)

CP2 (0.771) 0.5

37 CP3 (0.588)

Cultural Proximity 0.189

AP1(0.789) Country Image

AP2 (0.877) 0.6 0.593 0.3 57 65 AP3 (0.851)

Academic Reputation AP4 (0.715)

0.442

SL1 (0.613) Information Quality IQ1 (0.823) SL2 (0.772) 0.5 34 IQ2 (0.859) SL3 (0.843) 0.7

Socioeconomic Level 20 IQ3 (0.848) SL4 (0.673)

IQ4 (0.864) CD1 (0.733) 0.251 -0.014 CD2 (0.849) 0.6 23 0.560 City Effect Source Credibility SC1 (0.800) CD4 (0.781) City Dimension SC2 (0.868) 0.3 80 SC3 (0.880) CL1 (0.781) 0.7 0.680 16 0.154 SC4 (0.834) CL1 (0.817) 0.5 57 0.259 CL1 (0.726)

Cost of Living CL1 (0.650) PrUni Enrolment EC5 (0.742)

QP1 (0.859) IU1 (0.836) EC4 (0.783)

IU2 (0.870) 0.540 QP2 (0.855) 0.7 0.60 EC3 (0.791) 25 5 QP3 (0.845) IU3 (0.867) 0.6 EC2 (0.803)

63 Information Usefulness QP4 (0.812) IU4 (0.832) EC1 (0.769) Quality of Professor QP5 (0.712)

0.211 QP6 (0.793 0.462

-0.013 IR1 (0.732) Institution 0.3 Programme IR2 (0.679) Image 82 Evaluation

IR3 (0.752) 0.5 0.355 0.4 0.253 0.445 0.150 IR4 (0.774) 38 17 0.389 Institution Recognition IR5 (0.772) Programme Programme Cost and Programme Finance Recognition Suitability Specialization IR6 (0.686) 0.367

0.6 0.6 0.6 0.5 13 FC1 (0.754) PR1 (0.777) 17 10 98

PZ1 (0.717) FC2 (0.704) PR2 (0.820) PS1 (0.824) CF1 (0.701) PZ2 (0.734) FC3 (0.708) 0.5 PR3 (0.827) PS2 (0.748) (0.734) CF2 (0.737) 56 PZ3 (0.833) FC4 (0.767) PR4 (0.740) PS3 (0.852) CF3 (0.856) Facilities on Campus PZ4 (0.807) FC5 (0.793) PR5 (0.785) PS4 (0.689 CF4 (0.790) PZ6PZ5 (0.779)(0.820) FC6 (0.744) PR6 (0.762)

Figure 4.2: The Measurement Model after Adjustment

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4.3.2 Reliability Analysis

Reliability is an assessment of the degree of consistency between multiple measurements of a variable (Hair, Black, Babin & Anderson, 2010). As a measure of internal consistency, the composite reliability fulfils the same task as Cronbach‘s alpha. In fact, composite reliability is preferred compared to Cronbach‘s alpha as it is not influenced by existent items numbered in each scale and uses item loadings extracted from the casual model analysed (Barroso, Carrion & Roldan, 2010). As can be seen in Table 4.10, all the composite reliability values ranging from 0.744 to

0.922 exceeds the cut off value of 0.6 (Bagozzi & Yi, 1988). As such, based on the composite reliability, we can conclude that the measurement is reliable. Figure 4.2 presents the range of loadings in the reliability test and number of items for each of the construct after adjustment which is upon deletion of 2 items.

Table 4.10 Result of Reliability Test

Constructs Measurement Item Composite Loading *Number Reliability Range of Items Cultural CP1,CP2,CP3 0.774 0.588- 3(4) Proximity 0.819

Academic AP1,AP2,AP3,AP4 0.884 0.715- 4(4) Reputation 0.877

Socioeconomic SL1,SL2,SL3,SL4 0.818 0.613- 4(4) Level 0.843

City Dimension CD1,CD2,CD4 0.832 0.733- 3(4) 0.849

Cost of Living CL1,CL2,CL3,CL4 0.833 0.650- 4(4) 0.817

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Table 4.10 (Continued)

Constructs Measurement Item Composite Loading *Number Reliability Range of Items Quality of QP1,QP2,QP3,QP4,QP5,QP6 0.922 0.712- 6(6) Professors 0.859

Institution IR1,IR2,IR3,IR4,IR5,IR6 0.875 0.679- 6(6) Recognition 0.774

Facilities on FC1,FC2,FC3,FC4,FC5,FC6 0.882 0.704- 6(6) Campus 0.793

Programme PR1,PR2,PR3,P4,PR5,PR6 0.875 0.740- 6(6) Recognition 0.827

Programme PS1,PS2,PS3,PS4 0.861 0.689- 4(4) Suitability 0.852

Programme PZ1,PZ2,PZ3,PZ4,PZ5,PZ6 0.905 0.717- 6(6) Specialization 0.833

Cost and CF1,CF2,CF3,CF4 0.855 0.701- 4(4) Finance 0.856

Information IQ1,IQ2,IQ3,IQ4 0.911 0.823- 4(4) Quality 0.864

Source SC1,SC2,SC3,SC4 0.910 0.800- 4(4) Credibility 0.880

Information IU1,IU2,IU3,IU4 0.913 0.832- 4(4) Usefulness 0.870

PrUni EC1,EC2,EC3,EC4,EC5 0.884 0.742- 5(5) Enrolment 0.803 Choice

* Final item numbers (initial numbers)

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4.4 Assessment of Structural Model

The structural model represents the relationship between constructs or latent variables that were hypothesized in the research model. Since the primary objective of PLS is prediction (Hair et al., 2011), the goodness of the theoretical model is established by the variance explained (R2) of the endogenous constructs and the significance of all path estimates (Chin, 2010). The variance explained for each endogenous construct is shown in Table 4.11 below. As can be seen in the table, there are two endogenous variables altogether. The final endogenous construct (HEI enrolment choice) has an R2 of 0.292 (substantial) suggesting that 29.2% of the variance in extent of PrUni enrolment choice can be explained by country image, city effect, institution image, programme evaluation and information usefulness.

Table 4.11

Variance Explained (R2)

Endogenous Construct Variance Endogenous Construct Variance Explained (R2 ) Explained (R2 )

PrUni Enrolment Choice 0.292

Information Usefulness 0.415

The path coefficient range on the other hand should be greater than 0.1 to be considered as acceptable (Lohmoller, 1989). After computing the path estimates in the structural model, a bootstrap analysis was performed to assess the statistical significance of the path coefficients. From the initial set of paths, 3 were revealed as significant at 0.99 level (1%), 1 at 0.95 level (5%) and the remaining were not significant as shown in Table 4.12. Figure 4.3 shows the significant paths (at level of

0.01) for the model.

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Table 4.12

Path Coefficient (Without Moderating and Mediating Variables)

Beta Standard T-Value Error Country Image -> Information Usefulness 0.037 0.056 0.596

City Effect -> Information Usefulness 0.175 0.057 3.138***

Institution Image -> Information Usefulness 0.141 0.075 1.841**

Programme Evaluation -> Information Usefulness 0.385 0.071 5.397***

Information Usefulness -> PrUni Enrolment 0.265 0.063 4.284*** Choice

*** p< 0.01 (2.330), ** p < 0.05 (1.645), * p < 0.1(1.280); (based on one-tailed test)

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Academic Reputation

Cultural Proximity

Socioeconomic Level Country Image

City Dimension

Cost of Living City Effect

Institution

Usefulness Facility on Campus

PrUni Enrolment Institution Recognition Choice

Quality of Professors Institution Image

Programme Recognition

Programme Suitability

Programme Specialization Programme Evaluation Cost and Finance

Figure 4.3: Statistical Significant Path Coefficients

Significant Path

Non-Significant Path

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4.4.1 Mediating Effect

Mediation hypotheses posited on how and by what means an independent variable (X) affect a dependent variable (Y) through one or more potential intervening variables or mediators (M) (Preacher & Hayes, 2008). In other words, mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable or mediator (Preacher & Hayes, 2008). In order to verify the mediating effect of information usefulness, the testing method for mediation by Chin (2010) was followed. To establish the mediation effect, the indirect effect between (a) x (b) has to be significant (Helm, Eggert & Garnefeld,

2010). To test for significance, the t-value based on bootstrapping result is calculated

(Chin, 2010). If the t-value exceeds 1.28 (at p < 0.1) (1 tailed)) the hypotheses can be accepted. The t-value is formally defined as follows:

t = a * b Standard deviation of a * b

4.4.1(a) Mediating Effect of Information Usefulness between Country Image and PrUni Enrolment Choice As shown in Figure 4.4, there is no significant effect of country image onto information usefulness (ß=0.037, t= 0.596) although there is a significant effect of information usefulness onto PrUni enrolment choice (ß=0.265, t= 4.284***, p <

0.01), and the original direct effect of country image onto PrUni enrolment choice as significant (ß = 0.096, t = 1.831**p<0.05). To assess if there is a full or partial mediation, the method suggested by Baron & Kenny (1986) was used. An alternative

211 model capturing the direct link between country image onto PrUni enrolment choice was structured and tested in PLS. The results show the original direct effect of country image onto PrUni enrolment choice as significant (ß = 0.096, t = 1.831**p <

0.05). However, the study found that when the mediating effect of information usefulness is added, the significance becomes smaller (ß = 0.010, t = 0.584) and irrelevant in mediating the relationship between country image and enrolment choice.

As such, it can be concluded that information usefulness did not mediate the impact of country image towards PrUni enrolment choice. Therefore, H1 hypothesis has been rejected (Table 4.13).

Information (β=0.265, t=4.284) PrUni Enrolment Usefulness Choice

a (β=0.037, t=0.596) Country Image

Figure 4.4: Mediating Model of Information Usefulness between Country Image and PrUni Enrolment Choice

Table 4.13

Hypotheses Testing for Country Image-Information Usefulness Indirect Effect

BOOTSTRAPPING Indirect Total Mediating Effect Effect T- Hypotheses a*b c’ (a*b)+c’ S.E Value VAF Decision Not H3 CI→IU→EC 0.001 0.010 0.011 0.016 0.584 - Supported *** p< 0.01, ** p < 0.05, * p < 0.1 (based on one-tailed test)

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4.4.1(b) Mediating Effect of Information Usefulness between City Effect and PrUni Enrolment Choice As shown in Figure 4.5, there is a significant effect of city effect onto information usefulness (ß=0.175, t= 3.138***, p < 0.01) as well as information usefulness onto PrUni enrolment choice (ß=0.265, t= 4.284***, p < 0.01) and the original direct effect of city effect onto PrUni enrolment choice as significant (ß =

0.018, t = 0.280). To assess if there is full or partial mediation, the method suggested by Baron & Kenny (1986) was used. An alternative model capturing the direct link between city effects onto PrUni enrolment choice was structured and tested in PLS.

The results show the original direct effect of city effect onto PrUni enrolment choice is not significant (ß = 0.018, t = 0.280). However, the study found that when the mediating effect of information usefulness is added, the significance becomes greater

(ß = 0.046, t = 2.794***p < 0.01). As such, it can be concluded that information usefulness partially mediates the impact of city effect towards PrUni enrolment choice. Furthermore, to estimate the magnitude of indirect effect, Iacobucci &

Duhachek (2003) used the VAF (Variance Accounted for) value which represents the ratio of indirect effect to the total effect.

b (β=0.265, t=4.284) Information PrUni Enrolment Usefulness Choice a (β=0.175, t=3.138) City Effect

Figure 4.5: Mediating Model of Information Usefulness between City Effect and PrUni Enrolment Choice

213

VAF = a * b a * b + c = 0.175 * 0.265 0.175 * 0.265 + (0.046) = 0.502

The VAF value of 50.2% indicates that almost half of the total effect of city effect onto PrUni enrolment choice is explained by the indirect effect (information usefulness). Therefore, H2 hypothesis has been confirmed and accepted (Table 4.14).

Table 4.14

Hypotheses Testing for City Effect-Information Usefulness Indirect Effect

BOOTSTRAPPING Indirect Total Mediating Effect Effect Hypotheses a*b c’ (a*b)+c’ S.E T-Value VAF Decision Supported H2 CE→IU→EC 0.046 0.046 0.092 0.017 2.794*** 50.2% Partial Mediation *** p< 0.01, ** p < 0.05, * p < 0.1 (based on one-tailed test)

4.4.1(c) Mediating Effect of Information Usefulness between Institution Image and PrUni Enrolment Choice As shown in Figure 4.6, there is a significant effect of institution image onto information usefulness (ß=0.141, t= 1.841**, p < 0.05) as well as information usefulness onto PrUni enrolment choice (ß=0.265, t= 4.284***, p < 0.01) and the original direct effect of institution image onto PrUni enrolment choice is significant

(ß = 0.157, t = 1.795**p<0.05). To assess if there is full or partial mediation, the method suggested by Baron & Kenny (1986) was used. An alternative model capturing the direct link between institution image onto PrUni enrolment choice was

214 structured and tested in PLS. The results show that the original direct effect of institution image onto PrUni enrolment choice is significant (ß = 0.157, t =

1.795**p<0.05). However, the study found that when the mediating effect of information usefulness is added, the significance becomes smaller (ß = 0.038, t =

1.621, **p< 0.05). As such, it can be concluded that information usefulness partially mediates the impact of institution image towards PrUni enrolment choice.

Furthermore, to estimate the magnitude of indirect effect, Iacobucci & Duhachek

(2003) used the VAF (Variance Accounted For) value which represents the ratio of indirect effect to the total effect.

Information b (β=0.265, t=4.284) PrUni Enrolment Usefulness Choice

a (β=0.141, t=1.841) Institution Image

Figure 4.6: Mediating Model of Information Usefulness between Institution Image and PrUni Enrolment Choice

VAF = a * b a * b + c = 0.141 * 0.265 0.141 * 0.265 + (0.038) = 0.496

The VAF value of 49.8% indicates that almost half of the total effect of institution image onto PrUni enrolment choice is explained by the indirect effect

(information usefulness). Therefore, H3 hypothesis has been confirmed and accepted

(Table 4.15).

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Table 4.15

Hypotheses Testing for Institution Image-Information Usefulness Indirect Effect

BOOTSTRAPPING Indirect Total Mediating Effect Effect T- Hypotheses a*b c’ (a*b)+c’ S.E Value VAF Decision Supported H3 II→IU→EC 0.037 0.038 0.075 0.023 1.621* 49.6% Partial Mediation *** p< 0.01, ** p < 0.05, * p < 0.1 (based on one-tailed test)

4.4.1(d) Mediating Effect of Information Usefulness between Programme Evaluation and PrUni Enrolment Choice As shown in Figure 4.7, there is a significant effect of programme evaluation onto information usefulness (ß=0.385, t= 5.397***, p < 0.01) as well as information usefulness onto PrUni enrolment choice (ß=0.265, t= 4.284***, p < 0.01) and the original direct effect of programme evaluation onto PrUni enrolment choice is significant (ß = 0.230, t = 3.192*** p < 0.01). To assess if there is full or partial mediation, the method suggested by Baron & Kenny (1986) was used. An alternative model capturing the direct link between programme evaluations onto HEI enrolment choice was structured and tested in PLS. The results show that the original direct effect of programme evaluation onto PrUni enrolment choice is significant (ß =

0.230, t = 3.192*** p < 0.01). However, the study found that when the mediating effect of information usefulness is added, the significance becomes greater (ß =

0.103, t = 3.200, ***p < 0.01). As such, it can be concluded that information usefulness partially mediates the impact of programme evaluation towards PrUni enrolment choice. In addition, to estimate the magnitude of indirect effect, Iacobucci

& Duhachek (2003) used the VAF (Variance Accounted For) value which represents the ratio of indirect effect to the total effect.

216

Information b (β=0.265, t=4.284) PrUni Enrolment Usefulness Choice

a (β=0.385, t=5.397) Programme Evaluation

Figure 4.7: Mediating Model of Information Usefulness between Programme Evaluation and PrUni Enrolment Choice

VAF = a * b a * b + c = 0.385 * 0.265 0.385 * 0.265 + (0.103) = 0.498

The VAF value of 49.8% indicates that almost half of the total effect of programme evaluation onto PrUni enrolment choice is explained by the indirect effect (information usefulness). Therefore, H4 hypothesis has been confirmed and accepted (Table 4.16).

Table 4.16

Hypotheses Testing for Programme Evaluation Information Usefulness Indirect Effect

BOOTSTRAPPING Indirect Total Effect Effect Mediating a*b c’ (a*b)+c’ Hypotheses S.E T-Value VAF Decision Supported H4 PE→IU→EC 0.102 0.103 0.205 0.032 3.200*** 49.8% Partial Mediation *** p< 0.01, ** p < 0.05, * p < 0.1 (based on one-tailed test)

217

Consequently, the results of the hypothesized mediation for this research are shown in Table 4.17. Hence, based on the initial examination of four (4) proposed hypotheses, three of them; H2, H3 and H4 fulfilled the condition required to establish a mediation relationship through their significant indirect effect. H1 on the other hand did not fulfil the condition required to establish a mediation relationship through their indirect significant effect (Table 4.17).

Table 4.17

Summary of Hypotheses Testing for Indirect Effect

BOOTSTRAPPING Indirect Total Mediating Effect Effect Hypotheses a*b c’ (a*b)+c’ S.E T-Value VAF Decision Not H1 CI→IU→EC 0.001 0.010 0.011 0.016 0.584 - Supported Supported H2 CE→IU→EC 0.046 0.046 0.092 0.017 2.794*** 50.2% Partial Mediation Supported H3 II→IU→EC 0.037 0.038 0.075 0.023 1.621* 49.6% Partial Mediation Supported H4 PE→IU→EC 0.102 0.103 0.205 0.032 3.200*** 49.8% Partial Mediation *** p< 0.01, ** p < 0.05, * p < 0.1 (based on one-tailed test)

218

4.4.2 Moderating Effect

A moderator is a qualitative (e.g. sex, race, class etc.) or quantitative (e.g. level of reward) variable that affects the direction and/or the strength of the relationship between a predictor variable and criterion variable (Baron & Kenny,

1986). To test the moderating effect, the influence of the predictor variable on the criterion variable, the direct effect of the moderating variable on the criterion variable and the influence of the interaction variable on the criterion variable are estimated (Figure 4.8) (Helm et al., 2010). The moderator hypotheses are supported if the interaction path is significant (path c), independent of the magnitude of the path coefficients a and b (Baron & Kenny, 1986).

PREDICTOR VARIABLE MODERATOR VARIABLE PREDICTOR X MODERATOR VARIABLE

a b c

CRITERION VARIABLE

Figure 4.8: Moderator Model

219

4.4.2(a) Information Quality as a Moderator in the Relationship between Country Image and information usefulness

Firstly, the moderation effect of information quality is tested. In testing the possibility of such effect, country image (predictor) and information quality

(moderator) were multiplied to create an interaction construct (country image x information quality) to predict information usefulness (Chin, 2010). The AVE and

CR for this interaction is 0.720 and 0.911 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path

(path c) is -0.021 (t = 0.584) which is not significant with a of 0.473 (Figure 4.9) which is slightly higher than the of the main effect model which is 0.415. The influence of information quality between country image and information usefulness is visualised in Figure 4.10. The results show that regardless of the amount of information quality shown, high level and low level of country image information will have similar effect on information usefulness to the international students. This suggests that the moderation impact of information quality does not influence the relationship between country image and information usefulness. Therefore, hypothesis 5a is rejected.

220

Figure 4.9: Result of the Moderation Effect of Information Quality on the

Relationship between Country Image and Information Usefulness

4.4.2 (b) Information Quality as a Moderator in the Relationship between City

Effect and Information Usefulness

Moderation effect of information quality is tested on the relationship between city effect (predictor) and information quality (moderator). City effect (predictor) and information quality (moderator) were multiplied to create an interaction construct

(city effect X information quality) to predict information usefulness. The AVE and

CR for this interaction is 0.720 and 0.911 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path

(path c) is -0.080 (t = 2.271**) which is significant at p < 0.01 with a of 0.481

(Figure 4.10), slightly higher than the of the main effect model which is 0.415.

The effect size of the interaction is calculated as follows:

221

= model with moderator - model without moderator

1 - model with moderator = 0.481 – 0.415 1- 0.481 = 0.127

According to Cohen (1988), values of 0.02, 0.15 and 0.35 signify small, medium and large effects respectively.The result shows that the size of the moderating effect is small ( = 0.127) (Cohen, 1988). However, Chin (2010) stated that small does not imply that the moderating effect is insignificant because ―even small interaction effects can be meaningful under extreme moderating conditions, if the resulting beta changes are meaningful, then it is important to take these conditions into account‖.

The influence of information quality between city effect and information usefulness is visualised in Figure 4.11. The results show that the amount of information quality shown has influence on high level and low level of city effect information. To confirm this result, a graphical impact of this moderation effect was tested. Figure 4.11 illustrates the plotted graph used for analysing the moderating effect of information quality on the relationship between city effect and information usefulness. The plotted graph demonstrates that when the level of city effect is high the tendency for both high information quality and low information quality has higher moderating effect on the usefulness of the information received by an international student. The direction of the relationship between city effect and information usefulness for both high information quality and low information quality are similar. This suggests that the moderation impact of information quality does influence the relationship between city effect and information usefulness. This is also

222 supported by the significant effect of moderation (β=-0.080, t=2.302** p < 0.05).

Therefore, hypothesis 5b is accepted.

Figure 4.10: Result of the Moderation Effect of Information Quality on the

Relationship between City Effect and Information Usefulness

5 4.5

4 3.5 Low IQ 3 High IQ 2.5 2

1.5 Information Usefulness Information 1 Low CE High CE

Figure 4.11: Moderation Effect of Information Quality between City Effect and

Information Usefulness

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4.4.2 (c) Information Quality as a Moderator in the Relationship between Institution Image and Information Usefulness

Moderation effect of information quality is tested on the relationship between institution image (predictor) and information quality (moderator). Institution image

(predictor) and information quality (moderator) were multiplied to create an interaction construct (institution image x information quality) to predict information usefulness. The AVE and CR for this interaction is 0.720 and 0.911 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path (path c) is -0.044 (t = 1.218*) with of 0.475 (Figure 4.12) is slightly higher than the of the main effect model which is 0.415. The effect size of the interaction is calculated as follows:

= model with moderator - model without moderator

1 - model with moderator = 0.475 – 0.415 1– 0.475 = 0.114

The influence of information quality between institution image and information usefulness is visualised in Figure 4.13. The results show that the amount of information quality shown has influence on high level and low level of institution image information. Overall, high information quality has a greater moderating effect in the information usefulness received by international students compared to low information quality which is related to institution image. The plotted graph demonstrates that when the level of institution image is high, the tendency for both high information quality and low information quality has higher moderating effect on the usefulness of the information received by an international student. Comparatively international students who receive high institution image information have a greater

224 information usefulness compared to that low city effect information. This suggests that the moderation impact of information quality does influence the relationship between institution image and information usefulness. This is also supported by the significant effect of moderation (β=0.145, t=2.644*** p < 0.05). Therefore, hypothesis 5c is accepted.

Figure 4.12: Result of the Moderation Effect of Information Quality on the

Relationship between Institution Image and Information Usefulness

225

5 4.5

4 3.5 Low IQ 3 High IQ 2.5

2 Institution Image Institution 1.5 1 Low II High II

Figure 4.13: Moderation Effect of Information Quality between Institution Image and Information Usefulness

4.4.2 (d) Information Quality as a Moderator in the Relationship between Programme Evaluation and Information Usefulness

Moderation effect of information quality is tested on the relationship between programme evaluation (predictor) and information quality (moderator). Programme evaluation (predictor) and information quality (moderator) were multiplied to create an interaction construct (programme evaluation X information quality) to predict information usefulness. The AVE and CR for this interaction is 0.720 and 0.911 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path (path c) is -0.094 (t = 2.635) which is significant at p < 0.01 with a of 0.483 (Figure 4.14), slightly higher than the of the main effect model which is 0.415. The effect size of the interaction is calculated as follows:

226

= model with moderator - model without moderator

1 - model with moderator = 0.483 – 0.415 1 – 0.483 = 0.131

The influence of information quality between programme evaluation and information usefulness is visualised in Figure 4.15. The results show that the amount of information quality shown has influence on high and low levels of programme evaluation information. To confirm this result, a graphical impact of this moderation effect was tested. Figure 4.15 illustrated the plotted graph used for analysing the moderating effect of information quality on the relationship between programme evaluation and information usefulness. The plotted graph demonstrates that when the level of programme evaluation is high the tendency for both high information quality and low information quality has higher moderating effect on the usefulness of the information received by an international student. The direction of the relationship between programme evaluation and information usefulness for both high information quality and low information quality are similar. This suggests that the moderation impact of information quality does influence the relationship between programme evaluation and information usefulness. This is also supported by the significant effect of moderation (β=-0.094, t=2.653*** p < 0.01). Therefore, hypothesis 5d is accepted.

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Figure 4.14: Result of the Moderation Effect of Information Quality on the

Relationship between Programme Evaluation and Information Usefulness

4 Low IQ 3 High IQ 2

Programme Evaluatoion Programme 0 Low PE High PE

Figure 4.15: Moderation Effect of Information Quality between Programme

Evaluation and Information Usefulness

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4.4.2 (e) Source Credibility as a Moderator in the Relationship between Country Image and Information Usefulness

Moderation effect of source credibility is tested on the relationship between country image (predictor) and source credibility (moderator). Country image

(predictor) and source credibility (moderator) were multiplied to create an interaction construct (country image x source credibility) to predict information usefulness. The

AVE and CR for this interaction is 0.716 and 0.910 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path (path c) is -0.059 (t = 1.461*), significant at p < 0.10 with a of

0.486 (Figure 4.16) which is slightly higher than the of the main effect model which is 0.415. The effect size of the interaction is calculated as follows:

= model with moderator - model without moderator

1 - model with moderator = 0.486 – 0.415 1 – 0.486 = 0.138

The influence of source credibility between country image and information usefulness is visualised in Figure 4.17. The results show that the amount of source credibility shown has influence on high and low levels of country image information.

To confirm this result, a graphical impact of this moderation effect was tested. Figure

4.17 illustrates the plotted graph used for analysing the moderating effect of source credibility on the relationship between country image and information usefulness.

The plotted graph demonstrated that when the level of country image is high, the tendency for both high source credibility and low source credibility quality has

229 higher moderating effect on the usefulness of the information received by an international student. The direction of the relationship between country image and information usefulness for both high information quality and low information quality are similar. This suggests that the moderation impact of information quality does influence the relationship between country image and information usefulness. This is also supported by the significant effect of moderation (β=-0.059, t=1.435* p < 0.01).

Therefore, hypothesis 6a is accepted.

Figure 4.16: Result of the Moderation Effect of Source Credibility on the

Relationship between Country Image and Information Usefulness

230

5 4.5

4 3.5 Low SC 3 High SC 2.5 2 1.5

Information Usefulness Information 1 Low CI High CI

Figure 4.17: Moderation Effect of Source Credibility between Country Image and

Information Usefulness

4.4.2 (f) Source Credibility as a Moderator in the Relationship between City Effect and Information Usefulness

Moderation effect of source credibility is tested on the relationship between city effect (predictor) and source credibility moderator). City effect (predictor) and source credibility moderator) were multiplied to create an interaction construct (city effect x source credibility) to predict information usefulness. The AVE and CR for this interaction is 0.716 and 0.910 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path (path c) is -

0.106 (t = 2.672**), which is significant at p < 0.01 with a of 0.495 (Figure 4.18), slightly higher than the of the main effect model which is 0.415. The effect size of the interaction is calculated as follows:

231

= model with moderator - model without moderator

1 - model with moderator = 0.497 – 0.415 1 – 0.495 = 0.163

The influence of source credibility between city effect and information usefulness is visualised in Figure 4.19. The results show that the amount of source credibility shown has influence on high and low levels of city effect information. To confirm this result, a graphical impact of this moderation effect was tested. Figure

4.19 illustrates the plotted graph used for analysing the moderating effect of source credibility on the relationship between city effect and information usefulness. The plotted graph demonstrates that when the level of city effect is high, the tendency for both high source credibility and low source credibility quality has higher moderating effect on the usefulness of the information received by an international student. The direction of the relationship between city effect and information usefulness for both high information quality and low information quality are similar. This suggests that the moderation impact of information quality does influence the relationship between city effect and information usefulness. This is also supported by the significant effect of moderation (β=-0.106, t=2.586*** p < 0.01). Therefore, hypothesis 6b is accepted.

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Figure 4.18: Result of the Moderation Effect of Source Credibility on the

Relationship between City Effect and Information Usefulness

4 Low SC 3 High SC 2

1 Information Usefulness Information 0 Low CE High CE

Figure 4.19: Moderation Effect of Source Credibility between City Effect and

Information Usefulness

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4.4.2 (g) Source Credibility as a Moderator in the Relationship between

Institution Image and Information Usefulness

Source credibility moderation effect is tested on the relationship between institution image (predictor) and source credibility (moderator). Institution image

(predictor) and source credibility (moderator) were multiplied to create an interaction construct (institution image X source credibility) to predict information usefulness.

The AVE and CR for this interaction is 0.716 and 0.910 respectively, which exceed the minimum cut off point. The estimated standardized path coefficient for the interaction path (path c) is -0.041 (t = 0.948) which is not significant with a of

0.484 (Figure 4.20) which is slightly higher than the of the main effect model which is 0.415. This suggests that the moderation impact of source credibility does not influence the relationship between institution image and information usefulness.

Therefore, hypothesis 6c is rejected.

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Figure 4.20: Result of the Moderation Effect of Source Credibility on the

Relationship between Institution Image and Information Usefulness

4.4.2 (h) Source Credibility as a Moderator in the Relationship between

Programme Evaluation and Information Usefulness

Source credibility moderation effect is tested on the relationship between programme evaluation (predictor) and source credibility (moderator). Programme evaluation (predictor) and source credibility (moderator) were multiplied to create an interaction construct (programme evaluation x source credibility) to predict information usefulness (Chin, 2010). The AVE and CR for this interaction is 0.716 and 0.910 respectively, which exceed the minimum cut off point The estimated standardized path coefficient for the interaction path (path c) is -0.061 (t = 1.753**), significant at p < 0.05 with a of 0.487 (Figure 4.21) which is slightly higher than

235 the of the main effect model which is 0.415. The effect size of the interaction is calculated as follows:

= model with moderator - model without moderator

1 - model with moderator

= 0.487 – 0.415

1 – 0.487

= 0.140

The influence of source credibility between programme evaluation and information usefulness is visualised in Figure 4.22. The results show that the amount of source credibility shown has influence on high and low levels of programme evaluation information. To confirm this result, a graphical impact of this moderation effect was tested. Figure 4.22 illustrates the plotted graph used for analysing the moderating effect of source credibility on the relationship between programme evaluation and information usefulness. The plotted graph demonstrates that when the level of programme evaluation is high the tendency for both high source credibility and low source credibility quality has higher moderating effect on the usefulness of the information received by an international student. The direction of the relationship between programme evaluation and information usefulness for both high information quality and low information quality are similar. This suggests that the moderation impact of information quality does influence the relationship between programme evaluation and information usefulness. This is also supported by the significant effect of moderation (β=-0.061, t=1.793** p < 0.01). Therefore, hypothesis 6b is accepted.

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Figure 4.21: Result of the Moderation Effect of Source Credibility on the

Relationship between Programme Evaluation and Information Usefulness

4 Low SC 3 High SC 2

1 Information Usefulness Information 0 Low PE High PE

Figure 4.22: Moderation Effect of Source Credibility between Programme

Evaluation and Information Usefulness

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Consequently, the results of the hypothesized moderation for this research can be seen in Figure 4.23 and Table 4.18. Hence, based on the initial examination of eight (8) proposed hypotheses, six of them that are H5b, H5c, H5d, H6a, H6b and

H6d fulfilled the condition required to establish a moderation relationship through their significant indirect effect. However, H5a and H6c did not fulfil the condition required to establish a mediation relationship through their indirect significant effect

(Table 4.17).

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Information Orientation

COUNTRY IMAGE

INFORMATION QUALITY

CITY EFFECT H5b**, H6c***, H5d***

H2***, H3*, H4*** INFORMATION H7*** INFORMATION ADOPTION (PrUni ENROLMENT) USEFULNESS

INSTITUTION IMAGE

H6a*, H6b***, H6d**

SOURCE CREDIBILITY

***P<0.01 (2.33) PROGRAMMES EVALUATION **p<0.05 (1.645) *p<0.1(1.28) (Based on the one-tailed test) Figure 4.23: Theoretical Framework with significant effect

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Table 4.18

Summary of Hypotheses Testing for Moderating Effect

BOOTSTRAPPING Effect size Beta Mediating Hypotheses f b S.E T-Value

H5a CI*IQ→IU 0.110 Small -0.022 0.038 0.584

H5b CE*IQ→IU 0.127 Small -0.080 0.035 2.302**

H5c II*IQ→IU 0.114 Small 0.145 0.057 2.644***

0.131 -0.094 0.036 2.653*** H5d PE*IQ→IU Small

H6a CI*SC→IU 0.138 Small -0.059 0.044 1.435*

H6b CE*SC→IU 0.163 Small -0.106 0.043 2.586***

H6c II*SC→IU 0.134 Small 0.040 0.043 0.962

H6d PE*SC→IU 0.140 Small -0.061 0.036 1.793** *** p< 0.01 (2.330), ** p < 0.05 (1.645), * p < 0.1(1.28); (based on one-tailed test)

4.4.3 Summary of Hypotheses Testing As a next step, hypotheses can be examined to see which of them are supported by the analysis. Table 4.19 presents the summary of hypotheses testing. 10 out of 13 hypotheses are supported while 6 showed no significance results. The significance relationship is characterized by a path coefficient greater than 0.1

(Lohmoller, 1989) as depicted in Table 4.19. A close look on the table shows that city effect, institution image, programme evaluation and information usefulness were positively related to enrolment choice, thus H7 of this study was supported (ß =

0.265, p < 0.01).

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As for the case of mediation effect of information usefulness towards enrolment choice, this study found that a significant mediating effect in support of city effect, institution image and programme evaluation information was needed towards enrolment choice by international students. Thus, H2, H3 and H4 of this study were supported. As for the moderating effect of information quality and source credibility, this study found a significant moderating effect in support of 6 out of the

8 hypotheses. Therefore, H5b, H5c, H5d, H6a, H6b, H6d were supported.

Table 4.19 Summary of Hypotheses Testing

Hypotheses t-value Results

H1 Country image has a direct positive 0.584 Not Supported relationship on information usefulness towards PrUni enrolment choice.

H2 City effect has a direct positive relationship 2.794*** Supported on information usefulness towards PrUni enrolment choice.

H3 Institution image has a direct positive 1.621** Supported relationship on information usefulness towards PrUni choice decision.

H4 Programme evaluation has a direct positive 3.200*** Supported relationship on information usefulness towards PrUni enrolment choice.

H5a Information quality moderates the 0.563 Not Supported relationship between country image and information usefulness.

H5b Information quality moderates the 2.302** Supported relationship between city effect and information usefulness.

H5c Information quality moderates the 2.644*** Supported relationship between institution image and information usefulness.

H5d Information quality moderates the 2.653*** Supported relationship between programme evaluation and information usefulness.

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Table 4.19 (Continued)

Hypotheses t-value Results

H6a Source credibility moderates the relationship 1.435* Supported between country image and information usefulness.

H6b Source credibility moderates the relationship 2.386*** Supported between city effect and information usefulness.

H6c Source credibility moderates the relationship 0.962 Not Supported between institution image and information usefulness.

H6d Source credibility moderates the relationship 1.793** Supported between programme evaluation and information usefulness.

H7 Information usefulness mediates the 4.284*** Supported relationship between country image, city effect, institution image, programme evaluation and PrUni enrolment choice by international students.

4.4.4 Analysing Predictive Relevance (Q²)

In addition to assessing the structural model quality by seeing the R² values and effect sizes, another assessment of structural model is blindfolding. It contains procedure to generate the cross-validated communality and cross-validated redundancy. Based on the recommendation of Hair et al., (2014) and Hair et al.,

(2012), cross-validated redundancy impeccably fits the PLS-SEM method because it was assessed by the PLS-SEM estimates for the structural model and the measurement models to predict eliminated data point.

The Q² was calculated to indicate how well the predictive relevance to the model (Hair et al., 2014). According to Valerie (2012), Stone-Geisser‘s test was

242 calculated by the following formula: Q²=1-SSE/SSO. In order to obtain Q² through blind folding procedure, Hair et al., (2014) recommended that the number of cases in the data must not be a multiple integer number of the omission distance (G).

Otherwise, the blind folding procedure produces inaccurate results and G value should be selected between 5 and 10. In analysing the predictive relevance, blind folding procedure was carried out using omission distance G = 5 as recommended by

Chin & Newsted (1998), who indicates that, the omission distance value between 5 and 10 are feasible.

The results are presented in Table 4.20. The IU and EC present an acceptable cross validated communality and redundancy index of above 0 as recommended by

Fornell & Cha, (1994). Therefore, the model in this study can be considered to have predictive relevance.

Table 4.20 Prediction Relevance of the Model

Total SSO SSE Q²=1-SSE/SSO

PrUni Enrolment Choice 359,000 257,339 0.374

Information Usefulness 359,000 222,355 0.472

4.4.5 Goodness of Fit (GoF)

Goodness of Fit (GoF) is proposed by Tenenhaus Vinzi, Chatilin & Lauro

(2005) to highlight the global criterion of the path model performance in both the measurement and the structural model which was a focus on overall prediction performance of the model. GoF (0 ≤ GoF ≤ 1) index is obtained as a geometric mean

243 of the average communality index and average R2 value. Based on the AVE and R2 values (Table 4.21), the GoF value of 0.492 exceeds the cut off value of 0.36 for large effect size of R2. Thus, it can be concluded that the model of this study has a better prediction power in comparison with the baseline values (GoF small = 0.1,

GoF medium = 0.25 and GoF large = 0.36).

Table 4.21 Goodness-of-fit Index

Construct AVE R2 Cultural Proximity 0.537

Academic Reputation 0.657

Socioeconomic Level 0.534

City Dimension 0.623

Cost of Living 0.557

Quality of Professors 0.663

Institution Recognition 0.538

Facilities on Campus 0.556

Programme Recognition 0.617

Programme Suitability 0.610

Programme Specialization 0.613

Cost of Living 0.598

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Table 4.21(Continued)

Construct AVE R2 Information Quality 0.720

Source Credibility 0.716

Information Usefulness 0.725 0.491

PrUni Enrolment Choice 0.605 0.292

AVERAGE 0.617 0.392

GoF =√ 0.617 X 0.392

= 0.492

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4.5 Summary

This chapter provides overview on the study‘s findings and discussion. It has presented findings on the response rate, profile of respondents and the statistical results from PLS-SEM. Generally, three out of four constructs namely city effect, institution image and programme evaluation had a significant direct effect towards information usefulness. Accordingly, mediation analyses were carried out using PLS-

SEM bootstrapping methodology to determine the mediating effect of information usefulness on HEI enrolment choice by international students.

The statistical outputs had confirmed the existence of partial mediation and consequently, three mediation hypotheses were accepted. The moderating effects of information quality and source credibility have also been tested. Based on the study information, quality has small moderating effect towards the relationship between city effect, institution image and programme evaluation. Similarly, source credibility also has small moderating effect towards the relationship between country image, city effect and programme evaluation.

Based on the results, conclusion of the hypotheses explains that 10 out of 13 hypotheses were supported (H2, H3, H4, H5b, H5c, H5d, H6a, H6b, H6d and H7).

Finally, when the predictive relevance and Goodness of Fit tests were performed to assess the fitness of the model, it resulted as good fit.

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CHAPTER 5

DISCUSSION AND CONCLUSION

5.0 Introduction

The aim of this concluding chapter is to recapitulate and conclude the discovered outcomes of the study, deliberate their effects on marketing theory and marketing applications, as well as the limitation of the study and proposal for future research.

5.1 Recapitulation of the Study Findings

In the present competitive situation, it is imperative for organizations to complement on giving valuable information to the consumers. Previously, consumers in search of information were required to depend on marketer-generated sources.

However, with the development of Web 2.0, it inspires involvement and the sharing of information among consumers. According to King, Racherla & Bush (2014), Web

2.0 insurgency has provided consumers the most capable voice they have ever had - eWoM. It has been argued that the more useful the information provided by business, the greater the adoption of the information by consumers. Therefore, this study focuses on understanding the relationship among international students' information orientation search in eWoM, mediated by information usefulness and PrUni enrolment choice by international students.

In encouraging international students‘ enrolment choice, the main factor that needs to be focused is the information usefulness, an important determinant of an international student‘s enrolment choice decision. As such, focusing on information orientation in the eWoM (dimensioned by country image, cite effect, institution image and programme evaluation) and its relationship towards information

247 usefulness is a crucial part in understanding international students‘ enrolment choice.

This study also focused on understanding the moderating effect of information quality and source credibility between information orientation and information usefulness. Thus, this study is aims to accomplish the subsequent objectives:

1. Examine the effect of country image (cultural proximity, academic reputation

and socioeconomic level) and information usefulness towards PrUni

enrolment choice.

2. Examine the effect of city effect (city dimension and cost of living) and

information usefulness towards PrUni enrolment choice.

3. Examine the effect of institution image (quality of professors, institution

recognition and facilities on campus) and information usefulness towards

PrUni enrolment choice.

4. Examine the effect of programme evaluation (programmes recognition,

programmes suitability, programmes specialization and cost or finance) and

information usefulness towards PrUni enrolment choice.

5. Examine the mediating effect of information usefulness between the

information orientations and PrUni enrolment choice.

6. Examine the moderating effect of information quality on the relationship

between information orientation (country image, city effect, institution image

and programme evaluation) and information usefulness.

7. Examine the moderating effect of source credibility on the relationship

between information orientation (country image, city effect, institution image

and programme evaluation) and information usefulness.

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This is a cross sectional research and data was gathered at one point in time via established questionnaires. The preferred respondents for this research was international students from 27 selected PrUnis with University status (Table 3.5) and those utilised eWoM in searching for information prior to their PrHEI enrolment choice. In terms of demographics info, from 100% respondents, 54% are male respondents and 46% female respondents. From the 359 usable data, majority of the respondents were from China and contributed 16.4% followed by other countries, and age classifications spanned from 15 to 35 years old and above, with the majority of 55.8% of the respondents included in the survey sample are in the age group of

20-24 years old, followed by the age group of 15-19 years old at 35.9% and the third largest age group was 25-29 years old at 9.2%. In terms of the respondent course selection, 68.2% of the respondents were from Bachelor Degree course. This is followed by 11.8% of the respondents who were from Diploma course. Respondents from Master and Foundation programmes, contribute 10% respectively from the total respondents of this study. The majority of respondents represent PrUni – local origin, which contributes 85%, while respondents from PrUni – foreign origin contribute

15% for this study. Other than respondents‘ demographic data, this study also analysed respondents‘ choice of eWoM platform and the information category searched by respondents in eWoM platform. Table 4.5 shows that Facebook was the most widespread eWoM category operated by respondents in searching for information about PrHEIs. It is followed by Instagram (52) and Google+ (34). Table

4.6 shows the respondents‘ most searched PrUni information category. It clearly indicates that University image (110) and course information (104) are the most searched information by respondents in eWoM platform. This is followed by the quality of lecturer (49) and course recognition (46).

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To determine whether the responses received are bias-free, a correlation between early and late responses regarding the major variables of the study had been correspondingly performed using t-test. The results showed only a little significant variance and thus, it was insignificant. On the whole, it was noted that there were no genuine differences due to variation in the data collection procedures. To terminate any worries on the biasness that may emerge due to the cross-sectional survey technique used, the common variance method (CMV) utilizing Harman Single Factor was executed. Factor one represented just 29.41% of the aggregate fluctuation of

68.48%. Thus, CMV was not a significant issue in this investigation.

Subsequently, before advancing to examine the suggested relationship among the variables, the measurement model for this investigation was initially evaluated for their validity and reliability. Content validity was executed to quantify the sufficient scope on the investigative questions guiding this investigation. It comprises judgement by the expert individuals who are similarly active scholars in the field of business and marketing. Convergent validity was established in this investigation through factor loadings of all the items assessing the variable of the study, AVE and

CR which all loadings surpassed the suggested value. Hence, discriminant validity was established with the square root of AVE being more noteworthy contrasted with the relationship of other constructs. Further to that, reliability examination was determined utilizing CR with loadings surpassing the cut off estimation of 0.6 or more. With the validity and reliability of the measurement model determined, the structural model was then assessed to test the relationship hypothesized for the study.

Outcomes resulting from the examination of structural model are briefly discussed in correspondence to the 7 research questions highlighted for this study.

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1. What is the relationship between country image (cultural proximity, academic

reputation and socioeconomic level) and information usefulness towards

PrUni enrolment choice?

2. What is the relationship between city effect (city dimension and cost of

living) and information usefulness towards PrUni enrolment choice?

3. What is the relationship between institution image (quality of professors,

institution recognition and facilities on campus) and information usefulness

towards PrUni enrolment choice?

4. What is the relationship between programme evaluation (programmes

recognition, programmes suitability, programmes specialization and cost or

finance) and information usefulness towards PrUni enrolment choice?

5. Does information usefulness mediate the relationship between the

information orientations and PrUni enrolment choice?

6. Do information qualities moderate the relationship between information

orientation and information usefulness?

7. Does source credibility moderate the relationship between information

orientation and information usefulness?

The study has thirteen hypotheses as stated in Chapter 2. Hypotheses 1 to 4 and

7 (H1, H2, H3, H4, and H7) explains the direct relationship of main variables of this research. Hypotheses H1, H2, H3, and H4 stated that there is significant relationship between country image, city effect, institution image and programme evaluation towards information usefulness and HEI enrolment choice. Hypotheses 7 conjectured the mediating effect of information usefulness towards the relationship between country image, city effect, and institution image and programme evaluation towards

PrUni enrolment choice by international students.

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Hypotheses 5 and 6 which were divided into four sub hypotheses each (H5a to

H5d) and H6a to H6d) to understand further on the significance of information quality and source credibility. H5a to H5d stated that information quality would moderate the relationship between country image, city effect, institution image, programme evaluation and information usefulness. Relatively, H6a to H6d stated that source credibility would moderate the relationship between country image, city effect, institution image, programme evaluation and information usefulness. These hypotheses were developed to determine if the effect of country image, city effect, institution image, programme evaluation on information usefulness would result in dissimilar outcomes when moderated by information quality and source credibility.

The summary of hypotheses is shown in Table 5.0 below.

Table 5.1 A Summary of Hypotheses

No Hypotheses

H1 Country image has a direct positive relationship on information usefulness towards PrUni enrolment choice.

H2 City effect has a direct positive relationship on information usefulness towards PrUni enrolment choice.

H3 Institution image has a direct positive relationship on information usefulness towards PrUni choice decision.

H4 Programme evaluation has a direct positive relationship on information usefulness towards PrUni enrolment choice.

H5a Information quality moderates the relationship between country image and information usefulness.

H5b Information quality moderates the relationship between city effect and information usefulness.

H5c Information quality moderates the relationship between institution image and information usefulness.

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Table 5.1 (Continued)

No Hypotheses

H5d Information quality moderates the relationship between programme evaluation and information usefulness.

H6a Source credibility moderates the relationship between country image and information usefulness.

H6b Source credibility moderates the relationship between city effect and information usefulness.

H6c Source credibility moderates the relationship between institution image and information usefulness.

H6d Source credibility moderates the relationship between programme evaluation and information usefulness.

H7 Information usefulness mediates the relationship between country image, city effect, institution image, programme evaluation and PrUni enrolment choice by international students.

5.2 Discussion of Findings

The next segment explains on the outcomes of this study. It incorporates discussion of the outcomes where it commences with the discussion related to the main variables and their relationships. In addition, this research also discusses the significance of information usefulness as the mediating variable on the relationship between information orientation and HEI enrolment decision. Thirdly, the influence of moderating effect (information quality and source credibility) on the relationship between information orientation and information usefulness are demonstrated and discussed.

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5.2.1 The Relationship between Country Image, City Effect, Institution Image,

Programme Evaluation on Information Usefulness towards PrUni

Enrolment Choice by International Students

This study found that city effect, institution image and programme evaluation significantly and positively influence information usefulness towards PrHEI enrolment choice by international students. Comparatively, country image does not significantly and positively influence information usefulness towards PrUni enrolment choice by international students. The outcomes of the investigation acknowledged that the effect of programme evaluation on information usefulness was greater in comparison to the city effect and institution image. Thus, programme evaluation was identified to be the better predictor of information usefulness towards

PrUni enrolment choice. Comprehensive discussion of individual variable is discussed in the following subsections.

5.2.1(a) The Mediating Effect of Information Usefulness between Country

Image and PrUni Enrolment Choice

This study revealed that country image does not significantly influence the direct relationship towards information usefulness. According to Peng (2012), country image points out to the image, status and the stereotype that consumers perceive on the features of products or services of a particular country. Outcome of the current study is not consistent with previous studies. Previous studies which investigated the relationship between country image information usefulness and HEI enrolment choice stated there are associations between country image and information provided by an organization (Peng, 2012). Comparatively, Mazzarol & Soutar (2002) investigated the influence of country image and HEI choice by students and the

254 outcomes demonstrate that the country image plays a significant role in the selection of HEI enrolment choice by international students.

Despite the fact of country image information as an important contributor to international students‘ HEI enrolment choice, as per this study, there is no significant relation towards information usefulness of country image towards PrUni enrolment choice by international students in the eWoM platform. This is because international students are more likely to consider pursuing higher education in a country and location about which they have knowledge and familiarity, and where their friends and relatives live or have studied (Bodycott, 2009). According to Pimpa (2005), family members may also influence international students‘ choice of country to study. In the context of Malaysia, it can be highlighted that most international students are here based on knowledge and familiarity of culture and where their friends and relatives live or have studied (Singh, Jack, & Schapper, 2014). According to (Singh, Jack, & Schapper, 2014) many of the international students to find a study destination that is culturally familiar, that is considered to be safe and with relatively low risk. These expressed preferences for a study destination that offers the reassurance of sameness and familiarity are in contrast to other studies that highlight the opportunities for international students‘ personal growth and development of intercultural awareness when exposed to cultural diversity, new socioeconomic environment and difference when studying overseas (Williams, 2005).

Thus, gathering useful information on country image is a crucial stage for international students. Although PrUni official marketing medium provide information related to country image, but those information does not fulfil the information required by international students. Comparatively eWoM overload information about country image to the international students. The character of

255 eWoM – anonymity and deception (Kozinets et al., 2016) burden international students with unrelated country image information. Hence international students turn to their friends and family to gather useful country image information. Most of the information gathered by international students are from their friends and relatives live or have studied in the host country (Bodycott, 2009) compared to gathering information via eWoM. International students are more comfortable in receiving information from those who has experienced live or studied and are trusted by them, compared to receive information in eWoM and use the information from unknown source (Kozinets et al., 2016). Therefore, international students d0 not accentuate on gathering useful information related to country image in eWoM prior to their HEI enrolment choice. Thus, as per this study, international students d0 not stress on gathering useful information related to country image in eWoM prior to their PrUni enrolment choice.

5.2.1 (b) The Mediating Effect of Information Usefulness between City Effect

and PrUni Enrolment Choice

According to the results, city effect is significantly and positively related towards information usefulness. The environment in which the goods are manufactured and consumed will reflect the city‘s effects. The outcome of this study is in line with prior studies for example, Chen (2012), Ian Phau Tekle Shanka Neema

Dhayan (2010), Bodycott (2009) and Price, Matzdorf, Smith & Agahi (2003). These results show that international students are likely to utilise the information related to city of the PrUni if the information is useful to their decision on PrUni enrolment choice. International students are likely to search for information related to city effect prior to their enrolment choice. This information is difficult to gather with official

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HEI printed medium. This is highlighted by Hesketh & Knight (1999), Gatfield et al.,

(1999), Ismail & Leow (2008) and Castlemann (2015) investigation, expressing there was a substantial information gap among decision making by students and the printed medium information provided by HEI. Therefore, eWoM plays a crucial part in providing the information needed by international students. Electronic word-of- mouth is utilised by international students to exchange and adopt information because they principally pay more consideration to the information conveyed by former international students.

The result of this study also indicates that eWoM can be an effective platform in providing useful information related to city such as cost of living, safety, social facilities and convenient to find part time job prior to their enrolment choice. For example, information on cost of living in this study provides international students to plan on their expenses throughout their study period (e.g. accommodation, transportation cost, food). Historically, HEIs have provided students with traditional marketing materials such as brochures or general print pieces from newspapers and a magazine which mostly highlights the importance of programme offered and programme cost (Hossler & Foley, 1995). The information related to city such as cost of living, safety, social facilities and location of the HEI are not clearly spelled out and not up to date (Ian Phau, Tekle Shanka Neema Dhayan, 2010). Lack of coordination within various departments within the HEIs also lead to providing inaccurate information related to city effect for the international students. Thus international students gather useful information in eWoM. Kuzma & Wright (2013) also stated that eWoM could also be a cost-effective approach compared to more traditional way gathering information such as brochures, or general print pieces from newspapers and magazines.

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According to Phang (2013), international student‘s city effect information gathering is subject to the student‘s personal level of requirement for information and engrossment. While few students may have next to no information and consider it is satisfactory, other students may need additional information, reliant on their level of commitment in the HEI decision. According to Phang (2013), the involvement of students in searching for information is related to social and economic background of the students, for instance students who are cautious on the social economic issues will actively participate in the process of information search. The participation level reflects on the information searching process by a particular student. Since the official marketing medium fail to provide sufficient information related to city information, eWoM becomes an important platform for international students, especially those in lower socio-economic status, to gather useful information prior to their PrUni enrolment.

5.2.1 (c) The Mediating Effect of Information Usefulness between Institution

Image and PrUni Enrolment Choice

Higher education institution image is the third information orientation that was analysed in this study. Based on the outcomes, institution image is significantly and positively associated to information usefulness towards PrUni enrolment choice.

Institution image is related to academic reputation of the institution, the teaching faculty‘s expertise and quality of its teaching faculty, attractiveness and campus atmosphere from the neutral person. A positive image of an HEI is able to strongly effect the decision of international students to join a particular HEI (Qureshi, 1995;

Mazzarol 7 Southar 2002). The outcome of this investigation is in line with prior investigation conducted for example, Juan Antonio Moreno-Murcia et al., (2015),

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Kotler & Armstrong (2008), Price et al., (2003) and Kotler & Fox (1995) which explained the importance of providing useful institution image information to the international students.

Although HEI disseminates information related to their institution via official information medium, HEI still fails to provide significant information about their institution to the international students (Hesketh & Knight, 1999) and (Gatfield et al.,

1999). Furthermore, Kathryn Di Ana (2014) stressed those HEI admission departments which provide students with traditional marketing materials such as brochures, or general print pieces fail to attract students to enrol in their HEI. Hence

HEI fail in pooling their efforts to present a clear image of a HEI (Gurevitch,

Coleman & Blumler, 2009). Besides the official information from HEI, as per this study is PrUni, international students also gather information related to institution from their family members (Pimpa, 2005). According to Bodycott (2009) international students are incline to gather information about an institution from their family members who has studied in a particular HEI. The limitation of family members studied in a selected HEI has lead the international students fail to get appropriate information. Furthermore, the time frame of family members who studied in a selected HEI may lead to inaccurate information for international students to use prior to their enrolment choice (Lee, 2010). Thus both the official medium and international students‘ family members fail to address the key information needed by the international students. Therefore, international students tend to gather more information about institutions from online past and present students via eWoM.

The result of this study also indicates that information quality moderates the relationship between institution image of the PrUni and information usefulness, such

259 as quality of professors, institution recognition and facility in campus prior to their enrolment choice. Social Admissions Report (2012) further strengthens the result of this study. The study investigates more than 7,000 students and highlights that 72% of prospective university students acquired the information related to their prospective universities via eWoM. Electronic word-of-mouth might influence the purchasing decisions for goods categorized as expensive, complex, and highly exclusive, for example, HEI (Riegner, 2007) and as per this study, international students can receive positive or negative information about PrUni. According to

Chatterjee (2001), positive eWoM information would increase the usefulness of information received by online consumers, whereas negative eWoM information would decrease the usefulness of information received by online consumers.

Therefore, international students will gather the positive and negative information equally via eWoM and evaluate the usefulness of the information prior to their PrUni enrolment choice. This is also supported in the findings, as t value for institution image (1.621** P < 0.05) indicates that institution image information usefulness significantly influences PrUni enrolment choice by international students.

5.2.1 (d) The Mediating Effect of Information Usefulness between Programme

Evaluation and PrUni Enrolment Choice

Programme evaluation is the fourth information orientation that was analysed in this study. According to the result, programme evaluation is significantly and positively related to information usefulness towards PrUni enrolment choice.

Levitz‘s (2012) reports that HEI bound international students value academic information (programmes, courses, financial assistance or education fees, entrance fee procedure, campus visit, campus life, amenities, atmosphere and sports

260 programmes. Levitz (2012) highlighted that the above discussed information are the most valued information and difficult to be gathered by international students.

The outcome of this investigation is in line with prior investigation for example

Anil Tan (2015), Binsardi & Ekwulugo (2003) and Souter & Turner (2002), which explained the importance of providing useful programme information such as programme recognition, programme suitability, programme specialization and cost of the programme to the international students. Similar to the institution image, programme information provided by official HEI medium did not accommodate the information needed by international students. There was a significant gap between information needed by international students and information provided by HEI official medium, and as per this study, international students did not have significant information about programmes offered in PrUni. The gap indicates that the official document delivered for international students often fails to provide adequate information related to academic and applied features of the programme. Therefore, international students tend to search more useful information about the programmes offered by PrUni using eWoM. According to Riegner (2007), eWoM not only influences purchasing decision in tangible or intangible products or services, but eWoM also has a greater influence in more complex products or services, such as

HEI enrolment choice.

According to Jang, Prasad & Ratchford (2012), eWoM could have a greater influence throughout the information search point of the HEI choice procedure where

―choice set‖ of institutions is set by the students. Maringe (2007) explained that choice set is a critical stage, whereas international students‘ parents will search for affordable programme fees, programme recognition and programme suitability.

Therefore, information related to programme and its usefulness will significantly

261 influence the PrUni enrolment choice by international students. This is also supported in the findings, as t value for institution image (3.200*** P < 0.05) indicates that institution image information usefulness significantly influences PrUni enrolment choice by international students.

5.2.2 Information Usefulness on PrUni Enrolment Choice by International

Students

According to the results, information usefulness is significantly and positively related towards PrUni enrolment choice by international students.

According to Cheung et al., (2008), information usefulness is the level to which the readers observe the received information as useful, thus could assist them in making an improved purchasing decision. Choo (2002) further highlighted the importance of information usefulness by indicating that without attention given to information utilization, information searching, information gathering, information acceptance and action to be engaged is incomplete. As for this study, information usefulness is defined as the level to which the international students observe the received information as useful which could assist them to decide on PrUni enrolment choice.

According to Hesketh & Knight (1999) and Gatfield et al., (1999), Mortimer (1997),

Castlemann (2015) and Ismail & Leow (2008), there is significant information gap between information provided by HEI and information required by international students.

Eckel (2007) explained that there is generally insufficient information for students and their parents in making evaluations concerning HEIs; this is because of the poor marketing materials designed by HEI. This information tends to be not as much of informative as it should be but it is more as structured promotional

262 information from HEI. Frequently, HEI overabundance a prospective student with excessive information, some of which may possibly be unrelated and make the decision process more challenging for international students (Drummond, 2004).

Therefore, eWoM has created a platform for international students to search for useful information and avoid in getting too much information as stated by

Drummond (2004).

The outcome of this investigation is in line with prior investigation such as

Cheung et al., (2012) and Sussman & Siegal (2003). Even though the studies are not related to HEI enrolment choice, nevertheless it indicates the importance of information usefulness in eWoM, especially in understanding the information usefulness towards decision making of online customers. All the studies above highlighted the importance of information usefulness in eWoM communication, thus supports the result of this investigation. Therefore, eWoM is seen as a platform in allowing individuals to share and gather useful information related to a product or service. Analysis from this study also supported the findings, as t value for the relation between information usefulness and PrUni enrolment choice (4.284*** P <

0.01) indicates that information usefulness significantly influences PrHEI enrolment choice by international students. Kozinets et al., (2010) stated six major characteristics to define unique nature of eWoM, and the first character supports the findings of this study, that is eWoM enhances the volume of useful information dissemination to online customers.

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5.2.3 The Moderating Effect of Information Quality and Source Credibility

towards the Relationship between Country Image, City Effect, Institution

Image, Programme Evaluation and Information Usefulness.

On the moderating effect, this study hypothesized that, information quality and source credibility has moderating effect in the relationship between information orientation and information usefulness. Comprehensive discussion of individual variable is discussed in the subsequent sections.

5.2.3 (a) Moderating Effect of Information Quality

Hypotheses 5 (a, b, c, d) explain the moderating influence of information quality and the relationship among country image, city effect, institution image, programme evaluation and information usefulness. Information quality also sometimes is referred as argument quality. According to Sussman & Siegal (2003), the quality of the information confined inside the information will decide the significance of informational effect. Adding to Sussman & Siegal (2003),

Bhattacherjee & Sanford (2006) explained that the information quality as influential strength of information integrated in an informational message which leads to information usefulness for online consumers. The study found that information quality does moderate the relationship between city effect (CE*IQ→IU - 2.302** P

< 0.05), institution image (II*IQ→IU - 2.644*** P < 0.01) and programme evaluation (PE*IQ→IU - 2.653*** P < 0.01), and information usefulness as the t value indicates the significance. Comparatively, information quality does not moderate the relationship between country image (CI*IQ→IU – 0.584) and information usefulness as the t value does not reflect the significance of the relation.

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Country image has a great influence on HEI decision by students. It is a dominant influence on prospective international student where country image is exceptionally influential in the HEI information search and selection procedure.

Bodycott (2009) found that country image information is given the priority by international students throughout the HEI choice process. Although there is significant relation between country image and information usefulness, this relation is not moderated by the information quality in eWoM platform. Hypotheses 5a deals with the moderating effect of information quality on country image information towards information usefulness. The study found that information quality does not moderate the relationship between country image (CI*IQ→IU – 0.584) and information usefulness as the t value indicates there is no significance in the relationship. Most of the country image information is gathered by international students from their friends and relatives live or have studied in the host country

(Bodycott, 2009) compared to gathering quality information via eWoM.

Additionally, Kozinets et al. (2016) highlighted that the character of eWoM in providing information from multiple source could possibly mislead the international student‘s perception of country image. Gaining quality country image information is a crucial stage for international students in deciding their PrUni. Hence, international students are more comfortable in receiving quality information from those who has experienced live or studied and are trusted by them, compared to receiving information in eWoM and use the information from unknown source (Kozinets et al.,

2016). Therefore, information quality did not have a significant effect between country image and information usefulness. Therefore, hypotheses 5a is rejected.

Hypotheses 5b deals with the moderating effect of information quality on city effect information towards information usefulness. The study found that information

265 quality does moderate the relationship between city effect (CE*IQ→IU - 2.302** P

< 0.05) and information usefulness as the t value indicates the significance moderating effect of the information quality. Although the international students are clear about their choice of country to study based on their friends‘ and families‘ information, they find difficulties in understanding their city effect. Failure in gathering appropriate city effect information from PrUni official marketing medium will lead to ambiguous situation for international students. Hence, international students turn their attention in gathering information related to city effect from eWoM. According to Bone (1995), if consumers have difficulty in judging a product quality or if judgmental criteria are unclear, the value of available information for the purposes of analysis increases (Bone, 1995). This suggests that the effect of eWoM may be superior in some situations than in others; specifically, eWoM effects should be greater when the consumer faces an ambiguous situation (Bone, 1995).

Comparatively in this study, international students get unclear or sometimes fail to get quality information on the city effect such as cost of living, safety, social facilities and transportation and others which can be transformed to useful information. As suggested by Bone (1995), when consumers face an ambiguous situation, eWoM turns out to be an effective platform in providing quality information. Relatively, for this study, eWoM developed into an effective tool to search for information on the city effect. The influence of information quality between city effect and information usefulness is visualised in Figure 4.11. The plotted graph demonstrated that when the level of city effect is high the tendency for both high information quality and low information quality has higher moderating effect on the usefulness of the information received by an international student. This suggests that the moderation impact of information quality does influence the

266 relationship between city effect and information usefulness. Therefore, hypotheses

5b is accepted.

The next hypotheses – 5c deals with the moderating influence of information quality in the relationship concerning institution image and information usefulness.

The study found that information quality does moderate the relationship between institution image (II*IQ→IU - 2.644*** P < 0.01 and information usefulness as the t value indicates the significant moderating effect of the information quality. Similar to city effect, international students fail or gather clear information about the institution of their enrolment choice. HEI fails to provide detailed quality information needed by international students. The importance of providing quality information which lead international students to use the information towards HEI enrolment choice is highlighted in studies conducted by Juan Antonio Moreno-

Murcia et al., (2015), Kotler & Armstrong (2008) and Price et al., (2003). Their studies explained the importance of providing useful university image information to the international students. However, there are significant gap on the information provided by HEI and the information needed by international students. This has been emphasised by Hesketh & Knight (1999), Mortimer (1997), Gatfiels et al., (1999) and Ismail & Leow (2008) in their studies. Therefore, international students opt to search for more useful information related to institution image prior to their HEI enrolment choice.

Furthermore, Kathryn DiAna (2014) stressed those HEI admissions departments which provide students with traditional marketing materials such as brochures, or general print pieces fail to attract students to enrol in their HEI. Hence

HEI fail efforts in pooling their efforts to present a clear image of a HEI (Gurevitch,

Coleman & Blumler, 2009). According to Bodycott (2009) international students are

267 incline to gather information about an institution from their family members who had studied in a particular HEI. The limitation of family members studied in a selected

HEI has lead the international students fail to get appropriate information. Therefore, international students tend to gather more information about institutions from online past and present students via eWoM. Electronic word-of-mouth allows international students to gather quality information related to institution of their choice from various sources.

The influence of information quality between institution image and information usefulness is visualised in Figure 4.13. The plotted graph demonstrates that when the level of institution image is high, the tendency for both high information quality and low information quality has higher moderating effect on the usefulness of the information received by an international student. Comparatively international students who receive high institution image information have a greater information usefulness compared to that low city effect information. This suggests that the moderation impact of information quality does influence the relationship between institution image and information usefulness. Therefore, hypotheses 5c is accepted.

Hypotheses 5d deals with the moderating effect of information quality in the relationship between programme evaluation and information usefulness. The study found that information quality does moderate the relationship between programme evaluation (PE*IQ→IU - 2.653*** P < 0.01) and information usefulness as the t value indicates the significant moderating effect of the information quality. The components that impact the programme evaluation are an extensive choice of programmes (Qureshi, 1995), their superiority and worldwide acknowledgment of the degree, programme availability, enrolment requirements, programme cost and

268 availability of financial aid. Ambiguity of the education nature and most of the programme evaluation information originates from experience of past and present internationals students where it has become difficult for the potential international students to gather quality information on programme evaluation.

Furthermore, Maringe (2007) explained that choice set is a critical stage, whereas international students‘ parents will search for affordable programme fees, programme recognition and programme suitability. Failure in gathering quality information in official marketing medium, international students and their parents incline to gather information related to PrUni programmes in eWoM. Thus, eWoM becomes a platform for international students and their parents to search for information on the programmes offered by the HEI which mostly comes from past and present experience. Given that searching for information related to search products on the eWoM is much easier than searching for experience product information, consumers are relatively gaining more details, rich psychological structure for search products than for experience products. In addition, Hoch &

Young (1986) suggest that positive or negative information may have stronger effect for products where the quality is difficult to determine by consumers. Therefore, the assessment of experience goods such as HEI programme evaluation with eWoM may have greater effect in providing international students with quality information and useful information for the international students.

The influence of information quality between programme evaluation and information usefulness is visualised in Figure 4.15. The plotted graph demonstrates that when the level of programme evaluation is high, the tendency for both high information quality and low information quality has higher moderating effect on the usefulness of the information received by an international student. This suggests that

269 the moderation impact of information quality does influence the relationship between programme evaluation and information usefulness. Therefore, hypotheses 5d is accepted.

5.2.3 (b) Moderating Effect of Source Credibility

Hypotheses 6 (a, b, c, d) deal with the moderating effect of source credibility in the relationship between country image, city effect, institution image, programme evaluation and information usefulness. According to Petty & Cacioppo (1986), source credibility is explained as the level to which an information source is apparent to be believable, competent and reliable by receiver. The study found that source credibility does moderate the relationship between country image (CI*SC→IU –

1.453* P < 0.1), city effect (CE*SC→IU - 2.586*** P < 0.01), programme evaluation (PE*IQ→IU – 1.793** P < 0.05) and information usefulness as the t value indicates the significance. Comparatively, source credibility does not moderate the relationship between institution image (II*SC→IU – 0.962) and information usefulness as the t value does not reflect the significance of the relationship.

Hypotheses 6a deals with the moderating effect of source credibility on country image information towards information usefulness. The study found that source credibility does moderate the relationship between country image (CI*IQ→IU

– 1.435** P < 0.05) and information usefulness as the t value indicates the significant moderating effect of the source credibility. According to UNESCO

(2014), the increasing demand for education, combined with the monetary strength of the increasing middle classes has in shaped the development for students to select to leave their motherlands in pursuit of higher education abroad. This creates a scenario

270 where international students search for information from a credible source on their

HEI country location. Parents, family and friends become the first point in getting information on the HEI country location. This is highlighted in Sociological models of HEI choice (Hossler & Gallahger 1987) which have engrossed on the identification and inter-relationship of aspects comprising parental inspiration, as one of the main attributes in contributing towards international students‘ HEI enrolment choice.

Bodycott (2009) found that country image is consistently ranked highly important throughout the search phase of the HEI decision process. In Litten &

Brodigan‘s (1982) six-market study, country image was rated as the most important

HEI attribute by both the students and parents. Furthermore, Kotler & Armstrong

(2008), stated one of the methods that prospective customers usually obtain information sources is by using personal non-marketer controlled, for example, friends and family members and Pimpa (2005) explained that students favour the information from family as a foundation and guidance. The information from these credible circles clearly determines the country choice prior to their HEI choice.

Similarly, in the eWoM environment family, friends‘ and acquaintances‘ information is treated as information from credible source. This study also ricochets the effect of source credibility between country image and information usefulness.

The influence of source credibility between country image and information usefulness is visualised in Figure 4.17. The plotted graph demonstrates that when the level of country image is high the tendency for both high source credibility and low source credibility quality has higher moderating effect on the usefulness of the information received by an international student. This suggests that the moderation

271 impact of information quality does influence the relationship between country image and information usefulness. Therefore, hypotheses 6a is accepted.

Hypotheses 6b deals with the moderating effect of source credibility on city effect information towards information usefulness. The study found that source credibility does moderate the relationship between city effect (CE*SC→IU -

2.586*** P < 0.01) and information usefulness as the t value indicates the significance of the relationship. The work of Casttleman (2015) recognizes city impact as furthermost critical element associated to environmental situations which guide the students‘ decision. According to Kusumawati, Yanamandram & Perera

(2010), city effect or environment of the host country was identified as a significant element among international students in Australia. Subsequently, the HEI service is a complex service shaped together with an extensive collection of facilities while the physical setting will be made up of the HEI amenities and the city as a whole. Thus, the students‘ awareness about the city location will give impact on the decision making by international students. The official printed documents from HEI normally fail to provide relevant and comprehensive information about the city where HEI is located. Fagerstrom & Ghinea (2013), Ismail & Leow (2008) and Hesketh & Knight

(1999) identified that international students are looking for more formless information – eWoM from their peers before the decision was made. However, for the information to be more useful, the source credibility of information from eWoM must be trusted by the international students. In this study, source credibility influences the relation between city effect information and information usefulness.

This is supported by Ko, Kirsein & King (2005) which highlighted the information delivered by high degree credible sources is relatively to be reliable, and thus it simplifies the information transferral procedures.

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The influence of source credibility between city effect and information usefulness is visualised in Figure 4.19. The plotted graph demonstrates that when the level of city effect is high the tendency for both high source credibility and low source credibility quality has higher moderating effect on the usefulness of the information received by an international student. This suggests that the moderation impact of information quality does influence the relationship between city effect and information usefulness. Therefore, hypotheses 6b is accepted.

The image of an institution (Choudaha & Kono, 2012) appears to be a significant factor in international students‘ decisions to attend a particular HEI.

Institutional image and status has a great influence on HEI decision by students. It is a dominant influence on prospective student where HEI status is exceptionally influential in the HEI information search and selection procedure. Although there is significant relation between institution image and information usefulness, this relation is not moderated by the source credibility in eWoM platform. Hypotheses 6c deals with the moderating effect of source credibility on institution image information towards information usefulness. The study found that source credibility does not moderate the relationship between institution image (II*SC→IU – 0.962) and information usefulness as the t value indicates there is no significance in the relationship. Compared to moderation effect of information usefulness between institution image and information usefulness, source credibility does not evidently moderate the relationship between institution image and information usefulness.

Additionally, Gurevitch, Coleman & Blumler (2009) highlighted those PrUni official marketing mediums which provide students with traditional marketing materials such as brochures, or general print pieces fail to attract students to enrol in their HEI.

Similarly, the information provided in eWoM also does not give clear and accurate

273 information on the institution image. The anonymity and deception of eWoM character allows international students to gather positive and negative information without knowing their credibility. In addition, eWoM is greatly reachable since most content construct information on the Internet is archived for an unspecified period of time. Thus resulting the PrUni decision making process more complicated. This suggests that the moderation impact of information quality does not influence the relationship between institution image and information usefulness. Therefore, hypotheses 6c is rejected.

Hypotheses 6d deals with the moderating effect of source credibility on programme information towards information usefulness. The study found that source credibility does moderate the relationship between programme evaluation

(PE*SC→IU – 1.793** P < 0.05) and information usefulness as the t value indicates the significance of the relationship. International students will seek programme information from credible source as the programmes offered by HEI are categorised as experience good. According to Cheol Oark, Thae Min Lee (2009), experience goods are characterized by features that cannot be acknowledged up until the acquisitions and after the usage of the product or for which an information exploration procedure is more expensive and or challenging than direct product or service experience. In fact, programmes offered by HEI are grouped under experience goods. Therefore, international students will gather information from credible source in eWoM platform. According to Hesketh & Knight (1999), Gatfield et al., (1999), Mortimer (1997) and Ismail & Leow (2008), there was a substantial information inconsistency throughout decision aspects by students and the information that had been given by HEI in their printed medium. The information about PrUni programme is not updated accordingly. PrUni official marketing

274 medium provide inaccurate information related to programme offered to international students. Thus, making the PrUni enrolment choice decision process tougher for international students.

Comparatively, with the help of eWoM, it helps the international students who are digital native to gather credible information about the programmes offered by the HEI – PrHEI as per this study. International students currently entering HEI is commonly viewed as digital natives, which mean they are frequently communicating using internet in their daily life. This group also identified as ―the Social-Networking

Generation‖ (Thompson, 2007) in line to their extensive involvement in eWoM via social media which allows them to gather credible programme information offered by HEI. Relatively, this study also highlight that source credibility will have moderate effect between programme evaluation information and information usefulness in eWoM platform.

The influence of source credibility between programme evaluation and information usefulness is visualised in Figure 4.22. The plotted graph demonstrates that when the level of programme evaluation is high the tendency for both high source credibility and low source credibility quality has higher moderating effect on the usefulness of the information received by an international student. This suggests that the moderation impact of source credibility does influence the relationship between programme evaluation and source credibility. Therefore, hypotheses 6d is accepted.

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5.3 Implications of Research

Present study spreads the understanding of international students‘ PrUni enrolment choice. The findings highlighted previously lead to some implications to the international students PrUni enrolment choice, particularly Malaysian PrUni. The implication of this study in terms of practical and theoretical stand points is discussed in the following subheading.

5.3.1 Theoretical Implication

The foundation of research framework was based on the IAM and by integrating Hossler & Gallahger (1987) combined model of HEI choice procedures.

Hossler & Gallahger (1987) pointed out the information search period as critical and important period in HEI enrolment choice by international students. This study also postulates that international students search for informal information orientation as formal information from PrUni marketing platform does not really help the students to decide on PrUni enrolment choice. Information orientation such as country image, city effect, and institution image and programme evaluation is searched and studied further before PrUni enrolment choice is finalised. Accordingly, thirteen hypotheses were formulated from the research framework of present study that offers essential empirical evidence as a part of contribution to current academic knowledge.

Past studies had extensively used the relationship between information searched and HEI enrolment choice by international students (Phang, 2013;

Constantinides & Zinck Stagno, 2012; Griffin, 2007; Hossler & Gallagher, 1987) but did not highlight the importance of eWoM and the international students‘ information search behaviour in eWoM. Moreover, past studies frequently limit the

276 scope of information searched by international students to HEI official medium, which fail to accommodate the information needed by the international students.

Therefore, this study fulfils the academic gaps by confirming the relationship between information orientations searched on information usefulness towards PrUni enrolment choice. Firstly, the current study provides additional literature by establishing a relationship between Sussman & Siegal (2003) information adoption model and Hossler & Gallahger (1987) combined model of HEI choice. Hossler &

Gallahger (1987) combined model of HEI choice was utilized to understand the information orientation and HEI enrolment choice and Information Adoption Model

(Sussman & Siegal, 2003) was utilized to understand the relationship between information orientation, information quality, source credibility and information usefulness towards PrUni enrolment choice in eWoM platform. In this case, information orientation represented by country image, city effect, institution image and programme evaluation found that city effect, institution image and programme evaluation have significant relationship on information usefulness towards PrUni enrolment choice. This relationship was tested through four mediating hypotheses where country image, city effect, institution image and programme evaluation were mediated by information usefulness towards PrUni enrolment choice. Three (H2, H3 and H4) out of the four hypotheses were confirmed and accepted as partial mediation. The evidence of this study suggests that through information usefulness, the information gathered by international students give greater impact in international students‘ PrUni enrolment choice.

Moreover, the current study will complement to the developing body of literature by confirming and identify the influence of information orientation searched by potential international students via eWoM in the process of PrUni

277 enrolment choice. Even though many research has examined the HEI choice decision by students, only a few research concentrated on the eWoM effect in international students‘ HEI choice decision. Thus, current study incorporates Information

Adoption Model. IAM is used to understand the quality of information, and the credibility of the information source which moderates the relationship between information orientation and information usefulness. Information quality and source credibility were found to be an important determinant in perceiving information usefulness in eWoM platform (Cheung & Thadani, 2012). Therefore, this study contributes to eWoM literature by understanding the effectiveness of information orientation searched in eWoM (information quality and source credibility) among international students and its relation on information usefulness towards PrUni enrolment choice.

Thirdly, there are inadequate studies and research investigation on international students‘ HEI enrolment decision, particularly in PrUni in developing countries such as Malaysia (Maringe & Carter, 2007). Malaysia‘s current international students‘ percentage stands at approximately 2% of total global market share (UNESCO,

2014). From this 2%, 1.3% international students are enrolled in PrUni. This clearly shows the importance of PrUni in attracting international students. Therefore, this study will assist academicians to attempt more in depth research on the growing pattern of international students‘ search and utilization of information from WOM, specifically from eWoM. This is supported by Zahir & Mushtaq (2008) in their study which indicated that WOM will be the tool to attract international students to

Malaysia. Furthermore, this study also would assist academicians and researchers to understand further on the relationship between international students and information

278 orientation search in eWoM. Moreover, such relationship has not been tested in the

PrUni, particularly in Malaysian PrUni.

Lastly, an added contribution of this study is the comprehensiveness of the research framework. Most of the hypothesised relationship were supported and now, the framework is able to explain the factors that would affect international students

PrUni enrolment choice and the factors that would mediate the relationship between information orientation and HEI enrolment choice and factors that would and moderate the relationship between information orientation and information usefulness. Thus, this framework can be very useful in better explaining international students HEI enrolment choice process in the context of eWoM and PrUni in

Malaysia.

5.3.2 Managerial Implication

This sub heading highlights a few important managerial implications which are extracted from these findings. As stated in earlier chapters, there was a need to comprehend what is the information gathered by international students in eWoM prior to their decision on HEI enrolment choice. This study also highlighted that international students did not receive adequate information needed and there was a substantial information gap from information provided by universities in their official marketing medium as highlighted by Hesketh & Knight (1999), Gatfield et al., (1999), Mortimer (1997), Ismail & Leow (2008) and Castlemann (2015). Adding to Hesketh & Knight (1999), Gatfield et al., (1999), Mortimer (1997), Ismail & Leow

(2008) and Castlemann (2015), Nurlida (2009) highlighted that, besides the obvious cost aspect of official marketing medium, official marketing medium does not

279 present with accurate information for the international students as most of the official marketing medium are only broadcasted for a short period of time (Zenit Raval;

Dushyant Tanna; Dhwani Raval., 2014). The turn-around time for updating current information in the official marketing medium has led to the issue of not providing necessary information for the international students Ford, Bowden & Beard (2011).

Thus, it is of utmost importance for policy makers from the service providers - PrUni to identify the right mix of marketing strategy to attract international students to enrol in their respective PrUnis. A significant part of the current study is to discover, discuss and provide information on real-world to the service provider, strategy planners and system developers. The information discussed in this study would improve the comprehension on the significance of eWoM which can encourage especially the service provider and strategy planners in developing suitable arrangements to additionally empower the usage of eWoM as one of their promoting policy, especially PrUni in Malaysia. Since current study is customer focused and in view of established facts, therefore the discovered outcomes of this study could likewise provide significant proposal in the advancement of practice and policy creation.

Present study had showed that there is significant direct effect between information orientation, information usefulness and PrUni enrolment choice in eWoM. In this study, information gathered by international students in eWoM plays a vital role in international students‘ PrUni enrolment choice. Under those circumstances, the results of this study further acted as proof that the elements of information orientation, moderated by information quality and source credibility towards information usefulness will lead to international students‘ PrUni enrolment choice. This evidence was also matches with several past studies such as to Junco &

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Cole-Avent (2008) study that claimed information gathered in eWoM does influence international students‘ HEI enrolment choice. The fact that HEI enrolment choice is complex decisions associated with high costs and high risk service purchase, international students pursue a more volume of information over an extensive choice of sources (Henning Thurou, Thorsten, Andre & Paul Marx, 2010; Cheung &

Thadani, 2012) and one of them is eWoM. Therefore, it demands policy makers to recognize deeply on the influence of information orientation searched by international students in eWoM and moderating effect of information quality and source credibility. Thus, incorporate inside their marketing strategy towards achieving in attracting to enrol in their PrUni.

This study also highlighted the most used eWoM channels by international students in gathering information. According to marketingchart.com (2015),

Facebook leads the way, followed by Twitter and other channels. Similarly, this study also found that the most used eWoM channels by international students is

Facebook, followed by YouTube, Google+, Twitter and Instagram. According to

Treadaway & Smith (2010), there is no social network can match Facebook‘s broad international customer adoption. As the world‘s largest social network, Facebook owns more than one billion users all over the world now. Facebook provides a great opportunity for marketers to reach customers all over the world. Marketers quickly realize the value of brand promotion by using Facebook. A lot of renowned companies are attracted to promote their brands on Facebook, such as Coca-Cola,

Samsung Mobile, Starbucks, Nike Football, Pringles, and so on. They carry out marketing campaigns by leveraging Facebook‘s features (Safko, 2013). Effective marketing strategies help them build an engagement with current customers and attract potential customers.

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Facebook is a platform which satisfies marketers‘ needs to take part in a conversation with customers. It provides an open and transparent circumstance where information can flow freely between consumers and marketers (Dunay & Krueger

2010). According to Neti (2011) Facebook provides an excellent environment for marketers to build brand, and as a result of it viral marketing capabilities and

Facebook creates a platform to allow companies to build interaction with customers, thereby getting valuable customer views. Additionally, customers can see other customers‘ views towards the products and exchange experiences with each other.

Hence, giving a clear indication to the service provider‘s policy makers on the importance of Facebook and communicating effectively with international students.

It is not sufficient for PrUni to only start communications among their international students; but subsequently to draw their attention and involvement as well as to establish positive communication. Therefore, current study provides the much needed information for PrUni to understand the relation between Facebook, international students and PrUni enrolment choice. Thus, PrUnis are advised not to take lightly on quality and value information provided in their Facebook. The information should be useful for international students in relation to their PrUni enrolment choice.

Information usefulness is defined as the level to which the readers recognise the received information as useful, consequently could support them to make an improved purchasing decision. Under this circumstance, it is recommended for PrUni to do periodical assessments on international students‘ perceptions and expectations on the desired information where this assessment will help PrUni to acknowledge the international student‘s information preferences in developing an effective marketing strategy. Furthermore, understanding the international students‘ information

282 preferences will allow PrUni to customise their marketing strategy. This study highlighted that international students are actively searching for university information which are related to university image and course information of a particular PrUni prior to their enrolment choice. According to Haydon (2013), understanding the customer‘s viewpoint will help the policy makers to create marketing messages which is desired by the customers. Additionally, Safko, L.

(2013) emphasised that based on the customer needs for information; policy makers can develop an effective content strategy. Effective content strategy in eWoM will drive the engagement between organizations with their customer. Thus, understanding the information needed by an organization in eWoM will attract customers to engage with the organization. Based on the current study, providing information related to university image and course information will enhance the engagement between PrUni and international students in eWoM. Understanding this scenario will guide the PrUni to participate and deliver the precise information to the international students in eWoM. This guides an international student in a particular

PrUni enrolment decision.

Equally important, result of this study had recognized essential role of eWoM in providing accurate, timely and comprehensive information compared to official marketing medium from PrUni. It can be interpreted that PrUni are required to ensure updated information provided to international students without any disruption.

This eventually will lead international students to search for information provided from credible sources – PrUni itself compares to gathering information from an open eWoM channels. Thus, creating a one-to-one information sharing scenario (Cheung

& Thadani, 2012) between PrUni and international students. Hence, international

283 students may receive useful information from credible sources about a particular

PrUni.

Recently utilising eWoM as one of the marketing strategies by HEI has gain promising domain, even though HEI are still in the early phase of eWoM marketing strategies. The current study recommends the eWoM tactic as communication instruments which must be unique compared to traditional communication instruments. The main point of eWoM marketing is that it allows effective two-way communication, discussion and commitment instead of utilizing eWoM as communicating or advertising instruments. Although decreasing cost and expanding efficiency can be serious opinions for HEI to integrate eWoM in their marketing approaches, such approaches involve restructuring of marketing departments and changes in communication methods: from one-way communication to listening to customer opinion and customer involvement. Despite the fact most higher education marketing divisions are not comfortable with this kind of communication, PrUni management must try to rebuild and obtain work force with the right competences.

The implication of this study is not limited to practitioners only but the outcomes of this study also can be referred by the related ministries or agencies of Malaysian government such as the MOHE, Malaysia. Outcomes from this investigation may assist the Malaysian MOHE in achieving its target of 250,000 international students‘ enrolment in Malaysia which is highlighted in Malaysia Education Blueprint (2015 –

2025) (MOHE, 2015). To achieve these outcomes, the Ministry will enhance the end- to-end international student experience, increase brand visibility, strengthen existing and new markets for international students. There are three main key initiatives highlighted in the National Higher Education Strategic Plan 2020 (MOHE, 2015).

First is to collaborate with other ministries and agencies to improve and streamline

284 immigration procedures and processes to match international best practices. Second, increasing the proportion of postgraduate international students and students from high priority markets such as ASEAN nations by diversifying and raising the quality of niche programmes, and the third key initiative is to strengthen the promotion and marketing of Malaysia‘s higher education system through targeted measures such as hosting major international education conferences and strengthening My Alumni.

By understanding the key initiative and particularly the third key initiative, it is without a doubt marketing plays a greater role in attracting international students.

Thus, this study provides indication to HEI, either PuHEI or PrHEI to improvise their marketing strategy. Therefore, this study can be a guide to HEI to improvise their marketing strategy by utilising eWoM. By understanding the importance of eWoM and international students‘ relationship towards HEI enrolment choice, HEI, either

PuHEI or PrHEI may utilize the inputs from this study and revisit their marketing strategy. Hence, improving the international students‘ enrolment into Malaysian HEI and achieve the target of 250,000 international students by year 2025 which is set by

Malaysian MOHE.

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5.4 Methodological Contributions

The current study further discusses on the valuable input in terms of its methodological analysis. This study utilizes the new Variance based Structural

Equation Modelling which is Partial Least Square (PLS) method for testing the model. PLS was understood as a good statistical resource for testing the model due to its distinctive characteristics. Some of its important characteristics are:

 The capability to be functional to more complex structural equation models

with a huge amount of variables.

 Better suited for theory development than for theory testing

 Useful especially for prediction

 Can handle both reflective and formative constructs

Thus, the current study is considered a complex model with more than 80 items and it is more towards the theory development rather than theory testing, PLS has present a more substantial and valuable outcome on the findings.

5.5 Limitation of study

Even though the outcomes of the present study have discussed on numerous significant issues, its limitations to certain extend should be measured when interpreting the results. However, these limitations offer some opportunities for future studies to consider in order gaining further knowledge. Firstly, this research concentrate on international students‘ enrolled in PrUni in Malaysia. PrUni enrolment choice represents the internal response of individual as the outcome of information orientation searched in eWoM and information usefulness towards PrUni

286 enrolment choice. Thus, this study outcome was limited to internal response by international students only.

The second limitation is that besides direct relationships, this study had focused on the moderation effect of information quality and source credibility. There are a few other moderating variables that could possibly influence PrUni enrolment choice in eWoM platform, such as respondent demographics, interaction level, relationship between eWoM communicators and the effectiveness of different eWoM platforms. Thirdly, this study faced difficulties in finding enough empirical studies in the context of eWoM and PrUni enrolment choice that involves variables used in the study. Moreover, past studies gave less attention on the information orientation searched in eWoM by international students on information usefulness towards

PrUni enrolment choice. Furthermore, this study also found difficulties in gathering enough empirical studies to support the moderating effect of information quality and source credibility to support the findings of the study. The fourth limitation was related to respondents. The respondents for this study were international students in their first year of PrUni enrolment and utilised eWoM in their enrolment process.

However, it may not represent the overall population of international students in

Malaysian PrUni. Furthermore, most of the respondent of this study is represented from undergraduate international students and very minimal respondents from postgraduate international students. Thus, the finding does not represent the overall population of international students in Malaysian PrUnis.

Lastly, difficulty in getting high rate responses is considered as one of the major methodological limitations faced in this study. The questionnaires were collected in the early month of September 2016 and ended in the month of November

2016. Official letters requesting for permission to enter and collect data were emailed

287 in early month of August 2016 to the respective PrUnis. A total of 27 PrUnis (21 locally funded PrUnis and 6 foreign founded PrUnis) were selected to collect the data as per discussed in chapter 3. From the 27 selected PrUnis, only 18 (15 locally funded PrUnis and 3 foreign founded PrUnis) of them granted permission to collect data from their premises and students. Many PrHEIs rejected the request to conduct the research in their premises and on their international students for variety of reasons. Although the response rate from the selected PrUnis was 60%, it still does not represent the total population of international students from the selected PrHEIs.

5.6 Recommendation for Future Study Every research has its own particular impediments, yet in particular, the individual research project provides new outcomes and discoveries which structure the establishment for future research to expand on. Therefore, this subdivision discusses the potential area of future research. Although the study explained the relation of information orientation on information usefulness towards PrUni enrolment choice, future research could investigate with adding on new constructs.

Thus, strengthening the arguments on the relation between information orientations, information usefulness and PrUni enrolment choice. Adding more constructs such as interaction level, relationship between eWoM communicators would allow academics to further the research on understanding the relation between the effectiveness of eWoM and PrUni enrolment choice by international students. Future studies should consider on what other potential factors can influence international students‘ PrUni enrolment choice. Furthermore, there are possibilities for upcoming research to explore the moderating effect of the respondent demographic and the

288 efficiency of different eWoM platforms between information orientation and information usefulness.

Secondly, past studies have focused on individual components to endogenous variables creating high complex model and sometimes creating confusion interpreting the variable concept. Using low order and high order measurement as applied in this study makes research model simpler and support the concept of variables. Application of formative assessment at higher order level is able to generate high impact on endogenous variables and statistical power of each indicator that form the higher order construct can be identified. However, the concept of low and high order constructs or hierarchical order construct in the past studies were not widely used. Therefore, it is highly recommended that future studies use low and high order constructs and formative assessment that commensurate with the proposed concept. Thirdly, as indicated in the study, eWoM has been made known in early

2000; however, there are fragmented and limited studies to investigate the effectiveness of eWoM as a whole that linked to other constructs such as information orientation, information quality, source credibility, information usefulness and PrUni enrolment choice. In addition, there are limited studies to investigate the moderating impact of information quality and source credibility between information orientation and PrUni enrolment choice are insufficient. Hence, it would bring benefits to the academic knowledge when the said relationships are further investigated in future studies.

Current study discovers that majority of the respondents were male (male =

54.0%, female = 46.0%) comparatively to female respondents. According to Costa et al., (2001), the difference in gender of the respondents will indirectly influence the decision process of a respondent. Hence, gender differences of the international

289 students possibly will play an impact in influencing the international students‘ information orientation searched in eWoM towards PrUnis enrolment choice. Thus, future research may perhaps focus on the demographic of respondents, particularly comparing gender difference – male and female of the international students in the context of eWoM and PrUnis enrolment choice. Lastly, it is recommended that the sample could include PuHEI in future studies for more comprehensive result. Hence, gathering samples from diverse geographical PuHEI and PrHEI will enhance the result further. It is also suggested that the type of respondents should be expanded to other categories such as local students for generalization of study outcome.

Moreover, the respondents for present study were selected among private university

– local origin and private university – foreign origin. Therefore, replicating and extending this study in other categories of PrHEI such as university-colleges and colleges in both PuHEIs and PrHEIs would test the applicability of the present findings. Additionally, it would also provide a basis for further authentication of the research framework formulated in the current investigation to comprehend the variations of students.

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5.7 Conclusion

Research on international students‘ information orientation searching behaviour in eWoM towards HEI enrolment choice is comparatively new and still in early stages. Considering this, the main objective of this study is to provide an enhanced understanding on the information orientation (country image, city effect, institution image, programme evaluation) and relation towards information usefulness on HEI enrolment choice by international students, particularly on

Malaysian PrUni enrolment choice by international students. To achieve this, this study has proposed to conglomerate combined model of college choice and IAM.

This study was conducted among the international students in Malaysian PrUni.

Partial Least Squared (PLS) method was used to examine the statistical implication.

The proposed model achieved to provide some significant outcomes such as programme evaluation was identified to be the highest dominant variable towards

PrUni enrolment choice and the second most significant variable was information usefulness. The influence of country image was found to have no significant relationship towards PrUni enrolment choice by international students. Through this study, the IAM model has been adapted particularly to observe both information quality and source credibility moderating effect between information orientation and information usefulness. Although information quality and source credibility was tested in previous studies as independent variable, there are limited studies on observing them as moderators. Thus, this research is focused in understanding the significance of the moderating effect of information quality and source credibility throughout the information searched process in the eWoM environment.

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Furthermore, the current study is distinctive because of the comparatively new in the scope of study. Recent studies related to eWoM are focused on tangible items, and there are limited studies on complex services. PrUni enrolment choices by international students are considered as complex, high-risk service purchase. Hence, eWoM plays a vital role for international students to search for information before enrolling into their choice of PrUni. Additionally, analysing on the associated literatures has revealed that there is limited exposure on the information orientation searched in eWoM and the relationship towards the HEI enrolment choice by international students particularly in Malaysian PrUni. The finding of the study shows that information orientations searched by international students via eWoM have given the international students useful information prior to their PrUni enrolment choice. The nature of eWoM which provide international students with enhanced volume of information disseminated with persistence (Kozinets et al.,

2016) may provide international students with useful information. Additionally, the moderation effect of information quality and source credibility towards the relationship between information orientation and information usefulness reveals that a significant moderation effect does exist. Information quality does moderate the relationship between city effect, institution image, programme evaluation and information usefulness. Comparatively, source credibility does moderate the relationship between country image, city effect, programme evaluation and information usefulness.

As overall, this study points out a high statistical significance for majority of the hypotheses tested. Based on Tenenhaus et al. (2005), researches are required to examine the goodness of fit (GoF) for validating PLS globally. GoF measures the average communality and the average R2. According to this study, the GoF value is

292

0.492 which exceeds the cut off value for large effect size of R2. As such, it is concluded that the model of this study has a better predictive power in comparison with baseline model. Also, as indicated by Fornell & Cha (1994), the model under study is also considered to have predictive relevance as the cross validated communality and redundancy index are all above 0.

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APPENDIX A: SURVEY QUESTIONNAIRE

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A SURVEY ON THE EFFECTIVENESS OF ELECTRONIC WORD-OF-MOUTH IN ATTRACTING INTERNATIONAL STUDENTS TO ENROL INTO MALAYSIAN PRIVATE HIGHER EDUCATION INSTITUTIONS

Dear Respondent,

I am currently a PhD student from School of Management, University Sains Malaysia (USM) Penang. I am conducting a research on the EFFECTIVENESS OF ELECTRONIC WORD OF MOUTH IN ATTRACTING INTERNATIONAL STUDENTS TO ENROL INTO MALAYSIAN PRIVATE HIGHER EDUCATION INSTITUTION (PrHEI) under supervisor of Associate Professor Dr.Azizah Omar (principal supervisor) and Professor T.Ramayah (co-supervisor)

The aim of this research is to identify the effectiveness of eWoM in the enrolment choice of PrHEIs by international students.

I seek your assistance to be part of this study by answering the survey. This survey will only take 10 minutes of your time. Your participation is voluntary and you may discontinue anytime. However, your full participation is highly appreciated. Your responds will be kept strictly confidential and will be used only for the research purpose.

Your cooperation is highly appreciated, and your feedback is valuable to me. Should you have any questions pertaining to this survey, please do not hesitate to call me at 016- 7737348 or email me at [email protected].

Thank you

Yours sincerely

Vijayesvaran Arumugam Assoc. Prof Dr.Azizah Omar Professor T.Ramayah

Phd candidate Principal Supervisor Co-Supervisior

[email protected] [email protected] [email protected]

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Section A (Screening Question)

1. Are you a first year (Semester 1, Semester 2) student?

Yes

(If “Yes”, answer the following questions)

2. Have you ever used the electronic Word-of-Mouth – eWoM (e.g. Facebook, Twitter, LinkedIn, You Tube, Google+, Pinterest or Instagram) to search for higher education institution information?

Yes

(If “Yes”, answer the following questions, if “No” process ends .Thank you for your time and participation)

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Section B

1. Country of origin. ______

2. Gender

Male

Female

3. Age

15 – 19

20 – 24

25 – 29

30 – 35

36 and above

4. University Category

Private University – Local origin

Private University – Foreign origin

5. What is your current higher education institution name?

______

Section C, D, E, F, G, H, I and J based the higher education you are enrolled in, therefore your higher education institution will be identified as “X” in stated sections.

6. Which university course are you studying now (please tick one only)?

English Language Programme Bachelor‘s Degree

Foundation Master‘s Degree

Diploma PhD

7. Which university programme are you studying now? ______

323

8. Rank the Top 5 (FIVE) eWoM site(s) that you visited in searching for PrHEIs information. (Starting with 1 for the website you visit the most, 5= visit the least compare to previous 4).

Facebook

Twitter

Google+

YouTube

Instagram

Other Social Media sites ______

9. Rank the Top 5 (FIVE) information category did you search for on eWoM site (s) when searching for university information? (Starting with 1 for the website you visit the most, 5= visit the least compare to previous 4).

University image information

Course information

University course recognitions

University course opinions

Video of university facilities

Quality of lectures

City of the university located

Cultural similarity

Other Information ______

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Section C

The following set of statements relate to your feelings of Country Image of your current private higher education institution. Please indicate your response on each of the Country Image items by circling the numbers below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

* X is refers to the private higher education institution that you answered in Question 5

No Cultural Proximity Scale 1 The country of X has similar culture to my home country. 1 2 3 4 5 6 7

2 The country of X has perceived lower level of racial discrimination. 1 2 3 4 5 6 7

3 The country of X has religious affiliation of institutions. 1 2 3 4 5 6 7

4 The country of X has perceived lower level of crime. 1 2 3 4 5 6 7

No Academic Reputation Scale 1 The quality of X is better than my home country 1 2 3 4 5 6 7 2 The country of X have many choices of quality institution than in my home country 1 2 3 4 5 6 7

3 The country of X have many choices of quality academic programmes than in my home country 1 2 3 4 5 6 7

4 The country of X has destined them as education hub of Asia. 1 2 3 4 5 6 7

No Socioeconomic Level Scale 1 The quality of X country lifestyle is higher than my home country 1 2 3 4 5 6 7

2 The country of X has the option for international students to be employed while studying (part time 1 2 3 4 5 6 7 jobs) 3 The country of X has the option for international students to be employed after graduation 1 2 3 4 5 6 7

325

4 The country of X has the good medical facilities with affordable fees. 1 2 3 4 5 6 7

Section D

The following set of statements relate to your feelings of City Effect of your current higher education institution. Please indicate your response on each of the City Effect items by circling the numbers below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No City Dimension Scale 1 The city where X is located allows me to attend classes conveniently. 1 2 3 4 5 6 7

2 The city where X located is safe for me to study. 1 2 3 4 5 6 7 3 The city where X is located allows me to find part time job easily. 1 2 3 4 5 6 7

4 X friendly city atmosphere allows me to have peaceful life. 1 2 3 4 5 6 7

No Cost of Living Scale 1 The rental of house is affordable in the city where X is located. 1 2 3 4 5 6 7

2 The food prices are reasonable in the city where X is located. 1 2 3 4 5 6 7 3 Public transports are inexpensive in the city where X is located. 1 2 3 4 5 6 7 4 Recreational activities are free the city where X is located. 1 2 3 4 5 6 7

326

Section E

The following set of statements relate to your feelings of Institution Image of your current higher education institution. Please indicate your response on each of the Institution Image items by circling the numbers below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No Quality of Professor Scale 1 X lecturers teaching quality is good 1 2 3 4 5 6 7

2 X lecturers are competent in their subject areas 1 2 3 4 5 6 7 3 X lecturers profile is impressive 1 2 3 4 5 6 7 4 X lecturers maintains a respectful position with the international students. 1 2 3 4 5 6 7

5 X lecturers efficiently incorporates ICTs (Information and Communication Technologies) as 1 2 3 4 5 6 7 teaching medium.

6 X lecturers are fair in assessing international students 1 2 3 4 5 6 7

No Institution Recognition Scale 1 X has reputation for quality academic standards 1 2 3 4 5 6 7 2 X program is recognized worldwide 1 2 3 4 5 6 7 3 X has close link with the industries in Malaysia which help international students to attach for 1 2 3 4 5 6 7 industrial training. 4 X is affiliated with international professional bodies 1 2 3 4 5 6 7 5 X‘s graduates have the reputation of being recruited by major corporations upon completion of their 1 2 3 4 5 6 7 studies

6 Employment opportunities are much greater with a degree from X upon return to home country 1 2 3 4 5 6 7

327

No Facilities on Campus Scale 1 X has good facilities (for example, lecture hall, 1 2 3 4 5 6 7 library, sport recreation and etc)

2 X has robust internet connection facilities (wired and wireless connections) 1 2 3 4 5 6 7

3 X has strong international student support Services 1 2 3 4 5 6 7 4 X overall layout is attractive 1 2 3 4 5 6 7 5 X is well-guarded by university personal 1 2 3 4 5 6 7 6 X uphold conducive environment 1 2 3 4 5 6 7

Section F The following set of statements relate to your feelings of Programme Evaluation of your current higher education institution. Please indicate your response on each of the Programme Evaluation items by circling the numbers below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No Programme Recognition Scale 1 X courses are accredited by the Malaysian government. 1 2 3 4 5 6 7

2 X courses are accredited by international bodies 1 2 3 4 5 6 7 3 X courses are accredited by professional bodies 1 2 3 4 5 6 7 4 X courses are accredited by home country. 1 2 3 4 5 6 7 5 X courses are recognized by home country. 1 2 3 4 5 6 7 6 X courses are recognized among other overseas higher education institutions 1 2 3 4 5 6 7

328

No Programme Suitability Scale 1 X course duration is suitable for me 1 2 3 4 5 6 7 2 X course timetable is flexible to rearrange. 1 2 3 4 5 6 7 3 The flexibility of the minimum entry requirements in X, appealed to me 1 2 3 4 5 6 7

4 The flexibility in credit transfer in X, attracted to me. 1 2 3 4 5 6 7

No Programme Specialization Scale 1 The availability of specialized major courses in X attracted me 1 2 3 4 5 6 7

2 X twinning arrangement or strategic alliance with well-known overseas institution‘s appealed to me 1 2 3 4 5 6 7

3 X course content is suitable for me. 1 2 3 4 5 6 7 4 X course structure is suitable for me. 1 2 3 4 5 6 7 5 X course content X is well defined. 1 2 3 4 5 6 7 6 X course structure X is well defined. 1 2 3 4 5 6 7

No Cost and Finance Scale 1 X tuition fee is cheaper compare to my home country institution. 1 2 3 4 5 6 7

2 X provides flexible fee payment mode. 1 2 3 4 5 6 7 3 X offers scholarships (full scholarship or partial scholarship) for international students. 1 2 3 4 5 6 7

4 X offers financial aid for international students (tuition fee waiver upon getting good grades) 1 2 3 4 5 6 7

329

Section G

The following set of statement relates to Information Quality received about your current higher education institution (X) via electronic word-of-mouth. Please indicate your response on each of the Information Quality items by circling the number as stated below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No Information Quality Scale 1 I receive relevant information of X 1 2 3 4 5 6 7 2 I receive up-to-date information of X 1 2 3 4 5 6 7 3 I receive accurate information of X 1 2 3 4 5 6 7 4 I receive comprehensive information of X 1 2 3 4 5 6 7

Section H The following set of statement relates to information Source Credibility received about your current higher education institution (X) via electronic word-of-mouth. Please indicate your response on each of the Source Credibility items by circling the number as stated below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No Source Credibility Scale 1 I receive information of X from an expert source 1 2 3 4 5 6 7 2 I receive information of X from a trustworthy source 1 2 3 4 5 6 7 3 I receive information of X from a credible source 1 2 3 4 5 6 7 4 I receive information of X from a reliable source 1 2 3 4 5 6 7

330

Section I

The following set of statement relates to private higher education institutions Information Usefulness received about your current higher education institution (X) via electronic word- of-mouth. Please indicate your response on each of the Information Usefulness items by circling the number as stated below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No Information Usefulness Scale 1 X Information is valuable for me 1 2 3 4 5 6 7 2 X Information is informative for me. 1 2 3 4 5 6 7 3 X Information is helpful for me. 1 2 3 4 5 6 7 4 X Information is instructive for me. 1 2 3 4 5 6 7

Section J

The following set of statement relates to your private higher education institution (X) Enrolment Choice. Please indicate your response on each of the Enrolment Choice construct by circling the number as stated below.

1 2 3 4 5 6 7

Strongly Disagree Slightly Neither Slightly Agree Strongly Disagree Disagree Agree nor Agree Agree Disagree

No HEI Enrolment Choice Scale 1 Information orientation of X from eWoM made it easier for me to make enrolment choice. 1 2 3 4 5 6 7

2 Information orientation from eWoM guides me to enrol in X. 1 2 3 4 5 6 7

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3 The information orientation of X from eWoM motivates me to enrol in X 1 2 3 4 5 6 7

4 Information orientation from eWoM has enhanced my effectiveness in making enrolment choice. 1 2 3 4 5 6 7

5 Overall, i am satisfied to use the information from eWoM. 1 2 3 4 5 6 7

Thank you for your time and cooperation.

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APPENDIX B: SPSS OUTPUT FOR DEMOGRAPHIC VARIABLESS

1) FREQUENCY TABLE

2) COMMON METHOD VARIANCE

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APPENDIX B: FREQUENCIES

Which is your country of residence Frequency Percent Valid Percent Cumulative Percent Africa 1 .3 .3 .3 Australia 2 .6 .6 .8 Bangladesh 29 8.1 8.1 8.9 Botswana 2 .6 .6 9.5 Brunei 8 2.2 2.2 11.7 China 59 16.4 16.4 28.1 Egypt 4 1.1 1.1 29.2 Germany 2 .6 .6 29.8 Ghana 1 .3 .3 30.1 India 15 4.2 4.2 34.3 Indonesia 32 8.9 8.9 43.2 Iran 16 4.5 4.5 47.6 Iraq 4 1.1 1.1 48.7 Italy 1 .3 .3 49.0 Jamaica 1 .3 .3 49.3 Japan 3 .8 .8 50.1 Jordan 2 .6 .6 50.7 Kazakhstan 6 1.7 1.7 52.4 Valid Kenya 2 .6 .6 52.9 Libya 2 .6 .6 53.5 Maldives 8 2.2 2.2 55.7 Mauritius 7 1.9 1.9 57.7 Morocco 1 .3 .3 57.9 Myanmar 1 .3 .3 58.2 New Zealand 1 .3 .3 58.5 Nigeria 19 5.3 5.3 63.8 Pakistan 23 6.4 6.4 70.2 Palestine 2 .6 .6 70.8 Philippines 4 1.1 1.1 71.9 Portugal 1 .3 .3 72.1 Russia 1 .3 .3 72.4 Saudi Arabia 6 1.7 1.7 74.1 Singapore 6 1.7 1.7 75.8 Somalia 1 .3 .3 76.0 South Africa 5 1.4 1.4 77.4 South Korea 8 2.2 2.2 79.7

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Spain 3 .8 .8 80.5 Sri Lanka 7 1.9 1.9 82.5 Sudan 6 1.7 1.7 84.1 Syria 5 1.4 1.4 85.5 Thailand 5 1.4 1.4 86.9 Timor Leste 3 .8 .8 87.7 Turkmenistan 2 .6 .6 88.3 UAE 11 3.1 3.1 91.4 Uganda 1 .3 .3 91.6 United States of America 1 .3 .3 91.9 Uzbekistan 4 1.1 1.1 93.0 Vietnam 2 .6 .6 93.6 Yemen 21 5.8 5.8 99.4 Zimbabwe 2 .6 .6 100.0 Total 359 100.0 100.0

Gender Frequency Percent Valid Percent Cumulative Percent Male 194 54.0 54.0 54.0 Valid Female 165 46.0 46.0 100.0 Total 359 100.0 100.0

Age Frequency Percent Valid Percent Cumulative Percent 15 - 20 129 35.9 35.9 35.9 20 - 25 193 53.8 53.8 89.7 25 - 30 33 9.2 9.2 98.9 Valid 30 - 35 2 .6 .6 99.4 36 and above 2 .6 .6 100.0 Total 359 100.0 100.0

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University Category Frequency Percent Valid Percent Cumulative Percent Private University - Local 305 85.0 85.0 85.0 Origin Valid Private University - Foreign 54 15.0 15.0 100.0 Origin Total 359 100.0 100.0

Which university programme are you studying now? Frequency Percent Valid Percent Cumulative Percent Accounting 2 .6 .6 .6 Bachelor of Accounting 1 .3 .3 .8 Banking and Finance 5 1.4 1.4 2.2 Biomedical Science 4 1.1 1.1 3.3 Bioscience 2 .6 .6 3.9 Biotechemistry 2 .6 .6 4.5 Biotechnology 13 3.6 3.6 8.1 Business Administartion 8 2.2 2.2 10.3 Business Administration 166 46.2 46.2 56.5 Cinematics Art 1 .3 .3 56.8 Civil Engineering 9 2.5 2.5 59.3 Communication 2 .6 .6 59.9 Compter Science 1 .3 .3 60.2 Computer Science 11 3.1 3.1 63.2 Valid Electrical Engineering 3 .8 .8 64.1 Electronic Engineering 4 1.1 1.1 65.2 English Language 2 .6 .6 65.7 Programm English Programme 1 .3 .3 66.0 Foundation in Arts 5 1.4 1.4 67.4 Foundation in Science 26 7.2 7.2 74.7 Foundation of Arts 3 .8 .8 75.5 Hotel Management 4 1.1 1.1 76.6 Human Resource 4 1.1 1.1 77.7 Management Information System 11 3.1 3.1 80.8 Information Technology 19 5.3 5.3 86.1 International Business 5 1.4 1.4 87.5 Knowledge Management 1 .3 .3 87.7

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LAW 15 4.2 4.2 91.9 Markeing Management 2 .6 .6 92.5 Marketing 1 .3 .3 92.8 MBBS 11 3.1 3.1 95.8 Mechatronic Engineering 1 .3 .3 96.1 Mechnical Engineering 2 .6 .6 96.7 Medical Electronic Engine 1 .3 .3 96.9 MSC 2 .6 .6 97.5 Oil and Gas 1 .3 .3 97.8 Software Engineering 8 2.2 2.2 100.0 Total 359 100.0 100.0

Which university course are you studying now (please tick one only)? Frequency Percent Valid Percent Cumulative Percent English Language 5 1.4 1.4 1.4 Programme Foundation 36 10.0 10.0 11.4 Valid Diploma 42 11.7 11.7 23.1 Bachelor Degree 240 66.9 66.9 90.0 Master Degree 36 10.0 10.0 100.0 Total 359 100.0 100.0

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APPENDIX B: COMMON METHOD VARIANCE

Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Cumulative % Total % of Cumulative Variance Variance % 1 22.058 29.410 29.410 22.058 29.410 29.410 2 3.872 5.163 34.573 3.872 5.163 34.573 3 3.272 4.362 38.935 3.272 4.362 38.935 4 2.649 3.531 42.467 2.649 3.531 42.467 5 2.177 2.903 45.370 2.177 2.903 45.370 6 1.950 2.600 47.970 1.950 2.600 47.970 7 1.844 2.459 50.429 1.844 2.459 50.429 8 1.790 2.386 52.815 1.790 2.386 52.815 9 1.636 2.181 54.996 1.636 2.181 54.996 10 1.529 2.039 57.035 1.529 2.039 57.035 11 1.481 1.975 59.010 1.481 1.975 59.010 12 1.382 1.843 60.853 1.382 1.843 60.853 13 1.312 1.749 62.603 1.312 1.749 62.603 14 1.166 1.555 64.158 1.166 1.555 64.158 15 1.141 1.521 65.678 1.141 1.521 65.678 16 1.058 1.411 67.089 1.058 1.411 67.089 17 1.018 1.358 68.447 1.018 1.358 68.447 18 .979 1.305 69.752 19 .916 1.221 70.974 20 .897 1.196 72.169 21 .873 1.164 73.333 22 .799 1.065 74.399 23 .766 1.022 75.420 24 .730 .973 76.394 25 .728 .970 77.364 26 .690 .920 78.285 27 .667 .889 79.174 28 .644 .859 80.033 29 .618 .824 80.857 30 .601 .801 81.657 31 .589 .785 82.443 32 .572 .762 83.205 33 .559 .746 83.951 34 .543 .723 84.674 35 .530 .706 85.381 36 .504 .673 86.053 37 .471 .628 86.681 38 .450 .600 87.281 39 .442 .590 87.871 40 .427 .569 88.440 41 .411 .548 88.988 42 .404 .538 89.527 43 .389 .518 90.045 44 .368 .490 90.535 45 .365 .487 91.022 46 .363 .484 91.506

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47 .341 .454 91.960 48 .333 .444 92.404 49 .322 .429 92.833 50 .315 .420 93.253 51 .308 .411 93.663 52 .301 .401 94.064 53 .291 .388 94.453 54 .281 .374 94.827 55 .268 .357 95.184 56 .263 .351 95.535 57 .255 .340 95.876 58 .246 .327 96.203 59 .228 .304 96.507 60 .222 .295 96.802 61 .215 .287 97.089 62 .208 .278 97.367 63 .202 .270 97.637 64 .198 .264 97.900 65 .180 .240 98.141 66 .172 .230 98.370 67 .167 .223 98.593 68 .161 .214 98.808 69 .148 .198 99.005 70 .144 .192 99.197 71 .137 .182 99.380 72 .131 .174 99.554 73 .118 .158 99.712 74 .114 .152 99.863 75 .102 .137 100.000 Extraction Method: Principal Component Analysis.

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APPENDIX C: CROSSTABULATION FOR RESPONSES (EARLY AND LATE)

Gender Response Total Early Late Count 185 9 194 % within Gender 95.4% 4.6% 100.0% Male % within Response 53.8% 60.0% 54.0% % of Total 51.5% 2.5% 54.0% Gender Count 159 6 165 % within Gender 96.4% 3.6% 100.0% Female % within Response 46.2% 40.0% 46.0% % of Total 44.3% 1.7% 46.0% Count 344 15 359 % within Gender 95.8% 4.2% 100.0% Total % within Response 100.0% 100.0% 100.0% % of Total 95.8% 4.2% 100.0%

Chi-Square Tests Value df Asymp. Sig. Exact Sig. (2- Exact Sig. (1- (2-sided) sided) sided) Pearson Chi-Square .224a 1 .636 Continuity Correctionb .044 1 .835 Likelihood Ratio .226 1 .635 Fisher's Exact Test .793 .420 Linear-by-Linear .223 1 .637 Association N of Valid Cases 359

Symmetric Measures Value Approx. Sig. Phi -.025 .636 Nominal by Nominal Cramer's V .025 .636 N of Valid Cases 359

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Country Response Total Early Late Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Africa residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 2 0 2 % within Which is 100.0% 0.0% 100.0% your country of Australia residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 28 1 29 % within Which is 96.6% 3.4% 100.0% your country of Bangladesh residence? % within Response 8.1% 6.7% 8.1% % of Total 7.8% 0.3% 8.1% Which is your country Count 2 0 2 of residence? % within Which is 100.0% 0.0% 100.0% your country of Botswana residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 6 2 8 % within Which is 75.0% 25.0% 100.0% your country of Brunei residence? % within Response 1.7% 13.3% 2.2% % of Total 1.7% 0.6% 2.2% Count 57 2 59 % within Which is 96.6% 3.4% 100.0% your country of China residence? % within Response 16.6% 13.3% 16.4% % of Total 15.9% 0.6% 16.4% Egypt Count 4 0 4

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 1.2% 0.0% 1.1% % of Total 1.1% 0.0% 1.1% Count 2 0 2 % within Which is 100.0% 0.0% 100.0% your country of Germany residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Ghana residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 15 0 15 % within Which is 100.0% 0.0% 100.0% your country of India residence? % within Response 4.4% 0.0% 4.2% % of Total 4.2% 0.0% 4.2% Count 30 2 32 % within Which is 93.8% 6.3% 100.0% your country of Indonesia residence? % within Response 8.7% 13.3% 8.9% % of Total 8.4% 0.6% 8.9% Count 15 1 16 % within Which is 93.8% 6.3% 100.0% your country of Iran residence? % within Response 4.4% 6.7% 4.5% % of Total 4.2% 0.3% 4.5% Count 4 0 4 % within Which is 100.0% 0.0% 100.0% your country of Iraq residence? % within Response 1.2% 0.0% 1.1% % of Total 1.1% 0.0% 1.1% Italy Count 1 0 1

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Jamaica residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 2 1 3 % within Which is 66.7% 33.3% 100.0% your country of Japan residence? % within Response 0.6% 6.7% 0.8% % of Total 0.6% 0.3% 0.8% Count 1 1 2 % within Which is 50.0% 50.0% 100.0% your country of Jordan residence? % within Response 0.3% 6.7% 0.6% % of Total 0.3% 0.3% 0.6% Count 6 0 6 % within Which is 100.0% 0.0% 100.0% your country of Kazakhstan residence? % within Response 1.7% 0.0% 1.7% % of Total 1.7% 0.0% 1.7% Count 2 0 2 % within Which is 100.0% 0.0% 100.0% your country of Kenya residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 2 0 2 % within Which is 100.0% 0.0% 100.0% your country of Libya residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Maldives Count 8 0 8

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 2.3% 0.0% 2.2% % of Total 2.2% 0.0% 2.2% Count 7 0 7 % within Which is 100.0% 0.0% 100.0% your country of Mauritius residence? % within Response 2.0% 0.0% 1.9% % of Total 1.9% 0.0% 1.9% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Morocco residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Myanmar residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of New Zealand residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 19 0 19 % within Which is 100.0% 0.0% 100.0% your country of Nigeria residence? % within Response 5.5% 0.0% 5.3% % of Total 5.3% 0.0% 5.3% Count 23 0 23 % within Which is 100.0% 0.0% 100.0% your country of Pakistan residence? % within Response 6.7% 0.0% 6.4% % of Total 6.4% 0.0% 6.4% Palestine Count 2 0 2

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 4 0 4 % within Which is 100.0% 0.0% 100.0% your country of Philippines residence? % within Response 1.2% 0.0% 1.1% % of Total 1.1% 0.0% 1.1% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Portugal residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Russia residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 6 0 6 % within Which is 100.0% 0.0% 100.0% your country of Saudi Arabia residence? % within Response 1.7% 0.0% 1.7% % of Total 1.7% 0.0% 1.7% Count 5 1 6 % within Which is 83.3% 16.7% 100.0% your country of Singapore residence? % within Response 1.5% 6.7% 1.7% % of Total 1.4% 0.3% 1.7% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Somalia residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% South Africa Count 5 0 5

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 1.5% 0.0% 1.4% % of Total 1.4% 0.0% 1.4% Count 7 1 8 % within Which is 87.5% 12.5% 100.0% your country of South Korea residence? % within Response 2.0% 6.7% 2.2% % of Total 1.9% 0.3% 2.2% Count 3 0 3 % within Which is 100.0% 0.0% 100.0% your country of Spain residence? % within Response 0.9% 0.0% 0.8% % of Total 0.8% 0.0% 0.8% Count 6 1 7 % within Which is 85.7% 14.3% 100.0% your country of Sri Lanka residence? % within Response 1.7% 6.7% 1.9% % of Total 1.7% 0.3% 1.9% Count 6 0 6 % within Which is 100.0% 0.0% 100.0% your country of Sudan residence? % within Response 1.7% 0.0% 1.7% % of Total 1.7% 0.0% 1.7% Count 5 0 5 % within Which is 100.0% 0.0% 100.0% your country of Syria residence? % within Response 1.5% 0.0% 1.4% % of Total 1.4% 0.0% 1.4% Count 5 0 5 % within Which is 100.0% 0.0% 100.0% your country of Thailand residence? % within Response 1.5% 0.0% 1.4% % of Total 1.4% 0.0% 1.4% Timor Leste Count 3 0 3

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 0.9% 0.0% 0.8% % of Total 0.8% 0.0% 0.8% Count 2 0 2 % within Which is 100.0% 0.0% 100.0% your country of Turkmenistan residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 10 1 11 % within Which is 90.9% 9.1% 100.0% your country of UAE residence? % within Response 2.9% 6.7% 3.1% % of Total 2.8% 0.3% 3.1% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% your country of Uganda residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 1 0 1 % within Which is 100.0% 0.0% 100.0% United States of your country of America residence? % within Response 0.3% 0.0% 0.3% % of Total 0.3% 0.0% 0.3% Count 4 0 4 % within Which is 100.0% 0.0% 100.0% your country of Uzbekistan residence? % within Response 1.2% 0.0% 1.1% % of Total 1.1% 0.0% 1.1% Count 2 0 2 % within Which is 100.0% 0.0% 100.0% your country of Vietnam residence? % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Yemen Count 21 0 21

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% within Which is 100.0% 0.0% 100.0% your country of residence? % within Response 6.1% 0.0% 5.8% % of Total 5.8% 0.0% 5.8% Count 1 1 2 % within Which is 50.0% 50.0% 100.0% your country of Zimbabwe residence? % within Response 0.3% 6.7% 0.6% % of Total 0.3% 0.3% 0.6% Count 344 15 359 % within Which is 95.8% 4.2% 100.0% your country of Total residence? % within Response 100.0% 100.0% 100.0% % of Total 95.8% 4.2% 100.0%

Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 50.498a 49 .414 Likelihood Ratio 33.770 49 .952 N of Valid Cases 359 a. 82 cells (82.0%) have expected count less than 5. The minimum expected count is .04.

Symmetric Measures Value Approx. Sig. Phi .375 .414 Nominal by Nominal Cramer's V .375 .414 N of Valid Cases 359

Age Response Total Early Late Count 122 7 129 % within Age 94.6% 5.4% 100.0% 15 - 20 % within Response 35.5% 46.7% 35.9% % of Total 34.0% 1.9% 35.9% Age Count 186 7 193 % within Age 96.4% 3.6% 100.0% 20 - 25 % within Response 54.1% 46.7% 53.8% % of Total 51.8% 1.9% 53.8%

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Count 32 1 33 % within Age 97.0% 3.0% 100.0% 25 - 30 % within Response 9.3% 6.7% 9.2% % of Total 8.9% 0.3% 9.2% Count 2 0 2 % within Age 100.0% 0.0% 100.0% 30 - 35 % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 2 0 2 % within Age 100.0% 0.0% 100.0% 36 and above % within Response 0.6% 0.0% 0.6% % of Total 0.6% 0.0% 0.6% Count 344 15 359 % within Age 95.8% 4.2% 100.0% Total % within Response 100.0% 100.0% 100.0% % of Total 95.8% 4.2% 100.0%

Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square .931a 4 .920 Likelihood Ratio 1.074 4 .898 Linear-by-Linear Association .862 1 .353 N of Valid Cases 359 a. 5 cells (50.0%) have expected count less than 5. The minimum expected count is .08.

Symmetric Measures Value Approx. Sig. Phi .051 .920 Nominal by Nominal Cramer's V .051 .920 N of Valid Cases 359

PrHEI Category Response Total Early Late Count 290 15 305 % within University 95.1% 4.9% 100.0% Private University - University Category Local Origin Category % within Response 84.3% 100.0% 85.0% % of Total 80.8% 4.2% 85.0% Private University - Count 54 0 54

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Foreign Origin % within University 100.0% 0.0% 100.0% Category % within Response 15.7% 0.0% 15.0% % of Total 15.0% 0.0% 15.0% Count 344 15 359 % within University 95.8% 4.2% 100.0% Total Category % within Response 100.0% 100.0% 100.0% % of Total 95.8% 4.2% 100.0%

Chi-Square Tests Value df Asymp. Sig. Exact Sig. (2- Exact Sig. (1- (2-sided) sided) sided) Pearson Chi-Square 2.772a 1 .096 Continuity Correctionb 1.679 1 .195 Likelihood Ratio 5.005 1 .025 Fisher's Exact Test .140 .082 Linear-by-Linear 2.764 1 .096 Association N of Valid Cases 359 a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 2.26. b. Computed only for a 2x2 table

Symmetric Measures Value Approx. Sig. Phi -.088 .096 Nominal by Nominal Cramer's V .088 .096 N of Valid Cases 359

Crosstab Response Total Early Late Count 5 0 5 % within Which 100.0% 0.0% 100.0% Which university university course are course are you English Language you studying now studying now (please Programme (please tick one tick one only)? only)? % within Response 1.5% 0.0% 1.4% % of Total 1.4% 0.0% 1.4%

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Count 32 4 36 % within Which 88.9% 11.1% 100.0% university course are you studying now Foundation (please tick one only)? % within Response 9.3% 26.7% 10.0% % of Total 8.9% 1.1% 10.0% Count 41 1 42 % within Which 97.6% 2.4% 100.0% university course are you studying now Diploma (please tick one only)? % within Response 11.9% 6.7% 11.7% % of Total 11.4% 0.3% 11.7% Count 230 10 240 % within Which 95.8% 4.2% 100.0% university course are you studying now Bachelor Degree (please tick one only)? % within Response 66.9% 66.7% 66.9% % of Total 64.1% 2.8% 66.9% Count 36 0 36 % within Which 100.0% 0.0% 100.0% university course are you studying now Master Degree (please tick one only)? % within Response 10.5% 0.0% 10.0% 10.0% 0.0% 10.0% % of Total

Count 344 15 359 % within Which 95.8% 4.2% 100.0% university course are you studying now Total (please tick one only)? % within Response 100.0% 100.0% 100.0% % of Total 95.8% 4.2% 100.0%

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Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 6.449a 4 .168 Likelihood Ratio 6.917 4 .140 Linear-by-Linear Association 2.682 1 .101 N of Valid Cases 359 a. 5 cells (50.0%) have expected count less than 5. The minimum expected count is .21.

Symmetric Measures Value Approx. Sig. Phi .134 .168 Nominal by Nominal Cramer's V .134 .168 N of Valid Cases 359

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APPENDIX D: DIFFERENCE IN MAJOR VARIABLES BY EARLY AND LATE RESPONSES

Group Statistics Response N Mean Std. Deviation Std. Error Mean Early 344 4.4419 .93866 .05061 CP Late 15 4.5000 .71962 .18581 Early 344 4.5501 1.08672 .05859 AP Late 15 4.8667 .73719 .19034 Early 344 4.3837 1.04662 .05643 SL Late 15 4.3667 .71880 .18559 Early 344 4.7129 .91825 .04951 CD Late 15 4.3667 .89076 .22999 Early 344 4.5036 1.03307 .05570 CL Late 15 4.6833 1.11590 .28812 Early 344 4.9821 1.02784 .05542 QP Late 15 5.3333 .73733 .19038 Early 344 4.8416 .86599 .04669 IR Late 15 4.8667 .78224 .20197 Early 344 4.8929 .91690 .04944 FC Late 15 4.8222 .87393 .22565 Early 344 4.9322 .89473 .04824 PR Late 15 5.0111 .95839 .24746 Early 344 4.8016 .96347 .05195 PS Late 15 4.8833 .71256 .18398 Early 344 4.9506 .87499 .04718 PZ Late 15 5.3778 .76238 .19684 Early 344 4.1781 1.18992 .06416 CF Late 15 4.2333 1.32782 .34284 Early 344 4.8452 1.01852 .05491 IQ Late 15 4.8000 1.02295 .26412 Early 344 4.7398 .98914 .05333 SC Late 15 4.7333 .64411 .16631 Early 344 4.9113 .97852 .05276 IU Late 15 5.1500 .93446 .24128 Early 344 4.7895 .90705 .04891 EC Late 15 4.8267 .70454 .18191

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Independent Samples Test Levene's Test t-test for Equality of Means for Equality of Variances F Sig. t df Sig. Mean Std. Error 95% (2- Difference Difference Confidence tailed) Interval of the Difference Lower Upper Equal 2.044 .154 -.237 357 .813 -.05814 .24558 - .42482 variances .54110 assumed CP Equal -.302 16.151 .767 -.05814 .19257 - .34979 variances not .46607 assumed Equal 1.760 .186 - 357 .265 -.31652 .28359 - .24120 variances 1.116 .87424 assumed AP Equal - 16.773 .131 -.31652 .19916 - .10410 variances not 1.589 .73714 assumed Equal 1.458 .228 .062 357 .950 .01705 .27319 - .55432 variances .52021 assumed SL Equal .088 16.702 .931 .01705 .19398 - .42688 variances not .39277 assumed Equal .144 .704 1.431 357 .153 .34627 .24193 - .82205 variances .12951 assumed CD Equal 1.472 15.326 .161 .34627 .23526 - .84679 variances not .15425 assumed Equal .005 .944 -.657 357 .511 -.17970 .27338 - .35794 variances .71734 assumed CL Equal -.612 15.065 .549 -.17970 .29346 - .44556 variances not .80496 assumed Equal 2.112 .147 - 357 .192 -.35126 .26852 - .17682 QP variances 1.308 .87934 assumed

354

Equal - 16.468 .095 -.35126 .19828 - .06810 variances not 1.772 .77062 assumed Equal .984 .322 -.110 357 .912 -.02510 .22759 - .42250 variances .47269 assumed IR Equal -.121 15.535 .905 -.02510 .20730 - .41543 variances not .46563 assumed Equal .872 .351 .293 357 .770 .07070 .24141 - .54548 variances .40407 assumed FC Equal .306 15.375 .764 .07070 .23100 - .56203 variances not .42062 assumed Equal .255 .614 -.334 357 .739 -.07894 .23668 - .38652 variances .54441 assumed PR Equal -.313 15.083 .758 -.07894 .25211 - .45817 variances not .61605 assumed Equal 2.332 .128 -.325 357 .746 -.08173 .25186 - .41359 variances .57706 assumed PS Equal -.428 16.317 .675 -.08173 .19117 - .32290 variances not .48637 assumed Equal .601 .439 - 357 .064 -.42720 .22970 - .02454 variances 1.860 .87894 assumed PZ Equal - 15.652 .051 -.42720 .20242 - .00269 variances not 2.110 .85708 assumed Equal .081 .777 -.175 357 .861 -.05528 .31537 - .56493 variances .67549 assumed CF Equal -.158 14.997 .876 -.05528 .34879 - .68816 variances not .79873 assumed Equal .110 .740 .168 357 .866 .04520 .26870 - .57363 IQ variances .48323 assumed

355

Equal .168 15.235 .869 .04520 .26977 - .61944 variances not .52903 assumed Equal 3.228 .073 .025 357 .980 .00649 .25794 - .51376 variances .50078 assumed SC Equal .037 17.020 .971 .00649 .17465 - .37494 variances not .36196 assumed Equal .224 .636 -.926 357 .355 -.23866 .25766 - .26805 variances .74538 assumed IU Equal -.966 15.369 .349 -.23866 .24698 - .28666 variances not .76398 assumed Equal .741 .390 -.156 357 .876 -.03713 .23738 - .42971 variances .50398 assumed EC Equal -.197 16.093 .846 -.03713 .18837 - .36201 variances not .43627 assumed

356

APPENDIX E: COMMON METHOD VARIANCE - HARMAN SINGLE FACTOR TEST

357

54 .281 .374 94.827 55 .268 .357 95.184 56 .263 .351 95.535 57 .255 .340 95.876 58 .246 .327 96.203 59 .228 .304 96.507 60 .222 .295 96.802 61 .215 .287 97.089 62 .208 .278 97.367 63 .202 .270 97.637 64 .198 .264 97.900 65 .180 .240 98.141 66 .172 .230 98.370 67 .167 .223 98.593 68 .161 .214 98.808 69 .148 .198 99.005 70 .144 .192 99.197 71 .137 .182 99.380 72 .131 .174 99.554 73 .118 .158 99.712 74 .114 .152 99.863 75 .102 .137 100.000

358

APPENDIX F MEASUREMENT MODEL ANALYSIS

1) CONSTRUCT VALIDITY

a. LOADINGS AND CROSS LOADINGS

2) CONVERGENT VALIDITY

a. AVERAGE VARIANCE EXTRACTED (AVE)

b. COMPOSITE RELIABILITY (CR)

3) DISCRIMINANT VALIDITY

359

APPENDIX F: CONSTRUCT VALIDITY – LOADINGS AND CROSS LOADINGS

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr CP1 0.819 0.293 0.386 0.285 0.174 0.268 0.281 0.175 0.331 0.186 0.233 0.176 0.221 0.193 0.225 0.185 CP2 0.771 0.184 0.314 0.199 0.105 0.186 0.213 0.192 0.077 0.080 0.106 0.162 0.179 0.196 0.158 0.191 CP3 0.588 0.305 0.156 0.235 0.183 0.230 0.345 0.201 0.245 0.119 0.127 0.226 0.232 0.193 0.179 0.256 AP1 0.338 0.789 0.460 0.284 0.290 0.321 0.383 0.398 0.271 0.280 0.283 0.250 0.304 0.272 0.234 0.274 AP2 0.319 0.877 0.400 0.385 0.201 0.330 0.387 0.404 0.310 0.262 0.309 0.164 0.326 0.313 0.347 0.330 AP3 0.263 0.851 0.392 0.361 0.146 0.293 0.396 0.398 0.395 0.215 0.305 0.144 0.265 0.231 0.275 0.299 AP4 0.198 0.715 0.355 0.342 0.274 0.411 0.380 0.366 0.303 0.335 0.371 0.228 0.291 0.242 0.308 0.288 SL1 0.243 0.499 0.613 0.252 0.178 0.307 0.281 0.362 0.181 0.265 0.208 0.142 0.224 0.195 0.162 0.228 SL2 0.410 0.294 0.772 0.229 0.325 0.269 0.321 0.266 0.188 0.223 0.197 0.302 0.251 0.183 0.108 0.139 SL3 0.315 0.365 0.843 0.279 0.390 0.409 0.500 0.404 0.312 0.372 0.327 0.309 0.314 0.243 0.234 0.200 SL4 0.207 0.272 0.673 0.264 0.346 0.327 0.356 0.352 0.219 0.240 0.285 0.322 0.257 0.235 0.176 0.186 CD1 0.299 0.377 0.312 0.733 0.241 0.393 0.416 0.360 0.421 0.375 0.375 0.237 0.399 0.307 0.393 0.368 CD2 0.263 0.361 0.298 0.849 0.215 0.369 0.317 0.381 0.409 0.258 0.355 0.123 0.341 0.258 0.344 0.325 CD4 0.213 0.263 0.222 0.781 0.237 0.319 0.312 0.361 0.293 0.202 0.336 0.137 0.290 0.226 0.354 0.252 CL1 0.160 0.213 0.332 0.273 0.781 0.383 0.374 0.293 0.238 0.374 0.292 0.322 0.341 0.253 0.273 0.255 CL2 0.116 0.212 0.284 0.284 0.817 0.353 0.341 0.317 0.203 0.291 0.338 0.242 0.248 0.204 0.266 0.183 CL3 0.194 0.220 0.288 0.166 0.726 0.299 0.351 0.287 0.179 0.227 0.266 0.235 0.217 0.209 0.253 0.203 CL4 0.154 0.189 0.385 0.119 0.650 0.315 0.322 0.259 0.114 0.260 0.208 0.287 0.246 0.178 0.160 0.154 QP1 0.186 0.377 0.345 0.372 0.356 0.859 0.505 0.433 0.433 0.576 0.553 0.255 0.501 0.392 0.467 0.401 QP2 0.259 0.391 0.335 0.391 0.313 0.855 0.475 0.418 0.461 0.515 0.527 0.282 0.494 0.452 0.434 0.394 QP3 0.287 0.366 0.421 0.368 0.390 0.845 0.522 0.420 0.400 0.536 0.538 0.368 0.446 0.468 0.404 0.373 QP4 0.215 0.259 0.463 0.346 0.402 0.812 0.431 0.400 0.344 0.521 0.533 0.336 0.401 0.378 0.375 0.341 QP5 0.300 0.328 0.290 0.403 0.363 0.712 0.479 0.453 0.470 0.421 0.472 0.272 0.432 0.395 0.407 0.436

360

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr QP6 0.273 0.293 0.356 0.348 0.392 0.793 0.444 0.393 0.348 0.477 0.469 0.352 0.443 0.292 0.362 0.377 IR1 0.234 0.389 0.251 0.405 0.271 0.498 0.732 0.443 0.495 0.373 0.471 0.185 0.480 0.399 0.404 0.372 IR2 0.214 0.382 0.229 0.329 0.234 0.338 0.679 0.379 0.454 0.189 0.360 0.107 0.345 0.296 0.302 0.241 IR3 0.174 0.287 0.493 0.242 0.458 0.494 0.752 0.424 0.410 0.465 0.473 0.318 0.437 0.386 0.311 0.288 IR4 0.366 0.304 0.459 0.291 0.406 0.490 0.774 0.501 0.452 0.429 0.401 0.326 0.422 0.396 0.282 0.314 IR5 0.372 0.407 0.432 0.398 0.343 0.435 0.772 0.498 0.441 0.376 0.419 0.222 0.426 0.434 0.363 0.389 IR6 0.248 0.339 0.325 0.269 0.308 0.284 0.686 0.424 0.431 0.235 0.281 0.154 0.356 0.271 0.189 0.203 FC1 0.279 0.369 0.374 0.354 0.271 0.348 0.555 0.754 0.418 0.316 0.311 0.236 0.435 0.346 0.351 0.347 FC2 0.141 0.322 0.405 0.344 0.348 0.399 0.400 0.704 0.293 0.430 0.421 0.255 0.465 0.302 0.384 0.343 FC3 0.229 0.331 0.514 0.274 0.380 0.390 0.467 0.708 0.312 0.385 0.297 0.431 0.382 0.275 0.267 0.277 FC4 0.145 0.391 0.286 0.329 0.198 0.357 0.365 0.767 0.389 0.331 0.370 0.228 0.426 0.323 0.343 0.347 FC5 0.183 0.429 0.309 0.362 0.299 0.378 0.487 0.793 0.425 0.314 0.358 0.251 0.429 0.366 0.376 0.388 FC6 0.141 0.319 0.248 0.416 0.240 0.433 0.437 0.744 0.496 0.392 0.436 0.240 0.394 0.303 0.351 0.374 PR1 0.255 0.335 0.202 0.456 0.241 0.419 0.508 0.469 0.777 0.392 0.505 0.205 0.437 0.432 0.424 0.404 PR2 0.297 0.354 0.316 0.458 0.253 0.399 0.556 0.521 0.820 0.396 0.504 0.267 0.432 0.387 0.412 0.370 PR3 0.236 0.264 0.272 0.404 0.299 0.486 0.544 0.412 0.827 0.467 0.512 0.271 0.451 0.452 0.395 0.310 PR4 0.193 0.269 0.140 0.326 0.099 0.308 0.391 0.328 0.740 0.285 0.452 0.105 0.312 0.309 0.289 0.308 PR5 0.222 0.267 0.255 0.280 0.154 0.387 0.396 0.330 0.785 0.381 0.480 0.182 0.354 0.297 0.277 0.373 PR6 0.213 0.372 0.269 0.296 0.111 0.357 0.453 0.394 0.762 0.375 0.437 0.184 0.385 0.342 0.290 0.251 PS1 0.191 0.291 0.295 0.291 0.319 0.552 0.443 0.415 0.492 0.824 0.615 0.302 0.495 0.400 0.413 0.452 PS2 0.111 0.302 0.283 0.233 0.250 0.424 0.371 0.386 0.364 0.748 0.417 0.186 0.362 0.281 0.293 0.302

361

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr PS3 0.159 0.275 0.301 0.351 0.332 0.525 0.360 0.403 0.404 0.852 0.561 0.315 0.452 0.405 0.416 0.451 PS4 0.082 0.167 0.322 0.205 0.312 0.436 0.319 0.299 0.245 0.689 0.489 0.386 0.334 0.339 0.325 0.286 PZ1 0.244 0.361 0.232 0.394 0.201 0.446 0.490 0.385 0.559 0.509 0.717 0.251 0.450 0.433 0.430 0.417 PZ2 0.168 0.287 0.230 0.377 0.166 0.431 0.418 0.342 0.505 0.431 0.734 0.215 0.431 0.361 0.424 0.381 PZ3 0.207 0.352 0.261 0.400 0.310 0.516 0.436 0.435 0.503 0.544 0.833 0.182 0.458 0.465 0.496 0.422 PZ4 0.148 0.269 0.270 0.365 0.279 0.474 0.420 0.369 0.451 0.497 0.807 0.230 0.458 0.442 0.467 0.407 PZ5 0.179 0.289 0.326 0.277 0.372 0.534 0.397 0.384 0.439 0.601 0.820 0.297 0.415 0.406 0.463 0.404 PZ6 0.086 0.260 0.316 0.305 0.422 0.571 0.430 0.381 0.429 0.573 0.779 0.295 0.442 0.387 0.468 0.361 CF1 0.171 0.092 0.181 0.136 0.294 0.260 0.198 0.192 0.123 0.185 0.209 0.701 0.228 0.204 0.182 0.136 CF2 0.188 0.127 0.195 0.224 0.249 0.293 0.207 0.280 0.196 0.291 0.235 0.737 0.343 0.271 0.250 0.298 CF3 0.242 0.303 0.379 0.154 0.291 0.333 0.292 0.358 0.256 0.391 0.291 0.856 0.384 0.245 0.233 0.269 CF4 0.152 0.179 0.340 0.132 0.292 0.287 0.235 0.275 0.213 0.274 0.224 0.790 0.384 0.177 0.186 0.202 IQ1 0.280 0.306 0.271 0.412 0.216 0.464 0.500 0.455 0.519 0.433 0.535 0.362 0.823 0.549 0.558 0.509 IQ2 0.289 0.350 0.286 0.323 0.273 0.450 0.551 0.521 0.466 0.414 0.460 0.383 0.859 0.577 0.499 0.513 IQ3 0.201 0.270 0.372 0.339 0.391 0.518 0.423 0.447 0.324 0.492 0.478 0.410 0.848 0.500 0.467 0.457 IQ4 0.184 0.313 0.301 0.389 0.332 0.464 0.437 0.495 0.393 0.472 0.441 0.343 0.864 0.508 0.540 0.445 SC1 0.230 0.289 0.306 0.272 0.296 0.447 0.466 0.363 0.433 0.383 0.397 0.262 0.505 0.800 0.427 0.492 SC2 0.199 0.300 0.284 0.259 0.298 0.413 0.458 0.385 0.390 0.411 0.470 0.306 0.544 0.868 0.499 0.471 SC3 0.249 0.235 0.210 0.278 0.223 0.402 0.428 0.352 0.408 0.390 0.463 0.209 0.553 0.880 0.526 0.521 SC4 0.205 0.289 0.205 0.320 0.159 0.400 0.357 0.355 0.381 0.376 0.464 0.214 0.527 0.834 0.522 0.451 IU1 0.237 0.352 0.243 0.396 0.319 0.486 0.428 0.419 0.420 0.430 0.531 0.234 0.542 0.501 0.836 0.453 IU2 0.220 0.262 0.193 0.382 0.249 0.386 0.368 0.384 0.426 0.349 0.479 0.206 0.522 0.535 0.870 0.435 IU3 0.229 0.286 0.200 0.379 0.288 0.428 0.341 0.390 0.342 0.425 0.506 0.246 0.481 0.487 0.867 0.468 IU4 0.186 0.318 0.163 0.410 0.244 0.409 0.307 0.384 0.330 0.391 0.478 0.254 0.535 0.473 0.832 0.482

362

CulProx AcaRec Soci Lel CityDim Cost Liv QualPro IntReco FacCam ProReco ProgSuit ProgSpe Cost Fin InfoQua SourCre InfoUse HEEnr EC1 0.238 0.297 0.215 0.283 0.243 0.380 0.341 0.376 0.277 0.440 0.394 0.276 0.490 0.484 0.489 0.769 EC2 0.258 0.266 0.248 0.307 0.224 0.374 0.368 0.361 0.409 0.364 0.385 0.254 0.493 0.501 0.389 0.803 EC3 0.202 0.320 0.240 0.246 0.248 0.374 0.338 0.323 0.344 0.404 0.411 0.262 0.416 0.413 0.345 0.791 EC4 0.178 0.259 0.102 0.293 0.111 0.298 0.237 0.290 0.323 0.330 0.349 0.222 0.373 0.392 0.371 0.783 EC5 0.187 0.284 0.196 0.399 0.204 0.404 0.325 0.429 0.326 0.340 0.431 0.154 0.416 0.411 0.462 0.742

363

APPENDIX F: CONVERGENT VALIDITY – AVE AND CR

Composite Reliability Average Variance Extracted (AVE) Academic Reputation 0.884 0.657 City Dimension 0.832 0.623 City Effect 0.809 0.380 Cost and Finance 0.855 0.598 Cost of Living 0.833 0.557 Country Image 0.859 0.365 Cultural Proximity 0.774 0.537 Facilities on Campus 0.882 0.556 HEI Enrolment Choice 0.884 0.605 Information Quality 0.911 0.720 Information Usefulness 0.913 0.725 Institution Image 0.927 0.417 Institution Recognition 0.875 0.538 Programme Evaluation 0.922 0.382 Programme Recognition 0.906 0.617 Programme Specilization 0.905 0.613 Programme Suitability 0.861 0.610 Quality of Professor 0.922 0.663 Socioeconomic Level 0.818 0.534 Source Crdibility 0.910 0.716

364

APPENDIX F: DISCRIMINANT VALIDITY

AP CD CF CL CP FC EC IQ IU IR PR PZ PS QP SL SC Academic Recognition 0.810 City Dimension 0.422 0.789 Cost and Finance 0.240 0.208 0.773 Cost of Living 0.278 0.292 0.362 0.746 Cultural Proximity 0.356 0.329 0.253 0.210 0.734 Facilities on Campus 0.483 0.466 0.366 0.388 0.255 0.746 HEI Enrolment Choice 0.368 0.398 0.300 0.268 0.282 0.465 0.778 Information Quality 0.366 0.434 0.440 0.354 0.287 0.566 0.568 0.849 Information Usefulness 0.358 0.460 0.276 0.323 0.258 0.463 0.540 0.611 0.851 Institution Recognition 0.476 0.439 0.306 0.464 0.378 0.609 0.417 0.564 0.425 0.734 Programme Recognition 0.394 0.474 0.262 0.251 0.305 0.524 0.429 0.506 0.446 0.608 0.786 Programme Specialization 0.388 0.450 0.313 0.375 0.219 0.490 0.510 0.565 0.586 0.552 0.614 0.783 Programme Suitability 0.333 0.350 0.380 0.390 0.179 0.484 0.487 0.533 0.468 0.480 0.491 0.674 0.781 Quality of Professor 0.414 0.456 0.381 0.454 0.313 0.515 0.475 0.558 0.503 0.586 0.504 0.634 0.625 0.814 Socioeconomice Level 0.497 0.351 0.365 0.426 0.400 0.476 0.259 0.360 0.235 0.504 0.311 0.349 0.382 0.452 0.731 Source Credibility 0.328 0.333 0.290 0.284 0.263 0.429 0.570 0.629 0.586 0.502 0.474 0.532 0.460 0.488 0.293 0.846

365

APPENDIX G STRUCTURAL MODEL ANALYSIS

4) PATH COEFFICIENT WITHOUT MODERATING AND MEDIATING VARIABLES.

5) MEDIATING EFFECT OF INFORMATION USEFULNESS TESTING PARTIAL OR FULL MEDIATION.

6) MODERATING EFFECT

a. MODERATING GRAPH OF INFORMATION QUALITY i. COUNTRY IMAGE ii. CITY EFFECT iii. INSTITUTION IMAGE iv. PROGRAMME EVALUATION

b. MODERATING GRAPH OF SOURCE CREDIBILITY i. COUNTRY IMAGE ii. CITY EFFECT iii. INSTITUTION IMAGE iv. PROGRAMME EVALUATION

7) MAIN EFFECT MODEL

366

APPENDIX G: PATH COEFFICIENT WITHOUT MODERATING AND MEDIATING VARIABLES

Standard Original Sample Deviation T Statistics Sample (O) Mean (M) (STDEV) (|O/STDEV|) City Effect -> HEI Enrolment Choice 0.018 0.017 0.062 0.283 City Effect -> Information Usefulness 0.179 0.176 0.057 3.142 Country Image -> HEI Enrolment Choice 0.094 0.096 0.052 1.818 Country Image -> Information Usefulness 0.033 0.038 0.055 0.603 Information Usefulness -> HEI Enrolment Choice 0.271 0.265 0.062 4.343 Institution Image -> HEI Enrolment Choice 0.152 0.156 0.081 1.872 Institution Image -> Information Usefulness 0.137 0.138 0.075 1.821 Programme Evaluation -> HEI Enrolment Choice 0.231 0.233 0.072 3.190 Programme Evaluation -> Information Usefulness 0.382 0.386 0.072 5.330

367

APPENDIX G: MEDIATING EFFECT OF INFORMATION USEFULNESS TESTING PARTIAL OR FULL MEDIATION

Original Sample Standard Sample Mean Deviation T Statistics (O) (M) (STDEV) (|O/STDEV|) City Effect -> Information Usefulness -> HEI Enrolment Choice 0.048 0.046 0.017 2.840 Country Image -> Information Usefulness -> HEI Enrolment Choice 0.009 0.01 0.015 0.589 Institution Image -> Information Usefulness -> HEI Enrolment Choice 0.037 0.037 0.023 1.649 Programme Evaluation -> Information Usefulness -> HEI Enrolment Choice 0.103 0.103 0.032 3.198

368

APPENDIX G: MODERATING GRAPH OF INFORMATION QUALITY

4.5

3.5 Low IQ 3 High IQ 2.5

Information Usefulness Information 1.5

1 Low CE High CE

4.5

3.5 Low IQ 3 High IQ 2.5

Institution Image Institution 2

1.5

1 Low II High II

369

Low IQ 3 High IQ

1 Programme Evaluatoion Programme 0 Low PE High PE

370

APPENDIX G: MODERATING GRAPH OF SOURCE CREDIBILITY

4.5

3.5 Low SC 3 High SC 2.5

Information Usefulness Information 1.5

1 Low CI High CI

Low SC 3 High SC

1 Information Usefulness Information

0 Low CE High CE

371

Low SC 3 High SC

1 Information Usefulness Information

0 Low PE High PE

372

APPENDIX G: MAIN EFFECT MODEL

CP1 (0.819)

CP2 (0.771) 0.5

37 CP3 (0.588)

Cultural Proximity 0.189

AP1(0.789) Country Image

AP2 (0.877) 0.6 0.593 0.3 57 65 AP3 (0.851)

Academic Reputation AP4 (0.715)

0.442

SL1 (0.613) Information Quality IQ1 (0.823)

SL2 (0.772) 0.5 34 IQ2 (0.859) SL3 (0.843) 0.7

Socioeconomic Level 20 IQ3 (0.848) SL4 (0.673)

IQ4 (0.864) CD1 (0.733) 0.251 -0.014 CD2 (0.849) 0.6 23 0.560 City Effect Source Credibility SC1 (0.800) CD4 (0.781) City Dimension SC2 (0.868) 0.3 80 SC3 (0.880) CL1 (0.781) 0.7 0.680 16 SC4 (0.834) 0.154 CL1 (0.817) 0.5 57 0.259 CL1 (0.726)

Cost of Living CL1 (0.650) PrUni Enrolment EC5 (0.742)

QP1 (0.859) IU1 (0.836) EC4 (0.783)

IU2 (0.870) 0.540 QP2 (0.855) 0.7 0.60 EC3 (0.791) 25 5 QP3 (0.845) IU3 (0.867) EC2 (0.803) 0.6 63 Information Usefulness QP4 (0.812) IU4 (0.832) EC1 (0.769) Quality of Professor QP5 (0.712)

0.211 QP6 (0.793 0.462

-0.013 IR1 (0.732) Institution 0.3 Programme IR2 (0.679) Image 82 Evaluation

0.6 0.6 0.6 0.5 13 FC1 (0.754) PR1 (0.777) 17 10 98

PZ1 (0.717) FC2 (0.704) PR2 (0.820) PS1 (0.824) CF1 (0.701) PZ2 (0.734) FC3 (0.708) 0.5 PR3 (0.827) PS2 (0.748) CF2 (0.737) 56 PZ3 (0.833) FC4 (0.767) PR4 (0.740) PS3 (0.852) CF3 (0.856) Facilities on Campus PZ4 (0.807) FC5 (0.793) PR5 (0.785) PS4 (0.689 CF4 (0.790) PZ6PZ5 (0.779)(0.820) FC6 (0.744) PR6 (0.762)

373

LIST OF PUBLICATIONS

1 Vijayesvaran Arumugam, Azizah Omar, Ramayah Thurasamy (2017). A Literature Review of Electronic Word-of-Mouth on Higher Education Institutions Choice of Decision: International Student Perspectives, International Conference on Science Technology and Business Academic Research Innovation 2017 (IC-SABAI 2017), (in press).

2 Vijayesvaran Arumugam, Azizah Omar, and Abolfazl Keshavarzsaleh (2017). Critical Success Factors for Educational Exhibition Projects; Insights From Malaysia. International Review of Management and Marketing (in press).

3 Vijayesvaran Arumugam and Azizah Omar (2016). Electronic Word-of- Mouth Information Adoption by Online Consumers. International Journal of Science and Research (IJSR), 5(12), 1865 – 1869.

4 Vijayesvaran Arumugam and Azizah Omar (2016). The Role of Organization in Electronic Word of Mouth: A Concept Paper. E- Proceeding of The 2nd Global Conference on Economics and Management Sciences 2016, 28-29 November 2016.

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