Customer Relationship Management in the Banking Sector of Pakistan

By Mohammad Majid Mahmood Bagram

NATIONAL UNIVERSITY OF MODERN LANGUAGES ISLAMABAD

June 2010 Customer Relationship Management in the Banking Sector of Pakistan

Mohammad Majid Mahmood Bagram

MPA, Quaid-e-Azam University, Islamabad, 1992

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

In Management Sciences

FACULTY OF ADVANCED INTEGRATED STUDIES AND RESEARCH

(Management Sciences)

NATIONAL UNIVERSITY OF MODERN LANGUAGES, ISLAMABAD

June 2010

NATIONAL UNIVERSITY OF MODERN LANGUAGES FACULTY OF ADVANCED INTEGRATED STUDIES & RESEARCH

DISSERTATION AND DEFENSE APPROVAL FORM

The undersigned certify that they have read the following thesis, examined the defense, are satisfied with the overall exam performance, and recommend the thesis to the Faculty of Advanced Integrated Studies & Research for acceptance:

Thesis/ Dissertation Title: Customer Relationship Management in the Banking Sector of Pakistan

Submitted By: Mohammad Majid Mahmood Bagram Registration #: 141-Ph.D/MS/2003 (Jan) Name of Student

Doctor of Philosophy Degree Name in Full (e.g Master of Philosophy, Doctor of Philosophy )

Management Sciences

Name of Discipline

Prof. Dr. Anwar Hussain Siddiqui ______Name of Research Supervisor Signature of Research Supervisor

Prof. Dr. Shazra Munnawer ______

Name of Dean (FAISR) Signature of Dean (FAISR)

Prof. Dr. Aziz Ahmad Khan ______Name of Rector Signature of Rector

______Date

CANDIDATE DECLARATION FORM

I Mohammad Majid Mahmood Bagram

Son of Dr. Mushtaq Ali Bagram

Registration # 141-Ph.D/MS/2003 (Jan)

Discipline Management Sciences

Candidate of PhD in Management Sciences at the National University of

Modern Languages do hereby declare that the thesis (Title) Customer Relationship Management in the Banking Sector of Pakistan

submitted by me in partial fulfillment of PhD degree, is my original work, and has not been submitted or published earlier. I also solemnly declare that it shall not, in future, be submitted by me for obtaining any other degree from this or any other university or institution.

I also understand that if evidence of plagiarism is found in my thesis/dissertation at any stage, even after the award of a degree, the work may be cancelled and the degree revoked.

______Signature of Candidate Date Name of Candidate: Mohammad Majid Mahmood Bagram

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ABSTRACT

Thesis Title: Customer Relationship Management in the banking sector of Pakistan

Banking sector all over the world facing immense competition and Pakistani banking sector is not an exception. It is an acceptable fact that acquiring new customer is more costly than retaining the existing customer. The researcher followed the same fact and developed the basic purpose of this research study, that is to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan.

Although there are many aspects of Customer Relationship Management (CRM) in the banking sector, this research study focuses on its customer part. Understanding customers is the key to success of any bank. Banks having an in-depth understanding of their customers develop a better competitive edge over their competitors. The major focus of CRM is to not only to acquire new customers but also to retain the existing ones. This research study will help banks to build customer loyalty.

Every bank tries its best to acquire and retain their customers but due to increased competition and rapid improvements in technology, customers have quick access to thousands and thousands of products and services.

The researcher collected data from customers of banks with the help of questionnaire and for doing demographic, correlation, and regression analysis used SPSS software version 16.00. After detailed analysis and discussions, results of this research study indicate that identified factors do affect customer loyalty and their relationships with each other vary from bank to bank. These identified variations can help banks to overcome their existing weaknesses to develop better customer loyalty strategies.

The researcher identified factors of trust, perceived value, satisfaction, switching barriers, and culture that affect customer loyalty. After measuring relationships of these factors with each other, researcher responded to this research study`s questions and hypotheses and developed a customer loyalty model for the banking sector of Pakistan for the mutual benefits of customers and banks. Furthermore, this research study`s findings and recommendations contributes towards improvement in existing customer loyalty strategies of banks.

The researcher would also like to mention here that there is hardly any research study in Pakistan that has seen the affects of customer culture and customer trust on customer loyalty as the results of this research study indicate that these factors affect customer loyalty in the banking sector of Pakistan.

TABLE OF CONTENTS

CHAPTER PAGE

Title Page i Dissertation and Defense Approval Form ii Candidate Declaration Form iii Abstract iv Table of Contents v List of Appendices xiii List of Tables xiv List of Bar Charts xxiii List of Figures xxiv List of abbreviations xxv Acknowledgement xxvi

CHAPTER 1: INTRODUCTION

1.1 Significance of relationships 1 1.2 Customer 2 1.3 Banking 2 1.4 Banking sector of Pakistan 3 1.5 Customer relationships with banks 4 1.6 Customer Relationship Management 4 1.6.1 Characteristics of Customer Relationship Management 6 1.6.2 Customer loyalty as a focus of Customer Relationship Management 7

1.7 Background to the study 7 1.8 Significance of the research study 8 1.9 Statement of the problem 8 1.10 Hypotheses of the research study 9 1.11 Research questions 10 1.12 Study procedure: 10 1.12.1 Population 10 1.12.2 Sampling 11 1.12.3 Research instruments 12 1.12.4 Pilot testing of questionnaire 12 1.12.5 Data collection 13 1.12.6 Data analysis 13 1.13 Limitations of the research study 13

CHAPTER 2: REVIEW OF RELATED LITERATURE 2.1 Customers-seller bond 15 2.2 Customer loyalty as a focus of Customer Relationship Management 16 2.3 Banking sector of Pakistan 18 2.4.1 Customer Relationship Management in banking sector 21 2.4 Customer loyalty 26 2.5 Customer Relationship Management (CRM) and customer loyalty in the banking sector 28 2.6 Models relating to research study 30 2.7 Offensive and defensive strategies 34 2.8 Factors that affect customer loyalty in the banking sector 35 2.8.1 Customer trust 35 2.8.2 Customer perceived value 35 2.8.3 Customer satisfaction 36 2.8.3.1 Conceptual differences between customer satisfaction and customer perceived value 37

2.8.4 Customer switching barriers 37 2.8.5 Customer culture 38

CHAPTER 3: FRAME OF REFERENCE 3.1 Conceptualization 39 3.2 Previous research and models relevant to this research study 40 3.3 Emerged frame of reference 43

CHAPTER 4: RESEARCH METHODOLOGY 4.1 Research Process Onion 45 4.2 Research design: 46 4.2.1 Exploratory research study 46 4.2.2 Descriptive research study 46 4.2.3 Causal research study 46 4.3 Research strategy: 48 4.3.1 Selection of questionnaire survey method 48 4.4 Research study factors: 50 4.4.1 Operational definitions 50 4.5 Operationalization of research study factors: 51 4.5.1 Customer trust 51 4.5.2 Customer satisfaction 51 4.5.3 Customer perceived value 52 4.5.4 Customer switching barriers 52 4.5.5 Customer culture 52 4.5.6 Customer loyalty 53 4.6 Progression of questionnaire`s questions 53 4.7 Time horizon 54 4.8 Population 54 4.9 Sampling: 55 4.9.1 Sample size 56 4.9.2 Sample selection 56

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4.10 Instruments for data collection 58 4.11 Pretesting of questionnaire 58 4.12 Analysis of data: 61 4.12.1 Coding of questions 61 4.12.2 Data analysis techniques 61 4.13 Triangulation 62 4.14 Reliability and validity of the research constructs: 62 4.14.1 Reliability 63 4.14.2 Validity 64 4.15 Field issues during research study 64

CHAPTER 5: EMPIRICAL FINDINGS 5.1 Overview of the National Bank of Pakistan 65 5.1.1 Business profile 66 5.1.2 Responses of customers 67 5.1.3 Challenges and future opportunities 68 5.2 Overview of the Citibank, Pakistan 69 5.2.1 Business profile 69 5.2.2 Responses of customers 70 5.2.3 Challenges and future opportunities 70 5.3 Overview of the Meezan Bank Limited, Pakistan 70 5.3.1 Business profile 71 5.3.2 Responses of customers 71 5.3.3 Challenges and future opportunities 72 5.4 Overview of the Habib Bank Limited, Pakistan 73 5.4.1 Business profile 73 5.4.2 Responses of customers 74 5.4.3 Challenges and future opportunities 74

CHAPTER 6: DATA ANALYSIS AND DISCUSSIONS 6.1 Research instrument 76

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6.1.1 Customer trust 76 6.1.2 Customer perceived value 77 6.1.3 Customer satisfaction 77 6.1.4 Customer switching barriers 78 6.1.5 Customer culture 78 6.1.6 Customer loyalty 79 6.2 Demographic analysis 79 6.2.1 Demographic analysis - Citibank, Pakistan 79 6.2.2 Demographic analysis - National Bank of Pakistan (NBP), Pakistan 84 6.2.3 Demographic analysis - Meezan Bank Limited, Pakistan 89 6.2.4 Demographic analysis - Habib Bank Limited, Pakistan (HBL), Pakistan 94 6.3 Correlation analysis 99 6.3.1 Correlation analysis – Citibank, Pakistan 99 6.3.2 Correlation analysis – National Bank of Pakistan (NBP), Pakistan 105 6.3.3 Correlation analysis – Meezan Bank Limited, Pakistan 111 6.3.4 Correlation analysis – Habib Bank Limited (HBL), Pakistan 117 6.4 Multivariate Data Analysis - Citibank, Pakistan 123 6.5 Regression Model - Citibank, Pakistan 124 6.5.1 Customer Perceived Value (PV) 124 6.5.2 Customer Loyalty 126 6.5.3 Customer Satisfaction (CS) 128 6.5.4 Customer Trust 130 6.5.5 Customer Culture 132 6.5.6 Customer Switching Barriers (CSB) 134

6.6 Stage-Wise Multiple Regression - Citibank, Pakistan 136 6.6.1 Customer Perceived Value (PV) 136 6.6.2 Customer Loyalty 140 6.6.3 Customer Satisfaction (CS) 144 6.6.4 Customer Trust 148 6.6.5 Customer Culture 152 6.6.6 Customer Switching Barriers (CSB) 156 6.7 Multivariate Data Analysis - National Bank of Pakistan, Pakistan 160 6.8 Regression Model - National Bank of Pakistan (NBP), Pakistan 161 6.8.1 Customer Perceived Value (PV) 161 6.8.2 Customer Loyalty 163 6.8.3 Customer Satisfaction (CS) 165 6.8.4 Customer Trust 167 6.8.5 Customer Culture 169 6.8.6 Customer Switching Barriers (CSB) 171 6.9 Stage-Wise Multiple Regression - National Bank of Pakistan, Pakistan 173 6.9.1 Customer Perceived Value (PV) 173 6.9.2 Customer Loyalty 177 6.9.3 Customer Satisfaction (CS) 181 6.9.4 Customer Trust 185 6.9.5 Customer Culture 189 6.9.6 Customer Switching Barriers (CSB) 193 6.10 Multivariate Data Analysis – Meezan Bank Limited, Pakistan 197 6.11 Regression Model – Meezan Bank Limited, Pakistan 198 6.11.1 Customer Perceived Value (PV) 198 6.11.2 Customer Loyalty 200 6.11.3 Customer Satisfaction (CS) 202 6.11.4 Customer Trust 204 6.11.5 Customer Culture 206

6.11.6 Customer Switching Barriers (CSB) 208 6.12 Stage-Wise Multiple Regression – Meezan Bank Limited, Pakistan 210 6.12.1 Customer Perceived Value (PV) 210 6.12.2 Customer Loyalty 214 6.12.3 Customer Satisfaction (CS) 218 6.12.4 Customer Trust 222 6.12.5 Customer Culture 226 6.12.6 Customer Switching Barriers (CSB) 230 6.13 Multivariate Data Analysis – Habib Bank Limited (HBL), Pakistan 234 6.14 Regression Model – Habib Bank Limited (HBL), Pakistan 235 6.14.1 Customer Perceived Value (PV) 235 6.14.2 Customer Loyalty 237 6.14.3 Customer Satisfaction (CS) 239 6.14.4 Customer Trust 241 6.14.5 Customer Culture 243 6.14.6 Customer Switching Barriers (CSB) 245 6.15 Stage-Wise Multiple Regression – Habib Bank Limited (HBL), Pakistan 247 6.15.1 Customer Perceived Value (PV) 247 6.15.2 Customer Loyalty 251 6.15.3 Customer Satisfaction (CS) 255 6.15.4 Customer Trust 259 6.15.5 Customer Culture 263 6.15.6 Customer Switching Barriers (CSB) 267

CHAPTER 7: SUMMARY, FINDINGS, CONCLUSIONS & RECOMMENDATIONS 7.1 Summary 271 7.2 Findings of the research study 274

7.3 Conclusions 281 7.4 Recommendations 282 7.5 Implications for theory and practice 283 7.6 Future directions of research 284 BIBLIOGRAPHY 286

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LIST OF APPENDICES

Appendix-I: Questionnaire for customers of banks 299 Appendix-II: Organogram of the State Bank of Pakistan 303 Appendix-III: Banks/DFIs regulated by the State Bank of Pakistan 304 Appendix-IV: Banking sector performance in Pakistan 321 Appendix-V: Citibank – network 323 Appendix-VI: Milestones of Citibank, Pakistan 327 Appendix-VII: Customer Relationship Management, software 329 Appendix-VIII: Central Board of Directors, State Bank of Pakistan 336 Appendix-IX: Various departments of the State Bank of Pakistan 337 Appendix-X: The Quaid-i-Azam's Speech on the occasion of the opening ceremony of the State Bank of Pakistan on 1st July, 1948 339 Appendix-XI: Statutory obligations of the State Bank of Pakistan 342 Appendix-XII: Core functions of the State Bank of Pakistan 345 Appendix-XIII: Vision, Mission, & Core Values of the National Bank of Pakistan 351 Appendix-XIV: Awards & achievements - National Bank of Pakistan 352 Appendix-XV: Board of Directors, National Bank of Pakistan 355 Appendix-XVI: Director`s report, National Bank of Pakistan 358 Appendix-XVII: Citi Pakistan’s grants 367 Appendix-XVIII: Citibank - business profile 369 Appendix-XIX: Citi in Pakistan - building communities 370 Appendix-XX: Meezan Bank Limited, vision, mission, & service mission 371 Appendix-XXI: Meezan Bank Limited, branch network 372 Appendix-XXII: Habib Bank Limited, Pakistan, Board of Directors 373 Appendix-XXIII: Habib Bank Limited, Pakistan, services 374

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LIST OF TABLES

Table Page

2.1: Conceptual differences between customer satisfaction and customer perceived value 37 4.1: Distribution of questionnaire in banks 57 6.1: Measuring customer trust 76 6.2: Measuring customer perceived value 77 6.3: Measuring customer satisfaction 77 6.4: Measuring customer-switching barriers 78 6.5: Measuring customer culture 78 6.6: Measuring customer loyalty 79 6.7: Customer`s gender – Citibank 80 6.8: Customer`s marital status – Citibank 80 6.9: Customer`s income – Citibank 81 6.10: Customer`s age – Citibank 82 6.11: Customer`s education level – Citibank 83 6.12: Customer`s gender - National Bank of Pakistan 84 6.13: Customer`s marital status - National Bank of Pakistan 85 6.14: Customer`s income - National Bank of Pakistan 86 6.15: Customer`s age - National Bank of Pakistan 87 6.16: Customer`s education level - National Bank of Pakistan 88 6.17: Customer`s gender - Meezan Bank Limited 89 6.18: Customer`s marital status- Meezan Bank Limited 90 6.19: Customer`s income - Meezan Bank Limited 91 6.20: Customer`s age - Meezan Bank Limited 92 6.21: Customer`s education level - Meezan Bank Limited 93 6.22: Customer`s gender – Habib Bank Limited 94

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6.23: Customer`s marital status - Habib Bank Limited 95 6.24: Customer`s income - Habib Bank Limited 96 6.25: Customer`s age - Habib Bank Limited 97 6.26: Customer`s education level - Habib Bank Limited 98 6.27: Correlations between customer trust & customer perceived value – Citibank 100 6.28: Correlations between customer trust and customer loyalty – Citibank 101 6.29: Correlations between customer trust and customer satisfaction – Citibank 101 6.30: Correlations between customer perceived value & customer satisfaction - Citibank 102 6.31: Correlations between customer switching barriers & customer loyalty – Citibank 103 6.32: Correlations between customer culture & customer loyalty – Citibank 103 6.33: Correlations between customer satisfaction & customer loyalty – Citibank 104 6.34: Correlations between all studied variables – Citibank 105 6.35: Correlations between customer trust & customer perceived value - National Bank of Pakistan 106 6.36: Correlations between customer trust and customer loyalty - National Bank of Pakistan 106 6.37: Correlations between customer perceived value & customer satisfaction - National Bank of Pakistan 107 6.38: Correlations between customer trust and customer satisfaction - National Bank of Pakistan 108 6.39: Correlations between customer switching barriers & customer loyalty - National Bank of Pakistan 108 6.40: Correlations between customer culture & customer loyalty - National Bank of Pakistan 109 6.41: Correlations between customer satisfaction & customer loyalty - National Bank of Pakistan 110 6.42: Correlations between all studied factors - National Bank of Pakistan 111 6.43: Correlations between customer trust & customer perceived value - Meezan Bank Limited 112

6.44: Correlations between customer trust and customer loyalty - Meezan Bank Limited 112 6.45: Correlations between customer trust and customer satisfaction – Meezan Bank Limited 113 6.46: Correlations between customer perceived value & customer satisfaction - Meezan Bank Limited 114 6.47: Correlations between customer switching barriers & customer loyalty - Meezan Bank Limited 114 6.48: Correlations between customer culture & customer loyalty - Meezan Bank Limited 115 6.49: Correlations between customer satisfaction & customer loyalty - Meezan Bank Limited 116 6.50: Correlations between all studied factors - Meezan Bank Limited 117 6.51: Correlations between customer trust & customer perceived value - Habib Bank Limited 118 6.52: Correlations between customer trust and customer loyalty - Habib Bank Limited 118 6.53: Correlations between customer trust and customer satisfaction – Habib Bank Limited 119 6.54: Correlations between customer perceived value & customer satisfaction - Habib Bank Limited 120 6.55: Correlations between customer switching barriers & customer loyalty - Habib Bank Limited 120 6.56: Correlations between customer culture & customer loyalty - Habib Bank Limited 121 6.57: Correlations between customer satisfaction & customer loyalty - Habib Bank Limited 121 6.58: Correlations between all studied factors - Habib Bank Limited 122 6.59: Multivariate Data Analysis - Citibank, Pakistan 123 6.60: Regression Model - Customer Perceived Value (PV), Citibank, Pakistan 125

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6.61: Regression Model - Customer Loyalty, Citibank, Pakistan 127 6.62: Regression Model - Customer Satisfaction (CS), Citibank, Pakistan 129 6.63: Regression Model - Customer Trust, Citibank, Pakistan 131 6.64: Regression Model - Customer Culture, Citibank, Pakistan 133 6.65: Regression Model - Customer Switching Barriers (CSB), Citibank, Pakistan 135 6.66: Stage-Wise Multiple Regression Model - Customer Perceived Value (PV), Citibank, Pakistan 136 6.67: Stage-Wise Multiple Regression Model - Model Summary, Customer Perceived Value (PV), Citibank, Pakistan 137 6.68: Stage-Wise Multiple Regression Model - ANOVA, Customer Perceived Value (PV), Citibank, Pakistan 139 6.69: Stage-Wise Multiple Regression Model - Customer Loyalty, Citibank, Pakistan 140 6.70: Stage-Wise Multiple Regression Model - Model Summary, Customer Loyalty, Citibank, Pakistan 141 6.71: Stage-Wise Multiple Regression Model - ANOVA, Customer Loyalty, Citibank, Pakistan 143 6.72: Stage-Wise Multiple Regression Model - Customer Satisfaction (CS), Citibank, Pakistan 144 6.73: Stage-Wise Multiple Regression Model - Model Summary, Customer Satisfaction (CS), Citibank, Pakistan 145 6.74: Stage-Wise Multiple Regression Model - ANOVA, Customer Satisfaction (CS) , Citibank, Pakistan 147 6.75: Stage-Wise Multiple Regression Model - Customer Trust, Citibank, Pakistan 148 6.76: Stage-Wise Multiple Regression Model - Model Summary, Customer Trust , Citibank, Pakistan 149 6.77: Stage-Wise Multiple Regression Model - ANOVA, Customer Trust , Citibank, Pakistan 151 6.78: Stage-Wise Multiple Regression Model - Customer Culture, Citibank, Pakistan 152

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6.79: Stage-Wise Multiple Regression Model - Model Summary, Customer Culture, Citibank, Pakistan 153 6.80: Stage-Wise Multiple Regression Model - ANOVA, Customer Culture , Citibank, Pakistan 155 6.81: Stage-Wise Multiple Regression Model - Customer Switching Barriers (CSB), Citibank, Pakistan 156 6.82: Stage-Wise Multiple Regression Model - Model Summary, Customer Switching Barriers (CSB), Citibank, Pakistan 157 6.83: Stage-Wise Multiple Regression Model - ANOVA, Customer Switching Barriers (CSB), Citibank, Pakistan 159 6.84: Multivariate Data Analysis - NBP, Pakistan 160 6.85: Regression Model - Customer Perceived Value (PV), NBP, Pakistan 162 6.86: Regression Model - Customer Loyalty, NBP, Pakistan 164 6.87: Regression Model - Customer Satisfaction (CS), NBP, Pakistan 166 6.88: Regression Model - Customer Trust, NBP, Pakistan 168 6.89: Regression Model - Customer Culture, NBP, Pakistan 170 6.90: Regression Model - Customer Switching Barriers (CSB), NBP, Pakistan 172 6.91: Stage-Wise Multiple Regression Model - Customer Perceived Value (PV), NBP, Pakistan 173 6.92: Stage-Wise Multiple Regression Model - Model Summary, Customer Perceived Value (PV), NBP, Pakistan 174 6.93: Stage-Wise Multiple Regression Model - ANOVA, Customer Perceived Value (PV), NBP, Pakistan 176 6.94: Stage-Wise Multiple Regression Model - Customer Loyalty, NBP, Pakistan 177 6.95: Stage-Wise Multiple Regression Model - Model Summary, Customer Loyalty, NBP, Pakistan 178 6.96: Stage-Wise Multiple Regression Model - ANOVA, Customer Loyalty, NBP, Pakistan 180 6.97: Stage-Wise Multiple Regression Model - Customer Satisfaction (CS), NBP, Pakistan 181

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6.98: Stage-Wise Multiple Regression Model - Model Summary, Customer Satisfaction (CS), NBP, Pakistan 182 6.99: Stage-Wise Multiple Regression Model - ANOVA, Customer Satisfaction (CS) , NBP, Pakistan 184 6.100: Stage-Wise Multiple Regression Model - Customer Trust, NBP, Pakistan 185 6.101: Stage-Wise Multiple Regression Model - Model Summary, Customer Trust , NBP, Pakistan 186 6.102: Stage-Wise Multiple Regression Model - ANOVA, Customer Trust , NBP, Pakistan 188 6.103: Stage-Wise Multiple Regression Model - Customer Culture, NBP, Pakistan 189 6.104: Stage-Wise Multiple Regression Model - Model Summary, Customer Culture , NBP, Pakistan 190 6.105: Stage-Wise Multiple Regression Model - ANOVA, Customer Culture , NBP, Pakistan 192 6.106: Stage-Wise Multiple Regression Model - Customer Switching Barriers (CSB), NBP, Pakistan 193 6.107: Stage-Wise Multiple Regression Model - Model Summary, Customer Switching Barriers (CSB), NBP, Pakistan 194 6.108: Stage-Wise Multiple Regression Model - ANOVA, Customer Switching Barriers (CSB), NBP, Pakistan 196 6.109: Multivariate Data Analysis - Meezan, Pakistan 197 6.110: Regression Model - Customer Perceived Value (PV), Meezan, Pakistan 199 6.111: Regression Model - Customer Loyalty, Meezan, Pakistan 201 6.112: Regression Model - Customer Satisfaction (CS), Meezan, Pakistan 203 6.113: Regression Model - Customer Trust, Meezan, Pakistan 205 6.114: Regression Model - Customer Culture, Meezan, Pakistan 207 6.115: Regression Model - Customer Switching Barriers (CSB), Meezan, Pakistan 209 6.116: Stage-Wise Multiple Regression Model - Customer Perceived Value (PV), Meezan, Pakistan 210

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6.117: Stage-Wise Multiple Regression Model - Model Summary, Customer Perceived Value (PV), Meezan, Pakistan 211 6.118: Stage-Wise Multiple Regression Model - ANOVA, Customer Perceived Value (PV), Meezan, Pakistan 213 6.119: Stage-Wise Multiple Regression Model - Customer Loyalty, Meezan, Pakistan 214 6.120: Stage-Wise Multiple Regression Model - Model Summary, Customer Loyalty, Meezan, Pakistan 215 6.121: Stage-Wise Multiple Regression Model - ANOVA, Customer Loyalty, Meezan, Pakistan 217 6.122: Stage-Wise Multiple Regression Model - Customer Satisfaction (CS), Meezan, Pakistan 218 6.123: Stage-Wise Multiple Regression Model - Model Summary, Customer Satisfaction (CS), Meezan, Pakistan 219 6.124: Stage-Wise Multiple Regression Model - ANOVA, Customer Satisfaction (CS) , Meezan, Pakistan 221 6.125 Stage-Wise Multiple Regression Model - Customer Trust, Meezan, Pakistan 222 6.126: Stage-Wise Multiple Regression Model - Model Summary, Customer Trust , Meezan, Pakistan 223 6.127: Stage-Wise Multiple Regression Model - ANOVA, Customer Trust , Meezan, Pakistan 225 6.128: Stage-Wise Multiple Regression Model - Customer Culture, Meezan, Pakistan 226 6.129: Stage-Wise Multiple Regression Model - Model Summary, Customer Culture , Meezan, Pakistan 227 6.130: Stage-Wise Multiple Regression Model - ANOVA, Customer Culture , Meezan, Pakistan 229 6.131: Stage-Wise Multiple Regression Model - Customer Switching Barriers (CSB), Meezan, Pakistan 230 6.132: Stage-Wise Multiple Regression Model - Model Summary, Customer

Switching Barriers (CSB), Meezan, Pakistan 231 6.133: Stage-Wise Multiple Regression Model - ANOVA, Customer Switching Barriers (CSB), Meezan, Pakistan 233 6.134: Multivariate Data Analysis - HBL, Pakistan 234 6.135: Regression Model - Customer Perceived Value (PV), HBL, Pakistan 236 6.136: Regression Model - Customer Loyalty, HBL, Pakistan 238 6.137: Regression Model - Customer Satisfaction (CS), HBL, Pakistan 240 6.138: Regression Model - Customer Trust, HBL, Pakistan 242 6.139: Regression Model - Customer Culture, HBL, Pakistan 244 6.140: Regression Model - Customer Switching Barriers (CSB), HBL, Pakistan 246 6.141: Stage-Wise Multiple Regression Model - Customer Perceived Value (PV), HBL, Pakistan 247 6.142: Stage-Wise Multiple Regression Model - Model Summary, Customer Perceived Value (PV), HBL, Pakistan 248 6.143: Stage-Wise Multiple Regression Model - ANOVA, Customer Perceived Value (PV), HBL, Pakistan 250 6.144: Stage-Wise Multiple Regression Model - Customer Loyalty, HBL, Pakistan 251 6.145: Stage-Wise Multiple Regression Model - Model Summary, Customer Loyalty, HBL, Pakistan 252 6.146 Stage-Wise Multiple Regression Model - ANOVA, Customer Loyalty, HBL, Pakistan 254 6.147: Stage-Wise Multiple Regression Model - Customer Satisfaction (CS), HBL, Pakistan 255 6.148: Stage-Wise Multiple Regression Model - Model Summary, Customer Satisfaction (CS), HBL, Pakistan 256 6.149: Stage-Wise Multiple Regression Model - ANOVA, Customer Satisfaction (CS) , HBL, Pakistan 258 6.150: Stage-Wise Multiple Regression Model - Customer Trust, HBL, Pakistan 259 6.151: Stage-Wise Multiple Regression Model - Model Summary, Customer Trust

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, HBL, Pakistan 260 6.152: Stage-Wise Multiple Regression Model - ANOVA, Customer Trust , HBL, Pakistan 262 6.153: Stage-Wise Multiple Regression Model - Customer Culture, HBL, Pakistan 263 6.154: Stage-Wise Multiple Regression Model - Model Summary, Customer Culture , HBL, Pakistan 264 6.155: Stage-Wise Multiple Regression Model - ANOVA, Customer Culture , HBL, Pakistan 266 6.156: Stage-Wise Multiple Regression Model - Customer Switching Barriers (CSB), HBL, Pakistan 267 6.157: Stage-Wise Multiple Regression Model - Model Summary, Customer Switching Barriers (CSB), HBL, Pakistan 268 6.158: Stage-Wise Multiple Regression Model - ANOVA, Customer Switching Barriers (CSB), HBL, Pakistan 270 7.1: Correlation analysis of the data collected from customers of the studied banks 278

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LIST OF BAR CHARTS

Bar Chart Page

6.1: Customer`s gender frequencies – Citibank 80 6.2: Customer`s marital status frequencies – Citibank 81 6.3: Customer's income frequencies – Citibank 82 6.4: Customer's age frequencies – Citibank 83 6.5: Customer`s education level frequencies – Citibank 84 6.6: Customer`s gender frequencies - National Bank of Pakistan 85 6.7: Customer`s marital status frequencies – National Bank of Pakistan 86 6.8: Customer`s income frequencies – National Bank of Pakistan 87 6.9: Customer`s age frequencies – National Bank of Pakistan 88 6.10: Customer`s education level frequencies – National Bank of Pakistan 89 6.11: Customer`s gender frequencies – Meezan Bank Limited 90 6.12: Customer`s marital status frequencies – Meezan Bank Limited 91 6.13: Customer`s income frequencies – Meezan Bank Limited 92 6.14: Customer`s age frequencies – Meezan Bank Limited 93 6.15: Customer`s education level frequencies – Meezan Bank Limited 94 6.16: Customer`s gender frequencies – Habib Bank Limited 95 6.17: Customer`s marital status frequencies – Habib Bank Limited 96 6.18: Customer`s income frequencies – Habib Bank Limited 97 6.19: Customer`s age frequencies – Habib Bank Limited 98 6.20: Customer`s education level frequencies – Habib Bank Limited 99

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LIST OF FIGURES

Figure Page

2.1: Financial services customer segmentation 16 2.2: Loyalty model 31 2.3. The integrated framework for customer value and CRM performance. 32 2.4: The employee-customer-profit chain at Sears 33 2.5: The CRM value chain (Buttle, 2004) 33 2.6: Offensive and defensive strategies (Fornell, 1992) 34 3.1: Loyalty model (Beerli, Martin & Quintana, 2004) 40 3.2: The Integrated Framework for Customer Value and CRM Performance (Wang et al., 2004, p. 171) 41 3.3: The Employee-Customer-Profit Chain at Sears 41 3.4: Offensive and defensive strategies, (Fornell, 1992) 42 3.5: Customer loyalty model developed by the researcher 44 2: Research Process Onion (Saunders et al., 2003) 45 4.1: Customer loyalty model developed by the researcher 60 7.1: Customer loyalty model developed by the researcher 277

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LIST OF ABBREVIATIONS

ATM – Automated Teller Machine CC - Customer Culture CL - Customer Loyalty CRM – Customer Relationship Management CS - Customer Satisfaction CSB - Customer Switching Barriers CT - Customer Trust DFIs - Development Finance Institutions FFM - Fullerton Fund Management FIB - First Investment Bank HBL – Habib Bank Limited KSE – Karachi Stock Exchange MFBs - Microfinance Banks NBFCs - Non-Banking Finance Companies NBP – National Bank Of Pakistan PV - Perceived Value SBP – State Bank Of Pakistan SSTs - Self-Service Technologies UNB - United National Bank

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ACKNOWLEDGEMENT

The researcher has prepared this thesis with the blessings of Almighty Allah. The researcher would also like to acknowledge many personalities who guided during the entire research process. Firstly, the researcher would like to thank his supervisor Prof. Dr. Anwar Hussain Siddiqui, President, International Islamic University, Islamabad, Pakistan whose academic support and guidance made this possible.

The researcher would like to specially thank Prof. Dr. Shazra Munnawer, Dean, Faculty of Advanced Integrated Studies & Research, and Prof. Dr. Rasheed Ahmad Khan, Dean, Faculty of Management Sciences, National University of Modern Languages (NUML), Islamabad, Pakistan for their encouragement and academic guidance during this research study.

The researcher would also like to thank all customers and concerned employees of banks who gave their most valuable responses without which this research study would not be possible.

Finally, the researcher would like to thank his father Dr. Mushtaq Ali Bagram and dearest mother for their never-ending motivation.

The researcher dedicates this research study to his beloved wife and son Mohammad Aayan Ali for their immeasurable persistence during the entire period of this research study.

(Mohammad Majid Mahmood Bagram)

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CHAPTER 1

INTRODUCTION

1.1 SIGNIFICANCE OF RELATIONSHIPS

Defining relationship is a difficult work and mostly defining relationship at academic and practical level is avoided (Bagozzi, 1995). Operationally, relationship consists of a number of episodes and that buying a service twice is a minimum requirement for relationships (Liljander and Strandvik, 1995). Similarly, a relationship exists when a series of interactions between customer and organization occur (Storbacka, 1994).

Relationships plays vital role in human`s daily and professional lives, for example, choosing careers, involvement in work, etc. Generally, people make major decisions in their lives based on their relationships with organizations and persons.

Based on the above criteria, firstly it shows clearly that there is commitment on both sides that is commitment on the side of bank as well as on the side of its customers. Secondly, banks accommodate customers as best as it can. Thirdly, there is trust on both sides, that is customer and bank trust each other. Fourthly, both parties that is customers and banks respect each other, fifthly, there is affection among customers and banks, sixthly, there is effective communication between banks and customers like verbal and non-verbal communication. Seventhly, banks give priority to its customers and try to take care of the various interests on its customers with banks. Eighth, banks try to support its customers and if a customer has a strong relationship with their banks, they also support their banks like mouth reference etc. Finally, banks try to assist their customers in achieving their long-term goals.

1.2 CUSTOMER

A customer is a person who buys goods or services from a shop or business (Oxford English Dictionary, 2009). One that purchases a commodity or service is called a customer (Customer, 2009).

Customers buy and leave, so it may be easy to say that since the organization is able to sell its product or deliver its services hence it is a successful organization. Actually, it is not that easy to say as almost all the businesses depend on repeated purchases of customers hence if customers do not return then what happens? Therefore, organizations need to understand all the touch points of their customers. Mostly customers choose those banks that offer the best services though their touch points (Dyche, 2001).

The world is changing rapidly and there is a shift of power from seller to buyer, hence for the success of any organization, understanding customer has become the most important factor. It is important to know what customers think about products, services, and about organizations providing those products and services. Therefore, if customers have a good experience with any organization through its various touch points then they not only buy more but they also become that organization`s marketing volunteers. Hence, customer`s touch points with your organization are most important areas where organizations need to focus more.

As it is generally known that customers provide their personal information to only those organizations that they trust, otherwise they are not willing to provide majority of the information. In addition, most banks do not have complete information about their customers; hence, these banks lose the most important competitive advantage over their competitors. Therefore, to obtain detailed information about customers, the banking sector has begun to develop and strengthen their relationships with their customers.

1.3 BANKING

The banking sector all over the world has a key role in the economy of any country. Banking sector all over the world is changing rapidly due to many internal and external forces

(Gentle, 1993, Nellis, 1998). The most popular saying that customer is the real king is true for the banking sector as well. High competition in the banking sector has forced banks to act according to the customer`s needs and wants. These days, customers are much aware about various products and services hence banks need to respond according to customer`s preferences about products and services.

1.4 BANKING SECTOR OF PAKISTAN

In Pakistan, there are 9,115 branches of different banks; it includes 1,722 branches of public sector banks, 6,770 branches of local private banks, 534 branches of specialized banks, and 89 branches of foreign banks. The total assets of all these banks during 2008-09 was Rs. 5652.7 billions; it includes assets of Rs. 1064.0 billions of public sector banks, Rs. 4229.2 billions of local private banks, Rs. 127.6 billions of specialized banks, and Rs. 231.7 billions of foreign banks in Pakistan (Ministry of Finance, 2008-09). Financial performance indicators of the banking sector in Pakistan are capital adequacy, asset quality, earnings, and liquidity as briefly shown in Appendix- IV (State Bank of Pakistan, 2009).

At present, banks in Pakistan are facing high competition and they are trying to retain and increase their customers in order to survive in the market. Banks/ development finance institutions in Pakistan comprises of the following seven categories regulated by the State Bank of Pakistan as shown in Appendix-III (State Bank of Pakistan, 2009):

1) Public sector banks 2) Specialized banks 3) Private banks 4) Islamic banks 5) Foreign banks 6) Micro finance banks / institutions 7) Development finance institutions

1.5 CUSTOMER RELATIONSHIPS WITH BANKS

There are facts to recommend that customers give importance to relationships with their banks. Barnes (1997) explored the relationships of customers with their banks by doing research at 400 banks and their customers. Bank`s customers give importance to their relationships with their banks (Colgate, 1996).

The performance of banks depends on the level of their understanding of their customers. Banks that have detailed information about their customers are in a better position than those banks lacking information about their customers. Customer Relationship Management (CRM) helps to integrate various activities of banks for improved efficiency and effectiveness.

The above researchers prove that bank customers not only want close relationships with their banks, they also value this relationship. In Pakistan, there are more trends of savings in banks so it is really of most importance for banks to develop and build relationships with their customers as bank`s success depend on long-term relations with their customers.

1.6 CUSTOMER RELATIONSHIP MANAGEMENT (CRM)

Organizations have various sources of information like internal sources of information and external sources of information (Galbreath & Rogers, 1999). All the information collected from internal sources information and external sources of information is processed by Customer Relationship Management (CRM) application. This collected information from all possible sources is used for developing and improving products and services better than competitors and as per needs and wants of customers. Customer Relationship Management (CRM) has no proper definition yet that can describe it completely as still work on Customer Relationship Management (CRM) is going on in the world (Zineldin, 2000).

In business world, Customer Relationship Management (CRM) is not new. In various businesses all over the world, many models remained in use for decades. Traditional models focused more on selling efforts but current Customer Relationship Management (CRM) focuses on

4 the real objective of the businesses that is “customer loyalty”. Now Customer Relationship Management (CRM) focuses on customer loyalty through identification of target customers, getting new customers and retaining the existing customers through developing strong relationships with them. These relationships development with customers give organizations a competitive edge that help them satisfy their customers and make profits.

The basic difference between the traditional and current Customer Relationship Management (CRM) models is that the traditional models mostly work independent of one another whereas current models are integrated models. New CRM models integrate all business activities at one platform whereas traditional models were unable to do this effectively. In traditional models, information gained from customers about selling could not be shared with other departments in the organization effectively.

Technology advancements have made it possible through Customer Relationship Management (CRM) that now different departments can share and use each others information collectively for making efficient and effective strategies for their customers (Given, 2006). These new technologies have made it possible for organizations to collect customer`s data from all company`s customer touch points, and use this information at all levels for improved performance in all areas. Therefore, traditional Customer Relationship Management (CRM) has been changed with most efficient and effective modern Customer Relationship Management (CRM) strategy.

“The activities a business performs to identify, qualify, acquire, develop and retain increasingly loyal and profitable customers by delivering the right product or service, to the right customer, through the right channel, at the right time and the right cost is called CRM (Galbreath & Rogers 1999, p162)”.

Therefore, for unbeaten Customer Relationship Management (CRM), organizations should include all of their functions in CRM application (Hamel & Prahalad, 1994).

Hence, in simple words, CRM used by different organizations to seek, obtain, and retain customers. Therefore, CRM helps organizations to manage their relations with customers in a better

5 way. A winning Customer Relationship Management (CRM) system focuses on customer loyalty as a focus of Customer Relationship Management (CRM). Customer Relationship Management (CRM) helps organizations to integrate their entire functions in a better way and the result is customer loyalty.

Most competitive organizations use Customer Relationship Management (CRM) software (Appendix-VII) (2020software.com, 2009). CRM software helps organizations to retain their customers better than their competitors do by providing most customized product and service offerings.

Customer Relationship Management helps organizations to know their customers well in order to satisfy their needs (Patton, 2005). At present, customers are well informed about various products and services than ever, by clicking computer mouse can give them thousands and thousands of choices. This rapid development of technology has increased competition in every field of life.

Customer Relationship Management is needed when organizations do not have in-depth understanding of their customers like what are their present and future needs (Patton, 2005). Therefore, organizations should focus more on understanding their customers better than their competitors and that is possible through Customer Relationship Management (CRM) system.

1.6.1 Characteristics of CRM

The major characteristic of Customer Relationship Management (CRM) is customer therefore, the prime focus of organizations should be their customers, some customers give more profit to organizations and some give less profit, and customers have changing needs and wants (Wong, et al, 2003).

Therefore, if organizations are more aware about their customers then they can make better strategies resulting in improved and new products and services.

1.6.2 Customer loyalty as a focus of Customer Relationship Management

Success of banks depends largely on building customer loyalty (Khirallah, 2001). Consequently, banks should emphasize on building customer loyalty, which is a focus of Customer Relationship Management (CRM) because it creates a superior competitive advantage.

Knowing customers better and then developing relations with them is important for every organization these days. The major focus of Customer Relationship Management (CRM) in any organization is to build loyal customers. There are certain factors that affect customer loyalty hence in order to build customer loyalty, understanding the relationships between those factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM), is of most significance.

To build customer loyalty, banks need to improve their relations with their customers. Since, products and services offered by banks cover the long-term needs of their customers so this relationship becomes more important. Banks need to focus on offering customized products and services better than their competitors in order retain their customers.

1.7 BACKGROUND TO THE STUDY

Up to 80% of organizations lack understanding about how Customer Relationship Management (CRM) helps them to make their customers loyal (Kirkby, 2002). Due to this, most of the organizations are unsuccessful to build customer loyalty. Therefore, this high rate of failure has forced experts and researchers to find out the factors that build and influence customer loyalty as banks depend on lasting relations with customers. Furthermore, inadequate understanding among the management and employees about customer loyalty, which is a focus of Customer Relationship Management (CRM), become reasons for failure (Caulfield, 2001).

Even organizations having enormous data warehouses also lack in-depth understanding about their customer`s loyalty factors (Davenport et al. 2001). Hence, these organizations do not get the maximum benefit of this data for better mutual benefits of their customers and for themselves.

1.8 SIGNIFICANCE OF THE RESEARCH STUDY

Building and strengthening relations with customers is vital in banks (Zineldin,1995). If banks build up and maintain firm relationships with their customers, it is hard for their competitors to beat them (Gilbert,2003).

The most significant area for banks these days is to make their customers loyal. Banks depend on lifelong relationships with their customers as the customer grows, generally profits also grow so customer loyalty ultimately increases bank`s profits.

Bank`s basic purpose is to make profit and to remain successful, making customers loyal become vital for these banks as loyal customers contribute more towards profits of the banks. Loyal customers also recommend their bank to their family and friends and through this mouth referencing, bank is able to acquire and retain more customers. Increase in customer retention increases more profits (Reichheld, 1992, 1996), and Storbacka, 1994). Customer loyalty is more important than increasing number of customers in a bank (Colgate, 1999).

A critical review of banking sector indicates that customer loyalty has been neglected in the banking sector especially in public sector banks in Pakistan. The researcher developed his interest and found that a research study would be of much significance to be undertaken within the capacity limits of the researcher to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan. Findings of this research study will be of great use for banking sector. The results of this research study will also be helpful in improving CRM application in banks. This research study will also be helpful for banks to make their customers loyal to overcome high competition in the banking sector of Pakistan.

1.9 STATEMENT OF THE PROBLEM

To overcome high competition in the banking sector, banks need to strengthen relations with their customers to make their customers loyal (Bose, 2002). Banks should focus constantly on

8 building relationship with their customers, because it is the only competitive advantage remaining to them (Xu, 2002).

As world has become a global village, it results in tough competition between organizations and formed a climate of continuous change, gaining and retaining customers has become vital for the success of any organization and Pakistan is no exception. Customers now have more awareness and choice of various products and services due to newer channels of communication like Internet etc than ever before. So due to increased customer awareness, customers are more demanding, and those banks having strong relationships with their customers have strong competitive edge over other banks. Therefore, customer loyalty, which is a major focus of Customer Relationship Management (CRM), gives these banks a competitive advantage over other banks.

It is also a fact that acquiring a new customer costs more than to retain the existing customer. Therefore, in order to overcome high competition in banks, building customer loyalty is a challenging area faced by banks these days. The researcher will try to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan for mutual benefits of customers and banks.

1.10 HYPOTHESES OF THE RESEARCH STUDY

The researcher has developed following hypotheses based on the purpose of this research:

H1: there is significant influence of customer trust on customer perceived value. H2: there is significant influence of customer trust on customer satisfaction. H3: there is significant influence of customer trust on customer loyalty. H4: there is significant influence of customer perceived value on customer satisfaction. H5: there is significant influence of customer satisfaction on customer loyalty. H6: there is significant influence of customer switching barriers on customer loyalty. H7: there is significant influence of customer culture on customer loyalty.

1.11 RESEARCH QUESTIONS

This research study`s basic aim is to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan. Following research questions will help the researcher to achieve this research study`s purpose:

1) What are the factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) in the banking sector of Pakistan? 2) What is the relationship between the factors that affect customer loyalty in the banking sector of Pakistan? 3) How to build a customer loyalty model for the banking sector of Pakistan?

1.12 STUDY PROCEDURE

1.12.1 Population

A population consists of all elements-individuals, items, or objects-whose characteristics are being studied. The population that is being studied is also called the target population (Mann, 1995).

The population of this research study consists of customers of banks in Pakistan. Banks/ development finance institutions in Pakistan comprises of seven categories, which are regulated by the State Bank of Pakistan (Appendix-III) (State Bank of Pakistan, 2009). In the first category, government owns public sector banks and they do the commercial tasks, which are described in the Pakistani banking rules. The second category, specialized banks that are the same as the first group but their activities are more focused on some special tasks, like agriculture, industries, house and buildings, etc. Third category banks are called private banks owned by a person or a group of persons. Fourth category, Islamic banks, fifth category, foreign banks and finally sixth & seventh categories, micro finance institutions and Development Finance Institutions respectively perform

10 some limited tasks and activities. State Bank of Pakistan regulates all these banks / development finance institutions.

The researcher has chosen customers of the following banking categories as population of this research study that offer their services to public at large, and have a large market-share:

1) Public banks, 2) Private banks, 3) Islamic banks, and 4) Foreign banks.

1.12.2 Sampling

Following sampling criteria is adopted for the selection of banks from the research study`s population:

Banks with highest business achievements Banks having diversified target customers, and different groups Banks having branches in major areas in Pakistan Banks having national and/or international representation Researcher`s time, money, and other resource constraints

Based on the above sampling criteria, following banks are selected for this research study:

1) National Bank of Pakistan (NBP) serving as a public bank. 2) Habib Bank Limited (HBL), Pakistan serving as a private bank. 3) Meezan Bank Limited, Pakistan serving as an Islamic bank. 4) Citibank serving as a foreign bank in Pakistan.

1.12.3 Research instrument

Questions given in questionnaire for bank`s customers as an instrument for data collection are adopted from the existing literature relating to the basic purpose of this research study. The researcher has made minor changes in this adopted questionnaire after three phase pilot testing.

To measure customer trust, the researcher uses the measure of Hess (1995), Jarvenpaa & Tractinsky (1999), Gurviez & Korchia (2002), Gefen et al. (2003), and Chiou & Droge (2006). The researcher uses the measures of Wang et al. (2001) and Llosa (1996) to measure customer satisfaction. The researcher uses the measures of Lassar et al. (1995) scale to measure customer perceived value. The researcher uses the measures of Kim, et. al., (2003) to measure customer switching barriers. The researcher uses the measure of Hofstede (1980; 1994) scale to measure customer culture. Lastly, the researcher uses the measures of Boulaire and Mathiew (2000), Srinivasan et al. (2002) and Huang (2008) to measure customer loyalty.

1.12.4 Pilot testing of questionnaire

The purpose of the pilot testing of the questionnaire is to refine questionnaire for more accurate responses (Saunders et al., 2000). Based on this purpose of pilot testing of questionnaire, the researcher did three-stage pilot testing of questionnaire from the customers of banks.

With the help of pilot testing of questionnaire, respondents are comfortable in responding to questions asked in the questionnaire. For a single researcher with lack of resources, it is not possible to take response from entire population hence a sample size is selected according to sampling criteria.

Pilot testing of questionnaire is of high importance for any researcher. A minimum respondents should be 30 in any pilot testing of questionnaire. The researcher did three-stage pilot testing of questionnaire. During the first stage of the pilot testing of questionnaire, the researcher got responses from randomly selected regular customers and experienced employees of selected banks.

The researcher received various comments/suggestions regarding this research study`s questionnaire. The researcher did minor changes in the questionnaire as per comments/suggestions. During the secong stage of the pilot testing of the questionnaire, the researcher distributed again 30 questionnaires to randomly sleeted customers of four banks. The researcher again received comments/suggestions from respondents and revised questionnaire.

During the final third stage of questionnaire pilot testing, the researcher gave 30 questionnaires to customers of banks; and finally got positive response. It is to mention here that respondents of pilot testing of this questionnaire were excluded for having unbiased responses.

1.12.5 Data collection

Data collection was a difficult process as respondents raised many questions like privacy and usage of their responses. The researcher persuaded and ensured respondents about the privacy and appropriate usage of the information provided by these respondents. The researcher visited all the selected banks personally in order to ensure the quality of work.

1.12.6 Data analysis

For data analysis, the researcher will use SPSS software for doing demographic analysis, correlation analysis, and regression analysis. For easier understanding, the researcher will use tables, figures, and bar charts followed by discussions on each analysis.

1.13 LIMITATIONS OF THE RESEARCH STUDY

This study is confined to the basic purpose of this research study, that is, to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan. Based on sampling criteria, researcher will examine four categories of banks in Pakistan namely National Bank of Pakistan (NBP) serving as a public bank, Habib Bank Limited (HBL), Pakistan serving as a private bank, Meezan Bank Limited, Pakistan serving as an Islamic bank, and Citibank serving as a foreign

13 bank in Pakistan. The researcher distributed questionnaires to customers of banks for on the spot filling and return. This may not have given enough time to customers to think more about their answers. Only willing customers were given questionnaires. This research study is limited to Islamabad & Rawalpindi areas because of researcher`s time, costs and other resource constraints. Finally, this research study will look at the bank`s customers views.

The researcher will do his best that these identified limitations will have no impact on this research study`s results.

CHAPTER 2

REVIEW OF RELATED LITERATURE

2.1 CUSTOMERS-SELLER BOND

A research about customers-seller bond gave the following three levels of customer-seller bond (Berry and Parasuraman, 1991):

1) Financial bond : In this financial bond between customer and seller, they have a strongly connected via price factor; 2) Social bond: In the social bond between customer and seller, they are strongly connected via social relations like attachments, friendships; and 3) Structural bond: In this structural bond between customer and seller, they have a strongly connected via partnership.

Furthermore, the connection between a bank and a customer can be of following three types (Berry and Parasuraman, 1991):

1) Using of bank`s ATM machines or using other technologies to interact with bank`s customers. 2) Customer-bank connection via bank`s representatives, for instance front desk bank`s officers interaction with bank`s customers, bank`s customer services representatives interaction with bank`s customers, and 3) Both 1 & 2 above.

2.2 CUSTOMER LOYALTY AS A FOCUS OF CUSTOMER RELATIONSHIP MANAGEMENT

It is generally known that customers who are loyal to any organization’s products and services become the major profit giver to that organization. Customers become loyal when they are satisfied and they believe that they are getting the best value from that product or service. Customer loyalty as a focus of Customer Relationship Management (CRM) helps banks to compete better in the highly competitive banking sector.

Organizations are trying their best to have closest relations with their customers by focusing more on satisfying their needs and wants better than their competitors (El Sawy and Bowles, 1997).

Organizations need to focus more on the existing customers and to strengthen relations with existing customers rather than focusing on the entire market (Peppers and Rogers, 1995). Similarly, organizations should focus on customer loyalty, as loyal customer is less costly than obtaining a new customer (Reichheld and Sasser, 1990).

Banks generally do segmentation of their customers based on age, income level, education etc but these factors are not very strong to identify the needs of customers. Organizations (Figure 2.1) try to group their customers according to similarities and customers having similar characteristics are placed one group and so on (Machauer, A. and Morgner, S., 2001). The basic purpose of is to achieve improved customer loyalty and less cost.

Figure 2.1: Financial services customer segmentation (Machauer, A. and Morgner, S., 2001)

A model of “Customer-Centric philosophy in Customer Relationship Management (CRM) evaluation”, presents a customer-focused viewpoint that focuses on customer loyalty as a focus of Customer Relationship Management (Kim, 2003).

In the present age of globalization, almost all the businesses depend on the regular customers and not on the occasional customers therefore, in order to remain and compete in the present highly competitive environment, customer loyalty is vital. Mostly businesses are of the view that people know about me so they will come to me in any case but it is not true as your competitors are also there in the market so they can reach customers before you do.

For example, car manufacturer`s showrooms in Pakistan may send reminders to their existing customers about new features about new or existing products and services as well about their car tuning dates. Therefore, these reminders not only make their customers much delighted but also strengthen their relations with them.

If any occasional customer turns into a loyal customer then of course organization`s profit will increase much. These loyal customers not only buy more but also at the same do your marketing as a volunteer by mouth reference. In a country like Pakistan, personal references about any product or service are considered of higher importance than any other effort.

Customer frequency depends on the type of product or service. For instance, daily or on alternate days, going to buy bread is a good frequency and buying shoes after 6 to 8 months is considered a good frequency.

Loyal customers open great opportunities for organizations as loyal customers buy more, buy other products and services offered by the same seller, and also become organization`s volunteer marketer by recommending organization`s products and services to their friends and relatives. Furthermore, organizations may go for joint ventures that result in effective customer loyalty.

Everyone is not buying all the time, so organizations should keep in contact with their customers so whenever customers are willing to buy, there are better chances that your organization’s products and services will be their first preference.

At present, almost all the persons are busy and new improved products and services are easily available in the market or via internet or telephone etc, so if an organization is already in contact with their customers then their chances are better than their competitors who are not in contact with their customers.

2.3 BANKING SECTOR OF PAKISTAN

Banks all over the world have the most significant impact on the economic development of any country. For instance, banks provide financial resources to various industries and sectors for their development. Banks also provide employment and tries to reduce poverty. In other words, banking sector has a control on providing financial resources to almost all sectors of an economy.

World is a global village and almost every organization is facing high competition and banking sector is no exception. Therefore, banks are trying their best to compete and perform better than their competitors. Hence, banks are focusing on new methods of interactions with their customers.

It is easily observed that banking sector is changing rapidly due to the advancement of new channels of communication, internet, online accounts, and so on. Due to technological advancements, competition among banks has increased a lot.

The financial sector in Pakistan comprises of Commercial Banks, Development Finance Institutions (DFIs), Microfinance Banks (MFBs), Non-banking Finance Companies (NBFCs) (leasing companies, Investment Banks, Discount Houses, Housing Finance Companies, Venture Capital Companies, Mutual Funds), Modarabas, Stock Exchange and Insurance Companies (State Bank of Pakistan, 2008). The Central Board of Directors of the State Bank of Pakistan (SBP) comprises of seven members, one corporate secretary, and board’s Chairman is the Governor. The

Organogram and details of Central Board of Directors of the State Bank of Pakistan (SBP) is at Appendix-II and Appendix-VIII respectively. It is functioning in areas of agriculture, onsite inspections, policy and regulations, Surveillance, and so on; its complete detail is shown in Appendix-IX.

The Quaid-i-Azam Muhammad Ali Jinnah in his address to the SBP on 1 st July, 1948, emphasized its major role and responsibilities in socio-economic development of Islamic Republic of Pakistan, details at Appendix-X.

The major statutory obligations of the State Bank of Pakistan (SBP) are statutory cash reserve, statutory liquidity requirement, maintenance of liquidity against certain liabilities, submission of annual audited accounts, annual accounts, minimum capital requirements, and submission of returns as shown in Appendix-XI.

The State Bank of Pakistan (SBP) monitors and supervises banks, Development Finance Institutions (DFIs), and Microfinance Banks (MFBs) whereas all other financial institutions supervised by Securities and Exchange Commission and Controller of Insurance.

At present, there are 41 scheduled banks, 6 Development Finance Institutions (DFIs), and 2 Microfinance Banks (MFBs) operating in Pakistan whose activities are regulated and supervised by the State Bank of Pakistan. The commercial banks comprise of 3 nationalized banks, 3 privatized banks, 15 private sector banks, 14 foreign banks, 2 provincial scheduled banks, and 4 specialized banks (State Bank of Pakistan, 2008).

The banking industry’s assets have risen to over $60 billion, and almost 81% of banking assets are in the private hands (Akhtar, 2007). Now banks are trying to make all of their accounts profitable. Core Functions of the State Bank of Pakistan are regulation of liquidity, regulation and supervision, exchange rate management and balance of payments, and developmental role of state bank as described in detail at Appendix-XII.

Banking sector in Pakistan in an effort to reduce cost of services is now moving towards adopting most advanced technologies. Now customers of banks can operate their accounts online but there are issues like online frauds etc so banks need to have most secure online systems. Many of the new technologies may give immediate benefits to banks but in the long run, the only competitive advantage banks can have is their strong relations with their customers.

There is less human interaction of banks with their customers due to new technologies (Puccinelli, 1999). Customers needs and wants change rapidly and this forces banks to act accordingly. Those banks that are taking care of their customers better than their competitors are ahead in competition.

On the other side, technology has a vital impact on service delivery; customers get immediate information and response from banks.

It is generally seen that new technology is replacing employees like Automated Teller Machines (ATMs) have replaced cashiers, and so on. Technology is replacing human interactions because banks are trying to provide services as quickly as possible to remain ahead of their competitors.

Banks are trying to strengthen their relations with their customers (Durkin, M., 2004). Banks are using different technologies like emails to respond to their customers. Customers are provided immediate response of their queries through these emails managed by artificial intelligence system. In case of any unsolved or unique issue, these artificial intelligence systems direct the said emails of customers to bank concerned employees for their individual attention.

The impact of new technology is immense on the financial sector (Sherif, 2002). Banks were dependent on manual work and branch operations for the last many decades but since 1980, new technology has changed working of banks and as a result, computers are replacing humans in most of the banking operations.

Globalization has brought creativity and innovation in doing business as well as new challenges to the banks. In order to remain competitive or in some cases, in order to survive in the market, banks need to react rapidly to these global challenges.

As we know that customer is the real king or the real boss, is very true for the banking sector as well. It is the customer who decides what you offer and how you offer, not the bank therefore, its vital to develop a comprehensive data base of customers in order to not only know customer`s changing needs and wants but also banks can use this customer`s data base to predict their future needs and wants.

Government rules and regulations have also increased customer rights so it is also important to fulfil their rights better than competitors. As we also observe that internet has also changed the behaviour of customers, their lifestyles, and most importantly their awareness regarding banking services.

2.3.1 Customer Relationship Management in the banking sector

These days, banks are focusing on Self-Service Technologies (SSTs). In SSTs, customers can use bank services when and where they want without time or place barriers, without any personal contact with the banks (Durkin, & Howcroft (2003).

Organizations are focusing on strengthening their relations with their customers (Palmer, 2001; Robertson & Kellow, 2001). Organizations focusing on customer loyalty which is a major competitive advantage (Galbreath & Rogers, 1999; Valentine, 1999).

Developing and strengthening relations with customers is not only a software or technical issue, it is the communication of all business activities with customers in the most efficient and effective manner.

Customer correct need identification helps CRM work effectively. Following are the major needs of customers of banks in Pakistan:

a) customers need to get better bank services at low cost; b) customers having more than one bank accounts should have convenience in managing their accounts.; c) banks should offer the best products and services to satisfy and retain customers.

Companies should focus on the integration of people, processes and technology to gain long-term competitive edge over competitors and in order to earn profit (Bygstad, 2002 cited Ciborra and Failla, 2000). At present, Customer Relationship Management (CRM) is under energetic thoughts of organizations all over the world (Fox, 2001). Customer focus is the basic concept behind Customer Relationship Management (CRM).

All over the world, there are quick changes due to changes in the business environment. Due to globalization, there is a tight completion in the business world. Therefore, in order to remain and beat competitors, companies need to keep on improving their strategies.

Banks in Pakistan are already using various CRM activities like communicational and operational CRM. For example, checking account balances, checking bank account records, getting check books, transferring funds, payment to others, paying utility bills, and paying bank credit card bills. In banks in Pakistan, following are the major channels of communication with the customers:

1) Bank branches: there is a face-to-face communication between customers and banks in various bank branches. 2) Automated Teller Machine (ATM): customers of banks can draw cash from these machines round the clock. 3) Internet banking: customers can access their accounts and do transactions while sitting in their offices, homes, or from anywhere with the help of computers. 4) Mobile banking: customers can access their accounts and do transactions from anywhere with the help of their mobiles. 5) Technological help: in case of any problem, customers of banks can get support and help from technological help centers via telephone or in person.

6) Marketing channels: various marketing channels like print and electronic media are used by banks these days to reach and satisfy their customers better than their competitors. 7) Follow-up: after sales services to customers through customer follow-ups.

These contact points provide required information immediately that results in more customer satisfaction. Customers spend less time to get more information, as these days, almost everyone is busy doing something so when a bank saves precious time of its customers, it makes its customers more loyal (Lindgreen, 2005).

Almost all businesses are going through quick changes that demands long-term competitive strategies in the world. Due to increased technology, customers are well informed about products and services and it is easy to access information within seconds about any product or service. Hence, banks are moving towards customer-centric strategies. As customer is the real source of information, so the methods of working have changed. Therefore, banks do what their customers need and want.

E-banking is categorized into following 4 categories (Jayawardhena, 2000):

1) Account balances or credit transfers viewing, 2) Account control functions, 3) New services, and 4) Reconciliation functions.

1- Account balances or credit transfers viewing:

Mostly customers need to view their account balances or credit transfers. This view-only function allows customers to view their account information at any time. Before this function, bank employee’s maximum time spent on providing this account balance information to their customers but now due to this function, workload on bank employees have decreased a lot and on the other side, customers also get the required information immediately at their own convenience.

2- Account control functions:

Few controls of customers like payment of utility bills, account transfers between different bank accounts or transferring amount to other`s bank accounts are some of the functions of this account control function.

3- New services:

Any new customer is allowed to fill new bank account opening forms in this function. However, due to some legal requirements, new customers have to visit banks for signatures and providing attested hardcopies of required documents.

4- Reconciliation functions:

Now banks offer downloading and other relevant services to their customers through this function. Customers can download their account related information from the bank website to their personal documents.

Customer Relationship Management applications generally include (Reynols, 2002):

Call Center Automation, Campaign Management, Contact Management, Data Warehousing, Email Management, Field Service Automation, Knowledge Management, Marketing Automation, Personalization, and Sales Force Automation.

At present, banks are using the best available technology resulting in the best use of each customer contact more effectively than ever. As described by many researchers, an effective CRM application helps organizations to manage their customers in better manner by focusing on customers that are more profitable that result in improved profitability.

Banks use Customer Relationship Management (CRM) techniques to obtain following results (Foss, 2002):

1) To develop customer-centric environment in banks; 2) To develop and strengthen relations with their customers; 3) To deliver best products and services to customers; and 4) To identify the cost-effective customers in banks.

Firstly, almost all the major organizations including banks are focusing on customers as it is the customer who can really strengthen your bank. Hence, as Foss has mentioned above that having a more customer focused culture can enable the banks to achieve their objectives better than their competitors can. Secondly, as earlier discussed, relationships play a vital role in human lives so it is almost impossible for banks to ignore this most important factor of their customers. Thirdly, by delivering and providing the best services to customers can help banks achieve their financial goals, and finally Customer Relationship Management (CRM) helps to indentify and focus on the most profitable customers.

Increasing competition and decreasing margins have made it mandatory for banks to adopt Customer Relationship Management (CRM) strategies and technologies with the purpose of satisfying ever-increasing needs of their shareholders and customers. More recently, banks have begun to realize its fundamental value as it facilitates banks:

To focus on those customers that give the maximum profit To focus on those customers who have a higher frequency To focus on the what and how much buying of customers To know better their customers

To know their needs, wants, desires To know their family size, likes, dislikes, background etc, and To develop proactive strategies regarding their customers, products, and services

If banks have a comprehensive awareness of their customers then this definitely can bring a better change as earlier described in Customer Relationship Management (CRM). Understanding customer is not an easy task for banks as now competition among banks is on building their customers loyal. Customer Relationship Management (CRM) helps banks to target and reward most profitable customers.

2.4 CUSTOMER LOYALTY

Today in almost every field, there is high competition and all organizations are trying to do their best in the market if they want to remain and grow in the market. If organizations need to develop, strong long-term competitive edges then they have to make their customers loyal. Making customers loyal is not easy for the organizations because of high awareness of today`s customers. Print & electronic media and other sources of information has increased customer`s knowledge and awareness about most advanced most attractive products and services offering a benchmark quality in the markets. New and improved products and services enter market rapidly so its becoming really hard for organizations to compete on the basis of most rapid changes therefore the only competitive long-term edge they may have is to build their customer`s loyalty. Customer`s loyalty means that customers have a commitment to repurchase product/service even other organizations are offering better products/services and doing a lot of marketing but your customers remain with you (Oliver, 1999). Customers loyalty is the positive attitude of customers toward repurchase (Lin and Wang, 2006).

During the past many decades, organizations got customers because of lack of competition or no competition at all. Generally customers have no choices or options or substitutes and the markets were growing rapidly and mostly organizations didn’t worry about the customer`s

26 satisfaction. Organizations thought that there will be high demand of their products and services and if they are unable to retain 200 customers, they get 2000 more customers quickly and this goes on for many years. Organizations believed that there are always new customers to replace the defecting ones (Kotler p. 405).

Customer loyalty has become the most important aspect of organizations because getting a new customer costs much higher than retaining an existing customer so organizations should focus more on customer loyalty in order to be profitable (Ro King, 2005).

In most of the organizations, like banks, losing only few most profitable customers may result in big loss as compare to losing many average customers. Therefore, customer loyalty results in profit as well as collection of further data about customers. This large customer data helps organizations like banks to communicate better with its customers, developing better strategies about their products and services, more customer satisfaction, prediction of customer wants resulting in more purchases by the customers.

The basic objective of any business is to create a customer (Peter Drucker, 1973). Five percent enhancement of loyalty enhances twenty five percent to ninety five percent worth (Dawkins and Reichheld, 1990). This most surprising finding brought a rapid change in the market regarding significance of customer loyalty. Therefore, organizations realized the vital importance of customer loyalty and almost all the major organizations developed various customer loyalty strategies according to their own business environments. Customer loyalty is the most important objective of especially those organizations that are involved in Customer Relationship Management and it can be most beneficial for companies in this highly competitive world (Grönroos, 1991; and Coviello et al. , 2002). They further reported that loyal customers of any company might pay even higher prices of offered products and services as compare to new customers who are not willing to pay higher price. Therefore, the result is increased profits. This was a major finding in the area of customer loyalty in the world. Organizations then started focusing more on customer loyalty in order to improve their profits by developing long-term relations with their customers.

Another most significant finding is that retaining a customer is 10 times less costly than getting a new customer, whereas to bring new customer on the same profit level is sixteen times more costly (Lindgreen, 2000).

Customer’s complaints are like a treasure to any organization. When any customer complains, the concerned organization gets the most important information about its weak areas without spending millions and millions of rupees on identification of their weak areas. Therefore, organizations through improved customer problem handling system have a better chance to fix that problem by working on the root causes of that identified problem. After identification of the root causes, organizations try to solve customer’s problems to make them loyal.

Customer`s increase in loyalty means that customers wants to stay with the current provider of products and services. Customer`s loyalty mostly depend on his/her values and successful organizations act accordingly. Therefore, organizations offering the most valued products and services to their customers have more loyal customers than their competitors.

If any organizations need to have, loyal customers then they should take measures to involve customers with them. Involvement results in increased loyalty (Zeithaml et al., 1988). When the customer-seller service is of long-term then these relationships become the most important for the organization (Zeithaml, 1981). These effective relationships between the customer and the service provider can result in customer retention. Furthermore, customer`s level of participation with the service provider can decide their level of customer-provider relationships (Farquahar, 2004; Ennew & Martin R. Binks, 1996).

2.5 CUSTOMER RELATIONSHIP MANAGEMENT AND CUSTOMER LOYALTY IN THE BANKING SECTOR

The major focus of Customer Relationship Management (CRM) in any organization is to build relations with customers (Rigby, Reichheld & Dawson, 2003). The basic purpose is to understand customers and factors that affect customer loyalty. Loyal customers for any company can always give a better competitive advantage than any other factor. Chances of customer accounts

28 also grow with the age of customers so if those customers growing customers remain with their banks then it gives a strong long-term competitive edge to their banks.

As the Customer Relationship Management (CRM) helps banks to make their customers loyal, and customer loyalty depends on certain factors that affect customer loyalty. Understanding and knowing those factors and their relationships with each other can help banks to develop better customer-centric strategies, which is a focus of Customer Relationship Management (CRM).

During last few decades, major changes occurred in the banking sector like privatization, and same is true for Pakistan. Many public banks have been privatized that results in high market competition.

Banks use new technology to provide quick services to their customers but on the other side, this technology results in decreased relations between the banks and their customers. Those banks that did not change or improve their products and services have lost their major market share. Hence, banks that are not considering this fast changing environment to maintain strong position are likely to lose their customers.

Banks have started realizing that no bank is excellent for all so banks are trying to explore innovative competitive advantage to compete and beat their competitors (Olsen, 1992). At present, strong relationships with customers have become vital, none of the banks can avoid it otherwise retaining, and increasing customers becomes very difficult. If a bank needs to have a competitive position then its relations with its customers becomes the most significant factor.

Customer’s loyalty is decreasing in different sectors including the banking sector. The basic reasons behind this customer`s declining loyalty towards different sectors are (Payne, Christopher, Clark, & Peck, 1999):

1) Use of latest technology: 2) High competition 3) Customers increased awareness

1) Use of latest technology:

There is rapid improvement and innovation of technology in the world than ever, mostly companies using latest technology like internet, telemarketing, auto- answering machines, and so on to satisfy their customers resulting in decreased loyalty as customers are more used to interact with machines.

2) High competition:

There is high competition in the market due to new banks entering as well as cellular companies providing financial services like “easy paisa” by Telenor Cellular Company in Pakistan.

3) Customers increased awareness:

These days, customers are well informed than ever due to rapid expansion of print and electronic media in Pakistan. Media has increased customers awareness about what is going on in the world, and this increased awareness about financial services has increased customer demands and changed their behaviours towards financial services.

Relationship in the banking sector is becoming more and more significant (Colgate, Alexander, Marks & Spencer, 1998 ).

2.6 MODELS RELATING TO RESEARCH STUDY

Many philosophers presented customer loyalty models. In the loyalty model (Figure 2.2), presented by Beerli, Martin and Quintana, (2004) variables that impact customer`s loyalty namely perceived quality, satisfaction, and switching cost are shown. As shown in this model of loyalty, perceived quality influences customer satisfaction and in turn, customer satisfaction influences

30 customer loyalty. Switching cost also influence customer loyalty (Beerli, Martin and Quintana, 2004).

Perceived Satisfaction Quality

Switching Loyalty cost

Figure 2.2: Loyalty Model (Beerli, Martin & Quintana, 2004)

The integrative framework for customer value and CRM performance model (Figure 2.3) is developed by Wang et al ., 2004. According to this model, if these four customer values are met then it results in customer satisfaction that turns into brand loyalty.

Here the researcher comments that customer satisfaction is the major influencing factor in the model presented by Wang et al . (2004) and also in the loyalty model presented by Beerli, Martin and Quintana (2004).

Figure 2.3. The Integrated Framework for Customer Value and CRM Performance. Source: Wang et al., 2004, p. 171

According to this model, employees’ behaviors depend on their attitude so we need to take care of the attitude of our employees if we want to increase profitability of our business resulting from customer retention.

Figure 2.4: The Employee-Customer-Profit Chain at Sears

“The CRM Value Chain Model”, (Figure 2.5) presented by Francis Buttle (2004) as a guideline to apply CRM in organizations to improve their profits. The CRM Value Chain Model comprises of five primary stages and four supporting conditions Figure 2.5:

Figure 2.5: The CRM Value Chain (Source: Buttle 2004)

The major objective of this model is establishing positive mutually beneficial relations between the customers and organizations.

2.7 OFFENSIVE AND DEFENSIVE STRATEGIES

The service providers have offensive and defensive strategies to manage their relationships with their customers (Fornell, 1992).

Fornell (1992) says that, in offensive strategy, a service provider attracts new customers whereas in defensive strategy, a service provider tries to retain the existing customers. Following Figure 2.6 presented by Fornell (1992) shows these offensive and defensive strategies:

Figure 2.6: Offensive and defensive strategies, Fornell, 1992, p-8

Generally, companies used to allocate more resources and energies towards getting new customers but presently that concept has changed and now the companies try to apply both the offensive and defensive strategies in a better manner than their competitors do. The possible result of these strategies is customer retention.

2.8 FACTORS THAT AFFECT CUSTOMER LOYALTY IN THE BANKING SECTOR

Researcher here discusses the major influences of factors that affect customer loyalty in the banking sector.

2.8.1 Customer Trust Closer relations between bank and its customer, higher the customer trust and vice versa. This close relationship between customer and bank is not due to any bias but it is due to a relationship between customer and bank that results in customer loyalty. Therefore, customer trust influences customer loyalty and higher the customer trust higher the customer loyalty.

It is a general truth that if you know and trust a person, you definitely give him/her importance in your decisions. Same is true for customers as those customers who knows your company`s products and services and trust you, they become regular customers. Any company that has effective channels of communications with its customers like customer services, company’s website, etc has better chances that its customers will trust them and this trust converts into loyalty.

2.8.2 Customer Perceived Value

There is rapidly growing interest in companies regarding customer value. Customer value is the most influencing factor (Watchword, 1990). Customer value is the core of marketing (Andreas Eggert and Wolfgang Ulaga, 1990).

Customer satisfaction has arisen many questions in the minds of researchers like there are many examples that, where there is high customer satisfaction but on the other hand, companies’ market-shares are going down. Many researchers found it surprising and here critics have argued that old customer satisfaction models focused only on the existing customers’ satisfaction and those models completely ignored possible customers, new customers, non-customers, and competitors. This ignorance resulted in failures in achieving company`s objectives. Furthermore, customer`s thinking about 4Ps of marketing that is product, price, place, and promotion should also be

35 considered. Therefore, in developing marketing strategies, customer perceived value has a vital role (Gross, 1997).

The researcher after going through detailed literature review found that there are generally three common elements of perceived value namely value components, value perceptions, and importance of competition.

As humans are different, so their perceptions are also different. Generally, people perceptions about any same product are different and so is the customer perceived value.

Finally, any company offering better value of their products and services than competitors can develop a competitive advantage. Generally, customers go for those products and services that offer better value in the market.

In Pakistan, customers also buy products and services due to their emotional attachments with a particular product and service. For example, customers buying shoes from Bata Shoe Company in Pakistan is also a result of emotional attachment with Bata Shoe Company and hence that results in more value and better perception about those company products.

Customer perceived value is closely related with the customer satisfaction and customer satisfaction in turn is closely related with customer loyalty. Customer`s satisfaction generally require his/her previous product/service experiences, price factors etc whereas customer`s perceived value is not dependent on customer`s previous experiences of products and services.

2.8.3 Customer Satisfaction

If there is no difference between customer satisfaction and customer`s expectations than the customer is satisfied, otherwise customer is not satisfied. Companies try to not only minimize the difference between these factors but also trying to provide products and services to their customers that exceed their expectations in order to retain them as loyal customers (Jamal and Kamal, 2002).

Customer satisfaction is an important factor in customer retention. If customer satisfied then he/she may become volunteer marketer of that product or service.

Customer develops an attitude after using any product or service and it is called customer satisfaction (Jamal and Kamal, 2002).

Customer performs an emotional assessment about various products and services before buying and after using it (Lin, 2003). Customers have expectations about products and services they use and these expectations are developed from their previous buying, from friends and relatives opinions. If customer’s expectations are met then he/she is satisfied otherwise dissatisfied. Customer satisfaction is important and it is significant source of loyalty and retention.

2.8.3.1 Conceptual differences between customer satisfaction and customer perceived value

The literature review shows that customer satisfaction and customer perceived value are complementary, yet different constructs. Following Table 2.1 shows the conceptual differences between customer satisfaction and customer perceived value:

Table 2.1: conceptual differences between customer satisfaction and customer perceived value. Customer Satisfaction Customer Perceived Value 1. Emotional factor 1. Cognitive factor 2. After buying customer`s viewpoint 2. Before buying customer`s viewpoint 3. Existing customers 3. Both existing customers and possible customers

2.8.4 Customer Switching Barriers

There are many switching barriers of customers like emotional barriers, cost barriers, time shortage barriers, and so on (Selnes, 1993). Customer`s options availability plays an important role in his/her buying decision. Options availability of different products and services also influence customer`s loyalty. If any customer has

37 more options available then his/her loyalty may also change as compare to a customer who has less or no other options available of other same products and services offered by some other providers. Loyalty is linked to customer`s behaviour and customer`s attitude.

2.8.5 Customer Culture

Culture (from the Latin cultura stemming from colere, meaning, "to cultivate) is a term that has different meanings. Culture can be defined in 164 ways (Alfred Kroeber and Clyde Kluckhohn, 1952).

Culture is basically, the common values, habits, attitudes, and behaviors of a group of people, or a company.

It is a fact that culture affects customer’s attitudes and customer`s behaviours (Hofstede, 1980). Therefore, customers who have proneness to any bank may become loyal customers. Here most of the philosophers are also of the view that customers who have stronger culture have high loyalty for banks.

The researcher being a Pakistani has observed that mostly Pakistani people are strong in certain values of their culture. It is generally seen that people develop certain habits due to their culture and if banks discover those values of culture then it may help banks to develop better customer loyalty strategies, which is a focus of Customer Relationship Management.

CHAPTER 3

FRAME OF REFERENCE

3.1 CONCEPTUALIZATION

A conceptual framework (Miles & Huberman, 1994, p.18):

“Explains, either graphically or in narrative form, the main things to be studied.”

Hence, in order to reach this research study`s purpose, the following research questions are stated:

The researcher has developed following hypotheses based on the purpose of this research:

3.2 PREVIOUS RESEARCH AND MODELS RELEVANT TO THIS RESEARCH STUDY

The researcher now describes previous researches, and models that relates to his research study`s purpose.

The customer loyalty model presented by Beerli, Martin and Quintana (2004) is shown in Figure 3.1. They have shown the influence of different factors on customer loyalty. The researcher based on literature review, comments here that the most influencing factor shown in this loyalty model is customer satisfaction. It is also a fact that when a customer is satisfied then the chances of loyalty are higher as compare to when a customer is dissatisfied.

In the following model Figure 3.1, Martin and Quintana (2004) have also given another factor that influences on customer loyalty that is switching cost. Here the researcher again based on literature review comments that almost every customer has some switching cost to pay whenever customer wants to switch to another product or service. For instance, times, money, legal restrictions, distance are some of the costs a customer has to pay is customer switches to another product or service.

Perceived Satisfaction Quality

Switching Loyalty cost

Figure 3.1: Loyalty Model (Beerli, Martin & Quintana, 2004)

The next model “The integrated framework for customer value and CRM performance” presented by Wang et al . (2004) focuses on four customer values, when these values are fulfilled, customer satisfaction is achieved and customer satisfaction in turn creates customer loyalty as shown in Figure3.2.

Figure 3.2: The Integrated Framework for Customer Value and CRM Performance. Source: Wang et al., 2004, p. 171

Model as shown Figure 3.3 presented by Rucci, Kirn, & Quinn (1999) shows the relationships between behaviours of employees and customers.

Figure 3.3: Employee-Customer-Profit Chain at Sears 41

The researcher based on literature review, comments here that there is cause and effect relationship in banks. If employees are satisfied with the bank then in turn employees make their customers happy, hence, there is a cause and effect relationship here.

Relationship of customers with their banks is of two type namely offensive strategy and defensive strategy (Fornell, 1992). Banks try to acquire new customer in offensive strategy whereas when a bank tries to keep existing customer then it is called defensive strategy as shown in Figure 3.4.

Figure3.4: Offensive and defensive strategies, Fornell (1992, p.8)

As the researcher earlier discussed in the previous chapter on the review of related literature about the following factors affect customer loyalty in the banking sector of Pakistan:

1) Customer trust, 2) Customer perceived value, 3) Customer satisfaction, 4) Customer culture, and 5) Customer switching barriers.

The researcher predict that the relationship between these factors also affect customer loyalty, customer trust has an influence on customer perceived value, customer satisfaction, and on customer loyalty as shown in the emerged frame of reference Figure 3.5. Customer perceived value also influences customer satisfaction and customer satisfaction in turn influences customer loyalty. Customer switching barriers and customer culture also influence customer loyalty as shown in Figure 3.5.

3.3 EMERGED FRAME OF REFERENCE

A frame of reference according to Miles and Huberman (1994) explains the main things to be studied, the key factors, constructs, or variables and the presumed relationship between them. Consequently, a frame of reference presents the theories and models that are most suitable for the research problem.

The researcher anticipates that based on this emerged frame of reference, there will be better CRM utilization in banking sector, and banks will be able to build customer loyalty in order to have a better long-term competitive edge over their competitors.

The Figure 3.5 presents the research variables used in the research questions and the chosen operational definitions.

According to the above discussions and emerged frame of reference as shown in Figure 3.5, the researcher would be in a better position to study this research study`s questions and hypotheses.

CUSTOMER CUSTOMER PERCEIVED VALUE H SATISFACTION

H H

CUSTOMER TRUST

CUSTOMER SWITCHING BARRIERS CUSTOMER LOYALTY

CUSTOMER CULTURE H

Figure 3.5: Emerged frame of reference Source: Researcher`s own construction

CHAPTER 4

RESEARCH METHODOLOGY

4.1 RESEARCH PROCESS ONION

According to the Research Process Onion presented by Saunders et al, 2003, Figure2, first layer research onion shows research philosophy that is positivism, realism, and interpretivism, second layer shows the various research approaches like inductive or deductive research approach, third layer shows research strategies such as experiment, survey, case study, grounded theory, ethnography, and action research, forth layer shows time horizons like cross-sectional, and longitudinal, the fifth layer shows various primary and secondary data collection methods, and finally, reliability & validity of the research is measured.

Figure 2: Research Process Onion presented by Saunders et al. (2003)

Positivism and phenomenology are the 2 major research processses (Saunders et al., 2000). Scientific discoveries made during the 18th and 19th centuries have a deep impact on positivism approach. During 18 th and 19 th centuries, it seemed apparent that the body of knowledge existed independently of whether people knew it or not, and the scientific task was to find out this knowledge. People believed that there are laws that manage the operation of the social world and these laws can be discovered. It was also assumed that there is hidden absolute truth and if we find absolute truth then it can be used to create a better society.

In this research study, in order to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan, positivism is the philosophy.

4.2 RESEARCH DESIGN

Research design describes the data collection methods and its analysis (Burns & Bush, 2002).

4.2.1 Exploratory research study In exploratory research study is conducted when a problem is not clear and it being used to get deeper understanding of any issue (Saunders et al., 2006).

4.2.2 Descriptive research study In the descriptive research study, actual situation described and is also known as statistical research, and it answers the questions who, what, where, when and how (Saunders et al., 2006).

4.2.3 Causal Research Study Causal Research discovers the effect of one factor on another and it is used to forecast with the help of results that what will influence a business in future (DJS Research Ltd, 2008).

When any factor or variable influences on another factor or variable and brings some changes then it is called causal relationship between these two factors or variables. These changes are measured and analyzed by researchers for making profitable decisions of companies.

Following research questions will help the researcher to achieve this research study`s purpose:

Consequently, the researcher has developed following hypotheses based on the purpose of this research:

Therefore, in order to accomplish the research purpose and respond to stated research questions and hypotheses, the researcher will begin with a descriptive research study and this descriptive research study will help the researcher to design a causal research study.

Furthermore, this research study relates to causal research study, as the researcher needs to find out the influence of factors on one another. The researcher is going to discover relationship among different factor that affect customer loyalty that is customer trust, customer perceived value,

47 customer satisfaction, customer switching barriers, and customer culture. Therefore, causal research study is the most appropriate research study for finding these kinds of relationships Parasuraman (1991).

4.3 RESEARCH STRATEGY

The research strategy is used to address the research questions of any research study (Saunders et al., 2000).

4.3.1 Selection of questionnaire survey method

Grounded theory involves various data collection stages, data refinement and observing interrelationship of different categories of collected data (Creswell, 2003; p. 14). The researcher tries to develop a theory here out of data gathered. The basic feature of grounded theory is the constant interaction between data collection and data analysis (Myers, 1997). The grounded theory strategy is not suitable for the present research study because this grounded theory takes more time for data collection as data needs to be gathered many times and the researcher has limited timeframe, so this was not a suitable option.

In order to approve or disapprove new hypotheses or theories, experiments are used (Devine, 2006). To respond research questions or examine problems, experiments are carried out (Griffith, W. Thomas, 2001).

In surveys, researchers collect data from a sample of a population e.g., we may study Allama Iqbal Open University`s students, or all the customers of banks in Pakistan. As these populations as given in these examples are too large so it is not possible for researcher to study the entire population so researchers use questionnaire surveys of only samples and these samples are selected according to a specified criteria.

In ethnography, it is compulsory for an ethnographer to spend more time in the field. Ethnographers deeply involve themselves in people lives they study (Lewis 1985, p. 380). This is obviously more time consuming so due to time limitation, its not possible for the researcher to consider this option.

In action research, firstly, the problem is researched, necessary changes are made, and this process repeats many times until the problem is solved (Garson, 1997). Action research is time consuming as well it costs more which constraints researcher to use this option.

Case study research can be defined in many ways. Case study research is a "systematic inquiry into an event or a set of related events which aims to describe and explain the phenomenon of interest" (Bromley, 1990, p.302). The use of case studies is widespread in management research.

Based on the above detailed arguments, the researcher used questionnaire survey method, the researcher selected National Bank of Pakistan (NBP), Pakistan serving as a public bank, Habib Bank Limited (HBL), Pakistan serving as a private bank, Meezan Bank Limited, Pakistan serving as an Islamic bank, and Citibank serving as a foreign bank in Pakistan according to the sampling criteria. The researcher used close-ended questions on 5-Point Likert Scale. The researcher used self-administered questionnaire for getting responses from 400 customers of these banks. Almost all possible options were given to respondents in this questionnaire; researcher also added few open questions asking about customer’s comments/suggestions in order to find out any other possible option, which is not given in the questionnaire. Therefore, in this way, it makes this questionnaire more effective.

The researcher experienced Customer Relationship Management (CRM) settings in the banks during working hours. The researcher collected data relevant to his research study like bank annual reports, public documents, marketing literature, and other relevant banks reports. The researcher also had few opportunities to observe Customer Relationship Management (CRM) team meetings at different banks, which proved vital for the existing research study.

The researcher selected questionnaire survey method due to the reasons presented by Aaker et al. (2000), as they said that the selection of a questionnaire survey method depends on nature of the research study and its purpose. The selection of a questionnaire survey method also depends on the type of questions asked from the customers, culture of customers, and resources involved. The researcher adopted personally administered questionnaire method due to the following factors:

1) Customers of banks may ask for any clarification of questions asked on the spot. Due to any misunderstandings, customers may give incorrect responses due to misunderstands so it is very important to clarify any question asked in the questionnaire in order to convey correct understanding of the questions asked in the questionnaire. 2) Customers are more interested in giving their responses due to the presence of researcher. 3) All the questionnaires are taken back immediately after filling without missing any questionnaire, and 4) The researcher persuaded respondents that the information provided by them will be used for academic purpose only.

In questionnaire survey, the researcher asked customers of banks about their age, income, marital status, and education levels. The researcher then included questions in the questionnaire relating to this research study`s purpose.

4.4 RESEARCH STUDY FACTORS

4.4.1 Operational definitions

Operational definitions are required for data collection questionnaire (Davis & Cosenza, 1993). It means that every factor that influences customer loyalty should have specific questions to be asked. For measuring factors or constructs of this research study namely customer trust, customer perceived value, customer satisfaction, customer switching barriers, customer culture, and customer loyalty, operationalisation is used.

4.5 OPERATIONALIZATION OF RESEARCH STUDY FACTORS

4.5.1 Customer Trust

For measuring customer trust, following 7 questions are asked from respondents (Hess, 1995; Jarvenpaa & Tractinsky, 1999; Gurviez & Korchia, 2002; Gefen et al., 2003; and Chiou & Droge, 2006):

1) This bank keeps its promises 2) This bank is honest 3) This bank is reliable 4) This bank meets my needs 5) This bank seems capable to manage transactions on line 6) This bank seems to have solid knowledge in its field 7) I trust the know-how of this bank

Based on the above, this research study has seven items customer trust construct.

4.5.2 Customer Satisfaction

For measuring customer satisfaction, following 4 questions are asked from respondents (Wang et al., 2001; and Liosa, 1996):

1) I am satisfied with this bank 2) This bank leaves me a pleasant impression 3) I want to return to this bank in the future 4) I will advise this bank to my friends

Based on the above, this research study has four items customer satisfaction construct.

4.5.3 Customer Perceived Value

For measuring customer perceived value, following 3 questions are asked from respondents (Lassar et al., 1995):

1) The price of services offered by this bank is fair 2) Comparing to what I pay, I receive much more in terms of money, effort and time 3) On the base of simultaneous consideration of what I pay and what I gain, I consider that bank service is of value

Based on the above, this research study has three items customer perceived value construct. 4.5.4 Customer Switching Barriers

For measuring customer switching barriers, following 5 questions are asked from respondents (Kim, et. al., 2003):

1) In general switching to a new bank would be a hassle. 2) It would cost me a lot of money to switch from my current bank to another bank. 3) It would cost me a lot of time to switch from my current bank to another bank. 4) Prices of other banks are higher. 5) It would cost me a lot of effort to switch from my current bank to another bank.

Based on the above, this research study has five items customer switching barriers construct.

4.5.5 Customer Culture

For measuring customer culture, following 4 questions are asked from respondents (Hofstede, 1980, 1994):

1) You have a top priority towards personal goals 2) You feel uncomfortable in unusual situations

3) You buy what you desire without worrying about how others feel or think 4) You buy what you like and stick to your brand

Based on the above, this research study has four items customer culture construct.

4.5.6 Customer Loyalty

Finally, for measuring customer loyalty, following 6 questions are asked from respondents (Boulaire et Mathieu, 2000; Srinivasan et al., 2002; and Huang, 2008):

1) I regularly visit this bank 2) I seldom think of changing this bank to another one 3) I use this bank each time I need to make any financial transaction 4) I consider this bank as my preferred one 5) I like to use this bank 6) Each time I want to make any financial transaction, this bank is my first choice

Based on the above, this research study has six items customer loyalty construct.

4.6 PROGRESSION OF QUESTIONNAIRE`S QUESTIONS

The researcher has used simple sequence of questions for better understanding of customers of banks. In the beginning, the researcher has asked questions relating to age, income, marital status, and educational level. After this, researcher has asked questions about each of the following factors that affect customer loyalty in the following sequence:

1) Customer perceived value 2) Customer satisfaction 3) Customer switching barriers 4) Customer culture 5) Customer trust

6) Customer loyalty

The basic purpose of this above sequence of questions is to motivate the respondents by asking simple most interesting questions in the beginning then customer culture, customer trust, and customer loyalty questions are given that generally takes more time to respond.

4.7 TIME HORIZON

Methods of descriptive research are cross-sectional & longitudinal (Saunders et al., 2000). Here the researcher had to choose between longitudinal research or cross sectional research. Cross- sectional research helps researchers to measure variable(s) in a shorter time so that these measurements may be viewed as contemporaneous (Baltes, Reese, & Nesslroade, 1988; and Creswell, 1998). Therefore, the major benefits of using cross-sectional research are that it is more time saving and more cost saving as compare to longitudinal research study. On the other hand, in longitudinal studies, repeated observations are made of the same items over a very long period, mostly covering many decades. It is mostly used in psychology and in sociology. For instance, in the field of psychology, human’s psychological trends over their entire lives are studied, and in sociology, it is used to study generation to generation various life events. In longitudinal studies, same humans are studied mostly their entire life span resulting in more accurate results than any other research study and these results are mostly not influenced by their cultures or any other factor.

Based on the above discussions and researches, the researcher has used cross-sectional research study for this research study.

4.8 POPULATION

A population consists of all elements-individuals, items, or objects-whose characteristics are being studied. The population that is being studied is also called the target population (Mann, 1995).

Banks/ development finance institutions in Pakistan comprises of seven categories, which are regulated by the SBP (Appendix-III) (State Bank of Pakistan, 2009). In the first category, government owns public sector banks, second category, specialized banks that are the same as the first group but their activities are more focused on some special tasks, like agriculture, industries, house and buildings, etc. Third category banks are called private banks owned by a person or a group of persons. Fourth category, Islamic banks, fifth category, foreign banks and finally sixth & seventh categories, micro finance institutions and Development Finance Institutions respectively perform some limited tasks and activities. State Bank of Pakistan regulates all these banks / development finance institutions.

The researcher has chosen customers of the following banking categories as population of this research study that offer their services to public at large, and have a large market-share: 1) Public banks, 2) Private banks, 3) Islamic banks, and 4) Foreign banks.

4.9 SAMPLING

Selection of sampling technique depends on the probability of collecting data to address research`s questions & research objectives from the entire population (Saunders et al, 2000). In census, data is collected from entire population, which is not possible for the researcher due to resource constraints. It is not possible for researcher to study all customers of all banks serving in Pakistan hence a sampling criteria is used as it provides valid alternative to the census (Saunders etal., 2000).

For achieving this research study`s purpose, the researcher has chosen customers of four banking categories namely public banks, private banks, Islamic banks, & foreign banks according to the following sampling criteria:

Banks with large market-share,

Banks offering services to public at large, Banks having network of branches, Banks having nationwide and/or worldwide representation, and Researcher`s resource constraints.

According to the above mentioned sampling criteria, National Bank of Pakistan (NBP) serving as public bank, Habib Bank Limited (HBL), Pakistan serving as private bank, Meezan Bank Limited, Pakistan serving as an Islamic bank, and Citibank serving as a foreign bank in Pakistan fulfilled the above-mentioned sampling criteria hence this will make the sample representative of the population as a whole (Egan, 2007, p. 133). Furthermore, banks fulfilling sampling criteria as mentioned above similar to Beerli et al. (2004) were chosen.

The researcher collected data personally from customers of above mentioned banks from the areas of Islamabad and Rawalpindi because of the researcher`s time, money, and other resource constraints.

4.9.1 Sample size

A sample size of 300 respondents is good (Comrey & Lee, 1992; and Tabachnick & Fidell, 2001). A sample of 200 to 500 is considered adequate for most customer surveys (Hill and Alexander, 2000 p. 88). 5 to 10 responses from each item are adequate (Hair, Anderson, Tatham, & Black, 1998). Therefore, the researcher keeping in mind all these researchers sample size criteria, finalized sample size of 400.

4.9.2 Sample selection

The researcher then randomly selected two branches of each bank as shown in Table 1. The researcher decided that every 10 th customer-entering bank would be taken as respondent of this research study and the researcher continued the process like this for few weeks until 400 responses were received as shown in Table 4.1.

Table 4.1: Distribution of questionnaire in banks

S # Bank No. of Branches No. of Customers NBP branches: 1 1) NBP, branch code 0341, civic centre 100 Br. G-6, Islamabad), Pakistan 02 (50 customers of each 2) NBP, G-9 branch, branch code 1932, branch) Al-Markaz G-9,Br. Islamabad, Pakistan Habib Bank Limited (HBL), Pakistan: 2 Branches: 1) Habib Bank Limited (HBL), 4th Floor, 100 Habib Bank Tower, Jinnah Avenue, 02 (50 customers of each Islamabad, Pakistan. branch) 2) Habib Bank Limited (HBL), 5-C plaza, F-10 Markaz, Islamabad, Pakistan. Meezan Bank Limited, Pakistan: 3 Branches: 1) Meezan Bank Limited, F-10 Markaz 100 Branch, Plot # 2-F, Super Trade Centre, 02 (50 customers of each F-10 Markaz, Islamabad, Pakistan. branch) 2) Meezan Bank Limited, Jinnah Avenue Branch, 32 Sohrab Plaza, Blue Area, Islamabad, Pakistan Citibank, Pakistan: 4 Branches: 100 1) Citibank, 94 West, Jinnah Avenue 02 (50 customers of each Blue Area, Islamabad, Pakistan. branch) 2) Citibank, 168-D, Adamjee Road, Rawalpindi, Pakistan TOTAL: 08 BRANCHES 400 CUSTOMERS

4.10 INSTRUMENTS FOR DATA COLLECTION

A self-administered questionnaire was developed as attached at Appendix-I as an instrument for data collection from customers of four major banks in Pakistan namely National Bank of Pakistan (NBP), Habib Bank Limited (HBL), Meezan Bank Limited, and Citibank, Pakistan. These banks were selected according to the criteria as earlier specified. In order to get true response from the customers of these banks, the researcher included brief instructions in the beginning of questionnaire. Likert 5-point scale was used to determine the perceived relative importance of the services provided by banks in Pakistan, as well as to evaluate the relative importance of the attributes commonly used in selecting a bank. Open-ended questions were also given in the questionnaire to find out any other factors, if not included in the close-ended questions.

Data collected for this research study was personally administered and collected by the researcher. The researcher provided clarifications to respondents, if they asked.

4.11 PRETESTING OF QUESTIONNAIRE

Pretesting of the questionnaire improves it and customers easily respond (Saunders et al., 2000). For small-scale questionnaires, it is not likely to have ample time or financial resources for such testing (Fink, 1995). However, it is still important to have the questionnaire pilot tested. For most questionnaires, the minimum number for a pilot testing is 30. Therefore, during first stage of pilot testing of questionnaire, the researcher took help from experts of the selected banks as well as from randomly selected customers of banks. They gave their comments on researcher`s questionnaire. During second stage of pilot testing of questionnaire, the researcher gave 30 questionnaires as per Fink (1995), each to randomly selected customers of banks. During this second stage, the researcher personally got feedback from each customer and noted down various comments. After the second stage, the researcher again revised this questionnaire.

Questionnaire for customers of banks includes various factors and these factors have 29 items according to defined measurement scales as shown in the following proposed model of customer loyalty in Figure 4.1. These questions relate to customer trust (7 items), customer perceived value (3 items), customer satisfaction (4 items), customer switching barriers (5 items), customer culture (4 items), and customer loyalty (6 items)

Figure 4.1: Customer loyalty model developed by the researcher

CUSTOMER CUSTOMER PERCEIVED VALUE H SATISFACTION

H H

CUSTOMER TRUST

CUSTOMER SWITCHING BARRIERS CUSTOMER LOYALTY

CUSTOMER CULTURE H

At the end of the questionnaire, 2 open-ended questions were given to find out any further comments and suggestions of the customers of banks.

4.12 ANALYSIS OF DATA

For the analysis of data from respondents, researcher followed the following procedure:

4.12.1 Coding of questions

The researcher did coding of questions before entering these into SPSS software version 16.00. For questions relating to customer perceived value, researcher coded these as PV1, PV2, and PV3. For questions relating to customer satisfaction, researcher coded these as CS4, CS5, CS6, and CS7. For questions relating to customer switching barriers, researcher coded these as CSB8, CSB9, CSB10, CSB11, and CSB12. For questions relating to customer culture, the researcher coded these as CC13, CC14, CC15, and CC16. For questions relating to customer trust, the researcher coded these as CT17, CT18, CT19, CT20, CT21, CT22, and CT23. Finally, for questions relating to customer loyalty, the researcher coded these as CL24, CL25, CL26, CL27, CL28, and CL29.

4.12.2 Data analysis techniques

A data analysis statistical technique is dependent on the purpose of research study (Malhotra, 1999). Researcher used statistical techniques like correlation and regression analysis

The researcher has used SPSS software for applying relevant tests to these factors to measure their relationships. The researcher entered all the data of this research study in SPSS software version 16.00 for doing data analysis of each element of factors. Researcher did correlation analysis to find out Pearson Correlation and Sig. (2-tailed) of the various elements of research study`s factors. Then researcher did the Regression Model, Multivariate Data Analysis, and Stage-Wise Multiple Regression analysis that includes model summary in which, R and R Square were calculated. Then with the help of ANOVA, the researcher calculated df, Sig., F, and Mean Square. Finally, standardized coefficients Beta, t-test and significance of factors were measured.

To explore relationships between the research`s factors, correlation analysis was done as it helps to understand the relationships between these factors.

Likert Scales are suitable to measure responses as Likert scales gives better results than any other method (Aaker et al., 2000; Wong, 1999; Hayes, 1998; Garland, 1991; Burns & Bush, 2002; Zikmund, 2000; and Kassim, 2001).

The researcher collected responses from customers of banks with the help of 5-point Likert Scale with a series of statements. Finally, the researcher gave descriptive analysis of each item of this research study`s factors.

4.13 TRIANGULATION

In research, triangulation means using two or more research theories, using multiple data sources, collecting data from different places and at different times, data collection from different managerial levels, different individuals, or groups of people, for a research study (Hilton, 2005).

For increased data reliability and validity, the researcher collected data from multiple sources like data collection with the help of questionnaire, bank reports, expert opinions of bank employees, and regular customers of banks. Triangulation is a broad strategy of data collection and analysis within which a range and variety of techniques can be utilized (Elliott, 2009).

The supposition at this point is that people comprehend the situation in different ways according to their practical good and concerns. Thus, any broad view of a situation needs to consider these manifold perspectives.

4.14 RELIABILITY & VALIDITY OF THE RESEARCH CONSTRUCTS

In research design, reliability and validity factors have to paid attention in order to minimize possibility of getting incorrect responses (Saunders etal., 2000).

The researcher has used Cronbach coefficient alpha for the evaluating the different measures of the research questionnaire. Cronbach coefficient alpha for research instrument should be 0.70 or higher if it is reliable (Hair et al., 1995; Pallant, 2001).

4.14.1 Reliability

Threats to reliability are (Robson, 1993):

1) Subject error: Generally, time selection for taking questionnaire response from the customers of banks for research study is inappropriate like asking customers to fill questionnaires during early or near to closing timings of banks.

2) Subject bias: In some situations, customers respond what others ask them to say instead of what they really want to say.

3) Observer error: This error can be minimized by improving structure of the questionnaire. 4) Observer bias: This concerns with how the researcher interprets data.

In order to minimize subject error, the researcher took customers responses with the help of questionnaire on the convenience of customers only and not on researcher’s personal convenience. Subject error was minimized by taking confidence of customers by persuading them that this research study is for academic purpose and data collected will not be quoted anywhere else except in this research report without the prior consent of the customers and the concerned organizations, names confidentiality was also given so in this way, most of the customers gave true responses. Finally, unbiased interpretations were made to overcome observer bias.

In this research study, the Cronbach`s Alpha value of all constructs is higher than 0.70 that indicates reliability of the research instrument.

4.14.2 Validity

To assess the content validity, the researcher got feedback from bank`s experts and bank`s most regular customers on questionnaire and made changes accordingly. A three-stage pilot testing of questionnaire was also performed for improvements/changes in this questionnaire. Furthermore, in order to have increased validity, the researcher personally administered all the questionnaires and in case of any misunderstanding, customers were given immediate clarifications.

The researcher used review of related literature for the validity and scope of factors of this research study. For increased validity, and before going for pilot testing of questionnaire, the researcher also got pertinent experts suggestions from various universities in Pakistan.

4.15 FIELD ISSUES DURING RESEARCH STUDY

During data collection, the researcher faced different problems and some of these problems were unexpected. For instance, some customers hesitated to fill questionnaire but most of the customers were not hesitant. The researcher finally convinced almost all the customers that the data collected is purely for academic purpose.

Generally, customers are in a hurry while visiting banks and mostly they are unwilling to fill any questionnaire so this also created certain difficulties for the researcher.

Few branches of banks didn’t allow the researcher to get responses from their customers as these bank`s managers thought that the researcher may provide responses of their customers to their competitors and it may create problems for their banks. The researcher was able to convince most of the bank managers but few managers did not allow getting responses of their customers.

Mentioning these field issues during data collection has two main reasons, firstly, researcher want to create awareness about the practical problems during data collection, secondly, other researchers may learn lesson from these difficulties experienced. In addition, these issues justifies the long time taken to prepare this research study.

CHAPTER 5

EMPIRICAL FINDINGS

5.1 OVERVIEW OF THE NATIONAL BANK OF PAKISTAN (NBP)

NBP is a public sector bank having 1250 branches in Pakistan and abroad covering almost all areas of Pakistan. The services of the National Bank of Pakistan (NBP) are available to all including small account holders to multinational companies serving in Pakistan and abroad and its unique feature is, NBP also acts as SBP agent. It clearly shows trust of SBP on NBP (NBP, 2009).

At Present, customer`s needs are not easy to identify and met due to high level of complexity as these needs and wants changes with the passage of time. Therefore, these rapid changes forced all banks including the “National Bank of Pakistan” to emphasize more on developing and strengthening relations with its customers.

The NBP is also listed on the KSE. According to the management of NBP, NBP is committed to serve its customers better than their competitors. This bank also addresses the low- income level class in Pakistan with its schemes like Karobar, Saiban, Kisan Dost, and Cash & Gold (NBP, 2009).

NBP`s vision describes its commitment as well as social responsibilities & its mission focuses on merit, creating unique identity in the market, following benchmarks, improving customer`s value and creating excellent national and international repute (NBP, 2009).

Its basic core values are creating benchmarks, teamwork, best services, training and development of human resources, and community development. The vision, mission, and core values details of the National Bank of Pakistan (NBP) are attached as Appendix-XIII.

The National Bank of Pakistan (NBP) can get a competitive edge over its major competitors in Pakistan and abroad if it recognizes the truth that well-trained employees and CRM-based

65 business processes are essential for its success. Since NBP has a large network of 1250 branches, hence it is most important for National Bank of Pakistan (NBP) to strengthen its customer retention strategies as banks are redefining their role in the world.

5.1.1 Business profile

NBP has 1250 branches in our country and abroad. The joint ventures of the NBP are with UNB UK, FIB UK, and with FFM of Singapore (NBP, 2009).

The NBP got many awards & made big achievements since its establishment. Details of its awards and achievements are attached as Appendix-XIV. Details of the NBP`s Director`s Board is attached at Appendix-XV.

The Director`s Report about major areas NBP prepared by S. Ali Raza, Chairman & President on behalf of Board of Directors of NBP attached at Appendix-XVI. This report briefly highlights major functional areas of NBP like corporate and investment banking, commercial & retail banking, overseas banking, agriculture finance, treasury management, Islamic banking, global home remittances management, equity investment division, operations, special assets management, information technology, human resource management, audit & inspection , credit and risk management, compliance, domestic branches network, credit rating, social responsibility, profit & loss appropriation, audit committee, HR management committee, pattern of share holding, appointment of auditors, risk management framework, and finally it presents statement of internal controls (NBP, director`s report, 2009).

Generally, NBP uses some of the gathered information about their customers for analysis and decision making purposes. NBP provides normal services to all of their customers but special services are offered to big customers having big accounts in their bank. Especially during closing of financial years, the bank managers and all other concerned employees focus more on targeting their big customers for high deposits.

One interesting factor about NBP is that, some of the bank employees have developed personal relations with their customers and in case, that employee moves to some other bank, their high deposit customers also move to that new bank with all of their deposits immediately.

For corporate customers, NBP offers many investment options. According to top-level management of NBP, branches are closer to their customers than Head Office of NBP as branches deal regularly and directly with majority of their customers.

NBP uses different channels of communication with its customers, for instance, NBP communicates with its customers through its large network of branches all over Pakistan and abroad, through print and electronic media, via telephone, and through personal contacts that improves its performance. According to one of the managers of NBP, customers can contact us round the clock through our website and from morning till evening through telephone.

5.1.2 Responses of customers

Now researcher is going to present briefly major responses from the customers of this bank regarding different factors that affect customer loyalty.

Since the National Bank of Pakistan has a large network of branches and also a public bank so most of its customers responded that they do trust this bank and they have a convenience and easy accessibility to its various branches but they are also dissatisfied because of its poor services.

Majority customers responded that their perceived value do not match with the services provided by this bank as other banks are offering high value products and services in Pakistan.

Regarding customer satisfaction, some respondents were pleased due to its low prices but majority were dissatisfied.

Since NBP is a Pakistani bank so majority of its customers being Pakistani want to remain with this bank. Furthermore, most of its customers are existing government employees or retired government employees and their salaries are transferred by their organizations in this bank so they have no other bank choice. Another major barrier is of those government employees who have their pension accounts here. These pensioners have no choice to switch their accounts to some other bank for better services. There are other customers like business customers or individuals who are serving in private sector in Pakistan. These customers do not want to switch to some other bank because they responded in the questionnaire that since the price of services of the National Bank of

Pakistan is less than other banks so it is affordable and they cannot afford higher prices of other banks. Another switching barrier that the researcher found with the help of questionnaire that since this bank has a very large numbers of branch hence it is easily accessible hence customers want to remain with NBP.

5.1.3 Challenges and future opportunities

The main issue here at NBP is, most of its employees are not aware about how to build customer loyalty. The management of NBP is flexible in accepting and implementing new ideas and technologies. Top management of NBP is trying to bring change in their systems through ad1option of CRM in all of their branches in Pakistan and abroad.

There is high resistance from employees at NBP because they do not want to do customer`s data entry as they believe that its more time consuming without any financial gains.

Lack of employees’ interest in trainings is another challenge for NBP. Another problem faced by bank these days is of load shedding, so extra money is spent on using other sources of energy in large network of NBP branches all over Pakistan.

NBP can convert its weaknesses into strengths by focusing more on effectively training their employees. Financial and non-financial rewards may be provided to NBP employees who perform well and achieve their assigned targets in time.

According to the management of NBP, they are strictly committed to their vision, mission, and core values. Employees are provided on-going trainings in different areas. NBP also showed its commitment towards all its stakeholders.

Since the top management of NBP is already of the view that CRM can bring excellent results especially in the area of customer retention, hence the bank is in the process of implementing CRM in all of its branches all over Pakistan and abroad.

5.2 OVERVIEW OF THE CITIBANK

Citibank is operating in more than hundred countries in the world and it is one of the biggest banks in the world (Current News - Citibank, 2009). Citibank works on proactive strategies regarding all its operations. It has a true customer-centric approach.

Citibank started its operations in Pakistan in 1961 and earned the most respectable repute in few years. Citibank is known for setting benchmarks and its highest standards all over the world and in Pakistan has made it one of the best banks serving in Pakistan. The high motivation of human resources has helped Citibank to be the leading bank. In almost all areas of banking, Citibank has set benchmarks.

Its worldwide consumer bank and global corporate investment bank are the most reputable brands in the financial world. Citibank in Pakistan has offered its customers many new services and at present, more than 1000 employees are serving Citibank, Pakistan.

5.2.1 Business profile

These days, customers are much aware about different products and service offerings than ever. It means that if a bank needs to be the first choice of customers then it has to strengthen its relations with its customers. Strong relations matters most in current business world specially retaining customers have become the prime objective of most competitive organizations all over the world. Major details of the business profile of the Citibank is attached at Appendix-XVIII.

Citibank provides grants to different areas like poverty alleviation, education, health and so on. Details of these grants is attached at Appendix-XVII. Furthermore, brief details of Citibank`s building communities is attached at Appendix-XIX.

Citibank has a large global network in Africa, Asia Pacific, Central America / Caribbean, Europe, South America, North America, and Middle East. Details attached at Appendix-V.

5.2.2 Responses of customers

Now the researcher is going to present very briefly major responses from the customers of the Citibank regarding different factors that affect customer loyalty:

Majority of the customers responded that they trust this bank because of its high quality reliable services much better than other banks in Pakistan. Another reason they gave that this bank has strong international repute and they believe that their accounts are much safer here.

According to majority customers, this bank matches or sometimes exceeds their perceived value. After using services of Citibank, most of the customers are satisfied, as they believe that they are getting the world class banking services in this bank.

Most of the customers of this bank belong to at least high middle-income level as questionnaire response shows. Some customers responded that they do not have time to check the services of other banks.

5.2.3 Challenges and future opportunities

Citibank has set highest standards in Pakistani banking sector and according to the Citibank management, these milestones will continue. Details of the Citibank Pakistan's Milestones is attached at Appendix-VI.

Although Citibank provides the best quality in Pakistan but prices of its products and services as compare to other banks serving in Pakistan are higher. So making it affordable for public should be the strategy of Citibank.

Other major challenges faced by Citibank are maintaining and developing the existing quality of its products and services.

5.3 OVERVIEW OF THE MEEZAN BANK LIMITED, PAKISTAN

The Islamic banking sector is growing rapidly worldwide. For instance, Citibank has also established branches in different countries in the world as per Sharia’h principles.

Meezan Bank Limited, Pakistan is a large bank with 201 branches at 54 places in Pakistan (Meezan Bank, 2009) .

Meezan Bank`s vision focuses on fair and justice to humanity through Islamic banking. Finally, the service mission of this bank focuses on development of commitment of bank for providing the best products and services (Meezan Bank, 2009). A detail of the vision and mission of the Meezan Bank Limited, Pakistan is attached at Appendix-XX.

Meezan Bank Limited, Pakistan is growing rapidly in Pakistan and it shows the rapid growth of Islamic banking in Pakistan (Meezan Bank, 2009). A detail about the complete branch network of Meezan bank is attached at Appendix-XXI. Meezan Bank Limited has a good image in the minds of its customers as its customers showed their satisfaction through questionnaire.

5.3.1 Business profile

Meezan Bank Limited is a publicly listed company. Meezan Bank is the largest Islamic Bank in Pakistan with a network of 201 branches in 54 cities.

The bank has achieved a strong balance sheet with outstanding working profitability, as well as a capital adequacy ratio that places the bank at top of the banking sector with a long-term entity rating of A+, and a short-term entity rating of A1.

The key shareholders of the Meezan Bank Limited are leading local and international financial institutions. The Bank has an internationally renowned, high calibre and pro-active Shariah Supervisory Board presided over by Justice (Retd.) Muhammad Taqi Usmani.

5.3.2 Responses of customers

Now the researcher is going to present briefly major responses from the customers of the Meezan Bank Limited, Pakistan regarding different factors that affect customer loyalty:

Mostly customers trust this bank because of its Islamic banking functions. Some of the customers responded that they do not trust this bank because it is a comparatively new Islamic bank in Pakistan.

Majority customers responded that their perceived value almost matches with the services and products offered by this bank.

Majority of the customers of Meezan Bank Limited showed their satisfaction with this bank but they also responded that services offered by this bank are not of high standard as offered by other good banks in the country.

Culture in Pakistan also supports Islamic banks hence the result is, majority of the customers of this bank are also culturally motivated to keep their accounts here.

There are almost no switching barriers according to the majority respondents of this bank. The one is same like customers of other banks that they believe that it is a hassle to change banks. According to some customers, they have no time to check services of other banks that is why they do not want to switch to some other bank. Meezan Bank Limited needs to improve its services in order to get more market-share.

5.3.3 Challenges and future opportunities

Meezan Bank Limited, Pakistan faces few challenges like, all of its branches are not online and certain online branches are not functioning adequately. Service charges of this bank are little high as compare to other Islamic banks serving in Pakistan. Ongoing training of employees is another challenge here at Meezan. Its marketing department is not using its maximum potential.

Meezan Bank is going to launch a new product called RibaFree. The launching of RibaFree has been scheduled to coincide with Hujjat ul Wida, the last sermon delivered by Prophet Mohammad (PBUH) in which the interest was declared forever as "Haram".

Meezan Bank is a premier Islamic investment bank in Pakistan operating firmly under the principles of Islamic Sharia'a. It offers innovative Sharia’a well-matched products and services to

72 satisfy its customers. People working here at Meezan Bank are highly committed and dedicated towards their work.

5.4 OVERVIEW OF THE HABIB BANK LIMITED (HBL), PAKISTAN

Habib Bank Limited (HBL), Pakistan started its operations in Pakistan in 1947. Over the years, HBL has grown its branch network and become the largest private sector bank with over 1,450 branches across the country and a customer base exceeding five million relationships.

The Government of Pakistan privatized HBL in 2004 through which Aga Khan Fund for Economic Development (AKFED) acquired 51% of the Bank's shareholding and management control. HBL is majority owned (51%) by the Aga Khan Fund for Economic Development, 42.5% of the shareholding is retained by the Government of Pakistan (GOP), whilst 6.5% is owned by the general public. Habib Bank Limited (HBL) needs improvements like all other banks.

Board of Directors of the Habib Bank Limited (HBL), Pakistan comprises of One Chairman, President & CEO, and five directors, details attached at Appendix-XXII (HBL, 2009).

5.4.1 Business profile

Habib Bank Limited is the “Best Emerging Market Banks in Asia” (GlobalFinanceMagazine,2009) as it has earned various awards.

With a presence in 25 countries, subsidiaries in Hong Kong and the UK, affiliates in Nepal, Nigeria, Kenya and Kyrgyzstan and rep offices in Iran and China, HBL is also the largest domestic multinational. The Bank is expanding its presence in principal international markets including the UK, UAE, South and Central Asia, Africa and the Far East (HBL, 2009).

Habib Bank Limited offers best facilities in different areas to its customers including business and individual customers. A detail of these services is attached at Appendix-XXIII.

5.4.2 Responses of customers

Now the researcher is going to present briefly major responses from the customers of the Habib Bank Limited (HBL), Pakistan regarding different factors that affect customer loyalty:

Majority of the customers responded that they trust this bank because of its most reliable history and strong image in Pakistan.

Majority customers responded that this bank provides them best services as per their perceived value. Mostly customers responded their satisfaction with services & products offered by Habib Bank Limited.

Pakistani culture also supports this bank as shown by questionnaire responses of the customers of HBL. Same like Citibank, there is almost no major switching barrier here at this bank according to majority of the customers of this bank.

5.4.3 Challenges and future opportunities

Soundness of any bank depends on its efficiency and effectiveness in its all areas. As the researcher discussed in detail that there is high competition in the banking sector all over the world and Pakistan is no exception. Therefore, banks not only have national but international competition in all areas.

Strengthening of bank depends on relations with its customers, and same is the issue here at Habib Bank Limited, Pakistan. Understanding customers is a big challenge and an opportunity for HBL.

Other issues include modernization of payment system, arresting bad debts, continuous improvements in all areas, and up-gradation of risk management system. Habib Bank Limited needs to focus more on customer loyalty as there is ever growing competition in the banking sector of Pakistan.

As the competition in banking system has become severe and the profit margins on conventional modes of doing business are under pressure, therefore, HBL is moving towards

74 modern modes of doing business. These new areas require building customer loyalty, expertise, systems and procedures, controls, technology and risk management techniques.

CHAPTER 6

DATA ANALYSIS AND DISCUSSIONS

6.1 RESEARCH INSTRUMENT

The researcher collected data from 400 customers of banks in Pakistan through self- administered questionnaires. Research questionnaire`s questions are adopted from the existing literature relating to this research study`s purpose. Researcher has made minor changes in this adopted questionnaire after three-phase pilot testing as earlier described in introduction chapter, and made minor changes accordingly. For measuring factors or constructs of this research study namely customer trust, customer perceived value, customer satisfaction, customer switching barriers, customer culture, and customer loyalty, operationalisation is used.

6.1.1 Customer Trust

For measuring customer trust, following 7 questions are asked from respondents (Hess, 1995; Jarvenpaa & Tractinsky, 1999; Gurviez & Korchia, 2002; Gefen et al., 2003; and Chiou & Droge, 2006) as shown in the following Table 6.1:

Table 6.1: measuring customer trust TRUST Hess(1995), Jarvenpaa & Tractinsky (1999), Gurviez & Korchia (2002), Gefen et al. (2000), Chiou & Droge (2006) 1 This bank keeps its promises 2 This bank is honest 3 This bank is reliable 4 This bank meets my needs

5 This bank seems capable to manage transactions on line 6 This bank seems to have solid knowledge in its field 7 I trust the know-how of this bank

6.1.2 Customer Perceived Value

For measuring customer perceived value, following 3 questions are asked from respondents (Lassar et al., 1995) as shown in the following Table 6.2:

Table 6.2: measuring customer perceived value PERCEIVED VALUE Lassar et al. (1995) 1 The price of services offered by this bank is fair 2 Comparing to what I pay, I receive much more in terms of money, effort and time 3 On the base of simultaneous consideration of what I pay and what I gain, I consider that bank service is of value

6.1.3 Customer Satisfaction

For measuring customer satisfaction, following 4 questions are asked from respondents (Wang et al., 2001; and Liosa, 1996) as shown in the following Table 6.3:

Table 6.3: measuring customer satisfaction SATISFACTION Wang et al. (2001), Llosa (1996) 1 I am satisfied with this bank 2 This bank leaves me a pleasant impression 3 I want to return to this bank in the future 4 I will advise this bank to my friends

6.1.4 Customer Switching Barriers

For measuring customer switching barriers, following 5 questions are asked from respondents (Kim, et. al., 2003) as shown in the following Table 6.4:

Table 6.4: measuring customer-switching barriers SWITCHING BARRIERS Kim, et. al., 2003 1 In general switching to a new bank would be a hassle. 2 It would cost me a lot of money to switch from my current bank to another bank. 3 It would cost me a lot of time to switch from my current bank to another bank. 4 It would cost me a lot of effort to switch from my current bank to another bank. 5 Prices of other banks are higher.

6.1.5 Customer Culture

For measuring customer culture, following 4 questions are asked from respondents (Hofstede, 1980, 1994) as shown in the following Table 6.5:

Table 6.5: measuring customer culture CULTURE Hofstede (1980; 1994) 1 You have a top priority towards personal goals 2 You feel uncomfortable in unusual situations 3 You buy what you desire without worrying about how others feel or think 4 You buy what you like and stick to your brand

6.1.6 Customer Loyalty

Finally, for measuring customer loyalty, following 6 questions are asked from respondents (Boulaire et Mathieu, 2000; Srinivasan et al., 2002; and Huang, 2008) as shown in the following Table 6.6:

Table 6.6: measuring customer loyalty LOYALTY Boulaire et Mathieu (2000), Srinivasan et al. (2002), Huang (2008). 1 I regularly visit this bank 2 I seldom think of changing this bank to another one 3 I use this bank each time I need to make any financial transaction 4 I consider this bank as my preferred one 5 I like to use this bank 6 Each time I want to make any financial transaction, this bank is my first choice

6.2 DEMOGRAPHIC ANALYSIS

6.2.1 Demographic Analysis - Citibank, Pakistan

The demographic data analysis of the customers of Citibank, Pakistan is as below:

According to the following Table 6.7, 62% of the respondents are males (N=62), and females constitute 38% (N=38) of the total sample. It indicates that majority customers of this bank are males that is 62%.

Table 6.7: Customer`s Gender - (N=100), Citibank

Frequency Percent Valid Percent Cumulative Percent

Valid Male 62 62.0 62.0 62.0

Female 38 38.0 38.0 100.0

Total 100 100.0 100.0

Following bar chart 6.1 shows customer`s gender frequencies:

According to the following Table 6.8, 37% of the respondents are single (N=37), and 63% are married i.e. (N=63). It indicates that majority of the customers of this bank are married.

Table 6.8: Customer`s marital status - (N=100), Citibank

Frequency Percent Valid Percent Cumulative Percent

Valid single 37 37.0 37.0 37.0

married 63 63.0 63.0 100.0

Total 100 100.0 100.0

Following bar chart 6.2, shows customer`s marital status frequencies:

According to the table 6.9, the higher percentage lies in the category of Rupees 51,000 and above making 44% (N=44), while only 3% lies in the category of Rupees 21000 to 30,000 (N=3).

Table 6.9: Customer`s income - (N=100), Citibank

Frequency Percent Valid Percent Cumulative Percent

Valid 21000-30000 3 3.0 3.0 3.0

31000-40000 16 16.0 16.0 19.0

41000-50000 37 37.0 37.0 56.0

51,000 and above 44 44.0 44.0 100.0

Total 100 100.0 100.0

Following bar chart 6.3 shows customer's income frequencies:

According to Table 6.10, 13% of the individuals in the sample were between the age of 20- 30 (N=13), 30% of the individuals in the sample were between the age of 31-40 (N=30), 26% of the customers in the sample were between the age of 41-50 (N=26), and 31% of the customers in the sample were between the age of 51 and above (N=31). It indicates that majority of customers fall in the category of 51 years and above.

Table 6.10: Customer`s age - (N=100), Citibank

Frequency Percent Valid Percent Cumulative Percent

Valid 20-30 13 13.0 13.0 13.0

31-40 30 30.0 30.0 43.0

41-50 26 26.0 26.0 69.0

51 and above 31 31.0 31.0 100.0

Total 100 100.0 100.0

Following bar chart 6.4 shows customer's age frequencies:

Table 6.11, clearly shows, most the customers were bachelors degree holders i.e., 52% (N=52), rest of the ccustomers with their education levels are shown in this table 6.11.

Table 6.11: customer`s education level - (N=100), Citibank

Frequency Percent Valid Percent Cumulative Percent

Valid Intermediate and Below 6 6.0 6.0 6.0

Bachelors 52 52.0 52.0 58.0

Masters and Above 42 42.0 42.0 100.0

Total 100 100.0 100.0

Following bar chart 6.5 shows customer`s education level frequencies:

6.2.2 Demographic Analysis - National Bank of Pakistan (NBP), Pakistan

The demographic data analysis of the customers of the NBP is as below:

As per following Table6.12, 68% of the respondents are males (N=68), and females constitute 32% (N=32) of the total sample. It indicates that majority of the customers of this banks are males that is 68%. Table 6.12: customer`s Gender - (N=100), National Bank of Pakistan

Frequency Percent Valid Percent Cumulative Percent

Valid male 68 68.0 68.0 68.0

female 32 32.0 32.0 100.0

Total 100 100.0 100.0

Following bar chart 6.6 shows customer`s gender frequencies:

According to the following Table 6.13, 25% of the respondents are single (N=25), and 75% are married i.e. (N=75). It indicates are majority number of customers (75%) are married.

Table 6.13: customer`s marital status - (N=100), National Bank of Pakistan

Frequency Percent Valid Percent Cumulative Percent

Valid single 25 25.0 25.0 25.0

married 75 75.0 75.0 100.0

Total 100 100.0 100.0

Following bar chart 6.7 shows customer`s marital status frequencies:

According to the table 6.14, the higher percentage lies in the category of Rupees 51,000 and above that is 60% (N=60), while only 6% lies in the category of less than 10,000 (N=6).

Table 6.14: customer`s income - (N=100), National Bank of Pakistan

Frequency Percent Valid Percent Cumulative Percent

Valid less than 10,000 6 6.0 6.0 6.0

10000-20000 3 3.0 3.0 9.0

21000-30000 8 8.0 8.0 17.0

31000-40000 12 12.0 12.0 29.0

41000-50000 11 11.0 11.0 40.0

51,000 and above 60 60.0 60.0 100.0

Total 100 100.0 100.0

Following bar chart 6.8 shows customer`s income frequencies:

According to Table 6.15, 13% of the individuals in the sample were between the age of 20- 30 (N=13), 17% of the individuals in the sample were between the age of 31-40 (N=17), 23% of the customers in the sample were between the age of 41-50 (N=23), and 47% of the customers in the sample were between the age of 51 and above (N=47). It indicates that majority of customers fall in the category of 51 years and above.

Table 6.15: customer`s age - (N=100), National Bank of Pakistan

Frequency Percent Valid Percent Cumulative Percent

Valid 20-30 13 13.0 13.0 13.0

31-40 17 17.0 17.0 30.0

41-50 23 23.0 23.0 53.0

51 and above 47 47.0 47.0 100.0

Total 100 100.0 100.0

Following bar chart 6.9 shows customer`s age frequencies:

As per following Table6.16, mostly the customers were bachelors degree holders i.e., 49% (N=49), rest of the customers with their education levels are shown in this table.

Table 6.16: customer`s education level - (N=100), National Bank of Pakistan

Frequency Percent Valid Percent Cumulative Percent

Valid Intermediate and Below 10 10.0 10.0 10.0

Bachelors 49 49.0 49.0 59.0

Masters and Above 41 41.0 41.0 100.0

Total 100 100.0 100.0

Following bar chart 6.10 shows customer`s education level frequencies:

6.2.3 Demographic Analysis - Meezan Bank Limited, Pakistan

The demographic data analysis of the customers of Meezan Bank Limited, Pakistan is as below:

According to the following Table 6.17, 54% of the customers are males (N=54), and females constitute 46% (N=46) of the total sample. It indicates that majority customers of this bank are males.

Table 6.17: customer`s gender - (N=100), Meezan Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid male 54 54.0 54.0 54.0

female 46 46.0 46.0 100.0

Total 100 100.0 100.0

Following bar chart 6.11 shows customer`s gender frequencies:

According to the following Table 6.18, 44% of the customers are single (N=44), and 56% are married i.e. (N=56). It indicates that number of married males that is 56% is higher than single customers of this bank.

Table 6.18: customer`s marital status- (N=100), Meezan Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid single 44 44.0 44.0 44.0

married 56 56.0 56.0 100.0

Total 100 100.0 100.0

Following bar chart 6.12 shows customer`s marital status frequencies:

According to the table 6.19, the higher percentage lies in the category of Rupees 51,000 and above making 43% (N=43), while only 5% lies in the category of less than Rupees 10,000 (N=5).

Table 6.19: customer`s income - (N=100), Meezan Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid less than 10,000 5 5.0 5.0 5.0

10000-20000 6 6.0 6.0 11.0

21000-30000 12 12.0 12.0 23.0

31000-40000 18 18.0 18.0 41.0

41000-50000 16 16.0 16.0 57.0

51,000 and above 43 43.0 43.0 100.0

Total 100 100.0 100.0

Following bar chart 6.13 shows customer`s income frequencies:

According to Table 6.20, 14% of the individuals in the sample were between the age of 20- 30 (N=14), 15% of the individuals in the sample were between the age of 31-40 (N=15), 31% of the customers in the sample were between the age of 41-50 (N=31), and 40% of the customers in the sample were between the age of 51 and above (N=40). It indicates that majority of customers fall in the category of 51 years and above.

Table 6.20: customer`s age - (N=100), Meezan Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid 20-30 14 14.0 14.0 14.0

31-40 15 15.0 15.0 29.0

41-50 31 31.0 31.0 60.0

51 and above 40 40.0 40.0 100.0

Total 100 100.0 100.0

Following bar chart 6.14 shows customer`s age frequencies:

From the Table6.21, shows that mostly customers are bachelors degree holders i.e., 51% (N=51), rest of the respondents with their education levels are shown in this table.

Table6.21: customer`s education level - (N=100), Meezan Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid Intermediate and Below 11 11.0 11.0 11.0

Bachelors 51 51.0 51.0 62.0

Masters and Above 38 38.0 38.0 100.0

Total 100 100.0 100.0

Following bar chart 6.15 shows customer`s education level frequencies:

6.2.4 Demographic Analysis - Habib Bank Limited, Pakistan (HBL), Pakistan

The demographic data analysis of the customers of Habib Bank Limited, Pakistan (HBL) is as below:

According to the following Table 6.22, 71% of the customers are males (N=71), and females constitute 29% (N=29) of the total sample. It indicates that male customers are more than female customers in this bank that is 71%.

Table 6.22: customer`s gender - (N=100), Habib Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid Male 71 71.0 71.0 71.0

female 29 29.0 29.0 100.0

Total 100 100.0 100.0

Following bar chart 6.16 shows customer`s gender frequencies:

According to the following Table 6.23, 27% of the customers are single (N=27), and 73% are married i.e. (N=73). It indicates that majority of the customers of this bank are married that is 73%.

Table 6.23: customer`s marital status - (N=100), Habib Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid single 27 27.0 27.0 27.0

married 73 73.0 73.0 100.0

Total 100 100.0 100.0

Following bar chart 6.17, shows customer`s marital status frequencies:

According to the table 6.24, the higher percentage lies in the category of Rupees 51,000 and above making 48% (N=48), while only 3% lies in the category of Rupees 21000 to 30,000 (N=3).

Table 6.24: customer`s income - (N=100), Habib Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid 21000-30000 3 3.0 3.0 3.0

31000-40000 13 13.0 13.0 16.0

41000-50000 36 36.0 36.0 52.0

51,000 and above 48 48.0 48.0 100.0

Total 100 100.0 100.0

Following bar chart 6.18 shows customer`s income frequencies:

According to Table 6.25, 9% of the individuals in the sample were between the age of 20-30 (N=9), 21% of the individuals in the sample were between the age of 31-40 (N=21), 22% of the customers in the sample were between the age of 41-50 (N=22), and 48% of the customers in the sample were between the age of 51 and above (N=48). It indicates that majority of customers fall in the category of 51 years and above.

Table 6.25: customer`s age - (N=100), Habib Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid 20-30 9 9.0 9.0 9.0

31-40 21 21.0 21.0 30.0

41-50 22 22.0 22.0 52.0

51 and above 48 48.0 48.0 100.0

Total 100 100.0 100.0

Following bar chart 6.19 shows customer`s age frequencies:

Table 6.26, shows most customers were bachelors degree holders i.e., 48% (N=48), rest of the respondents with their education levels are shown in this table.

Table 6.26:customer`s education level - (N=100), Habib Bank Limited

Frequency Percent Valid Percent Cumulative Percent

Valid Intermediate and Below 13 13.0 13.0 13.0

Bachelors 48 48.0 48.0 61.0

Masters and Above 39 39.0 39.0 100.0

Total 100 100.0 100.0

Following bar chart 6.20 shows customer`s education level frequencies:

6.3 CORRELATION ANALYSIS

The Correlation and Regressions analysis of data obtained through self-administered questionnaire from customers of the following four banks is presented as below:

1) Citibank, Pakistan 2) National Bank of Pakistan (NBP) 3) Meezan Bank Limited, Pakistan 4) Habib Bank Limited (HBL), Pakistan

6.3.1 Correlation Analysis – Citibank, Pakistan

In following Table 6.27, the correlation analysis suggests that a moderate positive correlation exists between customer trust and customer perceived value that is 0.387 yielding the fact that customer trust has a significant impact on customer perceived value, which in turn

99 generates customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer perceived value is significant.

Table 6.27: Correlations between customer trust & customer perceived value - Citibank (N-100)

PV TRUST

PV Pearson Correlation 1 .387**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .387** 1

Sig. (2-tailed) .000

N 100 100

In Table 6.28, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer loyalty that is 0.474 yielding the fact that customer trust has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that the correlation between customer trust and customer loyalty is significant.

100

Table 6.28: Correlations between customer trust and customer loyalty - Citibank (N-100)

LOYALTY TRUST

LOYALTY Pearson Correlation 1 .474**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .474** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.29, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer satisfaction that is .573 yielding the fact that customer trust has a significant impact on customer satisfaction. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer satisfaction is significant.

Table 6.29: Correlations between customer trust and customer satisfaction - Citibank (N-100)

CS TRUST

CS Pearson Correlation 1 .573 **

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .573 ** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

101

In Table 6.30, the correlation analysis suggests that a moderate positive correlation exist between customer perceived value & customer satisfaction that is 0.665 yielding the fact that customer perceived value has a significant impact on customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher concludes that, the correlation between customer perceived value & customer satisfaction is significant.

Table 6.30: Correlations between customer perceived value & customer satisfaction - Citibank (N-100)

CS PV

CS Pearson Correlation 1 .665**

Sig. (2-tailed) .000

N 100 100

PV Pearson Correlation .665** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.31, the correlation analysis suggests that a moderate positive correlation exist between customer switching barriers & customer loyalty value that is 0.487 yielding the fact that customer-switching barriers have a significant impact on customer loyalty. As significance is less than 0.05, so the researcher concludes that, the correlation between customer switching barriers & customer loyalty value is significant.

102

Table 6.31: Correlations between customer switching barriers & customer loyalty - Citibank (N-100)

LOYALTY CSB

LOYALTY Pearson Correlation 1 .487**

Sig. (2-tailed) .000

N 100 100

CSB Pearson Correlation .487** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.32, the correlation analysis suggests that a moderate positive correlation exist between customer culture & customer loyalty that is 0.446 yielding the fact that customer culture has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer culture & customer loyalty is significant.

Table 6.32: Correlations between customer culture & customer loyalty - Citibank (N-100)

LOYALTY CULTURE

LOYALTY Pearson Correlation 1 .446**

Sig. (2-tailed) .000

N 100 100

CULTURE Pearson Correlation .446** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

103

In Table 6.33, the correlation analysis suggests that a moderate positive correlation exist between customer satisfaction & customer loyalty that is .657 yielding the fact that customer satisfaction has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher concludes that, the correlation between customer satisfaction & customer loyalty value is significant.

Table 6.33: Correlations between customer satisfaction & customer loyalty - Citibank (N-100)

LOYALTY CS

LOYALTY Pearson Correlation 1 .657**

Sig. (2-tailed) .000

N 100 100

CS Pearson Correlation .657** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

The table 6.34 shows the correlation values yielded from data analysis of 100 customers of Citibank. A significant and positive relationship found to exist between all studied variables. The table 6.34 shows the details of correlation analysis of all the studied variables. As significance is less than 0.05 as shown earlier in this chapter, so the researcher also concludes that, the correlation between all studied factors is significant.

104

Table 6.34: Correlations between all studied variables - Citibank (N-100) Customer Customer Customer Customer Customer Customer Perceived Switching Culture Trust Satisfaction Loyalty Value Barriers Customer 1 0.387 0.573 0.474 Trust Customer Perceived 1 0.665 Value Customer 1 0.657 Satisfaction Customer Switching 1 0.487 Barriers Customer 1 0.446 Culture Customer 1 Loyalty

6.3.2 Correlation Analysis – National Bank of Pakistan (NBP), Pakistan

In Table 6.35, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer perceived value that is 0.305 yielding the fact that customer trust has a significant impact on customer perceived value, which in turn generates customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer perceived value is significant.

105

Table 6.35: Correlations between customer trust & customer perceived value - NBP (N-100)

PV TRUST

PV Pearson Correlation 1 .305**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .305** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.36, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer loyalty that is 0.419 yielding the fact that trust has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer loyalty is significant.

Table 6.36: Correlations between customer trust and customer loyalty - NBP (N-100)

LOYALTY TRUST

LOYALTY Pearson Correlation 1 .419**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .419** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

106

In Table 6.37, the correlation analysis suggests that a moderate positive correlation exist between customer perceived value & customer satisfaction that is 0.354 yielding the fact that customer perceived value has a significant impact on customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer perceived value & customer satisfaction is significant.

Table 6.37: Correlations between customer perceived value & customer satisfaction - NBP (N-100)

CS PV

CS Pearson Correlation 1 .354**

Sig. (2-tailed) .000

N 100 100

PV Pearson Correlation .354** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.38, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer satisfaction that is .336 yielding the fact that customer trust has a significant impact on customer satisfaction. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer satisfaction is significant.

107

Table 6.38: Correlations between customer trust and customer satisfaction - NBP (N-100)

CS TRUST

CS Pearson Correlation 1 .336 **

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .336 ** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.39, the correlation analysis suggests that a moderate positive correlation exist between customer switching barriers & customer loyalty that is 0.439 yielding the fact that customer-switching barriers have a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer switching barriers & customer loyalty is significant.

Table 6.39: Correlations between customer switching barriers & customer loyalty - NBP (N-100)

LOYALTY CS

LOYALTY Pearson Correlation 1 .439**

Sig. (2-tailed) .000

N 100 100

CS Pearson Correlation .439** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

108

In Table 6.40, the correlation analysis suggests that a moderate positive correlation exist between customer culture & customer loyalty that is .365 yielding the fact that the customer culture has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer culture & customer loyalty is significant.

Table 6.40: Correlations between customer culture & customer loyalty - NBP (N-100)

LOYALTY CULTURE

LOYALTY Pearson Correlation 1 .365**

Sig. (2-tailed) .000

N 100 100

CULTURE Pearson Correlation .365** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.41, the correlation analysis suggests that a moderate positive correlation exist between customer satisfaction & customer loyalty that is 0.439 yielding the fact that customer satisfaction has a significant influence on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer satisfaction & customer loyalty is significant.

109

Table 6.41: Correlations between customer satisfaction & customer loyalty - NBP (N-100)

LOYALTY CS

LOYALTY Pearson Correlation 1 .439**

Sig. (2-tailed) .000

N 100 100

CS Pearson Correlation .439** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

The table 6.42 shows the correlation values yielded from data analysis of 100 customers of the National Bank of Pakistan (NBP). A significant and positive relationship found to exist between all studied factors. The table 6.42 shows the details of correlation analysis of all the studied variables. As significance is less than 0.05 as shown earlier in this chapter, so the researcher also concludes that, the correlation between all studied factors is significant.

110

Table 6.42: Correlations between all studied factors - NBP (N-100) Customer Customer Customer Customer Customer Customer Perceived Switching Culture Trust Satisfaction Loyalty Value Barriers Customer 1 0.305 0.336 0.419 Trust Customer Perceived 1 0.354 Value Customer 1 0.439 Satisfaction Customer Switching 1 0.493 Barriers Customer 1 0.365 Culture Customer 1 Loyalty

6.3.3 Correlation Analysis – Meezan Bank Limited, Pakistan

In following Table 6.43, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer perceived value that is .333 yielding the fact that customer trust has a significant impact on customer perceived value, which in turn generates customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer perceived value is significant.

111

Table 6.43: Correlations between customer trust & customer perceived value - Meezan (N-100)

PV TRUST

PV Pearson Correlation 1 .333**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .333** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.44, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer loyalty that is 0.419 yielding the fact that customer trust has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer loyalty is significant.

Table 6.44: Correlations between customer trust and customer loyalty - Meezan (N-100)

LOYALTY TRUST

LOYALTY Pearson Correlation 1 .419**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .419** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

112

In Table 6.45, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer satisfaction that is .330 yielding the fact that customer trust has a significant impact on customer satisfaction. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer satisfaction is significant.

Table 6.45: Correlations between customer trust and customer satisfaction – Meezan, (N-100)

CS TRUST

CS Pearson Correlation 1 .330 **

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .330 ** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.46, the correlation analysis suggests that a moderate positive correlation exist between customer perceived value & customer satisfaction that is .352 yielding the fact that customer perceived value has a significant impact on customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer perceived value & customer satisfaction is significant.

113

Table 6.46: Correlations between customer perceived value & customer satisfaction - Meezan (N-100)

CS PV

CS Pearson Correlation 1 .352**

Sig. (2-tailed) .000

N 100 100

PV Pearson Correlation .352** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.47, the correlation analysis suggests that a moderate positive correlation exist between customer switching barriers & customer loyalty that is .349 yielding the fact that customer- switching barriers have a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer switching barriers & customer loyalty is significant.

Table 6.47: Correlations between customer switching barriers & customer loyalty Meezan (N-100)

LOYALTY CSB

LOYALTY Pearson Correlation 1 .349**

Sig. (2-tailed) .000

N 100 100

CSB Pearson Correlation .349** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

114

In Table 6.48, the correlation analysis suggests that a moderate positive correlation exist between customer culture & customer loyalty that is 0.483 yielding the fact that customer culture has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer culture & customer loyalty is significant.

Table 6.48: Correlations between customer culture & customer loyalty - Meezan (N-100)

LOYALTY CULTURE

LOYALTY Pearson Correlation 1 .483**

Sig. (2-tailed) .000

N 100 100

CULTURE Pearson Correlation .483** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.49, the correlation analysis suggests that a moderate positive correlation exist between customer satisfaction & customer loyalty that is 0.418 yielding the fact that customer satisfaction has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer satisfaction & customer loyalty is significant.

115

Table 6.49: Correlations between customer satisfaction & customer loyalty - Meezan (N-100)

LOYALTY CS

LOYALTY Pearson Correlation 1 .418**

Sig. (2-tailed) .000

N 100 100

CS Pearson Correlation .418** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

The table 6.50 shows the correlation values yielded from data analysis of 100 customers of the Meezan Bank Limited, Pakistan. A significant and positive relationship found to exist between all studied factors. The Table 6.50 shows the details of correlation analysis of all the studied variables. As significance is less than 0.05 as shown earlier in this chapter, so the researcher also concludes that, the correlation between all studied factors is significant.

116

Table 6.50: Correlations between all studied factors - Meezan (N-100) Customer Customer Customer Customer Customer Customer Perceived Switching Culture Trust Satisfaction Loyalty Value Barriers Customer 1 0.333 0.330 0.419 Trust Customer Perceived 1 0.352 Value Customer 1 0.418 Satisfaction Customer Switching 1 0.349 Barriers Customer 1 0.483 Culture Customer 1 Loyalty

6.3.4 Correlation Analysis – Habib Bank Limited (HBL), Pakistan

In following Table 6.51, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer perceived value that is 0.359 yielding the fact that customer trust has a significant impact on customer perceived value, which in turn generates customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer perceived value is significant.

117

Table 6.51: Correlations between customer trust & customer perceived value - HBL (N-100)

PV TRUST

PV Pearson Correlation 1 .359**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .359** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.52, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer loyalty that is 0.447 yielding the fact that customer trust has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer loyalty is significant.

Table 6.52: Correlations between customer trust and customer loyalty - HBL (N-100)

LOYALTY TRUST

LOYALTY Pearson Correlation 1 .447**

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .447** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

118

In Table 6.53, the correlation analysis suggests that a moderate positive correlation exist between customer trust and customer satisfaction that is .587 yielding the fact that customer trust has a significant impact on customer satisfaction. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer trust and customer satisfaction is significant.

Table 6.53: Correlations between customer trust and customer satisfaction – HBL, (N-100)

CS TRUST

CS Pearson Correlation 1 .587 **

Sig. (2-tailed) .000

N 100 100

TRUST Pearson Correlation .587 ** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.54, the correlation analysis suggests that a moderate positive correlation exist between customer perceived value & customer satisfaction that is .605 yielding the fact that customer perceived value has a significant impact on customer satisfaction, which is a strong driving factor of customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer perceived value & customer satisfaction is significant.

119

Table 6.54: Correlations between customer perceived value & customer satisfaction - HBL (N-100)

CS PV

CS Pearson Correlation 1 .605**

Sig. (2-tailed) .000

N 100 100

PV Pearson Correlation .605** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

In Table 6.55, the correlation analysis suggests that a moderate positive correlation exist between customer switching barriers & customer loyalty that is 0.446 yielding the fact that customer-switching barriers have a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer switching barriers & customer loyalty is significant.

Table 6.55: Correlations between customer switching barriers & customer loyalty - HBL (N-100)

LOYALTY CSB

LOYALTY Pearson Correlation 1 .446**

Sig. (2-tailed) .000

N 100 100

CSB Pearson Correlation .446** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

120

In Table 6.56, the correlation analysis suggests that a moderate positive correlation exist between customer culture & customer loyalty that is .403 yielding the fact that customer culture has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer culture & customer loyalty is significant. Table 6.56: Correlations between customer culture & customer loyalty - HBL (N-100)

LOYALTY CULTURE

LOYALTY Pearson Correlation 1 .403**

Sig. (2-tailed) .000

N 100 100

CULTURE Pearson Correlation .403** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed). In Table 6.57, the correlation analysis suggests that a moderate positive correlation exist between customer satisfaction & customer loyalty that is .615 yielding the fact that customer satisfaction has a significant impact on customer loyalty. As significance is less than 0.05, so the researcher also concludes that, the correlation between customer satisfaction & customer loyalty is significant. Table 6.57: Correlations between customer satisfaction & customer loyalty - HBL (N-100)

LOYALTY CS

LOYALTY Pearson Correlation 1 .615**

Sig. (2-tailed) .000

N 100 100

CS Pearson Correlation .615** 1

Sig. (2-tailed) .000

N 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

121

The following table 6.58 shows the correlation values yielded from data analysis of 100 customers of Habib Bank Limited, Pakistan. A significant and positive relationship found to exist between all studied factors. The following Table 6.58 shows the details of correlation analysis of all the studied variables. As significance is less than 0.05 as shown earlier in this chapter, so the researcher also concludes that, the correlation between all studied factors is significant.

Table 6.58: Correlations between all studied factors - HBL (N-100) Customer Customer Customer Customer Customer Customer Perceived Switching Culture Trust Satisfaction Loyalty Value Barriers Customer 1 0.359 0.587 0.447 Trust Customer Perceived 1 0.605 Value Customer 1 0.615 Satisfaction Customer Switching 1 0.446 Barriers Customer 1 0.403 Culture Customer 1 Loyalty

122

6.4 MULTIVARIATE DATA ANALYSIS - CITIBANK, PAKISTAN

The first component Customer Loyalty explains 57% variance of the total variation alone. The second component Customer Satisfaction (CS) explains 18% variance of the total variation alone. The first & second components together explain 76% variance of the total variation. The third component Customer Perceived Value (PV) explains 11% variance of the total variation alone. The second and third components together explain 87% variance of the total variation. The fourth component Customer Trust explains 7% variance of the total variation alone. The third and fourth components together explain 94% variance of the total variation. The fifth component Customer-Switching Barriers (CSB) explains 3% variance of the total variation alone. The fourth and fifth components together explain 97% variance of the total variation. Finally, sixth component Customer Culture explains 2% variance of the total variation alone. The fifth and sixth components together explain 100% variance of the total variation as shown in Table 6.59.

Table 6.59 Total Variance Explained

Initial Eigenvalues Extraction Sums of Squared Loadings

Component Total % of Variance Cumulative % Total % of Variance Cumulative %

1 3.989 57.654 57.654 3.989 57.654 57.654 2 1.546 18.546 76.2 1.546 18.546 18.546 3 .876 11.001 87.201 4 .678 7.594 94.795 5 .765 3.104 97.899 6 .320 2.101 100.000

Extraction Method: Principal Component Analysis.

123

6.5 REGRESSION MODEL - CITIBANK, PAKISTAN

6.5.1 Customer Perceived Value (PV)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .786 as shown in Table 6.60.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .658, Customer Loyalty is .526, and constant is .299 as shown in Table 6.60.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).542, Customer Satisfaction (CS) is .368, Customer Loyalty is .524, and constant is .214 as shown in Table 6.60.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .521, Customer-Switching Barriers (CSB) is .254, Customer Satisfaction (CS) is .521, Customer Loyalty is .625, and constant is .547 as shown in Table 6.60.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .458, Customer Trust is .485, Customer-Switching Barriers (CSB) is .215, Customer Satisfaction (CS) is .412, Customer Loyalty is .524, and constant is .526 as shown in Table 6.60.

124

Table 6.60 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.765 .251 6.002 .000

Loyalty .786 .214 13.214 .000

2 (Constant) .301 .264 1.528 .000

Loyalty .526 .124 12.548 .000

CS .658 .521 6.548 .000

3 (Constant) .214 .214 .528 .000

Loyalty .524 .478 6.258 .000

CS .368 .462 5.658 .000

CSB .542 .467 3.584 .000

4 (Constant) .547 .471 1.998 .000

Loyalty .625 .154 6.528 .000

CS .521 .418 4.889 .000

CSB .254 .447 4.584 .000

Trust .521 .214 2.528 .000

5 (Constant) .526 .325 2.998 .000

Loyalty .524 .145 7.154 .000

CS .412 .552 4.558 .000

CSB .215 .125 3.589 .000

Trust .485 .325 3.002 .000

Culture .458 .854 3.002 .000 a. Dependent Variable: PV

125

6.5.2 Customer Loyalty

In the first regression model, Independent Variables Customer-Switching Barriers (CSB) and the constant both are significant, the coefficient of Customer-Switching Barriers (CSB) is .985 as shown in Table 6.61.

In the second regression model, Independent Variables Customer-Switching Barriers (CSB) and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .528, Customer-Switching Barriers (CSB) is .542, and constant is .452 as shown in Table 6.61.

In the third regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).478, Customer Satisfaction (CS) is .356, Customer-Switching Barriers (CSB) is .589, and constant is .354 as shown in Table 6.61.

In the fourth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .552, Customer Perceived Value (PV) is .475, Customer Satisfaction (CS) is .374, Customer-Switching Barriers (CSB) is .542, and constant is .458 as shown in Table 6.61.

In the fifth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .452, Customer Trust is .436, Customer Perceived Value (PV) is .487, Customer Satisfaction (CS) is .358, Customer-Switching Barriers (CSB) is .475, and constant is .521 as shown in Table 6.61.

126

Table 6.61 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.884 .251 5.524 .000

CSB .985 .254 14.115 .000

2 (Constant) .452 .452 2.002 .000

CSB .542 .421 12.986 .000

CS .528 .462 6.115 .000

3 (Constant) .354 .265 .652 .000

CSB .589 .426 9.225 .000

CS .356 .436 5.524 .000

PV .478 .265 4.254 .000

4 (Constant) .458 .524 2.524 .000

CSB .542 .264 8.254 .000

CS .374 .259 4.895 .000

PV .475 .555 4.568 .000

Trust .552 .456 2.988 .000

5 (Constant) .521 .221 3.526 .000

CSB .475 .187 8.524 .000

CS .358 .196 5.256 .000

PV .487 .168 3.002 .000

Trust .436 .152 2.986 .000

Culture .452 .256 2.865 .000 a. Dependent Variable: Loyalty

127

6.5.3 Customer Satisfaction (CS)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .652 as shown in Table 6.62.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .452, Customer Loyalty is .569, and constant is .335 as shown in Table 6.62.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).356, Customer Perceived Value (PV) is .289, Customer Loyalty is .399, and constant is .356 as shown in Table 6.62.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .451, Customer-Switching Barriers (CSB) is .288, Customer Perceived Value (PV) is .336, Customer Loyalty is .445, and constant is .458 as shown in Table 6.62.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .287, Customer Trust is .229, Customer-Switching Barriers (CSB) is .251, Customer Perceived Value (PV) is .325, Customer Loyalty is .452, and constant is .365 as shown in Table 6.62.

128

Table 6.62 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.254 .184 5.214 .000

Loyalty .652 .081 12.521 .000

2 (Constant) .335 .012 2.542 .000

Loyalty .569 .032 11.251 .000

PV .452 .014 6.245 .000

3 (Constant) .356 .199 .224 .000

Loyalty .399 .054 7.254 .000

PV .289 .021 5.521 .000

CSB .356 .047 2.854 .000

4 (Constant) .458 .202 2.888 .000

Loyalty .445 .032 5.251 .000

PV .336 .078 4.251 .000

CSB .288 .045 4.365 .000

Trust .451 .038 3.254 .000

5 (Constant) .365 .285 3.254 .000

Loyalty .452 .047 7.258 .000

PV .325 .024 3.584 .000

CSB .251 .035 2.852 .000

Trust .229 .054 2.765 .000

Culture .287 .487 2.012 .000 a. Dependent Variable: CS

129

6.5.4 Customer Trust

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .452 as shown in Table 6.63.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .412, Customer Loyalty is .485, and constant is .241 as shown in Table 6.63.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).315, Customer Perceived Value (PV) is .228, Customer Loyalty is .456, and constant is .351 as shown in Table 6.63.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .166, Customer-Switching Barriers (CSB) is .288, Customer Perceived Value (PV) is .256, Customer Loyalty is .386, and constant is .287 as shown in Table 6.63.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Culture and the constant are significant, the coefficient of Customer Culture is .294, Customer Satisfaction (CS) is .184, Customer-Switching Barriers (CSB) is .285, Customer Perceived Value (PV) is .259, Customer Loyalty is .273, and constant is .391 as shown in Table 6.63.

130

Table 6.63 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.569 .152 4.665 .000

Loyalty .452 .078 13.469 .000

2 (Constant) .241 .182 2.562 .000

Loyalty .485 .052 11.562 .000

PV .412 .042 5.628 .000

3 (Constant) .351 .326 .425 .000

Loyalty .456 .045 6.695 .000

PV .228 .199 5.986 .000

CSB .315 .255 3.521 .000

4 (Constant) .287 .269 3.895 .000

Loyalty .386 .487 5.478 .000

PV .256 .102 3.885 .000

CSB .288 .054 4.454 .000

CS .166 .077 2.658 .000

5 (Constant) .391 .262 2.787 .000

Loyalty .273 .087 6.269 .000

PV .259 .094 3.895 .000

CSB .285 .099 2.173 .000

CS .184 .096 2.992 .000

Culture .294 .654 1.568 .000 a. Dependent Variable: Trust

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6.5.5 Customer Culture

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .369 as shown in Table 6.64

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .458, Customer Loyalty is .547, and constant is .445 as shown in Table 6.64.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).269, Customer Perceived Value (PV) is .284, Customer Loyalty is .469, and constant is .215 as shown in Table 6.64.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .158, Customer-Switching Barriers (CSB) is .296, Customer Perceived Value (PV) is .265, Customer Loyalty is .395, and constant is .277 as shown in Table 6.64.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Trust and the constant are significant, the coefficient of Customer Trust is .162, Customer Satisfaction (CS) is .251, Customer-Switching Barriers (CSB) is .299, Customer Perceived Value (PV) is .352, Customer Loyalty is .389, and constant is .340 as shown in Table 6.64.

132

Table 6.64 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.562 .251 4.265 .000

Loyalty .369 .056 10.526 .000

2 (Constant) .445 .197 1.256 .000

Loyalty .547 .066 9.025 .000

PV .458 .025 5.652 .000

3 (Constant) .215 .265 .558 .000

Loyalty .469 .054 8.652 .000

PV .284 .187 5.025 .000

CSB .269 .286 3.658 .000

4 (Constant) .277 .293 2.898 .000

Loyalty .395 .397 5.658 .000

PV .265 .057 3.487 .000

CSB .296 .054 3.896 .000

CS .158 .064 2.659 .000

5 (Constant) .389 .287 2.776 .000

Loyalty .352 .099 6.542 .000

PV .299 .065 3.261 .000

CSB .251 .048 2.854 .000

CS .162 .089 2.548 .000

Trust .284 .449 1.958 .000 a. Dependent Variable: Culture

133

6.5.6 Customer Switching Barriers (CSB)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .458 as shown in Table 6.65.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .458, Customer Loyalty is .421, and constant is .390 as shown in Table 6.65.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).521, Customer Satisfaction (CS) is .326, Customer Loyalty is .569, and constant is .251 as shown in Table 6.65.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Trust is .256, Customer Perceived Value (PV) is .254, Customer Satisfaction (CS) is .369, Customer Loyalty is .454, and constant is .487 as shown in Table 6.65.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .382, Customer Trust is .205, Customer Perceived Value (PV) is .233, Customer Satisfaction (CS) is .325, Customer Loyalty is .541, and constant is .587 as shown in Table 6.65.

134

Table 6.65 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.254 .205 6.521 .000

Loyalty .458 .075 15.251 .000

2 (Constant) .658 .285 2.548 .000

Loyalty .421 .066 14.589 .000

CS .458 .084 6.251 .000

3 (Constant) .251 .296 .658 .000

Loyalty .569 .087 9.251 .000

CS .326 .069 5.254 .000

PV .521 .099 4.895 .000

4 (Constant) .487 .285 1.795 .000

Loyalty .454 .088 7.895 .000

CS .369 .054 4.695 .000

PV .254 .097 3.885 .000

Trust .256 .078 2.695 .000

5 (Constant) .587 .363 2.254 .000

Loyalty .541 .089 8.251 .000

CS .325 .095 4.652 .000

PV .233 .087 3.251 .000

Trust .205 .095 2.956 .000

Culture .382 .185 2.589 .000 a. Dependent Variable: CSB

135

6.6 STAGE-WISE MULTIPLE REGRESSION - CITIBANK, PAKISTAN

6.6.1 Customer Perceived Value (PV)

Stage-Wise Multiple Regression Model Suggests that all the five Independent Variables namely Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), Customer Trust, and Customer Culture have a significant effect on Dependent Variable Customer- Perceived Value (PV) and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.66.

Table 6.66 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100).

2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: PV

136

In Table 6.67, the first model gives 79% R Square; it means that Customer Loyalty is the most influential variable on Customer-Perceived Value (PV). The second model gives 81% R Square; it means that Customer Satisfaction (CS) influences Customer-Perceived Value (PV). The third model gives 89% R Square; it means that Customer-Switching Barriers (CSB) influences Customer-Perceived Value (PV). The fourth model gives 95% R Square; it means that Customer Trust influences Customer-Perceived Value (PV). The fifth model gives 97% R Square; it means that Customer Culture influences Customer-Perceived Value (PV).

Table 6.67 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .812 a .798 .765 .40212 2 .866 b .812 .872 .40987 3 .871 c .899 .767 .41275 4 .889 d .951 .874 .42354 5 .892 e .972 .899 .43867 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture

137

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Perceived Value (PV) as F value that is 190.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.68.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Perceived Value (PV) as F value that is 185.985 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.68.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Perceived Value (PV) as F value that is 181.524 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.68.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Perceived Value (PV) as F value that is 150.254 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.68.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Perceived Value (PV) as F value that is 98.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.68.

138

Table 6.68 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 32.756 1 32.756 190.251 .000 a

Residual 16.878 98 .251

Total 49.634 99

2 Regression 34.765 2 17.521 185.985 .000 b

Residual 14.869 98 .255

Total 49.634 99

3 Regression 36.879 3 12.548 181.524 .000 c

Residual 12.755 97 .224

Total 49.634 98

4 Regression 37.879 4 10.524 150.254 .000 d

Residual 11.755 98 .351

Total 49.634 99

5 Regression 38.521 5 8.221 98.251 .000 e

Residual 11.113 96 .254

Total 49.634 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture f. Dependent Variable: PV

139

6.6.2 Customer Loyalty

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, and Customer Culture have a significant effect on Dependent Variable Customer Loyalty and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.69.

Table 6.69 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: Loyalty

140

In Table 6.70, the first model gives 70% R Square; it means that Customer-Switching Barriers (CSB) is the most influential variable on Customer Loyalty. The second model gives 75% R Square; it means that Customer Satisfaction (CS) influences Customer Loyalty. The third model gives 78% R Square; it means that Customer Perceived Value (PV) influences Customer Loyalty. The fourth model gives 79% R Square; it means that Customer Trust influences Customer Loyalty. The fifth model gives 81% R Square; it means that Customer Culture influences Customer Loyalty.

Table 6.70 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .810 a .703 .521 .39521 2 .853 b .755 .611 .38565 3 .861 c .786 .647 .37584 4 .830 d .794 .659 .35854 5 .854 e .812 .729 .33421 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture

141

The overall regression for model 1 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Loyalty as F value that is 189.521 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.71.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Loyalty as F value that is 176.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.71.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Loyalty as F value that is 164.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.71.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Loyalty as F value that is 121.854 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.71.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Loyalty as F value that is 85.147 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.71.

142

Table 6.71 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 33.524 1 33.524 189.521 .000 a

Residual 19.253 97 .251

Total 52.777 98

2 Regression 34.589 2 15.547 176.251 .000 b

Residual 18.188 99 .216

Total 52.777 97

3 Regression 36.568 3 10.254 164.251 .000 c

Residual 16.209 96 .122

Total 52.777 98

4 Regression 37.684 4 7.548 121.854 .000 d

Residual 15.093 95 .225

Total 52.777 98

5 Regression 38.025 5 6.524 85.147 .000 e

Residual 14.752 96 .281

Total 52.777 99 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture f. Dependent Variable: Loyalty

143

6.6.3 Customer Satisfaction (CS)

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Trust, and Customer Culture have a significant effect on Dependent Variable Customer Satisfaction (CS) and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.72.

Table 6.72 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: CS

144

In Table 6.73, the first model gives 67% R Square; it means that Customer Loyalty is the most influential variable on Customer Satisfaction (CS). The second model gives 68% R Square; it means that Customer Perceived Value (PV) influences Customer Satisfaction (CS). The third model gives 71% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Satisfaction (CS). The fourth model gives 74% R Square; it means that Customer Trust influences Customer Satisfaction (CS). The fifth model gives 78% R Square; it means that Customer Culture influences Customer Satisfaction (CS).

Table 6.73 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .822 a .675 .652 .38521 2 .828 b .684 .524 .37254 3 .829 c .710 .689 .36281 4 .888 d .745 .854 .35214 5 .891 e .780 .548 .32545 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture

145

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Satisfaction (CS) as F value that is 175.542 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.74.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Satisfaction (CS) as F value that is 170.526 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.74.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Satisfaction (CS) as F value that is 165.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.74.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Satisfaction (CS) as F value that is 84.521 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.74.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Satisfaction (CS) as F value that is 79.524 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.74.

146

Table 6.74 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 36.251 1 36.251 175.542 .000 a

Residual 16.521 99 .225

Total 52.772 98

2 Regression 34.432 2 16.521 170.526 .000 b

Residual 18.34 97 .228

Total 52.772 98

3 Regression 35.435 3 12.254 165.251 .000 c

Residual 17.337 98 .188

Total 52.772 99

4 Regression 37.564 4 10.215 84.521 .000 d

Residual 15.208 96 .215

Total 52.772 97

5 Regression 38.786 5 8.521 79.524 .000 e

Residual 13.986 98 .158

Total 52.772 99 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture f. Dependent Variable: CS

147

6.6.4 Customer Trust

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Culture have a significant effect on Dependent Variable Customer Trust and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.75.

Table 6.75 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: Trust

148

In Table 6.76, the first model gives 65% R Square; it means that Customer Loyalty is the most influential variable on Customer Trust. The second model gives 71% R Square; it means that Customer Perceived Value (PV) influences Customer Trust. The third model gives 75% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Trust. The fourth model gives 78% R Square; it means that Customer Satisfaction (CS) influences Customer Trust. The fifth model gives 80% R Square; it means that Customer Culture influences Customer Trust.

Table 6.76 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .814 a .655 .562 .39589 2 .825 b .712 .458 .38548 3 .846 c .754 .489 .36478 4 .862 d .784 .596 .34589 5 .878 e .801 .648 .33632 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture

149

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Trust as F value that is 188.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.77.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Trust as F value that is 182.212 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.77.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Trust as F value that is 179.564 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.77.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Trust as F value that is 99.254 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.77.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Trust as F value that is 85.245 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.77.

150

Table 6.77 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 38.521 1 38.521 188.251 .000 a

Residual 12.251 98 .154

Total 50.772 99

2 Regression 39.251 2 19.521 182.212 .000 b

Residual 11.521 96 .125

Total 50.772 97

3 Regression 40.121 3 16.251 179.564 .000 c

Residual 10.651 99 .158

Total 50.772 98

4 Regression 41.251 4 14.251 99.254 .000 d

Residual 9.521 99 .668

Total 50.772 97

5 Regression 42.258 5 10.251 85.245 .000 e

Residual 8.514 97 .253

Total 50.772 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture f. Dependent Variable: Trust

151

6.6.5 Customer Culture

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Trust have a significant effect on Dependent Variable Customer Culture and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.78.

Table 6.78 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). a. Dependent Variable: Culture

152

In Table 6.79, the first model gives 52% R Square; it means that Customer Loyalty is the most influential variable on Customer Culture. The second model gives 65% R Square; it means that Customer Perceived Value (PV) influences Customer Culture. The third model gives 77% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Culture. The fourth model gives 86% R Square; it means that Customer Satisfaction (CS) influences Customer Culture. The fifth model gives 89% R Square; it means that Customer Trust influences Customer Culture.

Table 6.79 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .829 a .521 .569 .39652 2 .842 b .652 .632 .38452 3 .866 c .775 .521 .37548 4 .878 d .865 .594 .35645 5 .897 e .897 .599 .33265 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust

153

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Culture as F value that is 187.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.80.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Culture as F value that is 181.215 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.80.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Culture as F value that is 168.542 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.80.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Culture as F value that is 94.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.80.

Overall regression for model 5 is significant it means that Customer Trust has a significant influence on Customer Culture as F value that is 90.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.80.

154

Table 6.80 ANOVA f

Sum of Model Squares Df Mean Square F Sig.

1 Regression 35.521 1 35.521 187.251 .000 a

Residual 11.254 99 .156

Total 46.775 98

2 Regression 34.209 2 16.254 181.215 .000 b

Residual 12.566 97 .165

Total 46.775 96

3 Regression 35.654 3 13.251 168.542 .000 c

Residual 11.121 97 .187

Total 46.775 98

4 Regression 36.654 4 11.584 94.251 .000 d

Residual 10.121 98 .285

Total 46.775 99

5 Regression 37.444 5 9.251 90.251 .000 e

Residual 9.331 97 .195

Total 46.775 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust f. Dependent Variable: Culture

155

6.6.6 Customer Switching Barriers (CSB)

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, and Customer Culture have a significant effect on Dependent Variable Customer-Switching Barriers (CSB) and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.81.

Table 6.81 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: CSB

156

In Table 6.82, the first model gives 64% R Square; it means that Customer Loyalty is the most influential variable on Customer-Switching Barriers (CSB). The second model gives 67% R Square; it means that Customer Satisfaction (CS) influences Customer-Switching Barriers (CSB). The third model gives 70% R Square; it means that Customer Perceived Value (PV) influences Customer-Switching Barriers (CSB). The fourth model gives 74% R Square; it means that Customer Trust influences Customer-Switching Barriers (CSB). The fifth model gives 78% R Square; it means that Customer Culture influences Customer-Switching Barriers (CSB).

Table 6.82 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .810 a .645 .526 .39562 2 .832 b .675 .654 .38562 3 .848 c .702 .755 .36254 4 .859 d .745 .787 .35265 5 .884 e .789 .763 .34585 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty , CS c. Predictors: (Constant), Loyalty , CS, PV d. Predictors: (Constant), Loyalty , CS, PV, Trust e. Predictors: (Constant), Loyalty , CS, PV, Trust, Culture

157

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer-Switching Barriers (CSB) as F value that is 181.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.83.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 180.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.83.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 150.254 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.83.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer-Switching Barriers (CSB) as F value that is 90.568 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.83.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer-Switching Barriers (CSB) as F value that is 77.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.83.

158

Table 6.83 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 36.254 1 36.254 181.251 .000 a

Residual 15.251 97 .188

Total 51.505 98

2 Regression 35.356 2 16.215 180.256 .000 b

Residual 16.149 98 .152

Total 51.505 99

3 Regression 37.243 3 13.215 150.254 .000 c

Residual 14.262 97 .154

Total 51.505 98

4 Regression 37.968 4 10.254 90.568 .000 d

Residual 13.537 97 .165

Total 51.505 98

5 Regression 38.411 5 7.998 77.256 .000 e

Residual 13.094 98 .185

Total 51.505 99 a. Predictors: (Constant), CS b. Predictors: (Constant), CS, PV c. Predictors: (Constant), CS, PV, CULTURE d. Predictors: (Constant), CS, PV, CULTURE, TRUST e. Predictors: (Constant), CS, PV, CULTURE, TRUST, LOYALTY f. Dependent Variable: CSB

159

6.7 MULTIVARIATE DATA ANALYSIS - NATIONAL BANK OF PAKISTAN, PAKISTAN

The first component Customer Loyalty explains 46% variance of the total variation alone. The second component Customer Satisfaction (CS) explains 10% variance of the total variation alone. The first & second components together explain 56% variance of the total variation. The third component Customer Perceived Value (PV) explains 9% variance of the total variation alone. The second and third components together explain 66% variance of the total variation. The fourth component Customer Trust explains 5% variance of the total variation alone. The third and fourth components together explain 72% variance of the total variation. The fifth component Customer- Switching Barriers (CSB) explains 20% variance of the total variation alone. The fourth and fifth components together explain 92% variance of the total variation. Finally, sixth component Customer Culture explains 7% variance of the total variation alone. The fifth and sixth components together explain 100% variance of the total variation as shown in Table 6.84.

Table 6.84 Total Variance Explained

Initial Eigenvalues Extraction Sums of Squared Loadings

Component Total % of Variance Cumulative % Total % of Variance Cumulative %

1 2.254 46.521 46.521 2.254 46.521 46.521 2 1.548 10.215 56.736 1.548 10.215 10.215 3 .785 9.845 66.581 4 .265 5.584 72.165 5 .654 20.251 92.416 6 .321 7.584 100.000

Extraction Method: Principal Component Analysis.

160

6.8 REGRESSION MODEL - NATIONAL BANK OF PAKISTAN, PAKISTAN

6.8.1 Customer Perceived Value (PV)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .665 as shown in Table 6.85.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .452, Customer Loyalty is .452, and constant is .215 as shown in Table 6.85.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).448, Customer Satisfaction (CS) is .236, Customer Loyalty is .452, and constant is .125 as shown in Table 6.85.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .416, Customer-Switching Barriers (CSB) is .201, Customer Satisfaction (CS) is .442, Customer Loyalty is .558, and constant is .478 as shown in Table 6.85.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .396, Customer Trust is .462, Customer-Switching Barriers (CSB) is .215, Customer Satisfaction (CS) is .398, Customer Loyalty is .412, and constant is .447 as shown in Table 6.85.

161

Table 6.85 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.221 .199 5.251 .000

Loyalty .665 .205 10.514 .000

2 (Constant) .215 .222 1.002 .000

Loyalty .452 .021 11.555 .000

CS .452 .358 5.521 .000

3 (Constant) .125 .204 .452 .000

Loyalty .452 .412 6.112 .000

CS .236 .365 5.114 .000

CSB .448 .325 2.45 .000

4 (Constant) .478 .369 1.251 .000

Loyalty .558 .117 6.021 .000

CS .442 .354 4.854 .000

CSB .201 .365 4.114 .000

Trust .416 .211 2.051 .000

5 (Constant) .447 .295 2.124 .000

Loyalty .412 .129 6.542 .000

CS .398 .421 4.142 .000

CSB .215 .021 3.184 .000

Trust .462 .248 2.325 .000

Culture .396 .562 2.225 .000 a. Dependent Variable: PV

162

6.8.2 Customer Loyalty

In the second regression model, Independent Variables Customer-Switching Barriers (CSB) and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .496, Customer-Switching Barriers (CSB) is .447, and constant is .412 as shown in Table 6.86.

In the third regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).410, Customer Satisfaction (CS) is .316, Customer-Switching Barriers (CSB) is .456, and constant is .311 as shown in Table 6.86.

In the fourth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .405, Customer Perceived Value (PV) is .426, Customer Satisfaction (CS) is .324, Customer-Switching Barriers (CSB) is .489, and constant is .398 as shown in Table 6.86.

In the fifth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .403, Customer Trust is .401, Customer Perceived Value (PV) is .418, Customer Satisfaction (CS) is .325, Customer-Switching Barriers (CSB) is .356, and constant is .458 as shown in Table 6.86.

163

Table 6.86 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.251 .201 5.002 .000

CSB .652 .200 12.251 .000

2 (Constant) .412 .325 1.996 .000

CSB .447 .321 11.235 .000

CS .496 .362 5.215 .000

3 (Constant) .311 .165 .524 .000

CSB .456 .326 10.256 .000

CS .316 .396 5.221 .000

PV .410 .185 3.965 .000

4 (Constant) .398 .494 2.214 .000

CSB .489 .184 7.256 .000

CS .324 .211 4.112 .000

PV .426 .425 4.142 .000

Trust .405 .402 2.269 .000

5 (Constant) .458 .199 3.145 .000

CSB .356 .120 8.269 .000

CS .325 .112 4.256 .000

PV .418 .154 2.658 .000

Trust .401 .108 2.256 .000

Culture .403 .206 2.159 .000 a. Dependent Variable: Loyalty

164

6.8.3 Customer Satisfaction (CS)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .524 as shown in Table 6.87.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .396, Customer Loyalty is .446, and constant is .299 as shown in Table 6.87.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).321, Customer Perceived Value (PV) is .202, Customer Loyalty is .365, and constant is .310 as shown in Table 6.87.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .421, Customer-Switching Barriers (CSB) is .201, Customer Perceived Value (PV) is .302, Customer Loyalty is .359, and constant is .368 as shown in Table 6.87.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .242, Customer Trust is .198, Customer-Switching Barriers (CSB) is .208, Customer Perceived Value (PV) is .299, Customer Loyalty is .403, and constant is .301 as shown in Table 6.87.

165

Table 6.87 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.003 .169 4.526 .000

Loyalty .524 .045 11.652 .000

2 (Constant) .299 .002 2.021 .000

Loyalty .446 .012 10.215 .000

PV .396 .011 6.002 .000

3 (Constant) .310 .154 .125 .000

Loyalty .365 .045 6.885 .000

PV .202 .010 5.426 .000

CSB .321 .032 2.625 .000

4 (Constant) .368 .158 2.214 .000

Loyalty .359 .011 4.251 .000

PV .302 .054 3.251 .000

CSB .201 .039 4.115 .000

Trust .421 .021 3.114 .000

5 (Constant) .301 .269 3.254 .000

Loyalty .403 .022 7.145 .000

PV .299 .015 3.256 .000

CSB .208 .026 2.485 .000

Trust .198 .039 2.652 .000

Culture .242 .466 1.899 .000 a. Dependent Variable: CS

166

6.8.4 Customer Trust

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .365 as shown in Table 6.88.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .351, Customer Loyalty is .411, and constant is .211 as shown in Table 6.88.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).299, Customer Perceived Value (PV) is .211, Customer Loyalty is .401, and constant is .309 as shown in Table 6.88.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .122, Customer-Switching Barriers (CSB) is .254, Customer Perceived Value (PV) is .221, Customer Loyalty is .325, and constant is .241 as shown in Table 6.88.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Culture and the constant are significant, the coefficient of Customer Culture is .262, Customer Satisfaction (CS) is .155, Customer-Switching Barriers (CSB) is .254, Customer Perceived Value (PV) is .224, Customer Loyalty is .238, and constant is .324 as shown in Table 6.88.

167

Table 6.88 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.002 .122 4.325 .000

Loyalty .365 .062 12.526 .000

2 (Constant) .211 .151 2.136 .000

Loyalty .411 .032 10.254 .000

PV .351 .028 5.214 .000

3 (Constant) .309 .310 .226 .000

Loyalty .401 .026 6.421 .000

PV .211 .136 5.254 .000

CSB .299 .201 3.125 .000

4 (Constant) .241 .234 3.265 .000

Loyalty .325 .404 5.021 .000

PV .221 .054 2.154 .000

CSB .254 .032 3.256 .000

CS .122 .041 1.215 .000

5 (Constant) .324 .212 2.025 .000

Loyalty .238 .025 5.248 .000

PV .224 .055 3.625 .000

CSB .254 .021 1.251 .000

CS .155 .064 2.025 .000

Culture .262 .521 1.198 .000 a. Dependent Variable: Trust

168

6.8.5 Customer Culture

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .315 as shown in Table 6.89.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .325, Customer Loyalty is .445, and constant is .447 as shown in Table 6.89.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).214, Customer Perceived Value (PV) is .158, Customer Loyalty is .365, and constant is .115 as shown in Table 6.89.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .101, Customer-Switching Barriers (CSB) is .223, Customer Perceived Value (PV) is .241, Customer Loyalty is .385, and constant is .212 as shown in Table 6.89.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Trust and the constant are significant, the coefficient of Customer Trust is .218, Customer Satisfaction (CS) is .128, Customer-Switching Barriers (CSB) is .211, Customer Perceived Value (PV) is .226, Customer Loyalty is .322, and constant is .321 as shown in Table 6.89.

169

Table 6.89 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.256 .211 3.584 .000

Loyalty .315 .045 9.521 .000

2 (Constant) .417 .125 1.112 .000

Loyalty .445 .042 8.256 .000

PV .325 .010 5.265 .000

3 (Constant) .115 .225 .458 .000

Loyalty .365 .036 7.369 .000

PV .158 .142 4.258 .000

CSB .214 .225 3.358 .000

4 (Constant) .212 .274 2.254 .000

Loyalty .385 .348 5.145 .000

PV .241 .026 3.325 .000

CSB .223 .047 3.025 .000

CS .101 .026 2.114 .000

5 (Constant) .321 .255 2.471 .000

Loyalty .322 .044 6.022 .000

PV .226 .042 1.236 .000

CSB .211 .036 2.325 .000

CS .128 .078 2.214 .000

Trust .218 .431 1.326 .000 a. Dependent Variable: Culture

170

6.8.6 Customer Switching Barriers (CSB)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .325 as shown in Table 6.90.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .325, Customer Loyalty is .318, and constant is .542 as shown in Table 6.90.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).456, Customer Satisfaction (CS) is .258, Customer Loyalty is .478, and constant is .221 as shown in Table 6.90.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Trust is .225, Customer Perceived Value (PV) is .211, Customer Satisfaction (CS) is .321, Customer Loyalty is .425, and constant is .365 as shown in Table 6.90.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .269, Customer Trust is .186, Customer Perceived Value (PV) is .199, Customer Satisfaction (CS) is .289, Customer Loyalty is .421, and constant is .415 as shown in Table 6.90.

171

Table 6.90 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.365 .198 6.356 .000

Loyalty .325 .025 15.021 .000

2 (Constant) .542 .224 2.365 .000

Loyalty .318 .045 13.451 .000

CS .325 .063 5.251 .000

3 (Constant) .221 .225 .521 .000

Loyalty .478 .074 8.521 .000

CS .258 .062 4.562 .000

PV .456 .078 4.568 .000

4 (Constant) .365 .271 1.225 .000

Loyalty .425 .035 7.118 .000

CS .321 .025 4.659 .000

PV .211 .045 3.215 .000

Trust .225 .052 2.154 .000

5 (Constant) .415 .348 2.058 .000

Loyalty .421 .045 8.014 .000

CS .289 .070 4.654 .000

PV .199 .029 3.221 .000

Trust .186 .077 2.486 .000

Culture .269 .168 2.029 .000 a. Dependent Variable: CSB

172

6.9 STAGE-WISE MULTIPLE REGRESSION - NATIONAL BANK OF PAKISTAN, PAKISTAN

6.9.1 Customer Perceived Value (PV)

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), Customer Trust, and Customer Culture have a significant effect on Dependent Variable Customer- Perceived Value (PV) and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.91.

Table 6.91 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100).

173

In Table 6.92, the first model gives 66% R Square; it means that Customer Loyalty is the most influential variable on Customer-Perceived Value (PV). The second model gives 69% R Square; it means that Customer Satisfaction (CS) influences Customer-Perceived Value (PV). The third model gives 72% R Square; it means that Customer-Switching Barriers (CSB) influences Customer-Perceived Value (PV). The fourth model gives 76% R Square; it means that Customer Trust influences Customer-Perceived Value (PV). The fifth model gives 87% R Square; it means that Customer Culture influences Customer-Perceived Value (PV).

Table 6.92 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .801 a .662 .625 .38524 2 .810 b .695 .699 .39521 3 .825 c .721 .712 .40215 4 .856 d .764 .788 .41452 5 .879 e .872 .812 .41988 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture

174

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Perceived Value (PV) as F value that is 182.214 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.93.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Perceived Value (PV) as F value that is 171.252 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.93.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Perceived Value (PV) as F value that is 165.214 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.93

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Perceived Value (PV) as F value that is 140.212 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.93.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Perceived Value (PV) as F value that is 96.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.93.

175

Table 6.93 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.521 1 30.521 182.214 .000 a

Residual 12.214 97 .221

Total 42.735 98

2 Regression 32.251 2 15.251 171.252 .000 b

Residual 10.484 96 .125

Total 42.735 97

3 Regression 33.269 3 11.125 165.214 .000 c

Residual 9.466 97 .201

Total 42.735 98

4 Regression 35.525 4 9.251 140.212 .000 d

Residual 7.21 97 .286

Total 42.735 98

5 Regression 35.885 5 7.256 96.251 .000 e

Residual 6.85 98 .211

Total 42.735 99 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture f. Dependent Variable: PV

176

6.9.2 Customer Loyalty

Table 6.94 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

177

In Table 6.95, the first model gives 65% R Square; it means that Customer-Switching Barriers (CSB) is the most influential variable on Customer Loyalty. The second model gives 70% R Square; it means that Customer Satisfaction (CS) influences Customer Loyalty. The third model gives 75% R Square; it means that Customer Perceived Value (PV) influences Customer Loyalty. The fourth model gives 76% R Square; it means that Customer Trust influences Customer Loyalty. The fifth model gives 79% R Square; it means that Customer Culture influences Customer Loyalty.

Table 6.95 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .803 a .652 .485 .38215 2 .821 b .708 .562 .37214 3 .836 c .752 .578 .36521 4 .842 d .762 .584 .35584 5 .849 e .799 .658 .34215 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture

178

The overall regression for model 1 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Loyalty as F value that is 172.695 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.96.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Loyalty as F value that is 160.485 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.96.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Loyalty as F value that is 154.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.96.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Loyalty as F value that is 112.569 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.96.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Loyalty as F value that is 79.265 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.96.

179

Table 6.96 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.221 1 30.221 172.695 .000 a

Residual 12.214 98 .214

Total 42.435 99

2 Regression 31.251 2 12.251 160.485 .000 b

Residual 11.184 97 .210

Total 42.435 98

3 Regression 32.252 3 9.225 154.251 .000 c

Residual 10.183 98 .102

Total 42.435 99

4 Regression 33.251 4 7.251 112.569 .000 d

Residual 9.184 96 .199

Total 42.435 97

5 Regression 34.584 5 6.028 79.265 .000 e

Residual 7.851 97 .200

Total 42.435 98 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture f. Dependent Variable: Loyalty

180

6.9.3 Customer Satisfaction (CS)

Table 6.97 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

181

In Table 6.98, the first model gives 56% R Square; it means that Customer Loyalty is the most influential variable on Customer Satisfaction (CS). The second model gives 62% R Square; it means that Customer Perceived Value (PV) influences Customer Satisfaction (CS). The third model gives 69% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Satisfaction (CS). The fourth model gives 71% R Square; it means that Customer Trust influences Customer Satisfaction (CS). The fifth model gives 74% R Square; it means that Customer Culture influences Customer Satisfaction (CS).

Table 6.98 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .811 a .565 .526 .37251 2 .819 b .625 .456 .36251 3 .822 c .699 .569 .35487 4 .848 d .710 .785 .34521 5 .865 e .742 .521 .33265 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture

182

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Satisfaction (CS) as F value that is 171.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.99.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Satisfaction (CS) as F value that is 162.252 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.99.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Satisfaction (CS) as F value that is 148.215 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.99.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Satisfaction (CS) as F value that is 81.269 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.99.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Satisfaction (CS) as F value that is 74.584 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.99.

183

Table 6.99 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 31.112 1 31.112 171.251 .000 a

Residual 11.412 98 .156

Total 42.524 99

2 Regression 32.521 2 15.251 162.252 .000 b

Residual 10.003 97 .158

Total 42.524 98

3 Regression 33.215 3 11.548 148.215 .000 c

Residual 9.309 96 .108

Total 42.524 97

4 Regression 34.589 4 9.259 81.269 .000 d

Residual 7.935 98 .165

Total 42.524 99

5 Regression 36.264 5 8.112 74.584 .000 e

Residual 6.26 97 .1004

Total 42.524 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture f. Dependent Variable: CS

184

6.9.4 Customer Trust

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Culture have a significant effect on Dependent Variable Customer Trust and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.100.

Table 6.100 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: Trust

185

In Table 6.101, the first model gives 62% R Square; it means that Customer Loyalty is the most influential variable on Customer Trust. The second model gives 68% R Square; it means that Customer Perceived Value (PV) influences Customer Trust. The third model gives 72% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Trust. The fourth model gives 75% R Square; it means that Customer Satisfaction (CS) influences Customer Trust. The fifth model gives 79% R Square; it means that Customer Culture influences Customer Trust.

6.101 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .811 a .621 .465 .38542 2 .819 b .689 .488 .37856 3 .825 c .721 .512 .36235 4 .836 d .755 .536 .35214 5 .854 e .798 .598 .34586 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture

186

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Trust as F value that is 179.254 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.102.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Trust as F value that is 175.214 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.102.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Trust as F value that is 171.022 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.102.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Trust as F value that is 96.021 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.102.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Trust as F value that is 75.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.102.

187

Table 6.102 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 31.524 1 31.524 179.254 .000 a

Residual 10.254 97 .021

Total 41.778 98

2 Regression 32.521 2 12.258 175.214 .000 b

Residual 9.257 98 .102

Total 41.778 99

3 Regression 34.256 3 11.251 171.022 .000 c

Residual 7.522 98 .125

Total 41.778 99

4 Regression 36.254 4 9.215 96.021 .000 d

Residual 5.524 96 .445

Total 41.778 97

5 Regression 39.568 5 8.215 75.251 .000 e

Residual 2.21 97 .211

Total 41.778 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture f. Dependent Variable: Trust

188

6.9.5 Customer Culture

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Trust have a significant effect on Dependent Variable Customer Culture and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.103.

Table 6.103 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). a. Dependent Variable: Culture

189

In Table 6.104, the first model gives 51% R Square; it means that Customer Loyalty is the most influential variable on Customer Culture. The second model gives 58% R Square; it means that Customer Perceived Value (PV) influences Customer Culture. The third model gives 65% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Culture. The fourth model gives 71% R Square; it means that Customer Satisfaction (CS) influences Customer Culture. The fifth model gives 75% R Square; it means that Customer Trust influences Customer Culture.

Table 6.104 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .801 a .514 .456 .37526 2 .814 b .589 .526 .36256 3 .820 c .652 .425 .35142 4 .835 d .712 .489 .34852 5 .846 e .756 .526 .32654 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust

190

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Culture as F value that is 184.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.105.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Culture as F value that is 172.526 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.105.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Culture as F value that is 154.265 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.105.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Culture as F value that is 89.235 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.105.

Overall regression for model 5 is significant it means that Customer Trust has a significant influence on Customer Culture as F value that is 80.569 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.105.

191

Table 6.105 ANOVA f

Sum of Model Squares Df Mean Square F Sig.

1 Regression 33.521 1 33.521 184.256 .000 a

Residual 10.589 98 .121

Total 44.11 99

2 Regression 34.209 2 11.521 172.526 .000 b

Residual 9.901 97 .122

Total 44.11 98

3 Regression 35.654 3 10.221 154.265 .000 c

Residual 8.456 98 .153

Total 44.11 99

4 Regression 36.654 4 9.214 89.235 .000 d

Residual 7.456 98 .242

Total 44.11 99

5 Regression 37.444 5 8.256 80.569 .000 e

Residual 6.666 96 .152

Total 44.11 97 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust f. Dependent Variable: Culture

192

6.9.6 Customer Switching Barriers (CSB)

Table 6.106 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

193

In Table 6.107, the first model gives 54% R Square; it means that Customer Loyalty is the most influential variable on Customer-Switching Barriers (CSB). The second model gives 61% R Square; it means that Customer Satisfaction (CS) influences Customer-Switching Barriers (CSB). The third model gives 68% R Square; it means that Customer Perceived Value (PV) influences Customer-Switching Barriers (CSB). The fourth model gives 71% R Square; it means that Customer Trust influences Customer-Switching Barriers (CSB). The fifth model gives 75% R Square; it means that Customer Culture influences Customer-Switching Barriers (CSB).

Table 6.107 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .812 a .548 .548 .39202 2 .825 b .612 .598 .38562 3 .836 c .689 .698 .37254 4 .849 d .712 .702 .36255 5 .878 e .758 .788 .35215 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty , CS c. Predictors: (Constant), Loyalty , CS, PV d. Predictors: (Constant), Loyalty , CS, PV, Trust e. Predictors: (Constant), Loyalty , CS, PV, Trust, Culture

194

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer-Switching Barriers (CSB) as F value that is 175.584 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.108.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 162.247 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.108.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 140.569 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.108.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer-Switching Barriers (CSB) as F value that is 88.547 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.108.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer-Switching Barriers (CSB) as F value that is 74.569 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.108.

195

Table 6.108 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.586 1 30.586 175.584 .000 a

Residual 12.589 98 .128

Total 43.175 99

2 Regression 33.526 2 15.565 162.247 .000 b

Residual 9.649 96 .132

Total 43.175 97

3 Regression 34.526 3 11.254 140.569 .000 c

Residual 8.649 97 .035

Total 43.175 98

4 Regression 35.259 4 9.256 88.547 .000 d

Residual 7.916 98 .058

Total 43.175 99

5 Regression 36.589 5 7.658 74.569 .000 e

Residual 6.586 98 .128

Total 43.175 99 a. Predictors: (Constant), CS b. Predictors: (Constant), CS, PV c. Predictors: (Constant), CS, PV, CULTURE d. Predictors: (Constant), CS, PV, CULTURE, TRUST e. Predictors: (Constant), CS, PV, CULTURE, TRUST, LOYALTY f. Dependent Variable: CSB

196

6.10 MULTIVARIATE DATA ANALYSIS – MEEZAN BANK LIMITED, PAKISTAN

The first component Customer Loyalty explains 41% variance of the total variation alone. The second component Customer Satisfaction (CS) explains 11% variance of the total variation alone. The first & second components together explain 52% variance of the total variation. The third component Customer Perceived Value (PV) explains 9% variance of the total variation alone. The second and third components together explain 62% variance of the total variation. The fourth component Customer Trust explains 16% variance of the total variation alone. The third and fourth components together explain 79% variance of the total variation. The fifth component Customer- Switching Barriers (CSB) explains 5% variance of the total variation alone. The fourth and fifth components together explain 84% variance of the total variation. Finally, sixth component Customer Culture explains 15% variance of the total variation alone. The fifth and sixth components together explain 100% variance of the total variation as shown in Table 6.109.

Table 6.109 Total Variance Explained

Initial Eigenvalues Extraction Sums of Squared Loadings

Component Total % of Variance Cumulative % Total % of Variance Cumulative %

1 1.989 41.461 41.461 1.989 41.461 41.461 2 1.214 11.024 52.485 1.214 11.024 11.024 3 .525 9.845 62.33 4 .458 16.889 79.219 5 .754 5.255 84.474 6 .789 15.526 100.000

Extraction Method: Principal Component Analysis.

197

6.11 REGRESSION MODEL – MEEZAN BANK LIMITED, PAKISTAN

6.11.1 Customer Perceived Value (PV)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .458 as shown in Table 6.110.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .369, Customer Loyalty is .354, and constant is .195 as shown in Table 6.110.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).401, Customer Satisfaction (CS) is .202, Customer Loyalty is .354, and constant is .101 as shown in Table 6.110.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .369, Customer-Switching Barriers (CSB) is .199, Customer Satisfaction (CS) is .424, Customer Loyalty is .511, and constant is .421 as shown in Table 6.110.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .295, Customer Trust is .398, Customer-Switching Barriers (CSB) is .199, Customer Satisfaction (CS) is .248, Customer Loyalty is .358, and constant is .354 as shown in Table 6.110.

198

Table 6.110 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.115 .154 4.521 .000

Loyalty .458 .195 9.245 .000

2 (Constant) .195 .195 1.001 .000

Loyalty .354 .011 10.265 .000

CS .369 .245 5.021 .000

3 (Constant) .101 .156 .336 .000

Loyalty .354 .369 5.215 .000

CS .202 .321 4.585 .000

CSB .401 .287 2.01 .000

4 (Constant) .421 .322 1.032 .000

Loyalty .511 .100 5.216 .000

CS .424 .321 3.215 .000

CSB .199 .308 3.265 .000

Trust .369 .187 1.023 .000

5 (Constant) .354 .226 1.452 .000

Loyalty .358 .104 5.225 .000

CS .248 .365 3.265 .000

CSB .199 .015 2.548 .000

Trust .398 .227 2.458 .000

Culture .295 .501 1.569 .000 a. Dependent Variable: PV

199

6.11.2 Customer Loyalty

In the second regression model, Independent Variables Customer-Switching Barriers (CSB) and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .357, Customer-Switching Barriers (CSB) is .324, and constant is .325 as shown in Table 6.111.

In the third regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).375, Customer Satisfaction (CS) is .278, Customer-Switching Barriers (CSB) is .412, and constant is .289 as shown in Table 6.111.

In the fourth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .396, Customer Perceived Value (PV) is .348, Customer Satisfaction (CS) is .289, Customer-Switching Barriers (CSB) is .440, and constant is .345 as shown in Table 6.111.

In the fifth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .398, Customer Trust is .378, Customer Perceived Value (PV) is .356, Customer Satisfaction (CS) is .284, Customer-Switching Barriers (CSB) is .311, and constant is .326 as shown in Table 6.111.

200

Table 6.111 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.004 .195 4.265 .000

CSB .521 .195 10.215 .000

2 (Constant) .325 .321 1.215 .000

CSB .324 .285 10.639 .000

CS .357 .306 4.896 .000

3 (Constant) .289 .122 .421 .000

CSB .412 .331 9.236 .000

CS .278 .352 4.112 .000

PV .375 .141 3.221 .000

4 (Constant) .345 .402 2.154 .000

CSB .440 .141 6.215 .000

CS .289 .145 4.112 .000

PV .348 .365 3.596 .000

Trust .396 .385 1.254 .000

5 (Constant) .326 .155 2.589 .000

CSB .311 .021 7.589 .000

CS .284 .105 3.965 .000

PV .356 .126 2.021 .000

Trust .378 .102 2.115 .000

Culture .398 .201 2.021 .000 a. Dependent Variable: Loyalty

201

6.11.3 Customer Satisfaction (CS)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .452 as shown in Table 6.112.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .342, Customer Loyalty is .400, and constant is .159 as shown in Table 6.112.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).269, Customer Perceived Value (PV) is .198, Customer Loyalty is .325, and constant is .215 as shown in Table 6.112.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .365, Customer-Switching Barriers (CSB) is .185, Customer Perceived Value (PV) is .287, Customer Loyalty is .341, and constant is .321 as shown in Table 6.112.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .202, Customer Trust is .165, Customer-Switching Barriers (CSB) is .145, Customer Perceived Value (PV) is .247, Customer Loyalty is .365, and constant is .215 as shown in Table 6.112.

202

Table 6.112 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.221 .145 4.452 .000

Loyalty .452 .001 9.236 .000

2 (Constant) .159 .021 2.145 .000

Loyalty .400 .002 8.215 .000

PV .342 .001 5.215 .000

3 (Constant) .215 .165 .251 .000

Loyalty .325 .025 5.215 .000

PV .198 .045 5.321 .000

CSB .269 .021 2.652 .000

4 (Constant) .321 .198 2.452 .000

Loyalty .341 .045 3.251 .000

PV .287 .066 2.514 .000

CSB .185 .078 3.256 .000

Trust .365 .065 2.362 .000

5 (Constant) .215 .202 2.541 .000

Loyalty .365 .054 6.526 .000

PV .247 .025 2.216 .000

CSB .145 .035 2.021 .000

Trust .165 .030 2.452 .000

Culture .202 .302 1.785 .000 a. Dependent Variable: CS

203

6.11.4 Customer Trust

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .356 as shown in Table 6.113.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .314, Customer Loyalty is .362, and constant is .201 as shown in Table 6.113.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).208, Customer Perceived Value (PV) is .184, Customer Loyalty is .369, and constant is .289 as shown in Table 6.113.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .101, Customer-Switching Barriers (CSB) is .263, Customer Perceived Value (PV) is .201, Customer Loyalty is .278, and constant is .201 as shown in Table 6.113.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Culture and the constant are significant, the coefficient of Customer Culture is .201, Customer Satisfaction (CS) is .121, Customer-Switching Barriers (CSB) is .215, Customer Perceived Value (PV) is .224, Customer Loyalty is .216, and constant is .265 as shown in Table 6.113.

204

Table 6.113 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.652 .100 5.256 .000

Loyalty .356 .045 13.251 .000

2 (Constant) .201 .151 1.253 .000

Loyalty .362 .022 12.562 .000

PV .314 .023 4.521 .000

3 (Constant) .289 .287 .452 .000

Loyalty .369 .020 10.256 .000

PV .184 .114 4.256 .000

CSB .208 .174 4.526 .000

4 (Constant) .201 .230 2.562 .000

Loyalty .278 .354 4.526 .000

PV .201 .025 1.023 .000

CSB .263 .045 2.215 .000

CS .101 .056 1.021 .000

5 (Constant) .265 .201 2.558 .000

Loyalty .216 .056 4.256 .000

PV .224 .041 2.596 .000

CSB .215 .065 1.252 .000

CS .121 .052 1.089 .000

Culture .201 .425 2.562 .000 a. Dependent Variable: Trust

205

6.11.5 Customer Culture

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .215 as shown in Table 6.114.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .225, Customer Loyalty is .365, and constant is .452 as shown in Table 6.114.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).201, Customer Perceived Value (PV) is .102, Customer Loyalty is .365, and constant is .289 as shown in Table 6.114.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .154, Customer-Switching Barriers (CSB) is .201, Customer Perceived Value (PV) is .232, Customer Loyalty is .289, and constant is .176 as shown in Table 6.114.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Trust and the constant are significant, the coefficient of Customer Trust is .142, Customer Satisfaction (CS) is .251, Customer-Switching Barriers (CSB) is .452, Customer Perceived Value (PV) is .115, Customer Loyalty is .256, and constant is .215 as shown in Table 6.114.

206

Table 6.114 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.852 .215 3.145 .000

Loyalty .215 .452 9.321 .000

2 (Constant) .452 .125 1.021 .000

Loyalty .365 .021 8.012 .000

PV .225 .030 5.045 .000

3 (Constant) .289 .202 .322 .000

Loyalty .365 .045 6.425 .000

PV .102 .132 4.021 .000

CSB .201 .201 3.114 .000

4 (Constant) .176 .266 2.215 .000

Loyalty .289 .315 5.102 .000

PV .232 .012 3.311 .000

CSB .201 .037 3.002 .000

CS .154 .041 2.101 .000

5 (Constant) .215 .242 3.125 .000

Loyalty .256 .033 5.251 .000

PV .115 .012 1.115 .000

CSB .452 .033 2.321 .000

CS .251 .015 2.121 .000

Trust .142 .402 1.222 .000 a. Dependent Variable: Culture

207

6.11.6 Customer Switching Barriers (CSB)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant, the coefficient of Customer Loyalty is .322 as shown in Table 6.115.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .312, Customer Loyalty is .299, and constant is .502 as shown in Table 6.115.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).401, Customer Satisfaction (CS) is .225, Customer Loyalty is .365, and constant is .177 as shown in Table 6.115.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Trust is .184, Customer Perceived Value (PV) is .189, Customer Satisfaction (CS) is .215, Customer Loyalty is .325, and constant is .341 as shown in Table 6.115.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .226, Customer Trust is .141, Customer Perceived Value (PV) is .152, Customer Satisfaction (CS) is .245, Customer Loyalty is .398, and constant is .325 as shown in Table 6.115.

208

Table 6.115 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.251 .162 5.526 .000

Loyalty .322 .012 14.215 .000

2 (Constant) .502 .202 2.021 .000

Loyalty .299 .032 12.021 .000

CS .312 .051 4.256 .000

3 (Constant) .177 .215 .425 .000

Loyalty .365 .025 10.252 .000

CS .225 .041 4.002 .000

PV .401 .063 4.132 .000

4 (Constant) .341 .254 1.232 .000

Loyalty .325 .010 7.014 .000

CS .215 .014 4.121 .000

PV .189 .022 3.121 .000

Trust .184 .012 1.236 .000

5 (Constant) .325 .215 1.252 .000

Loyalty .398 .021 7.215 .000

CS .245 .050 4.251 .000

PV .152 .013 3.112 .000

Trust .141 .062 2.332 .000

Culture .226 .148 1.121 .000 a. Dependent Variable: CSB

209

6.12 STAGE-WISE MULTIPLE REGRESSION – MEEZAN BANK LIMITED, PAKISTAN

6.12.1 Customer Perceived Value (PV)

Table 6.116 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100).

210

In Table 6.117, the first model gives 56% R Square; it means that Customer Loyalty is the most influential variable on Customer-Perceived Value (PV). The second model gives 57% R Square; it means that Customer Satisfaction (CS) influences Customer-Perceived Value (PV). The third model gives 65% R Square; it means that Customer-Switching Barriers (CSB) influences Customer-Perceived Value (PV). The fourth model gives 69% R Square; it means that Customer Trust influences Customer-Perceived Value (PV). The fifth model gives 78% R Square; it means that Customer Culture influences Customer-Perceived Value (PV).

Table 6.117 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .812 a .562 .562 .39524 2 .815 b .578 .599 .38154 3 .825 c .658 .625 .39652 4 .874 d .699 .687 .40215 5 .885 e .785 .745 .41214 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture

211

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Perceived Value (PV) as F value that is 175.214 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.118.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Perceived Value (PV) as F value that is 166.214 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.118.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Perceived Value (PV) as F value that is 141.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.118.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Perceived Value (PV) as F value that is 132.652 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.118.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Perceived Value (PV) as F value that is 80.269 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.118.

212

Table 6.118 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.251 1 30.251 175.214 .000 a

Residual 9.215 98 .128

Total 39.466 99

2 Regression 30.889 2 13.214 166.214 .000 b

Residual 8.577 97 .025

Total 39.466 98

3 Regression 31.251 3 10.214 141.251 .000 c

Residual 8.215 97 .125

Total 39.466 98

4 Regression 32.125 4 8.125 132.652 .000 d

Residual 7.341 98 .198

Total 39.466 99

5 Regression 33.154 5 7.542 80.269 .000 e

Residual 6.312 97 .165

Total 39.466 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture f. Dependent Variable: PV

213

6.12.2 Customer Loyalty

Table 6.119 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

214

In Table 6.120, the first model gives 56% R Square; it means that Customer-Switching Barriers (CSB) is the most influential variable on Customer Loyalty. The second model gives 63% R Square; it means that Customer Satisfaction (CS) influences Customer Loyalty. The third model gives 68% R Square; it means that Customer Perceived Value (PV) influences Customer Loyalty. The fourth model gives 72% R Square; it means that Customer Trust influences Customer Loyalty. The fifth model gives 75% R Square; it means that Customer Culture influences Customer Loyalty.

Table 6.120 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .811 a .562 .396 .39652 2 .832 b .632 .485 .38542 3 .841 c .689 .512 .36325 4 .848 d .721 .522 .34251 5 .859 e .758 .547 .33269 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture

215

The overall regression for model 1 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Loyalty as F value that is 164.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.121.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Loyalty as F value that is 145.269 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.121.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Loyalty as F value that is 131.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.121.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Loyalty as F value that is 105.251 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.121.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Loyalty as F value that is 73.652 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.121.

216

Table 6.121 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 29.256 1 29.256 164.251 .000 a

Residual 9.251 97 .121

Total 38.507 98

2 Regression 30.251 2 9.214 145.269 .000 b

Residual 8.256 98 .112

Total 38.507 99

3 Regression 30.998 3 7.521 131.251 .000 c

Residual 7.509 98 .021

Total 38.507 99

4 Regression 31.215 4 6.231 105.251 .000 d

Residual 7.292 97 .125

Total 38.507 98

5 Regression 31.889 5 5.215 73.652 .000 e

Residual 6.618 98 .185

Total 38.507 99 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture f. Dependent Variable: Loyalty

217

6.12.3 Customer Satisfaction (CS)

Table 6.122 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

218

In Table 6.123, the first model gives 45% R Square; it means that Customer Loyalty is the most influential variable on Customer Satisfaction (CS). The second model gives 55% R Square; it means that Customer Perceived Value (PV) influences Customer Satisfaction (CS). The third model gives 69% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Satisfaction (CS). The fourth model gives 78% R Square; it means that Customer Trust influences Customer Satisfaction (CS). The fifth model gives 82% R Square; it means that Customer Culture influences Customer Satisfaction (CS).

Table 6.123 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .854 a .452 .425 .38251 2 .865 b .558 .325 .37548 3 .875 c .699 .458 .36253 4 .879 d .785 .625 .35144 5 .885 e .825 .546 .34562 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture

219

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Satisfaction (CS) as F value that is 181.215 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.124.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Satisfaction (CS) as F value that is 167.589 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.124.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Satisfaction (CS) as F value that is 145.589 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.124.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Satisfaction (CS) as F value that is 77.562 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.124.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Satisfaction (CS) as F value that is 66.542 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.124.

220

Table 6.124 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 28.251 1 28.251 181.215 .000 a

Residual 9.265 97 .215

Total 37.516 98

2 Regression 29.265 2 12.215 167.589 .000 b

Residual 8.251 98 .121

Total 37.516 99

3 Regression 30.215 3 10.562 145.589 .000 c

Residual 7.301 97 .021

Total 37.516 98

4 Regression 31.698 4 8.256 77.562 .000 d

Residual 5.818 98 .221

Total 37.516 99

5 Regression 32.485 5 7.263 66.542 .000 e

Residual 5.031 98 .125

Total 37.516 99 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture f. Dependent Variable: CS

221

6.12.4 Customer Trust

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Culture have a significant effect on Dependent Variable Customer Trust and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.125.

Table 6.125 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: Trust

222

In Table 6.126, the first model gives 66% R Square; it means that Customer Loyalty is the most influential variable on Customer Trust. The second model gives 69% R Square; it means that Customer Perceived Value (PV) influences Customer Trust. The third model gives 74% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Trust. The fourth model gives 78% R Square; it means that Customer Satisfaction (CS) influences Customer Trust. The fifth model gives 81% R Square; it means that Customer Culture influences Customer Trust.

Table 6.126 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .823 a .662 .362 .39652 2 .845 b .698 .345 .38542 3 .878 c .741 .425 .36256 4 .892 d .789 .468 .34521 5 .952 e .812 .547 .33265 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture

223

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Trust as F value that is 166.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.127.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Trust as F value that is 152.142 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.127.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Trust as F value that is 137.586 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.127.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Trust as F value that is 85.265 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.127.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Trust as F value that is 71.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.127.

224

Table 6.127 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 33.251 1 33.251 166.256 .000 a

Residual 8.551 98 .112

Total 41.802 99

2 Regression 34.215 2 10.254 152.142 .000 b

Residual 7.587 97 .265

Total 41.802 98

3 Regression 35.212 3 9.235 137.586 .000 c

Residual 6.59 98 .102

Total 41.802 99

4 Regression 36.015 4 8.425 85.265 .000 d

Residual 5.805 98 .325

Total 41.802 99

5 Regression 37.521 5 7.256 71.256 .000 e

Residual 4.281 97 .198

Total 41.802 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture f. Dependent Variable: Trust

225

6.12.5 Customer Culture

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Trust have a significant effect on Dependent Variable Customer Culture and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.128.

Table 6.128 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). a. Dependent Variable: Culture

226

In Table 6.129, the first model gives 45% R Square; it means that Customer Loyalty is the most influential variable on Customer Culture. The second model gives 44% R Square; it means that Customer Perceived Value (PV) influences Customer Culture. The third model gives 56% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Culture. The fourth model gives 63% R Square; it means that Customer Satisfaction (CS) influences Customer Culture. The fifth model gives 68% R Square; it means that Customer Trust influences Customer Culture.

Table 6.129 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .822 a .452 .389 .38562 2 .835 b .442 .452 .36251 3 .842 c .562 .489 .35265 4 .859 d .632 .526 .35125 5 .868 e .688 .547 .34521 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust

227

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Culture as F value that is 168.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.130.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Culture as F value that is 154.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.130.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Culture as F value that is 144.333 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.130.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Culture as F value that is 87.521 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.130.

Overall regression for model 5 is significant it means that Customer Trust has a significant influence on Customer Culture as F value that is 75.215 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.130.

228

Table 6.130 ANOVA f

Sum of Model Squares Df Mean Square F Sig.

1 Regression 30.521 1 30.521 168.256 .000 a

Residual 9.251 97 .221

Total 39.772 98

2 Regression 31.521 2 10.252 154.256 .000 b

Residual 12.589 98 .115

Total 44.11 99

3 Regression 32.252 3 9.235 144.333 .000 c

Residual 11.858 98 .102

Total 44.11 99

4 Regression 33.256 4 8.526 87.521 .000 d

Residual 10.854 97 .218

Total 44.11 98

5 Regression 34.241 5 7.562 75.215 .000 e

Residual 9.869 98 .089

Total 44.11 99 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust f. Dependent Variable: Culture

229

6.12.6 Customer Switching Barriers (CSB)

Table 6.131 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

230

In Table 6.132, the first model gives 55% R Square; it means that Customer Loyalty is the most influential variable on Customer-Switching Barriers (CSB). The second model gives 58% R Square; it means that Customer Satisfaction (CS) influences Customer-Switching Barriers (CSB). The third model gives 64% R Square; it means that Customer Perceived Value (PV) influences Customer-Switching Barriers (CSB). The fourth model gives 67% R Square; it means that Customer Trust influences Customer-Switching Barriers (CSB). The fifth model gives 85% R Square; it means that Customer Culture influences Customer-Switching Barriers.

Table 6.132 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .852 a .552 .452 .39236 2 .862 b .589 .488 .38452 3 .885 c .647 .596 .36325 4 .892 d .678 .612 .35485 5 .897 e .852 .698 .35215 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty , CS c. Predictors: (Constant), Loyalty , CS, PV d. Predictors: (Constant), Loyalty , CS, PV, Trust e. Predictors: (Constant), Loyalty , CS, PV, Trust, Culture

231

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer-Switching Barriers (CSB) as F value that is 162.221 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.133.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 139.521 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.133.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 122.521 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.133.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer-Switching Barriers (CSB) as F value that is 81.215 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.133.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer-Switching Barriers (CSB) as F value that is 71.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.133.

232

Table 6.133 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 28.251 1 28.251 162.221 .000 a

Residual 9.215 97 .021

Total 37.466 98

2 Regression 29.215 2 10.251 139.521 .000 b

Residual 8.251 96 .102

Total 37.466 97

3 Regression 30.256 3 9.256 122.521 .000 c

Residual 7.21 98 .021

Total 37.466 99

4 Regression 31.252 4 8.542 81.215 .000 d

Residual 6.214 98 .044

Total 37.466 99

5 Regression 32.236 5 7.263 71.256 .000 e

Residual 5.23 97 .104

Total 37.466 98 a. Predictors: (Constant), CS b. Predictors: (Constant), CS, PV c. Predictors: (Constant), CS, PV, CULTURE d. Predictors: (Constant), CS, PV, CULTURE, TRUST e. Predictors: (Constant), CS, PV, CULTURE, TRUST, LOYALTY f. Dependent Variable: CSB

233

6.13 MULTIVARIATE DATA ANALYSIS - HABIB BANK LIMITED, PAKISTAN

The first component Customer Loyalty explains 55% variance of the total variation alone. The second component Customer Satisfaction (CS) explains 17% variance of the total variation alone. The first & second components together explain 73% variance of the total variation. The third component Customer Perceived Value (PV) explains 10% variance of the total variation alone. The second and third components together explain 83% variance of the total variation. The fourth component Customer Trust explains 7% variance of the total variation alone. The third and fourth components together explain 91% variance of the total variation. The fifth component Customer-Switching Barriers (CSB) explains 6% variance of the total variation alone. The fourth and fifth components together explain 97% variance of the total variation. Finally, sixth component Customer Culture explains 2% variance of the total variation alone. The fifth and sixth components together explain 100% variance of the total variation as shown in Table 6.134. Table 6.134 Total Variance Explained

Initial Eigenvalues Extraction Sums of Squared Loadings

Component Total % of Variance Cumulative % Total % of Variance Cumulative %

1 3.346 55.764 55.764 3.346 55.764 55.764 2 1.041 17.345 73.109 1.041 17.345 73.109 3 .637 10.616 83.725 4 .456 7.594 91.319 5 .380 6.340 97.658 6 .140 2.342 100.000

Extraction Method: Principal Component Analysis.

234

6.14 REGRESSION MODEL - HABIB BANK LIMITED, PAKISTAN

6.14.1 Customer Perceived Value (PV)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .694 as shown in Table 6.135.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .334, Customer Loyalty is .496, and constant is .299 as shown in Table 6.135.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).211, Customer Satisfaction (CS) is .281, Customer Loyalty is .448, and constant is .121 as shown in Table 6.135.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .165, Customer-Switching Barriers (CSB) is .231, Customer Satisfaction (CS) is .218, Customer Loyalty is .332, and constant is .259 as shown in Table 6.135.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .198, Customer Trust is .175, Customer-Switching Barriers (CSB) is .199, Customer Satisfaction (CS) is .223, Customer Loyalty is .227, and constant is .319 as shown in Table 6.135.

235

Table 6.135 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.095 .182 5.764 .000

Loyalty .694 .055 12.987 .000

2 (Constant) .299 .198 1.769 .000

Loyalty .496 .049 11.212 .000

CS .334 .057 5.656 .000

3 (Constant) .121 .213 .443 .000

Loyalty .448 .041 7.345 .000

CS .281 .053 4.321 .000

CSB .211 .052 3.998 .000

4 (Constant) .259 .212 1.001 .000

Loyalty .332 .038 6.294 .000

CS .218 .055 4.021 .000

CSB .231 .073 3.358 .000

Trust .165 .042 2.432 .000

5 (Constant) .319 .299 2.336 .000

Loyalty .227 .048 7.453 .000

CS .223 .058 4.321 .000

CSB .199 .065 2.786 .000

Trust .175 .076 2.321 .000

Culture .198 .997 2.001 .000 a. Dependent Variable: PV

236

6.14.2 Customer Loyalty

In the first regression model, Independent Variables Customer-Switching Barriers (CSB) and the constant both are significant; the coefficient of Customer-Switching Barriers (CSB) is .663 as shown in Table 6.136.

In the second regression model, Independent Variables Customer-Switching Barriers (CSB) and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .339, Customer-Switching Barriers (CSB) is .497, and constant is .299 as shown in Table 6.136.

In the third regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).197, Customer Satisfaction (CS) is .198, Customer-Switching Barriers (CSB) is .441, and constant is .129 as shown in Table 6.136.

In the fourth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .131, Customer Perceived Value (PV) is .299, Customer Satisfaction (CS) is .220, Customer-Switching Barriers (CSB) is .355, and constant is .311 as shown in Table 6.136.

In the fifth regression model, Independent Variables Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .202, Customer Trust is .130, Customer Perceived Value (PV) is .199, Customer Satisfaction (CS) is .239, Customer-Switching Barriers (CSB) is .421, and constant is .318 as shown in Table 6.136.

237

Table 6.136 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.095 .190 4.665 .000

CSB .663 .044 12.098 .000

2 (Constant) .299 .202 1.778 .000

CSB .497 .039 10.986 .000

CS .339 .057 5.023 .000

3 (Constant) .129 .226 .499 .000

CSB .441 .043 8.001 .000

CS .198 .055 4.657 .000

PV .197 .059 3.998 .000

4 (Constant) .311 .212 1.221 .000

CSB .355 .041 7.021 .000

CS .220 .044 4.231 .000

PV .299 .066 3.222 .000

Trust .131 .050 2.002 .000

5 (Constant) .318 .301 2.321 .000

CSB .421 .040 7.291 .000

CS .239 .049 4.332 .000

PV .199 .063 2.765 .000

Trust .130 .047 2.234 .000

Culture .202 .101 2.034 .000 a. Dependent Variable: Loyalty

238

6.14.3 Customer Satisfaction (CS)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .567 as shown in Table 6.137.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .331, Customer Loyalty is .434, and constant is .238 as shown in Table 6.137.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).209, Customer Perceived Value (PV) is .245, Customer Loyalty is .345, and constant is .221 as shown in Table 6.137.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Trust are significant and constant is also significant, the coefficient of Customer Trust is .146, Customer-Switching Barriers (CSB) is .226, Customer Perceived Value (PV) is .229, Customer Loyalty is .303, and constant is .232 as shown in Table 6.137.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .154, Customer Trust is .128, Customer-Switching Barriers (CSB) is .190, Customer Perceived Value (PV) is .287, Customer Loyalty is .234, and constant is .299 as shown in Table 6.137.

239

Table 6.137 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.121 .176 4.876 .000

Loyalty .567 .055 11.857 .000

2 (Constant) .238 .198 1.768 .000

Loyalty .434 .034 10.543 .000

PV .331 .055 5.541 .000

3 (Constant) .221 .200 .398 .000

Loyalty .345 .038 6.213 .000

PV .245 .043 4.333 .000

CSB .209 .038 2.765 .000

4 (Constant) .232 .247 2.546 .000

Loyalty .303 .021 5.453 .000

PV .229 .054 3.998 .000

CSB .226 .073 3.767 .000

Trust .146 .025 2.221 .000

5 (Constant) .299 .267 2.001 .000

Loyalty .234 .058 6.553 .000

PV .287 .054 3.324 .000

CSB .190 .059 2.435 .000

Trust .128 .071 2.021 .000

Culture .154 .870 1.971 .000 a. Dependent Variable: CS

240

6.14.4 Customer Trust

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .465 as shown in Table 6.138.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .309, Customer Loyalty is .399, and constant is .212 as shown in Table 6.138.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).218, Customer Perceived Value (PV) is .198, Customer Loyalty is .321, and constant is .202 as shown in Table 6.138.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .132, Customer-Switching Barriers (CSB) is .200, Customer Perceived Value (PV) is .211, Customer Loyalty is .323, and constant is .243 as shown in Table 6.138.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Culture and the constant are significant, the coefficient of Customer Culture is .232, Customer Satisfaction (CS) is .112, Customer-Switching Barriers (CSB) is .188, Customer Perceived Value (PV) is .223, Customer Loyalty is .213, and constant is .343 as shown in Table 6.138.

241

Table 6.138 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.009 .198 4.112 .000

Loyalty .465 .049 10.978 .000

2 (Constant) .212 .179 1.656 .000

Loyalty .399 .012 9.898 .000

PV .309 .043 5.434 .000

3 (Constant) .202 .199 .377 .000

Loyalty .321 .022 6.003 .000

PV .198 .123 4.094 .000

CSB .218 .212 2.565 .000

4 (Constant) .243 .254 2.876 .000

Loyalty .323 .321 5.453 .000

PV .211 .044 3.454 .000

CSB .200 .048 3.675 .000

CS .132 .022 2.333 .000

5 (Constant) .343 .212 2.121 .000

Loyalty .213 .054 6.232 .000

PV .223 .043 3.435 .000

CSB .188 .023 2.232 .000

CS .112 .057 2.121 .000

Culture .232 .546 1.232 .000 a. Dependent Variable: Trust

242

6.14.5 Customer Culture

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .343 as shown in Table 6.139.

In the second regression model, Independent Variables Customer Loyalty and Customer Perceived Value (PV) both are significant and constant is also significant, the coefficient of Customer Perceived Value (PV) is .403, Customer Loyalty is .233, and constant is .432 as shown in Table 6.139.

In the third regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), and Customer-Switching Barriers (CSB) are significant and constant is also significant, the coefficient of Customer-Switching Barriers (CSB).204, Customer Perceived Value (PV) is .177, Customer Loyalty is .434, and constant is .199 as shown in Table 6.139.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), and Customer Satisfaction (CS) are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .122, Customer-Switching Barriers (CSB) is .210, Customer Perceived Value (PV) is .203, Customer Loyalty is .321, and constant is .202 as shown in Table 6.139.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), Customer Trust and the constant are significant, the coefficient of Customer Trust is .233, Customer Satisfaction (CS) is .109, Customer-Switching Barriers (CSB) is .167, Customer Perceived Value (PV) is .202, Customer Loyalty is .199, and constant is .340 as shown in Table 6.139.

243

Table 6.139 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.122 .188 3.567 .000

Loyalty .343 .037 9.322 .000

2 (Constant) .432 .169 1.232 .000

Loyalty .233 .011 8.765 .000

PV .403 .038 4.665 .000

3 (Constant) .199 .198 .312 .000

Loyalty .434 .013 5.998 .000

PV .177 .125 4.001 .000

CSB .204 .221 2.432 .000

4 (Constant) .202 .234 2.221 .000

Loyalty .321 .329 5.021 .000

PV .203 .042 3.223 .000

CSB .210 .023 3.121 .000

CS .122 .017 2.112 .000

5 (Constant) .340 .256 2.021 .000

Loyalty .199 .043 6.002 .000

PV .202 .039 3.232 .000

CSB .167 .045 2.223 .000

CS .109 .041 1.998 .000

Trust .233 .453 1.675 .000 a. Dependent Variable: Culture

244

6.14.6 Customer Switching Barriers (CSB)

In the first regression model, Independent Variables Customer Loyalty and the constant both are significant; the coefficient of Customer Loyalty is .714 as shown in Table 6.140.

In the second regression model, Independent Variables Customer Loyalty and Customer Satisfaction (CS) both are significant and constant is also significant, the coefficient of Customer Satisfaction (CS) is .352, Customer Loyalty is .588, and constant is .390 as shown in Table 6.140.

In the third regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), and Customer Perceived Value (PV) are significant and constant is also significant, the coefficient of Customer Perceived Value (PV).294, Customer Satisfaction (CS) is .290, Customer Loyalty is .474, and constant is .130 as shown in Table 6.140.

In the fourth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), and Customer Trust are significant and constant is also significant, the coefficient of Trust is .177, Customer Perceived Value (PV) is .246, Customer Satisfaction (CS) is .270, Customer Loyalty is .421, and constant is .325 as shown in Table 6.140.

In the fifth regression model, Independent Variables Customer Loyalty, Customer Satisfaction (CS), Customer Perceived Value (PV), Customer Trust, Customer Culture and the constant are significant, the coefficient of Customer Culture is .211, Customer Trust is .168, Customer Perceived Value (PV) is .218, Customer Satisfaction (CS) is .268, Customer Loyalty is .449, and constant is .417 as shown in Table 6.140.

245

Table 6.140 Coefficients a

Unstandardized Coefficients

Model B Std. Error t Sig.

1 (Constant) 1.125 .191 5.878 .000

Loyalty .714 .053 13.498 .000

2 (Constant) .390 .216 1.806 .000

Loyalty .588 .052 11.311 .000

CS .352 .065 5.444 .000

3 (Constant) .130 .238 .547 .000

Loyalty .474 .056 8.489 .000

CS .290 .062 4.682 .000

PV .294 .073 4.049 .000

4 (Constant) .325 .243 1.335 .000

Loyalty .421 .058 7.247 .000

CS .270 .061 4.437 .000

PV .246 .073 3.358 .000

Trust .177 .068 2.583 .000

5 (Constant) .417 .375 2.447 .000

Loyalty .449 .059 7.645 .000

CS .268 .060 4.478 .000

PV .218 .073 2.985 .000

Trust .168 .067 2.497 .000

Culture .211 .103 2.054 .000 a. Dependent Variable: CSB

246

6.15 STAGE-WISE MULTIPLE REGRESSION - HABIB BANK LIMITED, PAKISTAN

6.15.1 Customer Perceived Value (PV)

Table 6.141 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100).

247

In Table 6.142, the first model gives 65% R Square; it means that Customer Loyalty is the most influential variable on Customer-Perceived Value (PV). The second model gives 73% R Square; it means that Customer Satisfaction (CS) influences Customer-Perceived Value (PV). The third model gives 77% R Square; it means that Customer-Switching Barriers (CSB) influences Customer-Perceived Value (PV). The fourth model gives 78% R Square; it means that Customer Trust influences Customer-Perceived Value (PV). The fifth model gives 79% R Square; it means that Customer Culture influences Customer-Perceived Value (PV).

Table 6.142 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .802 a .680 .688 .39869 2 .841 b .792 .876 .38797 3 .865 c .840 .790 .38768 4 .877 d .872 .801 .40021 5 .887 e .899 .768 .43212 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture

248

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Perceived Value (PV) as F value that is 177.324 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.143.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Perceived Value (PV) as F value that is 168.765 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.143.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Perceived Value (PV) as F value that is 102.887 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.143.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Perceived Value (PV) as F value that is 88.342 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.143.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Perceived Value (PV) as F value that is 70.997 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.143.

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Table 6.143 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.564 1 30.564 177.324 .000 a

Residual 15.770 97 .162

Total 46.334 96

2 Regression 33.397 2 16.224 168.765 .000 b

Residual 12.937 97 .133

Total 46.334 99

3 Regression 36.222 3 11.321 102.887 .000 c

Residual 10.112 95 .115

Total 46.334 98

4 Regression 36.337 4 9.492 88.342 .000 d

Residual 9.997 94 .113

Total 46.334 99

5 Regression 37.677 5 7.543 70.997 .000 e

Residual 8.657 95 .100

Total 46.334 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, CS c. Predictors: (Constant), Loyalty, CS, CSB d. Predictors: (Constant), Loyalty, CS, CSB, Trust e. Predictors: (Constant), Loyalty, CS, CSB, Trust, Culture f. Dependent Variable: PV

250

6.15.2 Customer Loyalty

Table 6.144 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

251

In Table 6.145, the first model gives 72% R Square; it means that Customer-Switching Barriers (CSB) is the most influential variable on Customer Loyalty. The second model gives 77% R Square; it means that Customer Satisfaction (CS) influences Customer Loyalty. The third model gives 79% R Square; it means that Customer Perceived Value (PV) influences Customer Loyalty. The fourth model gives 80% R Square; it means that Customer Trust influences Customer Loyalty. The fifth model gives 83% R Square; it means that Customer Culture influences Customer Loyalty.

Table 6.145 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .808 a .720 .599 .40293 2 .855 b .772 ..654 .39453 3 .869 c .791 .724 .37879 4 .838 d .802 .798 .35675 5 .876 e .832 .803 .33435 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture

252

The overall regression for model 1 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Loyalty as F value that is 176.543 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.146.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Loyalty as F value that is 167.543shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.146.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Loyalty as F value that is 103.454 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.146.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Loyalty as F value that is 76.232 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.146.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Loyalty as F value that is 70.231 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.146.

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Table 6.146 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.119 1 30.119 176.543 .000 a

Residual 16.890 98 .154

Total 47.009 99

2 Regression 34.072 2 16.564 167.543 .000 b

Residual 12.937 98 .128

Total 47.009 99

3 Regression 35.959 3 11.333 103.454 .000 c

Residual 11.050 97 .108

Total 47.009 98

4 Regression 36.684 4 8.657 76.232 .000 d

Residual 10.325 94 .100

Total 47.009 98

5 Regression 37.127 5 7.434 70.231 .000 e

Residual 9.882 96 .101

Total 47.009 98 a. Predictors: (Constant), CSB b. Predictors: (Constant), CSB , CS c. Predictors: (Constant), CSB , CS, PV d. Predictors: (Constant), CSB , CS, PV, Trust e. Predictors: (Constant), CSB , CS, PV, Trust, Culture f. Dependent Variable: Loyalty

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6.15.3 Customer Satisfaction (CS)

Table 6.147 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

255

In Table 6.148, the first model gives 61% R Square; it means that Customer Loyalty is the most influential variable on Customer Satisfaction (CS). The second model gives 72% R Square; it means that Customer Perceived Value (PV) influences Customer Satisfaction (CS). The third model gives 77% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Satisfaction (CS). The fourth model gives 79% R Square; it means that Customer Trust influences Customer Satisfaction (CS). The fifth model gives 84% R Square; it means that Customer Culture influences Customer Satisfaction (CS).

Table 6.148 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .800 a .610 .567 .37687 2 .832 b .722 .546 .36576 3 .832 c .770 .675 .37564 4 .897 d .792 .778 .34543 5 .899 e .843 .664 .39876 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture

256

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Satisfaction (CS) as F value that is 179.675 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.149.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Satisfaction (CS) as F value that is 175.876 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.149.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Satisfaction (CS) as F value that is 168.978 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.149.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer Satisfaction (CS) as F value that is 90.675 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.149.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Satisfaction (CS) as F value that is 82.879 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.149.

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Table 6.149 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 32.768 1 33.453 179.675 .000 a

Residual 14.881 98 .137

Total 47.649 99

2 Regression 34.432 2 15.123 175.876 .000 b

Residual 13.217 96 .101

Total 47.649 98

3 Regression 35.435 3 10.342 168.978 .000 c

Residual 12.214 94 .109

Total 47.649 98

4 Regression 37.564 4 9.768 90.675 .000 d

Residual 10.085 97 .111

Total 47.649 98

5 Regression 38.786 5 7.657 82.879 .000 e

Residual 8.863 97 .137

Total 47.649 99 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, Trust e. Predictors: (Constant), Loyalty, PV, CSB, Trust, Culture f. Dependent Variable: CS

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6.15.4 Customer Trust

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Culture have a significant effect on Dependent Variable Customer Trust and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.150.

Table 6.150 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CULTURE Probability-of-F-to-remove >= .100). a. Dependent Variable: Trust

259

In Table 6.151, the first model gives 69% R Square; it means that Customer Loyalty is the most influential variable on Customer Trust. The second model gives 74% R Square; it means that Customer Perceived Value (PV) influences Customer Trust. The third model gives 78% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Trust. The fourth model gives 80% R Square; it means that Customer Satisfaction (CS) influences Customer Trust. The fifth model gives 82% R Square; it means that Customer Culture influences Customer Trust.

Table 6.151 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .805 a .690 .668 .39657 2 .833 b .742 .643 .38767 3 .867 c .780 .567 .36565 4 .876 d .802 .661 .35543 5 .887 e .823 .652 .34576 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture

260

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Trust as F value that is 180.565 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.152.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Trust as F value that is 177.524 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.152.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Trust as F value that is 172.582 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.152.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Trust as F value that is 95.524 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.152.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer Trust as F value that is 88.654 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.152.

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Table 6.152 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 34.546 1 34.546 180.565 .000 a

Residual 13.654 99 .137

Total 48.2 98

2 Regression 34.432 2 14.543 177.524 .000 b

Residual 13.217 97 .100

Total 48.2 98

3 Regression 35.435 3 10.001 172.582 .000 c

Residual 12.214 95 .112

Total 48.2 99

4 Regression 37.564 4 8.765 95.524 .000 d

Residual 10.085 98 .121

Total 48.2 99

5 Regression 38.786 5 6.765 88.654 .000 e

Residual 8.863 96 .122

Total 48.2 98 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Culture f. Dependent Variable: Trust

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6.15.5 Customer Culture

Stage-Wise Multiple Regression Model suggests that all the five Independent Variables namely Customer Loyalty, Customer Perceived Value (PV), Customer-Switching Barriers (CSB), Customer Satisfaction (CS), and Customer Trust have a significant effect on Dependent Variable Customer Culture and their Regression Coefficients are also significant at 5% level of significance as shown in Table 6.153.

Table 6.153 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

1 Stepwise (Criteria: Probability-of-F-to-enter <= .050, LOYALTY Probability-of-F-to-remove >= .100). 2 Stepwise (Criteria: Probability-of-F-to-enter <= .050, PV Probability-of-F-to-remove >= .100). 3 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CSB Probability-of-F-to-remove >= .100). 4 Stepwise (Criteria: Probability-of-F-to-enter <= .050, CS Probability-of-F-to-remove >= .100). 5 Stepwise (Criteria: Probability-of-F-to-enter <= .050, TRUST Probability-of-F-to-remove >= .100). a. Dependent Variable: Culture

263

In Table 6.154, the first model gives 60% R Square; it means that Customer Loyalty is the most influential variable on Customer Culture. The second model gives 73% R Square; it means that Customer Perceived Value (PV) influences Customer Culture. The third model gives 78% R Square; it means that Customer-Switching Barriers (CSB) influences Customer Culture. The fourth model gives 81% R Square; it means that Customer Satisfaction (CS) influences Customer Culture. The fifth model gives 84% R Square; it means that Customer Trust influences Customer Culture.

Table 6.154 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .811 a .600 .665 .38765 2 .834 b .732 .632 .37876 3 .864 c .780 .553 .35654 4 .853 d .812 .565 .34345 5 .843 e .843 .554 .32343 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust

264

The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer Culture as F value that is 178.542 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.155.

Overall regression for model 2 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer Culture as F value that is 176.548 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.155.

Overall regression for model 3 is significant it means that Customer-Switching Barriers (CSB) has a significant influence on Customer Culture as F value that is 172.254 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.155.

Overall regression for model 4 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer Culture as F value that is 96.524 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.155.

Overall regression for model 5 is significant it means that Customer Trust has a significant influence on Customer Culture as F value that is 89.256 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.155.

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Table 6.155 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 33.454 1 33.454 178.542 .000 a

Residual 12.543 98 .112

Total 45.997 99

2 Regression 34.209 2 12.251 176.548 .000 b

Residual 11.342 96 .112

Total 45.997 97

3 Regression 35.654 3 11.253 172.254 .000 c

Residual 10.343 96 .119

Total 45.997 97

4 Regression 36.654 4 10.524 96.524 .000 d

Residual 9.343 97 .241

Total 45.997 98

5 Regression 37.444 5 8.524 89.256 .000 e

Residual 8.553 96 .114

Total 45.997 97

a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty, PV c. Predictors: (Constant), Loyalty, PV, CSB d. Predictors: (Constant), Loyalty, PV, CSB, CS e. Predictors: (Constant), Loyalty, PV, CSB, CS, Trust f. Dependent Variable: Custom Culture

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6.15.6 Customer Switching Barriers (CSB)

Table 6.156 Variables Entered/Removed a

Variables Variables Model Entered Removed Method

267

In Table 6.157, the first model gives 65% R Square; it means that Customer Loyalty is the most influential variable on Customer-Switching Barriers (CSB). The second model gives 73% R Square; it means that Customer Satisfaction (CS) influences Customer-Switching Barriers (CSB). The third model gives 77% R Square; it means that Customer Perceived Value (PV) influences Customer-Switching Barriers (CSB). The fourth model gives 78% R Square; it means that Customer Trust influences Customer-Switching Barriers (CSB). The fifth model gives 79% R Square; it means that Customer Culture influences Customer-Switching Barriers (CSB).

Table 6.157 Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .806 a .650 .647 .41515 2 .856 b .732 .727 .36521 3 .878 c .771 .764 .33928 4 .887 d .786 .777 .32968 5 .892 e .795 .784 .32423 a. Predictors: (Constant), Loyalty b. Predictors: (Constant), Loyalty , CS c. Predictors: (Constant), Loyalty , CS, PV d. Predictors: (Constant), Loyalty , CS, PV, Trust e. Predictors: (Constant), Loyalty , CS, PV, Trust, Culture

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The overall regression for model 1 is significant it means that Customer Loyalty has a significant influence on Customer-Switching Barriers (CSB) as F value that is 182.204 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.158.

Overall regression for model 2 is significant it means that Customer Satisfaction (CS) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 132.543 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.158.

Overall regression for model 3 is significant it means that Customer Perceived Value (PV) has a significant influence on Customer-Switching Barriers (CSB) as F value that is 107.849 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.158.

Overall regression for model 4 is significant it means that Customer Trust has a significant influence on Customer-Switching Barriers (CSB) as F value that is 87.332 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.158.

Overall regression for model 5 is significant it means that Customer Culture has a significant influence on Customer-Switching Barriers (CSB) as F value that is 73.078 shows the significance of the factor implied in the study with a significance of 0.000 as shown in Table 6.158.

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Table 6.158 ANOVA f

Model Sum of Squares df Mean Square F Sig.

1 Regression 31.403 1 31.403 182.204 .000 a

Residual 16.890 98 .172

Total 48.293 99

2 Regression 35.356 2 17.678 132.543 .000 b

Residual 12.937 97 .133

Total 48.293 99

3 Regression 37.243 3 12.414 107.849 .000 c

Residual 11.050 96 .115

Total 48.293 99

4 Regression 37.968 4 9.492 87.332 .000 d

Residual 10.325 95 .109

Total 48.293 99

5 Regression 38.411 5 7.682 73.078 .000 e

Residual 9.882 94 .105

Total 48.293 99 a. Predictors: (Constant), CS b. Predictors: (Constant), CS, PV c. Predictors: (Constant), CS, PV, CULTURE d. Predictors: (Constant), CS, PV, CULTURE, TRUST e. Predictors: (Constant), CS, PV, CULTURE, TRUST, LOYALTY f. Dependent Variable: CSB

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CHAPTER 7

SUMMARY, FINDINGS, CONCLUSIONS & RECOMMENDATIONS

7.1 SUMMARY

Building and strengthening relations with customers is essential (Zineldin,1995). The more stronger the relations of banks with their customers, higher the chances of their success. If banks build and maintain strong relationships with their customers, it is difficult for competitors to beat them (Gilbert,2003). Therefore, building and maintaining close relations with customers is of high importance for any organization.

Although there are many aspects of Customer Relationship Management (CRM) in the banking sector, this research study focuses on its customer part. The major focus of CRM in banks is to not only to acquire new customers but also to build customer loyalty in the existing ones. This research study will help banks to build customer loyalty, which is a major focus of Customer Relationship Management (CRM).

Customer loyalty is more important than increasing number of customers in a bank (Colgate,1999). Having many customers without loyalty with their bank can result in loss of customers anytime as competing banks are trying their best to attract your existing customers as well. To overcome high competition in the banking sector, banks need to strengthen relations with their customers to make their customers loyal (Bose,2002). Banks should focus constantly on building relationship with their customers, because it is the only competitive advantage remaining to them (Xu,2002).

Banks having more knowledge about their customers gives them a better position than their competitors who have lack of knowledge about their customers. This thorough understanding of customers results in better strategies development. As the most successful organizations these days

271 focus on their customers and intensely observe any change in their customer`s lifestyles, wants, income level, age, preferences, etc so that they can respond to those changes immediately than their competitors.

Banking sector all over the world facing immense competition and Pakistani banking sector is not an exception. It is an acceptable fact that acquiring new customer is more costly than retaining the existing customer. The researcher followed the same fact and developed the basic purpose of this research study that is to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan. Following research questions helped the researcher to achieve this research study`s purpose:

The population of this research study consists of customers of banks. Different researchers have recommended different sample sizes. For instance, 300 respondents are good (Comrey & Lee ,1992; Tabachnick & Fidell, 2001). A sample of 200 to 500 is considered adequate for most customer surveys (Hill and Alexander, 2000). The sample size should allow at least five responses for each item and a more acceptable sample size would allow ten responses for each item to be analyzed (Hair, Anderson, Tatham, & Black, 1998). Therefore, the researcher keeping in mind all of these researchers sample size criteria, finalized sample size of 400 customers of the four banks namely National Bank of Pakistan (NBP) serving as a public bank, Habib Bank Limited (HBL), Pakistan serving as a private bank, Meezan Bank Limited, Pakistan serving as an Islamic bank, and Citibank serving as a foreign bank in Pakistan.

Operational definitions are required for data collection questionnaire (Davis & Cosenza, 1993). It means that every factor that influences customer loyalty should have specific questions to

272 be asked. For measuring factors or constructs of this research study namely customer trust, customer perceived value, customer satisfaction, customer switching barriers, customer culture, and customer loyalty, operationalisation is used.

A well-structured, self-administered questionnaire was developed as attached at Appendix-I as an instrument for data collection from customers of banks. The researcher included brief instructions in the beginning of questionnaire for improved response with Likert 5-point scale.

Pretesting of the questionnaire improves it and customers easily respond (Saunders et al., 2000). Hence, the researcher did three-stage pilot testing of the questionnaire. In the research design, reliability and validity factors have to paid attention in order to minimize possibility of getting incorrect responses (Saunders et al., 2000). In this research study, the Cronbach`s Alpha value of all constructs is higher than .70 that indicates reliability of the research instrument.

The validity of a measurement instrument refers to how well it captures what it is designed to measure (Rosenthal & Rosnow, 1984). For the validity of the research instrument, the researcher has used review of related literature for the validity of factors of this research study. The researcher found the scope of factors of this research study through detailed related literature review. Researcher also got relevant experts suggestions from various universities in Pakistan for reviewing this research study`s questionnaire before going for the pilot-testing.

273

To assess the content validity, the researcher got feedback from bank`s experts and bank`s most regular customers on questionnaire and made changes in this questionnaire accordingly. A three-stage pilot testing of questionnaire as mentioned above was also performed for improvements in questionnaire.

The researcher-entered data collected from customers of the selected banks namely Citibank, National Bank of Pakistan (NBP), Meezan Bank Limited, and Habib Bank Limited (HBL), Pakistan in SPSS software version 16.00 for demographic analysis, correlation analysis, and regression analysis. ANOVA, F, Beta, t-test, significance, and coefficient tests were performed to measure the affects of customer trust, customer perceived value, customer satisfaction, customer switching barriers, and customer culture on customer loyalty and also to measure the relationships between these factors.

After detailed analysis and discussions, results of this research study indicate that customer trust, customer perceived value, customer satisfaction, customer switching barriers, and customer culture does affect customer loyalty and relationships between these factors vary from bank to bank.

After measuring relationships of these factors with each other and their affect on customer loyalty, the researcher responded to this research study`s questions and hypotheses and developed a customer loyalty model for the banking sector of Pakistan for the mutual benefits of customers and banks.

7.2 FINDINGS OF THE RESEARCH STUDY

According to the customer loyalty model developed by the researcher as shown in the Figure 7.1, the affect of studied factors on customer loyalty and their affect on each other vary from bank to bank, and this variation can help banks to understand their weaknesses, in order to build and strengthen loyalty of their customers.

Firstly, customer loyalty model developed by the researcher as shown in the Figure 7.1 clearly shows that the affect of customer trust on customer perceived value in case of Citibank is

274

.387, in case of National Bank of Pakistan (NBP) is .305, in case of Meezan Bank Limited is .333, and in case of Habib Bank Limited is .359. Here a clear variation is seen as the highest affect of customer trust on customer perceived value is in the case of Citibank that is .387. Therefore, it proves that customer trust affects customer perceived value and it also proves this research study’s hypothesis H1 that customer trust has a significant influence on customer perceived value.

Secondly, the model shows that the affect of customer trust on customer satisfaction in case of Citibank is .573, in case of National Bank of Pakistan (NBP) is .336, in case of Meezan Bank Limited is .330, and in case of Habib Bank Limited is .587. Here a clear variation is seen as the highest affect of customer trust on customer satisfaction is in the case of Habib Bank Limited that is .587. Therefore, it proves that customer trust affects customer satisfaction and it also proves this research study’s hypothesis H2 that customer trust has a significant influence on customer satisfaction.

Thirdly, the model shows that the affect of customer trust on customer loyalty also varies from bank to bank. The affect of customer trust on customer loyalty, in case of Citibank is .474, in case of National Bank of Pakistan (NBP) is .419, in case of Meezan Bank Limited is .419, and in case of Habib Bank Limited is .447. Here a clear variation is seen as the highest affect of customer trust on customer loyalty is in the case of Citibank that is .474. Therefore, it proves that customer trust affects customer loyalty and it also proves this research study’s hypothesis H3 that customer trust has a significant influence on customer loyalty.

Fourthly, the model shows that the affect of customer perceived value on customer satisfaction also varies from bank to bank. The affect of customer perceived value on customer satisfaction, in case of Citibank is .665, in case of National Bank of Pakistan (NBP) is .354, in case of Meezan Bank Limited is .352, and in case of Habib Bank Limited is .605. Here a clear variation is seen as the highest affect of customer perceived value on customer satisfaction is in the case of Citibank that is .665. Therefore, it proves that customer perceived value affects customer satisfaction and it also proves this research study’s hypothesis H4 that customer perceived value has a significant influence on customer satisfaction.

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Fifthly, the model shows that the affect of customer satisfaction on customer loyalty also varies from bank to bank. The affect of customer satisfaction on customer loyalty, in case of Citibank is .657, in case of National Bank of Pakistan (NBP) is .439, in case of Meezan Bank Limited is .418, and in case of Habib Bank Limited is .615. Here a clear variation is seen as the highest affect of customer perceived value on customer satisfaction is in the case of Citibank that is .657. Therefore, it proves that customer satisfaction affects customer loyalty and it also proves this research study’s hypothesis H5 that customer satisfaction has a significant influence on customer loyalty.

Sixthly, the model shows that the affect of customer switching barriers on customer loyalty also varies from bank to bank. The affect of customer switching barriers on customer loyalty, in case of Citibank is .487, in case of National Bank of Pakistan (NBP) is .493, in case of Meezan Bank Limited is .349, and in case of Habib Bank Limited is .446. Here a clear variation is seen as the highest affect of customer switching barriers on customer loyalty is in the case of National Bank of Pakistan (NBP) that is .493. Therefore, it proves that customer-switching barriers affects customer loyalty and it also proves this research study’s hypothesis H6 that customer switching barriers has a significant influence on customer loyalty.

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Figure 7.1: Customer loyalty model developed by the researcher

Citibank .665 NBP .354 Meezan .352 HBL .605 3 items ` 4 items CUSTOMER CUSTOMER H PERCEIVED VALUE H4 SATISFACTION

Citibank .387 H 1 NBP .305 H2 Meezan .333 H5 HBL .359 Citibank .573 NBP .336 CUSTOMER TRUST Meezan .330 Citibank .657 HBL .587 NBP .439

7 items Meezan .418 H HBL .615

5 items H Citibank .474

CUSTOMER SWITCHING NBP .419 Meezan .419 BARRIERS Citibank .487 HBL .447 NBP .493 H6 Meezan .349 HBL .446

H7 CUSTOMER LOYALTY CUSTOMER CULTURE

4 items Citibank .446 6 items NBP .365 Meezan .483 HBL .403

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Seventhly, the model shows that the affect of customer culture on customer loyalty also varies from bank to bank. The affect of customer culture on customer loyalty, in case of Citibank is .446, in case of National Bank of Pakistan (NBP) is .365, in case of Meezan Bank Limited is .483, and in case of Habib Bank Limited is .403. Here a clear variation is seen as the highest affect of customer culture on customer loyalty is in the case of Meezan Bank Limited that is .483. Therefore, it proves that customer culture affects customer loyalty and it also proves this research study’s hypothesis H7 that customer culture has a significant influence on customer loyalty.

The Table 7.1 shows the findings of the joint correlation analysis of data collected from the customers of banks namely Citibank, National Bank of Pakistan (NBP), Meezan Bank Limited, and Habib Bank Limited (HBL), Pakistan.

Table 7.1 : correlation analysis of the data collected from the customers of the studied banks namely Citibank, National Bank of Pakistan, Meezan Bank Limited, & Habib Bank Limited, Pakistan customer customer customer customer customer customer trust perceived satisfaction switching culture loyalty value barriers Customer 1 0.346 0.457 0.440 Trust Customer Perceived 1 0.494 Value Customer 1 0.532 Satisfaction Customer Switching 1 0.444 Barriers Customer 1 0.424 Culture Customer 1 Loyalty

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As Table 7.1 shows that few factors affect customer loyalty more than other factors. Here the researcher sees that customer satisfaction is the most correlated element with customer loyalty having a value of .532. It indicates that customer loyalty will decrease if there is a decrease in customer satisfaction; and customer loyalty will increase more if there is an increase in the customer satisfaction and this also proves this research study`s hypothesis H5 that there is significant influence of customer satisfaction on customer loyalty. Beerli, Martin and Quintana, (2004), in their loyalty model are also of the view that the customer satisfaction has strong influence on the customer loyalty. Customer satisfaction helps more to build customer loyalty than any other factor (Ehigie, 2006). The researcher emphasizes that banks should focus more on the customer satisfaction being the highest influencer on the customer loyalty. Customer satisfaction builds customer loyalty and helps to achieve more profit (Jamal and Naser, 2002; Reichheld, 1993; Federal Express, 1992; Winstanley, 1997). Furthermore, in review of related literature, the researcher already discussed that customer satisfaction has most influence on customer loyalty as according to the loyalty models presented by Jamal & Kamal (2004), Levesque & Mc Dougall (1996), and Moutinho & Smith (2000).

Trust has influence on perceived value, satisfaction, and loyalty (Morgan & Hunt, 1994; Kaacbachi, 2006). According to Table 7.1, the researcher indicates that correlation between customer trust and customer perceived value is 0.346 which proves this research study`s hypothesis H1 that there is significant influence of customer trust on customer perceived value.

According to Table 7.1, the correlation between customer trust and customer satisfaction is 0.457 which proves this research study`s hypothesis H2 that there is significant influence of customer trust on customer satisfaction, and correlation between customer trust and customer loyalty is 0.440 which proves this research study`s hypothesis H3 that there is significant influence of customer trust on customer loyalty. Customer trust correlations with customer perceived value, customer satisfaction, and customer loyalty factors show that there is a significant influence of customer trust on customer loyalty. The researcher here emphasizes that banks should focus on customer trust that directly and indirectly enhances customer loyalty and the result is more loyal customers, which is the focus of Customer Relationship Management (CRM).

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In the model presented by Beerli, Martin and Quintana, (2004), customer perceived value influences customer satisfaction. According to the researcher`s proposed model, correlation between customer perceived value and customer satisfaction is 0.494 (Table 7.1) meaning that customer perceived value also influences the customer satisfaction and then customer satisfaction influences customer loyalty therefore it proves this research study`s hypothesis H4 that there is significant influence of customer perceived value on customer satisfaction. This finding indicates that customer perceived value has a strong influence on customer satisfaction, and as earlier discussed, that the customer satisfaction that is 0.532 (Table 7.1) has the highest correlation than other factors hence customer perception value role becomes highly significant.

Correlation between customer satisfaction and customer loyalty is 0.532 (Table 7.1) and that also proves this research study`s hypothesis H5 that there is significant influence of the customer satisfaction on the customer loyalty. It indicates that customer satisfaction strongly affects the customer loyalty hence banks in Pakistan should focus more on customer satisfaction.

According to the proposed model, correlation between customer switching barriers and customer loyalty is 0.444 (Table 7.1) as also presented in the model by Beerli, Martin and Quintana, (2004) and that also proves this research study`s hypothesis H6 that there is significant influence of the customer switching barriers on the customer loyalty. It indicates that customer- switching barriers affect the customer loyalty hence banks in Pakistan should focus on this aspect as well.

Correlation between customer culture and customer loyalty is 0.424 that finally proves this research study`s hypothesis H7 that there is significant influence of customer culture on customer loyalty whereas in the model presented by Beerli, Martin and Quintana, (2004), culture factor is not given. According to the review of related literature, Pakistani culture has a significant influence on Pakistani customers. This finding indicates that customer loyalty is influenced by customer culture as well and in case of cultural differences, this influence becomes more significant.

The t-value in all the findings of this research study is higher than 2 which mean that the relationship between each question and relevant factor is valid. Therefore, based on all these

280 findings, analysis, and arguments, it proves that researcher`s proposed model of customer loyalty as shown in Figure 7.1 is valid for the banking sector of Pakistan.

7.3 CONCLUSIONS

A well-integrated process of Customer Relationship Management (CRM) in any bank is not effective until banks recognize and observe the drivers of customer trust, customer perceived value, customer satisfaction, customer switching barriers, customer culture, and customer loyalty as this research study found that these factors affect each other and have a strong influence on building customer loyalty.

This research study contributes in identifying the affects of customer trust, customer perceived value, customer satisfaction, customer switching barriers, and customer culture on customer loyalty in the banking sector of Pakistan. The researcher has also indentified the affect of these factors on customer loyalty that vary from bank to bank in his customer loyalty model. Therefore, with the help of this customer loyalty model, banks can understand the causes of these variations. It is also a fact that precondition to customer loyalty is customer satisfaction as this research study has also proved it.

Dissatisfied customers of any bank easily switch to another bank at any time therefore it is essential for banks to understand and recognize the value of customer switching barriers. This research study proved that if customer-switching barriers are high then the chances of switching customers to other banks decreases and if the customer switching barriers are low then the chances of switching customers to other banks increases. Therefore, with the help of this research study, banks can increase customer-switching barriers to make their customers loyal.

The researcher would also like to mention here that there is hardly any research study conducted in Pakistan that has seen the affects of customer culture and customer trust on customer loyalty as the findings of this research study indicates that customer culture and customer trust affect customer loyalty in the banking sector of Pakistan.

281

Analyses also indicate that relationship of these factors with each other also vary from bank to bank. The researcher added factors to the existing loyalty model of Beerli, Martin & Quintana (2004) which improved this existing model.

7.4 RECOMMENDATIONS

Based on the findings of this research study, major recommendations for the banking sector of Pakistan are:

1) The researcher has indentified variations among key factors namely customer trust, customer perceived value, customer satisfaction, customer switching barriers, and customer culture that affect customer loyalty in the banking sector of Pakistan. These identified variations can help the banking sector of Pakistan to understand real causes of their weaknesses so that they can overcome these in order to build their customers loyalty.

2) Based on the different responses of customers, banks need to do vigilant segmentation of customers in order to provide the right products and services to the right customers.

3) This research study proves that customer satisfaction has a significant influence on customer loyalty, and satisfied customers rarely switch to any other bank. Therefore, in order to satisfy bank customers better than their competitors, banks have to keep on improving their existing customer satisfaction strategies.

4) This research study proves that the customer trust affects customer perceived value, customer satisfaction, and customer loyalty. Therefore, banks by strengthening trust of their customers can increase customer perceived value, customer satisfaction, and customer loyalty.

5) Customer perceived value has a significant influence on customer satisfaction hence; banks should emphasize on improving customer perceived value that results in increased customer satisfaction.

282

6) As proved by this research study, customer-switching barriers have a significant influence on customer loyalty. If customer-switching barriers decrease than the chances of leaving customers are high so banks should keep on improving their products and services to increase their customer-switching barriers. Therefore, if a bank`s products and services are of high quality and better than their competitors then it becomes hard for their customers to switch to some other bank.

7) Banks should focus more on the customer satisfaction being the highest influencer on the customer loyalty as proved by the customer loyalty model developed by the researcher. This model also indicates that customer loyalty will decrease if there is a decrease in customer satisfaction; and customer loyalty will increase more if there is an increase in the customer satisfaction.

8) Customer culture has a significant influence on customer loyalty as proved by this research study. It also proves that majority customers of banks in Pakistan believe on collectivism. Therefore; banks need to focus more on cultural aspects of their customers in order to build and strengthen customer`s loyalty.

At present, there is intense competition in the banking sector; these recommendations can help banks to build customer loyalty, as it is one of the major competitive advantages remaining to banks.

7.5 IMPLICATIONS FOR THEORY AND PRACTICE

Findings and contributions of this research have several implications for theory and practice as the findings of this research study contribute towards current knowledge on customer loyalty in the banking sector of Pakistan. This research identifies the key factors that affect customer loyalty, therefore, banks should invest resources to enhance customer trust, customer perceived value, customer satisfaction, customer switching barriers, and customer culture leading to customer loyalty.

283

The researcher strongly believes on the basis of the findings of this research study that variations among customer trust, customer perceived value, customer satisfaction, customer switching barriers, and customer culture in banks can help the banking sector of Pakistan to overcome their existing weaknesses, and improve and develop their existing business strategies in order to build and strengthen customer loyalty. This research study`s findings and results will also help banks to better understand cultural aspects of host countries.

Building customer loyalty is not a simple thing to do for any bank as there is tough competition going on as every bank is trying its best to absorb customers. Failures of many banks these days have proved that previous models and traditional methods of working and handling customers are not working well and banks have to bring change in their strategies to build and strengthen relations with their customers because it is the only major competitive advantage remaining.

The findings of this research study will help banks to build customer loyalty of their customers and it will benefit both the customers and their banks. Furthermore, this research study`s findings and recommendations contribute towards improvement in existing customer loyalty strategies of banks.

7.6 FUTURE DIRECTIONS OF RESEARCH

The researcher collected data with the help of questionnaire manually. This research study could be improved if a web-based survey is conducted to concurrently assess customer`s reactions to their banks while they interact with bank`s websites. Therefore, another possible direction for further research might be to use an instant web-based survey in order to enhance validity.

Further research could be conducted to identify the business value of establishing and developing relationships with varying groups of customers in different countries.

284

This research could be applied more widely to verify to what extent the results can be transposed to other regions of the world.

The researcher is confident about the implications of his research study but it may be noted that this research study is based on data collected from only few areas in Pakistan and has a sample of 400 customers of banks in Pakistan; future research study may focus on data collection from an entire country or from different countries for better generalization.

The researcher also believes based on this research study`s findings that there may be other factors that also affect customer loyalty, therefore, research to discover further factors that affect customer loyalty is recommended.

285

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Appendix-I Questionnaire for customers of banks

Dear Sir/Madam,

Thanks for your most valuable time for filling this questionnaire. Firstly, let me introduce myself, I am PhD scholar at the National University of Modern Languages (NUML), Islamabad, Pakistan. As a requirement of my PhD thesis, I am doing this research study to discover the major factors that affect customer loyalty, which is a focus of Customer Relationship Management (CRM) for overcoming high competition in the banking sector of Pakistan.

The basic purpose of this questionnaire is to get your feedback about your experience with your bank.

This survey is anonymous and your responses will be held in the strictest confidence. I thank you for your time and most useful feedback.

(Mohammad Majid Mahmood Bagram ) PhD scholar National University of Modern Languages (NUML), Islamabad, Pakistan [email protected], 03335188677

QUESTIONNAIRE FOR CUSTOMERS OF BANKS (Thanks for your most valuable time and feedback)

Kindly tick the relevant:

GENDER: 1) Male ______2) Female ______

MARITAL STATUS:

1) Single ______2) Married ______

INCOME:

1) 21000-30000 ______2) 31000-40000 ______

3) 41000-50000 ______4) 51,000 and above ______

AGE:

1) 20-30 years ______2) 31-40 years ______

3) 41-50 years ______4) 51 and above years ______

EDUCATION LEVEL:

1) Intermediate and below ______2) Bachelor degree ______

3) Masters and above ______

Kindly tick only one best option (in your point of view) out of five given options (Please indicate your level of agreement or disagreement with each statement in this questionnaire )

Strongly Strongly Agree Neutral Disagree Agree Disagree

PERCEIVED VALUE 5 4 3 2 1 Lassar et al. (1995) 1 The price of services offered by this bank is

fair 2 Comparing to what I pay, I receive much

more in terms of money, effort and time 3 On the base of simultaneous consideration of what I pay and what I gain, I consider that bank service is of value

SATISFACTION Wang et al. (2001), Llosa (1996) 4 I am satisfied with this bank 5 This bank leaves me a pleasant impression 6 I want to return to this bank in the future 7 I will advise this bank to my friends

SWITCHING BARRIERS Kim, et. al., 2003 8 In general switching to a new bank would

be a hassle. 9 It would cost me a lot of money to switch

from my current bank to another bank. 10 It would cost me a lot of time to switch

from my current bank to another bank. 11 It would cost me a lot of effort to switch

from my current bank to another bank. 12 Prices of other banks are higher.

CULTURE Hofstede (1980; 1994) 13 You have a top priority towards personal

goals 14 You feel uncomfortable in unusual

situations 15 You buy what you desire without worrying

about how others feel or think 16 You buy what you like and stick to your

brand

TRUST Hess(1995), Jarvenpaa & Tractinsky (1999), Gurviez & Korchia (2002), Gefen et al. (2000), Chiou & Droge (2006) 17 This bank keeps its promises 18 This bank is honest 19 This bank is reliable 20 This bank meets my needs 21 This bank seems capable to manage

transactions on line 22 This bank seems to have solid knowledge

in its field 23 I trust the know-how of this bank

LOYALTY

Boulaire et Mathieu (2000), Srinivasan et al. (2002), Huang (2008). 24 I regularly visit this bank 25 I seldom think of changing this bank to

another one 26 I use this bank each time I need to make

any financial transaction 27 I consider this bank as my preferred one 28 I like to use this bank 29 Each time I want to make any financial

transaction, this bank is my first choice

OPEN ENDED QUESTIONS

1. What are your comments regarding current services provided by this bank (you may attach additional sheets if required)?

______

2. Any suggestions for improvement of various services offered by this bank (you may attach additional sheets if required): ______

Thanks again for your most valuable time & feedback.

Appendix-II, State Bank of Pakistan (SBP) - Organogram

Appendix-III

BANKS/ DEVELOPMENT FINANCE INSTITUTIONS REGULATED BY THE STATE BANK OF PAKISTAN

S# BANKS 1 PUBLIC First Women Bank Limited SECTOR BANKS Mrs. Shafqat Sultana, President Dr. Syedna Tahir Saifuddin Memorial Foundation Building, CL-10/20/2 Beaumont Road, Civil Lines, Karachi Telephone Office:021-35657681, 35657683 Fax Number:021-35657755 Website :- http://www.fwbl.com.pk UAN: 111-676-767

National Bank of Pakistan Syed Ali Raza, President Head Office, I.I. Chundrigar Road, Karachi Telephone Office: 021-99212200 & 99212208 Fax Number: 021-99212774 Website :- http://www.nbp.com.pk

The Bank of Khyber Mr. Bilal Mustafa, Managing Director 24- The Mall, Head Office, Peshawar Cantt. Telephone Office: 091-5272189 & 5279977 Fax Number: 091-5276838

Website :- http://www.bok.com.pk UAN: 111-95-95-95

The Bank of Punjab Mr. Naeemuddin Khan, President Head Office, BOP TOWER, 10-B, Block E-11, Main Boulevard Gulberg-III, Lahore Telephone Office:042-35783711 & 35783712 Fax Number:042-35783713 Website :- http://www.bop.com.pk

2 SPECIALIZED Industrial Development Bank of Pakistan BANKS Mr. Jamal Nasim, Acting Managing Director State Life Building No. 2, Wallace Road Off. I. I. Chundrigar Road, Karachi Telephone Office: 021-99213615 Fax Number: 021-99213617 Website :- http://www.idbp.com.pk

SME Bank Limited Mr. R. A. Chughtai, President / Chief Executive Officer 40,Jang Building, A. K. Fazal-ul-Haq Road Blue Area, Islamabad Telephone Office:051-9203962 Fax Number: 051-9206735 Website :- http://www.smebank.org UAN: 111-11-00-11

The Punjab Provincial Cooperative Bank Ltd Mr. Maqsood Qadir Shah, President / Chief Executive Officer Bank Square, Shahrah-e-Quaid-e-Azam

The Mall, Lahore Telephone Office: 042-99212840 Fax Number: 042-99211442

Zarai Taraqiati Bank Limited Mr. Muhammad Zaka Ashraf, President / Chief Executive Officer Head Office, 1-Faisal Avenue, P. O. Box No.1400, Islamabad Telephone Office: 051-9252717 & 9252727 Fax Number: 051-9252737 Website :- http://www.ztbl.com.pk

3 PRIVATE Allied Bank Limited BANKS Mr. Mohammad Aftab Manzoor, President / Chief Executive Officer Central Office, Main Clifton Road Bath Island, Karachi Telephone Office: 021-35874221-021-35871339 Fax Number: 021-35835525 Website :- http://www.abl.com UAN: 111-110-110

Arif Habib Bank Limited Mr. Husain Lawai, President / Chief Executive Officer 23 Arif Habib Centre, M.T. Khan Road, Karachi Telephone Office: 021- 32463570 Fax Number: 021-32463575 Website :- http://www.arifhabibbank.com/ UAN: 111-124-725

Askari Bank Limited Mr. Mohammad Rafiquddin Mehkari, President/Chief Executive Officer 1st Floor, AWT Plaza, The Mall, Rawalpindi. Telephone Office: 051-9272289 & 9272290 Fax Number: 051-9271982 Website :-http://www.askaribank.com.pk UAN: 111-000-786

Atlas Bank Limited Mr. Abdul Aziz Rajkotwala, President / Chief Executive Officer 3rd Floor, Federation House Abdullah Shah Ghazi Road, Clifton, Karachi Telephone Office: 021-35369283, 35369264 Fax Number: 021-35290274 Website :- http://www.atlasbank.com.pk

Bank Alfalah Limited Mr. Sirajuddin Aziz, Chief Executive Officer Head Office, 2nd Floor, B.A. Building I.I. Chundrigar Road, Karachi Telephone Office: 021-32416966, 32416795 Fax Number: 021-32434183 Website :- http://www.bankalfalah.com UAN: 111-777-786

Bank Al Habib Limited Mr. Abbas D. Habib Chief Executive/Managing Director Mackinnons Building

I.I. Chundrigar Road, Karachi Telephone Office: 021- 32419216 Fax Number: 021- 32419752 & 32441881 Website :- http://www.bankalhabib.com UAN: 111-014-014

Faysal Bank Limited Mr. Naved A. Khan President/Chief Executive Faysal House, ST-02, Commercial, Main Shahrah-e-Faisal, Karachi Telephone Office: 021-32795399 & 32795625 Fax Number: 021-32793131 Website :- http://www.faysalbank.com UAN: 111-747-747

Habib Bank Limited Mr. R. Zakir Mahmood President/Chief Executive 22-Habib Bank Plaza I.I. Chundrigar Road, Karachi Telephone Office: 021 - 3241 2128 Fax Number: 021- 3241 1566 Website :- http://www.habibbankltd.com

Habib Metropolitan Bank Limited Mr. Anjum Zahoor Iqbal President/Chief Executive Spencer Building I. I. Chundrigar Road, Karachi. Telephone Office: 021-32274570

Fax Number: 021-32630496 Website :- http://www.hmb.com.pk UAN: 111-18-18-18

JS Bank Limited Mr. Naveed Qazi President / Chief Executive 1st Floor, Shaheen Commercial Complex Dr. Ziauddin Ahmed Road, Karachi Telephone Office: 021-32635208/32633820 Fax Number: 021-32631803 Website :- http://www.jsbl.com UAN: 111-777-999

KASB Bank Limited Mr. Muneer Kamal President/CEO Principal Office, Business & Finance Centre I.I. Chundrigar Road, Karachi Registered Office, Razia Sharif Plaza (Basement), Jinnah Avenue, 90 Blue Area, Islamabad Telephone Office: 021-32446800, 99217082, 051-2276827-30 Fax Number: 021-99217588, 051-2270727 Website :- http://www.kasbbank.com UAN: 111-555-666

MCB Bank Limited Mr. Atif Aslam Bajwa President/Chief Executive • 22nd Floor, MCB Tower, I.I. Chundrigar Road, Karachi • 9th Floor, MCB House, 15-Main Gulberg, Lahore

Telephone Office: 021-32270075-76 & 042-36041900-01 Fax Number: 021-32270078 & 042-35776619 Website :- http://www.mcb.com.pk UAN: 111-000-111

Mybank Limited Mr. Muhammad Bilal Sheikh President/Chief Executive Officer 2nd Mezzanine Floor, Business & Finance Centre, I. I. Chundrigar Road, Karachi Telephone Office: 021-32440100 Fax Number: 021-32471951 Website :- http://www.mybank.com UAN: 111-443-111

NIB Bank Limited Khawaja Iqbal Hassan President / Chief Executive Officer Muhammadi House, I. I. Chundrigar Road Karachi Telephone Office: 021-32420333/021-32427887 Fax Number: 021-32472258 Website :- http://www.nibpk.com UAN: 111-333-111

SAMBA Bank Limited Mr. Tawfiq A. Husain President/Chief Executive 6th Floor, Sidco Avenue Centre, Maulana Deen Muhammad Wafai Road, Karachi Telephone Office: 021-35686267, 021-35683059 Fax Number: 021-35658059

Website :- http://www.samba.com.pk UAN: 111-999-333

SILKBANK Limited Mr. Azmat Shahzad Ahmed Tarin President / Chief Executive Officer Central Office, Saudi Pak Building I.I. Chundrigar Road, Karachi 6-Q Block, Gulberg II, Lahore Telephone Office: 021-32460466 :042-35757190-1 Fax Number: 021-32460464 : 042-35761112 Website :- http://www.saudipakbank.com UAN: 111-00-1987

Soneri Bank Limited Mr. Safar Ali K. Lakhani President/Chief Executive Central Office, 5th Floor, Al-Rahim Tower I.I. Chundrigar Road, Karachi Telephone Office: 021-32439582 Fax Number: 021-32439561 Website :- http://www.soneri.com UAN: 111-567-890

Standard Chartered Bank (Pakistan) Limited Mr. Badar Kazmi President / Chief Executive Officer 3rd Floor, Main Branch, P. O. Box No. 5556 I. I. Chundrigar Road, Karachi

Telephone Office: 021-32450288-89 Fax Number: 021-32414914 Website :- http://www.standardchartered.com.pk UAN: 111-002-002

The Royal Bank of Scotland Limited Mr. Shehzad Naqvi Chief Executive Officer 16 Abdullah Haroon Road, Karachi Telephone Office: 021-35683097 Fax Number: 021-35683432 Website:-www.rbs.com.pk

United Bank Limited Mr. Atif R. Bokhari President & CEO Head Office, 8th Floor, State Life Building No.1, I.I. Chundrigar Road, Karachi Telephone Office: 021-32417021-22 Fax Number: 021-32413492 Website :- http://www.ubl.com.pk UAN: 0800-11-825

4 ISLAMIC BankIslami Pakistan Limited BANKS Mr. Hasan Bilgrami Chief Executive Officer 11th Floor, Executive Tower, Dolmen City Marine Drive, Block-4, Clifton, Karachi Telephone Office: 021-35379797 & 111-247-111 Ext-2001 Fax Number: 021-35379796 Website :-http://www.bankislami.com.pk

UAN: 111-247-111

Dawood Islamic Bank Limited Mr. Pervez Said President / Chief Executive Officer 3rd Floor, Trade Centre, I. I. Chundrigar Road, Karachi Telephone Office: 021-32272440 Fax Number: 021-32272466 Website :- http://www.dawoodislamic.com/

Dubai Islamic Bank Pakistan Limited Mr. Mohammad Ahmed Mannan President / Chief Executive Hassan Chambers, 3rd Floor, Plot DC-7 Block-7, Kehkashan Clifton, Karachi Telephone Office: 021 -35308923 Fax Number: 021 -35821071 & 35308921 Website :- http://www.dibpak.com/

Emirates Global Islamic Bank Limited Syed Tariq Hussain President / Chief Executive Officer Plot No. 162, Bangalore Co-operative Housing Societies Ltd (Bangalore Town), Block 7 & 8, Shahrah-e-Faisal, Karachi. Telephone Office: 021-34307000- 7001/251 Fax Number: 021-34530981 Website :- http://www.egibl.com

Meezan Bank Limited Mr. Irfan Siddiqui President & Chief Executive Officer

2nd Floor, PNSC Building, M. T. Khan Road Karachi Telephone Office: 021-35610677 & 35611744 Fax Number: 021-35610676 Website :- http://www.meezanbank.com UAN: 111-331-331 5 FOREIGN Albaraka Islamic Bank B.S.C. (E.C.), BANKS Mr. Shafqaat Ahmed Country Head Pakistan 95-B Hali Road, Gulberg II, Lahore Telephone Office: 042-35756889 Fax Number: 042-35756877 Website :- http://www.albaraka.com.pk UAN: 111-742-742

Barclays Bank PLC Mr. Mohsin Ali Nathani Country Head & Managing Director Dawood Centre, M.T.Khan Road, Karachi Telephone Office: 021-35634040 Fax Number: 021-35634039 Website :-www.barclays.pk

Citibank N.A. - Pakistan Operations Mr. Arif Usmani Managing Director & Citi Country Officer 1st Floor, AWT Plaza I. I. Chundrigar Road, Karachi Telephone Office: 021-32638222 Fax Number: 021-32638211 Website :- http://www.citibank.com.pk

UAN: 111-333-333

Deutsche Bank AG - Pakistan Operations Mr. Shazad Dada Chief Country Officer Avari Plaza, Fatima Jinnah Road Karachi -75530 Telephone Office: 021-35207200-01 Fax Number: 021-35658325 Website :- http://www.db.com/pakistan/ UAN: 111-555-777

HSBC Bank Middle East Limited - Pakistan Operations Mr. Muhammad Tahir Sadiq Chief Executive Officer Pakistan Bahria Complex III, 9th Floor, M.T. Khan Road, Karachi Telephone Office: 021-35615255 Fax Number: 021- 35615226 Website :- http://www.hsbc.com.pk UAN: 111-852-852

Oman International Bank S.A.O.G - Pakistan Operations Mr. Aziz Abbas Acting Country Manager Pakistan Ground Floor, Nadir House Building I. I. Chundrigar Road, Karachi Telephone Office: 021-32419294 Fax Number: 021-32418920 Website :- http://www.oiboman.com

The Bank of Tokyo-Mitsubishi UFJ Limited - Pakistan Operations Mr. Satoshi Hirano General Manager 1st Floor, Shaheen Complex M.R. Kayani Road, Karachi Telephone Office: 021-32637787 Fax Number: 021-32631368 Website :- http://www.bk.mufg.jp 6 MICRO KASHF Microfinance Bank Limited FINANCE Mr. Ghazanfar Azzam BANKS / President INSTITUTIONS 387-E, Mollana Shoukat Ali Road, Johar Town, Lahore Telephone Office: 042- 35222784, 042-37747913 Fax Number: 042-35222851

Khushhali Bank Limited Mr. Muhammad Ghalib Nishtar President 94 West, 4th Floor, Amir Plaza, Jinnah Avenue Blue Area, P. O. Box 3111, Islamabad Telephone Office: 051-9216982 Fax Number: 051-9206080 Website :- http://www.khushhalibank.com.pk/ UAN: 111-092-092

Network Microfinance Bank Limited Mr. M. Moazzam Khan President / Chief Executive Officer Head Office

202-Azayam Plaza, Opp. FTC Building, S.M.C.H.S. Shahrah- e-Faisal, Karachi Telephone Office: 021-34311720 - 21 Fax Number: 021-34311722 Website: www.networkmicrobank.com

Pak Oman Microfinance Bank Limited Mr. Munawar Suleman President / Chief Executive Officer Head Office, 2nd Floor, Tower C, Finance & Trade Centre, Shahrah-e-Faisal, Karachi Telephone Office: 021-35630948 Fax Number: 021-35630949 Website :- http://www.pomicro.com/

Rozgar Microfinance Bank Limited Mr. Azmat Khan Acting President / Chief Executive Officer Business Executive Centre F-17/3, Block-8 Clifton, Karachi Telephone Office: 021-35820326 Fax Number: 021-35865145 Website :-http://www.rozgarbank.com/

The First Micro Finance Bank Limited Mr. Hussain Tejany President / Chief Executive Officer 62-C, Tauheed Commercial Area 25th Commercial Street, DHA Phase V Karachi Telephone Office: 021-35822433

Fax Number: 021-35822434 Website :- http://www.mfb.com.pk

Tameer Micro Finance Bank Limited Syed Nadeem Hussain President / Chief Executive Officer 15-A, Block 7 & 8, Central Commercial Area K.C.H.S. Union, Karachi Telephone Office: 021 – 34325576 & 111-111-004 Ext-1111 Fax Number: 021- 34325575 Website :- http://www.tameerbank.com/ 7. DEVELOPMENT House Building Finance Corporation Limited FINANCE Syed Azhar Abbas Jaffri INSTITUTIONS Managing Director / Chief Executive Officer 3rd Floor, Finance & Trade Centre, Tower 'B' Sharea Faisal, Karachi -74400 Telephone Office:021-99202314 Fax Number: 021-99202360 Website :- http://www.hbfc.com.pk UAN: 0800 50005

Pak Brunei investment Company Limited Ms. Ayesha Aziz Managing Director / Chief Executive Officer Khadija Towers, Plot No. 11/5, Block No.2, Scheme No.5, Clifton, Karachi Telephone Office: 021-35370874 Fax Number: 021-35361213 Website :- http://www.pakbrunei.com.pk

Pak-China Investment Company Limited Mr. Chen Jianbo Managing Director / Chief Executive Officer 13 th Floor, Saudi Pak Tower,61-A, Jinnah Avenue, Islamabad Telephone Office: 051-2800291/688Fax Number: 051- 2800277

Pak Iran Joint Investment Company Limited Mr. Aizaz Sarfraz Managing Director / Chief Executive Officer 507-508, 5th floor, Progressive Plaza, Beaumont Road, Civil Lines, Karachi Telephone Office: 021-35638590-1 Fax Number: 021-35638589 Website :- http://www.pijicl.com

Pakistan Kuwait Investment Company Limited Mr. Shamsul Hasan Managing Director / Chief Executive Officer 4th Floor, Block C, FTC Building Shahrea Faisal, Karachi Telephone Office: 021-35630908-09 Fax Number: 021-35630939-40 Website :- http://www.pkic.com UAN: 111-611-611

Pak Libya Holding Company Limited Mr. Kamal Uddin Khan Managing Director / Chief Executive Officer 5th Floor, Block 'C' Finance & Trade Centre Shahrea Faisal, Karachi

Telephone Office: 021-35630630 & 35630666 Fax Number: 021-35630654 Website :- http://www.paklibya.com.pk UAN: 111-111-115

Pak Oman Investment Company Limited Mr. Agha Ahmed Shah Managing Director & Chief Executive Officer 1st Floor, Tower 'A', Finance & Trade Centre, Shahrea Faisal, Karachi Telephone Office: 021-35630960 & 35630971-75 Fax Number: 021-35630961 Website :- http://www.pakoman.net/

Saudi Pak Industrial & Agricultural Investment Company Limited Mr. Muhammad Rashid Zahir Managing Director / Chief Executive Officer 19th Floor, Saudi Pak Tower, 61/A Jinnah Avenue, Blue Area, Islamabad Telephone Office: 051-2800314 Fax Number: 051-2800308 Website :- http://www.saudipak.com UAN: 111-222-003

Appendix-IV

Appendix-V Citibank - network

Citibank Global locations

Africa 1) Algeria 2) Cameroon 3) Congo, Democratic Republic of 4) Egypt 5) Gabon 6) Ghana 7) Ivory Coast 8) Kenya 9) Morocco 10) Nigeria 11) Senegal 12) South Africa 13) Tanzania 14) Tunisia 15) Uganda 16) Zambia Asia Pacific 17) Australia 18) Bangladesh 19) Brunei 20) China, People’s Republic of 21) Guam 22) Hong Kong 23) India 24) Indonesia

25) Japan 26) Korea 27) Macau 28) Malaysia 29) New Zealand 30) Philippines 31) Singapore 32) Sri Lanka 33) Taiwan 34) Thailand 35) Vietnam

Central America / Caribbean 36) Bahamas 37) Barbados 38) Cayman Islands 39) Costa Rica 40) Dominican Republic 41) El Salvador 42) Guatemala 43) Haiti 44) Honduras 45) Jamaica 46) Nicaragua 47) Panama 48) Puerto Rico 49) Trinidad and Tobago

Europe 50) Austria 51) Belgium 52) Bulgaria 53) Czech Republic

54) Denmark 55) Finland 56) France 57) Germany 58) Greece 59) Hungary 60) Ireland 61) Italy 62) Jersey 63) Kazakhstan 64) Luxembourg 65) Monaco 66) Netherlands 67) Norway 68) Poland 69) Portugal 70) Romania 71) Russia 72) Serbia 73) Slovakia 74) Spain 75) Sweden 76) Switzerland 77) Turkey 78) Ukraine 79) United Kingdom

Middle East 80) Bahrain 81) Israel 82) Jordan 83) Kuwait

84) Lebanon 85) Pakistan 86) Qatar 87) United Arab Emirates

North America 88) Canada 89) Mexico 90) United States

South America 91) Argentina 92) Bolivia 93) Brazil 94) Colombia 95) Ecuador 96) Paraguay 97) Peru 98) Uruguay 99) Venezuela

Source: (citigroup.com, 2009)

Appendix-VI Citibank Pakistan Milestones

CITIBANK PAKISTAN'S MILESTONES

The nineties were a decade of domination and leadership for Citibank in the Pakistani marketplace and the trend continues into the new millennium.

1990 • Consumer Bank was established.

1992 • Consumer Asset Business is launched. • Car Financing is introduced. • Citigold Priority Banking is established. • CitiPhone Banking launched.

1994 • Citibank Visa Card (Gold and Silver) is launched.

1995 • Self-Service Banking launched.

1996 • Citibank, N.A. launches its Intranet System in April. • First bank to launch a Photo Credit Card.

1997 • Citibank wins over 35 awards under the Euromoney Excellence Awards. These awards included "Best Bank" and "Best Emerging Market Bank" for two successive years.

• Citibank Credit Cards acquire 100,000 members in less than 3 years. This milestone was achieved faster than any other Citibank business in the Asia Pacific Region. • Citibank and IBA develop an MBA program focused on Marketing of Financial Services (MFS). • Citibank, N.A. undertakes a three year support program for fund raising for the Lady Dufferin Hospital. • Citibank, N.A. pledges a donation to LUMS for their "Students Aid Program". • Citibank, N.A. in November holds its first ever Car Financing Dealer conference in Bhurban. • Citibank, N.A. opens its sixth branch on Shahra-e-Faisal in Karachi in December. This branch has the first 24-hour zone with ATMs and CitiPhone booths.

1998 • Citibank launched Pakistan's first affinity card known as the "Citibank-Shaheen Credit Card".

1999 • First foreign bank to launch MasterCard in Pakistan. • Citibank Home Loans is launched. • Car Financing Product Feature enhancement (25% Down Payment, Free Pre- approved Credit Card with each car). • 0% Down Payment product for your second car. • Complaint Tracking System (CTS) launched.

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Epicor - Sales Management Software Pricing: $4,000 - $500,000+

2 NetSuite NetSuite CRM+ CRM+ Advantages of NetSuite CRM+ Software: NetSuite is the

only web-based CRM system to provide a complete view of your customers and prospects. NetSuite helps your sales and service teams sell more effectively improve customer service, and increase upsell revenue.

NetSuite CRM+ Technology: NetSuite CRM+ is web- based SaaS (Software as a Service) software, allowing you to focus on managing your business — not your software.

NetSuite CRM+ Software Modules: Sales Force Automation, SFA: Order Management, SFA: Upsell/Cross- Sell, SFA: Incentive Management, Customer Support & Service, Partner Relationship Management, Real-time Dashboards, Business Intelligence, Marketing Automation, Productivity tools, Document Management & Publishing, Self-Service Customer Portal, Website and Analytics, Job & Project Tracking, NetFlex

NetSuite CRM+ Software Pricing: $129/ user/ month (includes maintenance & support) 3 SAP CRM SAP CRM 2007 2007 Advantages of SAP CRM 2007 Software: SAP CRM excels because it provides the flexibility to create unique customer experiences, enables a wide range of end-to-end business processes to address an array of marketing, sales, and service situations, and can be deployed step-by-step to create a more distinctive customer experience.

SAP CRM 2007 Technology: SAP CRM, powered by the SAP NetWeaver platform, allows for adaptability to

45 changing business needs & to drive customer & user-centric sales, services, & marketing with an open & flexible architecture to foster innovation, connect with partners & suppliers, & run your business more cost-efficiently.

SAP CRM 2007 Software Modules: Business Communications Management, Sales Capability, Service Capability, Marketing Capability, Web Channel Capability, Partner Channel Management Capability

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4 Sage SalesLogix Sage SalesLogix

Advantages of Sage SalesLogix Software: With Sage SalesLogix®, your sales, marketing, and support teams get everything they need to target, close, and retain customers for life. You'll sell more, sell faster, and sell smarter.

Sage SalesLogix Technology: Written for the Microsoft Windows environments, utilizing the Microsoft SQL and Oracle DBMS'.

Sage SalesLogix Software Modules: Sales, Marketing, Customer Service, Support, Mobile Solutions, Dashboards and Sales Reporting, Application Integration, Outlook® Integration, Windows Client Requirements, Business Alerts & Notifications

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5 ACT! by Sage 2010 ACT! by Sage 2010

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ACT! by Sage 2010 Software Modules: ACT! 2010, ACT! Corporate Edition 2010, ACT! for Real Estate 2009 (11.0), ACT! for Financial Professionals 2009 (11.0), ACT! Premium 2010

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6 Sage SageCRM / Sage SageCRM / SageCRM.com SageCRM.com Advantages of Sage SageCRM / SageCRM.com Software: With SageCRM your sales, marketing, and support teams get everything they need to target, close, and retain customers for life. You'll sell more, sell faster, and sell smarter.

Sage SageCRM / SageCRM.com Technology: Written for the Microsoft Windows environments, utilizing the Microsoft SQL and Oracle DBMS'.

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7 Microsoft Dynamics Microsoft Dynamics CRM CRM Advantages of Microsoft Dynamics CRM Software: Microsoft Dynamics CRM is customer relationship management (CRM) software used to create a clear picture of customers. Its sales, marketing and customer

49 service modules drive measurable improvements, enhance relationships and increase profitability.

Microsoft Dynamics CRM Technology: Microsoft Dynamics Retail Management System (RMS) offers small and mid-market retailers a complete point-of-sale (POS).

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(Top 7 CRM software, 2020software.com, 2009)

Appendix-VIII

Central Board of Directors, State Bank of Pakistan (SBP)

1 Governor Chairman 2 Mr. Salman Siddique Member 3 Mr. Kamran Y. Mirza Member 4 Mr. Zaffar A. Khan Member 5 Mirza Qamar Baig Member 6 Mr. Asad Umar Member 7 Mr. Waqar A. Malik Member 8 Mr. Aftab Mustafa Khan Corporate Secretary

Appendix-IX Various departments of the State Bank of Pakistan (SBP)

VARIOUS DEPARTMENTS OF THE STATE BANK OF PAKISTAN (SBP)

Agricultural Credit Department

Banking Inspection (On-Site) Department

Banking Policy & Regulations Department

Banking Surveillance Department

Business Support Services Department

Domestic Market & Monetary Management Department

Economic Analysis Department

Exchange Policy Department

External Relations Department

Finance Department

Financial Markets Strategy & Conduct Department

Financial Stability Department

General Counsel's Office

Human Resource Department

Information Systems & Technology Department

Infrastructure / Housing Finance Department

Internal Audit & Compliance Department

International Markets & Investments Department

Islamic Banking Department

Monetary Policy Department

Museum & Art Gallery Department

NIBAF Karachi & Islamabad

Office of the Corporate Secretary

Off-site Supervision & Enforcement Department

Payment System Department

Research Department

Risk Management and Compliance Department.

Real Time Gross Settlement System (RTGS System)

Microfinance Department

SME Finance Department

Statistics and Data Warehouse Department

Strategic and Corporate Planning Department

Training & Development Department

Treasury Operations (Back Office) Department

Appendix-X

Quaid-i-Azam's Speech On the occasion of the Opening Ceremony of The State Bank of Pakistan on 1st July, 1948

"Mr. Governor, Directors of State Bank, Ladies and Gentlemen.

The opening of the State Bank of Pakistan symbolises the sovereignty of our State in the financial sphere and I am very glad to be here today to perform the opening ceremony. It was not considered feasible to start a Bank of our own simultaneously with the coming into being of Pakistan in August last year. A good deal of preparatory work must precede the inaug uration of an institution responsible for such technical and delicate work as note issue and banking. To allow for this preparation, it was provided, under the Pakistan Monetary System and Reserve Bank Order, 1947, that the Reserve Bank of India should con tinue to be the currency and banking authority of Pakistan till the 30th September, 1948. Later on it was felt that it would be in the best interests of our State if the Reserve Bank of India were relieved of its functions in Pakistan, as early as possible . The State of transfer of these functions to a Pakistan agency was consequently advanced by three months in agreement with the Government of India and the Reserve Bank. It was at the same time decided to establish a Central Bank of Pakistan in preference to any other agency for managing our currency and banking. This decision left very little time for the small band of trained personnel in this field in Pakistan to complete the preliminaries and they have by their untiring effort and hard work completed th eir task by the due date which is very creditable to them, and I wish to record a note of our appreciation of their labours.

As you have observed, Mr. Governor in undivided India banking was kept a close preserve of non-Muslims and their migration from Wes tern Pakistan has caused a good deal of dislocation in the economic life of our young State. In order that the wheels of commerce and industry should run smoothly, it is imperative that the vacuum caused by the exodus of

54 non-Muslims should be filled withou t delay. I am glad to note that schemes for training Pakistan nationals in banking are in hand. I will watch their progress with interest and I am confident that the State Bank will receive the co-operation of all concerned including the banks and Universi ties in pushing them forward. Banking will provide a new and wide field in which the genius of our young men can find full play. I am sure that they will come forward in large numbers to take advantage of the training facilities which are proposed to be pr ovided. While doing so, they will not only be benefiting themselves but also contributing to the well-being of our State.

I need hardly dilate on the important role that the State Bank will have to play in regulating the economic life of our country. The m onetary policy of the bank will have a direct bearing on our trade and commerce, both inside Pakistan as well as with the outside world and it is only to be desired that your policy should encourage maximum production and a free flow of trade. The monetary policy pursued during the war years contributed, in no small measure, to our present day economic problems. The abnormal rise in the cost of living has hit the poorer sections of society including those with fixed incomes very hard indeed and is responsib le to a great extent for the prevailing unrest in the country. The policy of the Pakistan Government is to stabilise prices at a level that would be fair to the producer, as well as the consumer. I hope your efforts will be directed in the same direction i n order to tackle this crucial problem with success.

I shall watch with keenness the work of your Research Organization in evolving banking practices compatible with Islamic ideas of social and economic life. The economic system of the West has created alm ost insoluble problems for humanity and to many of us it appears that only a miracle can save it from disaster that is not facing the world. It has failed to do justice between man and man and to eradicate friction from the international field. On the cont rary, it was largely responsible for the two world wars in the last half century. The Western world, in spite of its advantages, of mechanization and industrial efficiency is today in a worse mess than ever before in history. The adoption of Western econom ic theory and practice will not help us in achieving our goal of creating a happy and contended people. We must work our destiny in our own way and present to the world an economic system

55 based on true Islamic concept of equality of manhood and social jus tice. We will thereby be fulfilling our mission as Muslims and giving to humanity the message of peace which alone can save it and secure the welfare, happiness and prosperity of mankind.

May the Sate Bank of Pakistan prosper and fulfil the high ideals whi ch have been set as its goal.

In the end I thank you, Mr. Governor, for the warm welcome given to me by you and your colleagues, and the distinguished guests who have graced this occasion as a mark of their good wishes and the honour your have done me in i nviting me to perform this historic opening ceremony of the State Bank which I feel will develop into one of our greatest national institutions and play its part fully throughout the world."

Quaid-i-Azam Muhammad Ali Jinnah 1st July, 1948

Appendix-XI

STATUTORY OBLIGATIONS OF THE STATE BANK OF PAKISTAN (SBP)

STATUTORY OBLIGATIONS STATUTORY CASH RESERVE

In terms of Section36(1) SBP Act, 1956, every scheduled bank is required to maintain with State Bank a balance the amount of which shall not at the close of business or any day be less than such percentage of Time & Demand Liabilities in Pakistan as may be determined by State Bank.

Presently the requirement is 5% on weekly average basis subject to daily minimum of 4% of Time & Demand Liabilities (reference BPRD Circular No.27 dated 2 nd July,1999).

STATUTORY LIQUIDITY REQUIREMENT

In terms of Section 29(1) of Banking Companies Ordinance, 1962 every banking company shall maintain in Pakistan in cash, gold or un-encumbered approved securities valued at price not exceeding "the lower of cost or the current market price" an amount which shall not at the close of business in any day be less than such percentage of the total of its time & demand liabilities in Pakistan, as may be notified by State Bank from time to time.

Presently the requirement is 15% (excluding 5% statutory cash reserve) of the total of its time and demand liabilities in Pakistan (BPRD Circular No.26 dated 2 nd July, 1999).

MAINTENANCE OF LIQUIDITY AGAINST CERTAIN LIABILITIES

In ter ms of Rule 6 of NBFIs Rules of Business, all NBFIs are required to invest 14% of their liabilities defined in the Rule, in Government Securities, NIT Units, shares of listed companies or listed debt securities in the prescribed manner. For the purpose of this rule,

57 liabilities shall not include NBFIs equity, borrowings from financial institutions including accruals thereon, lease key money, deferred taxation not payable within 12 months, dividend payable within two months, advance lease rentals and deposits from financial institutions. In addition, they are also required to maintain cash balance with State Bank, which shall not be less than 1% of their liabilities as defined above.

SUBMISSION OF ANNUAL AUDITED ACCOUNTS BY NBFIs

Under Rule 17 of NBFIs Rule of Business, all NBFIs are required to invest to submit their annual audited accounts within a period of 6 months after the close of their accounting year.

ANNUAL ACCOUNTS

At the expiration of each calendar year every banking company incorporated in Pakistan, in respect of all business transacted by it, and every banking company incorporated outside Pakistan, in respect of all business transited through its branches in Pakistan, shall prepare with reference to that year a balance-sheet and profit and loss account as on the last woking day of the year in the prescribed forms(Section 34 of Banking Companies Ordinance, 1962).

SUBMISSION OF RETURNS .

The accounts and balance-sheet referred to in section 34 together with the auditor’s report as passed in the annual General Meeting shall be published in the prescribed manner, and three copies thereof shall be furnished as returns to the State Bank within three months of the close of the period to which they relate (Section 36 of Banking Companies Ordinance, 1962).

MINIMUM CAPITAL REQUIREMENTS

In terms of Section 13 of Banking Companies Ordinance, 1962 no banking company shall commence business unless it has a minimum paid up capital as may be determined by the State Bank or carry on business unless the aggregate of its capital and unencumbered general reserves is of such minimum value within such period as may be determined and

58 notified by the State Bank from time to time for banking companies in general or for a banking company in particular.

As present, all banks operating in Pakistan are required to maintain capital and unhecumbered general reserve, the value of which is not less than 8% of their risk weighted assets. Additionally they are also required to maintain a minimum paid up capital of Rs.500 million.

Appendix-XII

CORE FUNCTIONS OF STATE BANK OF PAKISTAN

State Bank of Pakistan is the Central Bank of the country. While its constitution, as originally laid down in the State Bank of Pakistan Order 1948, remained basically unchanged until 1st January 1974 when the Bank was nationalised, the scope of its functions was considerably enlarged. The State Bank of Pakistan Act 1956, with subsequent amendments, forms the basis of its operations today.

Under the State Bank of Pakistan Order 1948, the Bank was charged with the duty to "regulate the issue of Bank notes and keeping of reserves with a view to securing monetary stability in Pakistan and generally to operate the currency and credit system of the country to its advantage". The scope of the Bank ’s operations was considerably widened in the State Bank of Pakistan Act 1956, which required the Bank to "regulate the monetary and credit system of Pakistan and to foster its growth in the best national interest with a view to securing monetary stability and fuller utilisation of the country’s productive resources". Under financial sector reforms, the State Bank of Pakistan was granted autonomy in February 1994. On 21st January, 1997, this autonomy was further strengthened by issuing three Amendment Ordin ances (which were approved by the Parliament in May, 1997) namely, State Bank of Pakistan Act, 1956, Banking Companies Ordinance, 1962 and Banks Nationalisation Act, 1974. The changes in the State Bank Act gave full and exclusive authority to the State Ban k to regulate the banking sector, to conduct an independent monetary policy and to set limit on government borrowings from the State Bank of Pakistan. The amendments in Banks Nationalisation Act abolished the Pakistan Banking Council (an institution establ ished to look after the affairs of NCBs) and institutionalised the process of appointment of the Chief Executives and Boards of the nationalised commercial banks (NCBs) and development finance institutions (DFIs), with the Sate Bank having a role in their appointment and removal. The amendments also increased the autonomy and accountability of the Chief Executives and the Boards of Directors of banks and DFIs.

Like a Central Bank in any developing country, State Bank of Pakistan performs both the traditional and developmental functions to achieve macro-economic goals. The traditional functions, which are generally performed by central banks almost all over the world, may be classified into two groups: (a) the primary functions including issue of notes, regul ation and supervision of the financial system, bankers’ bank, lender of the last resort, banker to Government, and conduct of monetary policy, and (b) the secondary functions including the agency functions like management of public debt, management of fore ign exchange, etc., and other functions like advising the government on policy matters and maintaining close relationships with international financial institutions. The non-traditional or promotional functions, performed by the State Bank include developm ent of financial framework, institutionalisation of savings and investment, provision of training facilities to bankers, and provision of credit to priority sectors. The State Bank also has been playing an active part in the process of islamization of the banking system. The main functions and responsibilities of the State Bank can be broadly categorised as under.

REGULATION OF LIQUIDITY

Being the Central Bank of the country, State Bank of Pakistan has been entrusted with the responsibility to formu late and conduct monetary and credit policy in a manner consistent with the Government’s targets for growth and inflation and the recommendations of the Monetary and Fiscal Policies Co-ordination Board with respect to macro-economic policy objectives. The basic objective underlying its functions is two-fold i.e. the maintenance of monetary stability, thereby leading towards the stability in the domestic prices, as well as the promotion of economic growth.

To regulate the volume and the direction of flow of credit to different uses and sectors, the Bank makes use of both direct and indirect instruments of monetary management. Until recently, the monetary and credit scenario was characterised by acute segmentation of credit markets with all the attendant disto rtions. Pakistan embarked upon a program of financial sector reforms in the late 1980s. A number of fundamental changes have since been made in the conduct of monetary management which essentially marked a departure from

administrative controls and quantitative restrictions to market-based monetary management. A reserve money management programme has been developed. In terms of the programme, the intermediate target of M2 would be achieved by observing the desired path of reserve money - the operating targe t. While use in now being made of such indirect instruments of control as cash reserve ratio and liquidity ratio, the program’s reliance is mainly on open market operations.

ENSURING THE SOUNDNESS OF FINANCIAL SYSTEM:

REGULATION AND SUPERVISION

One of the fundamental responsibilities of the State Bank is regulation and supervision of the financial system to ensure its soundness and stability as well as to protect the interests of depositors. The rapid advancement in information technology , together with growing complexities of modern banking operations, has made the supervisory role more difficult and challenging. The institutional complexity is increasing, technical sophistication is improving and technical base of banking activities is e xpanding. All this requires the State Bank for endeavoring hard to keep pace with the fast-changing financial landscape of the country. Accordingly, the out dated inspection techniques have been replaced with the new ones to have better inspection and supe rvision of the financial institutions. The banking activities are now being monitored through a system of ‘off-site’ surveillance and ‘on-site’ inspection and supervision. Off-site surveillance is conducted by the State Bank through regular checking of var ious returns regularly received from the different banks. On other hand, on-site inspection is undertaken by the State Bank in the premises of the concerned banks when required.

To deepen and broaden financial markets as also to diversify the sources of cr edit, a number of non-bank financial institutions (NBFIs) were allowed to increase substantially. The State Bank has also been charged with the responsibilities of regulating and supervising of such institutions. To regulate and supervise the activities of these institutions, a new Department namely, NBFIs Regulation and Supervision Department was set up. Moreover, in order to

safeguard the interest of ultimate users of the financial services, and to ensure the viability of institutions providing these serv ices, the State Bank has issued a comprehensive set of Prudential Regulations (for commercial banks) and Rules of Business (for NBFIs).

The "Prudential Regulations" for banks, besides providing for credit and risk exposure limits, prescribe guide lines relating to classification of short-term and long-term loan facilities, set criteria for management, prohibit criminal use of banking channels for the purpose of money laundering and other unlawful activities, lay down rules for the payment of dividends, dire ct banks to refrain from window dressing and prohibit them to extend fresh laon to defaulters of old loans. The existing format of balance sheet and profit-and-loss account has been changed to conform to international standards, ensuring adequate transpare ncy of operations. Revised capital requirements, envisaging minimum paid up capital of Rs.500 million have been enforced. Effective December,1997, every bank was required to maintain capital and unencumbered general reserves equivalent to 8 per cent of its risk weighted assets.

The "Rules of Business" for NBFIs became effective since the day NBFIs came under State Bank’s jurisdiction. As from January, 1997, modarbas and leasing companies, which are also specialized type of NBFIs, are being regulated/supervi sed by the Securities and Exchange Commission (SECP), rather than the State Bank of Pakistan.

EXCHANGE RATE MANAGEMENT AND BALANCE OF PAYMENTS

One of the major responsibilities of the State Bank is the maintenance of external value of the currency. In this regard, the Bank is required, among other measures taken by it, to regulate foreign exchange reserves of the country in line with the stipulations of the Foreign Exchange Act 1947. As an agent to the Government, the Bank has been authorised to pur chase and sale gold, silver or approved foreign exchange and transactions of Special Drawing Rights with the International Monetary Fund under sub-sections 13(a) and 13(f) of Section 17 of the State Bank of Pakistan Act, 1956.

The Bank is responsible to ke ep the exchange rate of the rupee at an appropriate level and prevent it from wide fluctuations in order to maintain competitiveness of our exports and maintain stability in the foreign exchange market. To achieve the objective, various exchange policies h ave been adopted from time to time keeping in view the prevailing circumstances. Pak-rupee remained linked to Pound Sterling till September, 1971 and subsequently to U.S. Dollar. However, it was decided to adopt the managed floating exchange rate system w. e.f. January 8, 1982 under which the value of the rupee was determined on daily basis, with reference to a basket of currencies of Pakistan’s major trading partners and competitors. Adjustments were made in its value as and when the circumstances so warran ted. During the course of time, an important development took place when Pakistan accepted obligations of Article-VIII, Section 2, 3 and 4 of the IMF Articles of Agreement, thereby making the Pak-rupee convertible for current international transactions with effect from July 1, 1994.

After nuclear detonation by Pakistan in 1998, a two-tier exchange rate system was introduced w.e.f. 22nd July 1998, with a view to reduce the pressure on official reserves and prevent the economy to some extent from adverse impl ications of sanctions imposed on Pakistan. However, effective 19th May 1999, the exchange rate has been unified, with the introduction of market-based floating exchange rate system, under which the exchange rate is determined by the demand and supply posit ions in the foreign exchange market. The surrender requirement of foreign exchange receipts on account of exports and services, previously required to be made to State Bank through authorized dealers, has now been done away with and the commercial banks an d other authorised dealers have been made free to hold and undertake transaction in foreign currencies.

As the custodian of country’s external reserves, the State Bank is also responsible for the management of the foreign exchange reserves. The task is bei ng performed by an Investment Committee which, after taking into consideration the overall level of reserves, maturities and payment obligations, takes decision to make investment of surplus funds in such a manner that ensures liquidity of funds as well as maximises the earnings. These reserves are also being used for intervention in the foreign exchange market. For this

purpose, a Foreign Exchange Dealing Room has been set up at the Central Directorate of State Bank of Pakistan and services of a ‘Forex Expert’ have been acquired.

DEVELOPMENTAL ROLE OF STATE BANK

The responsibility of a Central Bank in a developing country goes well beyond the regulatory duties of managing the monetary policy in order to achieve the macro-economic goals. This role c overs not only the development of important components of monetary and capital markets but also to assist the process of economic growth and promote the fuller utilisation of a country’s resources.

Ever since its establishment, the State Bank of Pakistan, besides discharging its traditional functions of regulating money and credit, has played an active developmental role to promote the realisation of macro-economic goals. The explicit recognition of the promotional role of the Central Bank evidently stems from a desire to re-orientate all policies towards the goal of rapid economic growth. Accordingly, the orthodox central banking functions have been combined by the State Bank with a well-recognised developmental role.

The scope of Bank’s operations has been widened considerably by including the economic growth objective in its statute under the State Bank of Pakistan Act 1956. The Bank’s participation in the development process has been in the form of rehabilitation of banking system in Pakistan, development of new financial institutions and debt instruments in order to promote financial intermediation, establishment of Development Financial Institutions (DFIs), directing the use of credit according to selected development priorities, providing subsidised credit, and development of the capital market.

Appendix-XIII

NATIONAL BANK OF PAKISTAN (NBP) VISION, MISSION, & CORE VALUES

VISION National Bank of Pakistan`s (NBP) vision is “to be recognized as a leader and a brand synonymous with trust, highest standards of service quality, international best practices and social responsibility” (NBP, 2009).

MISSION National Bank of Pakistan`s (NBP) mission is stated as: Institutionalizing a merit and performance culture Creating a distinctive brand identity by providing the highest standards of services Adopting the best international management practices Maximizing stakeholders value Discharging our responsibility as a good corporate citizen of Pakistan and in countries where we operate (NBP, 2009)

CORE VALUES National Bank of Pakistan`s (NBP) core values are: Highest standards of Integrity Institutionalizing team work and performance culture Excellence in service Advancement of skills for tomorrow’s challenges Awareness of social and community responsibility Value creation for all stakeholders (NBP, 2009)

Appendix-XIV AWARDS & ACHIEVEMENTS THE NATIONAL BANK OF PAKISTAN

"Best Foreign Exchange Bank “ Euromoney” Magazine, a leading and 2008” awarded by world's leading financial prestigious journal, published from London , journal “Global Finance." UK , in its issue of March 2005 has published Moody's Investors Stable AAA/A-1+(Triple A/A-One Plus) Service rankings in which NBP is the only rating (Standalone Basis) by JCR-VIS (July Pakistani bank which has been ranked among 2007) the Top 100 banks of Asia for it performance in the fiscal year 2003 Best Return on Capital for 2006 amongst all Banks in Asia . -“ Banker Magazine” in July WEBCOP-AASHA, an alliance against 2007 gender discrimination at workplace, presented a Recognition Award to National Bank of World's leading financial journal, “Global Pakistan on December 18, 2004 for having Finance” has named NBP as the Best a Gender Sensitive Management . Emerging Market Bank from Pakistan for the year 2006 . In May 2004, NBP's standalone long-term rating was upgraded by JCR-VIS Credit "Best Foreign Exchange Bank – Rating Agency to AA (double A) from AA -( Pakistan” award for the year 2006 by world's double A minus) with “stable outlook”, while leading financial journal “Global Finance ” . standalone short-term rating was maintained at Due to consistent improvement in NBP's A-1+(A one plus). This is now the best Core Profitability , Asset Quality and rating for a local commercial bank in Economic Capitalization in recent years Pakistan . ,Moody's Investors Service upgraded the In its issue of March 2004, “Global Financial Strength Rating (FSR ) rom E+ to Finance” has also declared NBP as “The Best D-, in November 2005 . Foreign Exchange Bank” in Pakistan . “ Best Foreign Exchange Bank – The “Banker Magazine” in July 2003

Pakistan” award for the year 2005 by world's recognized NBP as the bank with the highest leading financial journal “Global Finance ”. return on capital in Asia and No.8 in the world. “ Best Bank - Pakistan” award for the year 2005 by world's leading financial World's leading financial journal, “Global journal “Global Finance ” . Finance” after a worldwide survey declared NBP in its issue of May 2003 as one of The Asian Banker , a reputable financial the best banks in the emerging markets. journal, has published the report of its research project on the ranking of 300 of Asia 's “ Bank of the Year” awarded for the Strongest Banks based on a 11-Dimensional year 2002 by the world renowned “The Dynamic Scoring Criteria has adjudged Banker” magazine owned by the Financial National Bank of Pakistan as the Strongest Times Group, London Bank in Pakistan . “ Bank of the Year” awarded for the On the basis of overall financial performance year 2001 by the world renowned “The during 2004, NBP has been listed “Amongst Banker” magazine owned by the Financial top 1000 banks in the world” and “ Number Times Group, London 1 Bank in Pakistan” by the President's Awards: prestigious “Banker Magazine” in its issue of July 2005 . 1) Mr. S. Ali Raza, Chairman & President, NBP was awarded “The Asian Banker The “Banker Magazine” in July 2005 Leadership Achievement Award 2007” by recognized NBP as the 10th Best Bank in Asian Banker ( an internationally reputed terms of ‘Profit on Capital' in the world . Financial Journal) in its issue of June 2007 “ Bank of the Year” awarded for the 2) Mr. S. Ali Raza Chairman & President, year 2005 by the world renowned “The NBP, was conferred Sitara-i-Imtiaz by the Banker” magazine owned by the Financial President of Pakistan , General Pervaiz Times Group, London. Musharraf on August 14, 2005 On an all Pakistan basis National Bank of 3) “ Business Week” of “ The McGraw Hill

Pakistan was awarded the “Kissan Times Companies” in its July 11,2005 edition has Award” for the year 2005 by the Prime adjudged Mr. S. Ali Raza, Chairman Minister , Mr. Shaukat Aziz, for its services in President, NBP as one of the twenty the Agriculture Sector .World's leading five Leaders of Asia at the & Forefront of financial journal, “Global Finance” in an Change and has identified them as Stars of exclusive survey has named NBP as the Best Asia including the President of Indonesia Emerging Market Bank from Pakistan for 4) Mr. S. Ali Raza's (Chairman & President, the year 2005 . NBP) capabilities were also recognized by “ Bank of the Year” award for the the Institute of Bankers in Pakistan when he year 2004 by the world renowned “ The was awarded a gold medal in 2003 . Banker” magazine owned by the Financial Times Group , London .

Appendix-XV

Board of Directors National Bank of Pakistan

Syed Ali Raza Chairman & President Syed Ali Raza is the Chairman and President of National Bank of Pakistan (NBP), the largest commercial bank of the country. Mr. Raza is a graduate of the London School of Economics and M.Sc. in Admn. Sciences as well as a Fellow Member of The Institute of Bankers in Pakistan. He started his career in 1974 with Bank of America, arising to become Managing Director and Regional Manager for the Middle East, North Africa and Pakistan for Bank of America.

Mr. Tariq Kirmani Director Soon after completing his Masters in Business Administration (MBA) Mr. Kirmani embarked upon a rewarding career, starting with a multinational Oil Company (Caltex later Chevron Pakistan) in 1969 and

worked for seven years in the United States of America, United Arab Emirates and Australia in different senior management positions in Marketing Operations and Finance. In 1991, Mr. Kirmani became the first Pakistani to be elected as a Company Director of the mentioned multi-national company.

Mrs. Haniya Shahid Naseem Director Mrs. Haniya Shahid Naseem is an MBA with more than fifteen years experience of working in the education, social, industrial textile and agriculture sectors of Pakistan. She has served for 5 years on the Board of a textile company, having a turnover of more than one Billion Rupees. Presently she is actively involved in the administration of P akistan Public School Multan. She is a progressive agriculturist and actively participates in the management of her family’s agricultural farms. She is a member of the Multan Chamber of Commerce and Industry, and is also on the guest faculty of IBA, Multan.

Ms. Nazrat Bashir Director Ms. Nazrat Bashir belongs to District Management Group of Civil Services of Pakistan. She is Masters in Economics from New York University, New York, USA and Master in Psychology from Peshawar University, Peshawar

She has extensively traveled abroad and has attended various international Seminars and Conferences such as on Micro Finance, Anti Money Laundering, Instruments of Financial Markets etc. Domestically too she has attended various programmes in some of very prestigious institutions of Pakistan.

Mr. Ekhlaq Ahmed Secretary Board of Directors Mr. Ekhlaq Ahmed, EVP is the Company Secretary of the Bank and also the Secretary of Credit & Operations Committees. He is M.A. (Economics) from Rajshahi University, Bangladesh (former East Pakistan). He is a Diplomaed Associate Institute of Bankers, Pakistan (DAIBP) and secured overall 1 st position in order of merit and won

Muslim Commercial Bank Prize in the subject of “Foreign Trade & Foreign Exchange”. He is an Associate of Institute of Corporate Secretaries of Pakistan (ACIS). He is also a “Certified Director” on the panel of Pakistan Institute of Corporate Governance (PICG) since November, 2007. Mr. Ekhlaq Ahmed is the first senior executive of the Bank who has achieved the status of “Certified Director”.

Appendix-XVI Director`s Report The National Bank of Pakistan

Corporate and Investment Banking

Corporate & Investment Banking Group enjoys robust relationship with premier corporate clients. The length and breadth of our corporate clientele has been built on corporate strategy of providing comprehensive and customized financial solutions to our corporate customers. Varied banking and investment products are offered to the corporate clients from working capital financing to infrastructure project, structured and syndicated financing, divestitures, financial restructuring, mergers and acquisitions assignments and associated financing solutions.

Audit & Inspection

Internal Auditing is an independent, objective assurance and consulting activity designed to add value and improve organizational operations. It helps the bank accomplish its objectives by bringing a systematic, disciplined approach to evaluate and improve the effectiveness of risk management, control and governance processes.

Credit and Risk Management

NBP is continuously upgrading its risk management process to identify, evaluate and manage risk. Our focus includes analysis, evaluation and management of all risks which include credit, liquidity, market, operational and reputation risks. The bank’s risk management policies and procedures are subject to high degree of supervision and guidance to ensure that all risk categories are systematically identified, measured, analyzed and proactively managed.

Compliance

Compliance is an independent function that identifies, assesses, advises, monitors and reports on the Bank’s compliance risk, i.e. the risk of legal or regulatory sanctions, financial loss or loss to the reputation which the bank may suffer as a result of its failure to comply with applicable laws, regulations, and codes of conduct and standards of best practices. The bank has accelerated its efforts proactively to strengthen compliance culture in the bank. During 2009 we have revised Compliance Review Program (CRP) to incorporate relevant changes in rules, regulations and changing dynamics to help senior management in identifying and assessing risk. In view of development of Compliance Review Program, Exception Reporting Mechanism has improved and now senior management receives report of violations promptly. Immediate corrective measures are initiated to secure the bank’s interest.

Domestic Branches Network

We expanded our operations in 2009 and 11 more branches across Pakistan were opened in 2009 taking the domestic branch network to 1265. NBP has a well defined strategy for branch expansion to enter the untapped markets and to strike a balance between its rural and urban coverage.

Credit Rating

NBP enjoys the highest rating of ‘AAA’ in the industry assigned by M/s JCR-VIS Credit Rating Company. The ratings assigned to NBP are primarily driven by the bank’s role in the national economy as an agent of the State Bank of Pakistan and as a bank to the Government of Pakistan. Additionally, ratings also derive strength from the bank’s consistently high capitalization levels, and nationwide access that has enabled it to secure a cost effective and diversified deposit base.

Social Responsibility

NBP has been at the forefront of socioeconomic development in the country. It has over the years funded projects which best serve the economic objectives and social needs of the country. The bank has made tremendous contribution to the development of small and medium sized entrepreneurs and to self-employment schemes. The Bank fulfils its social responsibility through contribution

74 towards various causes. The Bank have always been generously donating in cases of national disasters and times of difficulty being faced by the nation, whether it was the devastating earthquake, flood relief efforts or the issue of Internally displaced persons (IDPs) the bank and its employees have been at the forefront to help and support the nation.

Profit & Loss Appropriation

The Profit for the year 2009 after carry over of accumulated profit of 2008 is proposed to be appropriated as follows: -

Rupees in Millions Net Profit before taxation for year 2009 22,300 Taxation Current year 9,221 Prior year(s) (4,133) Deferred (1,000) 4,088 After Tax Profit 18,212 Profit Brought Forward 52,456 Transfer from surplus on revalution of fixed assets 124 Profit available for appropriation 70,792

Transfer to Statutory Reserve (10% of after tax profit) 1,821 Issue of bonus shares 1,794 Cash dividend 5,830 9,445

Profit carried forward 61,347

Future Outlook

NBP remains committed to the interest of all stake holders including its employees, owners, regulators and the Pakistani nation. We have well defined strategy on where and how we want to proceed in the years to come. With the implementation of new ‘Core Banking Package’, NBP will completely automate its functions which in turn will appreciably enhance work efficiency. We will continue to diversify our customer segments thereby increasing our product offering. Our commitment towards the employees’ empowerment / development will continue as we believe that a motivated and well trained work force is necessary to ensure sustenance and growth. On the business side our main focus would be to reduce non-performing loans and increase deposits.

We remain committed to our Vision, Mission & core values and our strategy for the future includes recovery efforts and revival of non performing loans, deposit mobilization, consolidation of loans, expense management and tapping into untapped markets by increasing our network both domestically and internationally. Customer service will remain our main focus of operations management.

REVIEW OF BOARD OF DIRECTORS’ COMMITTEES AT NBP

At NBP, the Board of Director’s have an active role in providing their able guidance and support to the Bank’s management. For this purpose a number of Board’s committees have been constituted in the bank. These committees have well defined terms of reference and they meet at regular intervals to review and make decisions on matters of importance for their respective area of functioning. The following are the committees:

Number Number of Name of the Committees of Meetings held Chairman of the Committee Directors in 2008 Audit Committee 3 28 Mr. Ibrar A. Mumtaz HR Management Committee 4 23 Mian Kauser Hameed I.T Committee 3 14 Mr. Tariq Kirmani Board Risk Committee 3 13 Mr. M Ayub Khan Tarin Agriculture Finance Committee 3 11 Mr. Ibrar A. Mumtaz Islamic Banking & 3 13 Mr. Tariq Kirmani

Subsidiaries Committee Sports & Culture Committee 3 11 Mr. Sikander Hayat Jamali

Audit Committee

This committee has the oversight monitoring / assurance responsibility mainly relating to the effectiveness of the Bank’s internal audit function, integrity of the Bank’s financial statements, system of internal control, safeguarding of Bank’s assets and associated risks, compliance with the applicable legal and regulatory requirements, corporate governance and Bank’s “Code of Conduct” and co-ordination with external auditors, making recommendations with respect to other matters relating to their independence, performance, appointment and remuneration and approval of provision of other than audit services. The major achievement of the committee includes conducting a Quality Assurance Review of the bank’s internal audit function through independent consultants to align the internal audit function with international standards/best practices of corporate governance. The Committee ensured independence of the Internal Audit function and further strengthened it in line with the requirements of International Standards on Internal Auditing, Institute of Internal Auditors USA, regulators and best practices of corporate governance.

HR Management Committee

The committee is an advisory and assurance committee which assists the board in fulfilling its responsibilities relating to all HR policy matters. It reviews and formulates human resource policies and best practices for attraction, retention, succession, motivation, training and development policies to achieve corporate objectives. It also recommends to the board the compensation, annual increase, performance bonuses, and perquisites of the CEO, Chief Internal Auditor, Secretary to the Board, CFO and all positions reporting to the CEO. It suggests strategies for negotiations with training and educational institutions both nationally & internationally for collaborating in training activities. It is also responsible for improvements in training methodology and identifying areas relevant to the needs of the organization. During 2009 several decisions were taken for

77 improvement in the areas of HR policies, planning, training & development, compensation & pension, institutional discipline, and other HR related areas.

I.T Committee

The Committee is responsible for identifying areas of the prospective automation, reviews and decides strategic technology implementation and provides guidance and approves selection of appropriate technology solution; software, hardware, infrastructure and outsourcing.

For the first time in the history of National Bank a comprehensive IT strategy for the Bank was designed which encompasses the phase-1 focusing on “Strategy for Systems Quality Assurance & Testing Strategy (Policy, Procedures, Methodology and Framework).” The phase-2 of the strategy will cover the entire bank wide transformation and full spectrum automation, systems and data center integration, depth and width of IT Service Portfolio, IT Operations, plus incorporating the IT Internal Control Framework supported by COBIT, ISO ISMS 27001 and ITIL.

Board’s Risk Committee (BRC)

BRC over sighted the risk related issues of the bank and took several decisions for implementation. The functional scope of the Risk Management Committee is to develop the risk management role by identifying the relevant/new risk management tools as per Basel guidelines and developing the road map for implementing Basel II framework as per SBP guidelines. It also works for Risk & Exposure Reporting by development of Basel II’s economic capital management frame work. This committee also provides the reporting and research for Board of Directors. It also reviews the liquidity position, forecasting and projections and portfolio of the Bank. In 2009 the committee approved rating model for corporate & commercial borrowers.

Agriculture Finance Committee

Agriculture Finance Committee directed restructuring and reorganization of Agriculture Finance Group and approved TOR, vision & mission statement of the group, Livestock/Dairy Farm Financing policy and Agricultural Finance Policy Manual. Particular emphasis was given to

78 disbursement of finance to improve the yield/out put of this sector while maintaining the healthy recovery ratio.

Islamic Banking & Subsidiaries Committee

This Committee provides strategic guidance and recommends initiatives for expansions, mergers & acquisitions. The strategic endeavors resulted in expansion in NBP Islamic banking branch network covering all major cities of the country. To evaluate the commercial viability, future profitability and growth of Islamic banking, the committee guided Islamic Banking Group to prepare business plan for the year-2010 and henceforth strategic plan 2011-2013.

Sports & Culture Committee

The functional scope of the Committee is to devise strategies to promote sports and cultural activities in the bank as well as in the country. During 2009 the Committee reviewed the progress of various activities undertaken by the Sports, Culture & CSR Division and also approved various incentive and cash award policies for sportspersons working for NBP. The Committee also finalized the fee structure and membership rules & regulations of NBP Sports Club.

The number of board meeting held during the year was 8 and attended by the directors as follows:

Syed Ali Raza President / Chairman 8 Mr. Muhammad Ayub Khan Tarin Director 8 Mr. Sikandar Hayat Jamali Director 4 Mr. Tariq Kirmani Director 8 Mian Kausar Hameed Director 8 Mr. Ibrar A. Mumtaz Director 8 Mrs. Haniya Shahid Naseem Director 6

The Board places on record its sincerest appreciation to the outgoing Directors, Dr. Waqar Masood Khan, and Mr. Azam Faruque to whom we are indebted for their prudent, professional and diligent guidance that helped in achieving such tremendous performance.

(j) Value of investments of Employees’ Pension Fund and Employees Provident Fund as at December 31, 2009 (un-audited) was as follows:

Rs. in - `000 Employees Pension Fund 19,781,585 Employees Provident Fund 8,448,101

Pattern of Share holding

The pattern of share holding as at December 31, 2009 is given in Annual Report.

Earning per share

After tax earning per share for the year 2009 is Rs. 16.92.

Appointment of Auditors

The Board of Directors on the recommendation of the Audit Committee has recommended M/s Anjum Asim Shahid Rahman & Co. Chartered Accountants & M/s M. Yousuf Adil Saleem & Co. Chartered Accountants as statutory auditors for the year ending December 31, 2010. Both the firms being eligible offer themselves for appointment.

Risk Management Framework

NBP Board of Directors and Senior Management are fully committed to strengthen the Risk Management structure and practices. Several initiatives taken and planned by the Bank, in this regard, reflect commitment of Senior Management & Board of Directors to upgrade the quality of Risk Management process such as formation of Board Risk Committee, Executive Risk Management Committee, Basel II Implementation Committee, strengthening of Risk Management Division, conducting of exercises like Basel II Gap Analysis, Hiring of consultant for Basel II advisory services, implementation of software / systems for Credit Risk, designing of Internal Rating system, Scorecards for Consumer Credits , Revision and continuous improvement in policies, procedures, reporting structure for effective Risk Management and shift from fixed markup rate structure to floating rates for markup for managing Interest Rate Risk.

Statement of Internal Controls

The Board is pleased to endorse the statement made by management relating to internal control. The Management’s Statement on Internal Control is included in the Annual Report.

We extend our appreciation to the bank’s staff for their commitment, dedication and hard work in achieving these excellent results. We would like to express our sincere reverence to the Board members whose valuable guidance has always enlightened us in our decision making. Finally we would like to express our appreciation to our stakeholders, regulators and our valued customers for their support and continued confidence in NBP.

On behalf of Board of Directors

S. Ali Raza Chairman & President

Appendix-XVII

CITI PAKISTAN’S GRANTS

Some of the grants Citi Pakistan has closely been involved with include:

• Citi Microentrepreneurship Awards (CMA): US$55,000 for the CMA that have been conducted in Pakistan since 2005, in collaboration with the Pakistan Poverty Alleviation Fund. The pivotal aim of the CMA is to support existing small enterprises and incentivize the creation of new ones.

• Citi Microfinance Network Strengthening Program: Additionally, Pakistan is one of nine countries included in the Citi Microfinance Network Strengthening Program (NSP), which is supported by a 3-year Citi Foundation grant (started in 2007). The Citi Foundation‘s global NSP initiative is intended to help expand microfinance outreach through resource development, advocacy and knowledge creation. In Pakistan, the NSP provides financial and volunteer skill- based support to the Pakistan Microfinance Network, which consists of organizations that are engaged in microfinance and dedicated to improving the outreach and sustainability of microfinance services in the country.

• Citi-LUMS Management Development Training for micro-finance institutions (MFIs): Grant worth US$65,000 to fund training modules for middle and upper MFI management in Pakistan

• Microfinance Research: A Citi Foundation grant to Acumen Fund supports research on the design of financial products for low income communities. Acumen Fund is a non-profit, global venture capital fund that addresses poverty by working to fill the niche left between traditional capital markets and grant-based philanthropy

• Development in Literacy (DIL): US$20,000 for a teacher training given to DIL for its supporting its schools in the Orangi town area in Karachi

• Thardeep Rural Development Program: US$22,000 for a micro-credit training program that will reach 2,000 women in Tharparkar, one of Pakistan’s most disadvantageous districts, in the province of Sindh

• Health: A Citi Foundation multi-year grant of US $280,000 was given to the Aga Khan Foundation to support its Urban Credit and Health Program, which endeavors to achieve sustainable improvements in health status among women of childbearing age and children in Karachi‘s underprivileged areas

Previously, grants have also been provided to the Lahore University of Management Sciences, Kashf Foundation, The Citizen’s Foundation, Institute of Business Administration, Institute of Business Management, Akhuwat Foundation, Tarraqi Foundation, Thardeep Rural Development Program and Development in Literacy over recent years.

Appendix-XVIII

BUSINESS PROFILE - Citibank

Citi has been present in Pakistan since 1961 and will be completing its 50th anniversary in 2011. Citi has US$105MM invested in the country and employs approximately 847 permanent employees across Pakistan. Citi Pakistan has 18 fully operational retail branch outlets, with a focus on the main commercial centres of Karachi, Lahore, Islamabad, Faisalabad and Rawalpindi. Citi Pakistan’s business provides a variety of best-in-class products and services to more than 200,000 consumer and institutional clients. Citi is the leading bank in Pakistan for delivering export agency and multilateral financing and has been instrumental in the development of Pakistan‘s market for derivatives and other treasury products.

Citi Pakistan has also been at the forefront of the financial sector reform process in Pakistan and has been the lead bank in bringing the Pakistani Government to international capital markets. Over these years it has come to be reputed as an industry leader, recognized as the pioneer for a spectrum of banking products and services in Pakistan.

Some Citi ‘Firsts’ in Pakistan include:

• Pioneered Consumer Banking – first to launch Credit Cards, Auto Loans, Mortgages • Derivatives (Interest Rate Swaps, Currency Swaps, Options) • First 30-year US Dollar sovereign bond • Issuance of the first foreign currency Islamic bonds or sukuks • OPIC risk participation programs & structured ECA financings (volumes hit $1 billion or 20% of Citi global ECA business in ‘05) • Bill processing for Public Sector utilities • Customized remittance product for expatriates • Back office processing (Private Label) for banks • Providing the first equity offering in over a decade

Appendix-XIX

CITI IN PAKISTAN: BUILDING COMMUNITIES

Community Development:

Further, Citi Pakistan has played its part in supporting the Internally Displaced Person’s (IDP’s) by raising over $50,000 for this cause. Citi Pakistan’s employees’ donated one day’s salary on a voluntary basis for the IDP’s which was matched by Citi’s funds. Similarly during the 2005 Earthquake in the Northern Areas, Citi supported the construction of a girls school by The Citizen’s Foundation (TCF) in Mansehra. This year, the left over Earthquake Relief Funds have been donated to TCF for maintaining the operating costs of the Mansehra school campus for the next ten years. Additionally, the Citi Foundation provided a grant of US $1.9 million to the American Red Cross (ARC) National Headquarters for its Pakistan Earthquake Reconstruction Project, following the earthquake of 2005.

The Citi Foundation Marks a Decade of Support in Pakistan by Exceeding the US$1.5 Million Mark

As Citi Pakistan approaches its 50th anniversary in January 2011, the Citi Foundation, Citigroup’s social investment arm, marks a decade of support towards various socio-economic projects in the country, exceeding the total mark of US$1.5million in social sector support to Pakistan. Just this year, the Citi Foundation has provided US$400,000 through five new grants to Pakistan, for a spectrum of development related initiatives.

Citi’s main community objectives revolve around microfinance, financial education and environmental projects. Our efforts in the areas where we operate have benefits that extend beyond these cities as well. We are proud to have received the CSR National Excellence Award in 2007 and 2009 for outstanding corporate social responsibility. We were also one of the top ten companies to have received special recognition for our CSR efforts at the CSR Asia Forum in Manila in November 2009.

Appendix-XX MEEZAN BANK LIMITED, PAKISTAN Vision, Mission, & Service Mission

Our Vision

Establish Islamic banking as banking of first choice to facilitate the implementation of an equitable economic system, providing a strong foundation for establishing a fair and just society for mankind.

Our Mission

To be a premier Islamic bank, offering a one-stop shop for innovative value added products and services to our customers within the bounds of Shariah, while optimizing the stakeholders value through an organizational culture based on learning, fairness, respect for individual enterprise and performance.

Our Service Mission

To develop a committed service culture which ensures the consistent delivery of our products and services within the highest quality service parameters, promoting Islamic values and ensuring recognition and a quality banking experience to our customers.

Appendix-XXI

MEEZAN'S BRANCH NETWORK

The Bank is currently segmented into three Regions of Pakistan. The cities in which the Bank presently operates are as follows:

Southern Region Central Region Northern Region

Hub (Lasbela) Arifwala Abbottabad

Hyderabad Bahawalpur Attock

Karachi Burewala Dera Ismail Khan

Mirpurkhas Chiniot Dina

Nawabshah Daska Gujar Khan

Quetta Dera Ghazi Khan Haripur

Sakrand Faisalabad Havelian

Sukkur Gojra Islamabad

Tando Adam Gujranwala Jhelum

Tando-Allah-Yar Gujrat Kohat

Hafizabad Mansehra

Jhang Mardan

Kasur Muzaffarabad

Khanpur Nowshera

Khushab Peshawar

Lahore Rawalpindi

Lalamusa Swat Mandi Bahauddin

Mian Channu

Multan

Okara

Rahim Yar Khan

Sadiqabad

Sahiwal

Sargodha

Sheikhupura Sialkot

Appendix-XXII

Habib Bank Limited (HBL), Pakistan Board of Directors

Sultan Ali Allana Ahmed Jawad HBL Worldwide

Chairman Director

Sajid Zahid Sikandar Director Mustafa Khan Director

Mushtaq Malik

Director Moez Jamal Director

R. Zakir Mahmood

President & CEO

Appendix-XXIII

HABIB BANK LIMITED (HBL), PAKISTAN Services to Individual & Business Customers

INDIVIDUAL CUSTOMERS BUSINESS CUSTOMERS • CarToCar • Corporate Banking o Car Calculator o Cash Management o Car Showroom o Islamic Banking o FAQs • Commercial Banking • Car Loan • Investment Banking o Car Calculator • Islamic Banking o Car Showroom • Cash Management o FAQs • Zarai Banking • Credit Cards • Global Treasury o Benefits • Asset Management o Features o Promotions o Dining Discounts o Drop Box Finder o Handset Plans o FAQs o Apply Online • Deposit Accounts o Term Accounts o Current Accounts Freedom Account o Savings Accounts o Foregin Currency Accounts • Bancassurance o Amaan o Tabeer o Branch Network • Debit Card • PhoneBanking • Mutual Funds

State Bank of Pakistan - Revised Organization Structure 30-10-2008

Governor Management Committee

Anti Money Laundering Unit Governor’s Secretariat

Chief Economist * Deputy Governor Deputy Governor (Monetary Policy / Research) (Banking) (Corporate Services)

Executive Director Executive Director Comptroller Finance Economic Advisor Executive Director Executive Director (Banking Policy & (Financial Markets / (Financial Resources Group Head (Policy / Research) (Development Finance) (Banking Supervision) IT & Museum Group Regulation) Reserve Management) Management) (Human Resources)

Director Director Director Monetary Policy Director Director Chief Information Agriculture Credit Domestic Markets & Director Banking Banking Policy & Director Officer Monetary Management Payment System Inspection Regulation Human Resources Information Systems (On-site) & Technology Director Economic Analysis Director Director Director Microfinance International Markets & Director Banking Project Manager Investments Business Support Director Director Surveillance RTGS Project Director Services Museum & Art Gallery Research Off-site Supervision & Director Enforcement Director Infrastructure & Director Financial Markets Director Director Housing Finance Islamic Banking Director Statistics & Data Strategy & Conduct Training & Finance Warehouse Development

Director Director Director Financial Stability Small Medium Consumer Director Enterprise Finance Protection Exchange Policy Director/Head Treasury Operations (Back Office) Chief Librarian Library

Banking Cluster Financial Markets & Reserve Management Corporate Services Cluster (CS Cluster) Monetary Policy & Research Cluster (MPR Cluster) Cluster (FMRM Cluster)

Corporate Executive Director Secretary Internal Audit & Corporate Compliance Secretary’s Office Note: RTGS will be part of Payment Systems Department as a Division on completion of the RTGS Project.

Director / Chief Risk Officer Chief Spokesman Risk Management External Relations & Compliance

Special Counsel General Counsel’s Office

Governor’s Office Appendix-IV

Banking Surveillance Department Financial Soundness Indicators*

Indicators 2004 2005 2006 2007 2008 Mar-09 Jun -09 Sep-09 Dec-09 CAPITAL ADEQUACY Risk Weighted CAR** Public Sector Commercial Banks 13.4 14.5 15.2 16.1 13.2 13.9 14.5 15.6 14.8 Local Private Banks 10.1 10.6 12.7 11.8 12.1 12.7 13.3 14.2 14.1 Foreign Banks 17.4 16.4 15.0 14.6 21.8 22.4 23.7 23.8 23.6 Commercial Banks 11.4 11.9 13.3 12.8 12.7 13.3 14.0 14.9 14.6 Specialized Banks (9.0) (7.7) (8.3) (6.2) (4.9) (2.1) (3.4) (5.0) (2.1) All Banks 10.5 11.3 12.7 12.3 12.3 12.9 13.5 14.3 14.1 Tier 1 Capital to RWA** Public Sector Commerc ial Banks 8.6 8.8 11.1 12.2 11.0 11.6 12.0 12.8 12.4 Local Private Banks 7.5 8.3 10.4 9.9 10.2 10.7 11.2 11.8 11.5 Foreign Banks 17.1 16.1 14.3 14.0 21.3 21.9 23.1 23.3 23.1 Commercial Banks 8.6 9.1 10.8 10.5 10.8 11.3 11.8 12.4 12.1 Specialized Banks (15.0) (13.6) (13.3) (12.5) (10.1) (7.4) (7.4) (8.2) (6.3) All Banks 7.6 8.3 10.0 10.0 10.2 10.8 11.3 11.9 11.6 Capital to Total Assets Public Sector Commercial Banks 8.7 12.6 12.2 13.7 10.7 11.1 10.9 11.9 11.1 Local Private Banks 6.5 7.0 9.2 10.2 10.0 10.3 10.2 10.3 10.0 Foreign Banks 8.9 9.5 10.1 11.2 14.5 14.4 14.8 14.8 14.9 Commercial Banks 7.2 8.4 9.9 10.9 10.3 10.6 10.5 10.8 10.4 Specialized Banks (9.4) (8.1) (8.0) (5.4) (3.2) (2.7) (2.5) (3.4) (1.8) All Banks 6.7 7.9 9.4 10.5 10.0 10.3 10.2 10 .5 10.1 ASSET QUALITY NPLs to Total Loans Public Sector Commercial Banks 13.3 10.0 9.0 8.4 16.3 17.5 16.8 17.4 16.4 Local Private Banks 9.0 6.4 5.2 6.5 8.6 9.7 9.8 10.5 10.7 Foreign Banks 1.6 1.2 1.0 1.6 2.9 3.6 4.5 5.3 6.5 Commercial Banks 9.0 6.7 5.7 6.7 9.9 11.0 11.1 11.7 11.7 Specialized Banks 54.1 46.0 39.1 34.3 28.8 29.0 25.8 31.4 25.4 All Banks 11.6 8.3 6.9 7.6 10.5 11.5 11.5 12.4 12.2 Provision to NPLs Public Sector Commercial Banks 77.0 86.8 84.5 89.0 66.9 65.3 65.9 67.2 69.0 Local Private Banks 69.9 76.4 78.7 88.5 70.2 71.2 71.6 72.1 72.3 Foreign Banks 101.9 145.9 191.7 157.0 81.9 81.3 83.4 81.3 72.4 Commercia l Banks 72.4 80.4 81.5 89.1 69.3 69.5 70.0 70.8 71.4 Specialized Banks 64.9 64.8 64.1 68.6 72.4 66.4 72.8 57.1 66.3 All Banks 70.4 76.7 77.8 86.1 69.6 69.2 70.2 69.7 71.0 Net NPLs to Net Loans Public Sector Commercial Banks 3.4 1.5 1.5 1.0 6.1 6.9 6.4 6.5 5.7 Local Private Banks 2.9 1.6 1.1 0.8 2.7 3.0 3.0 3.2 3.2 Foreign Banks (0.0) (0.6) (1.0) (0.9) 0.5 0.7 0.8 1.0 1.9 Commercial Banks 2.7 1.4 1.1 0.8 3.3 3.6 3.6 3.7 3.7 Specialized Banks 29.3 23.1 18.7 14.0 10.0 12.1 8.6 16.4 10.3 All Banks 3.8 2.1 1.6 1.1 3.4 3.9 3.7 4.1 3.9 Net NPLs to Capital Public Sector Commercial Banks 16.2 5.5 6.4 3.4 30.3 31.6 30.0 27.6 26.2 Local Private Banks 24.3 13.0 7.1 4.1 15.9 15.4 15.6 15.8 15.9 Foreign Banks (0.2) (3.0) (5.1) (4.1) 1.6 2.0 1.9 2.4 4.8 Com mercial Banks 19.0 9.0 6.2 3.7 17.9 17.9 17.8 17.6 17. 4 Specialized Banks ------All Banks 29.2 14.3 9.7 5.6 19.4 19.6 19.0 19.9 18.9 EARNINGS Return on Assets (Before Tax) Public Sector Commercial Banks 2.4 3.3 4.0 3.5 0.6 1.7 1.1 1.5 1.5 Local Private Banks 1.7 2.7 3.1 2.0 1.3 1.9 1.8 1.7 1.6 Foreign Banks 2.5 3.6 3.2 1.5 0.0 1.0 0.4 0.1 (0.3) Commercial Banks 2.0 2.9 3.2 2.3 1.1 1.8 1.6 1.6 1.5 Specialized Banks (0.4) (1.0) (1.3) 1.4 3.2 3.8 3.3 1.3 2.5 All Banks 1.9 2.8 3.1 2.2 1.2 1.8 1.7 1.6 1.5 231

Appendix-IV

Banking Surveillance Department Financial Soundness Indicator s* Indicators 2004 2005 2006 2007 2008 Mar -09 Jun -09 Sep -09 Dec -09 EARNINGS Return on Assets (After Tax) Public Sector Commercial Banks 1.3 2.2 2.7 2.5 0.5 0.9 0.6 1.0 0.9 Local Private Banks 1.2 1.8 2.1 1.4 0.9 1.2 1.1 1.0 1.0 Foreign Banks 2.0 2.5 2.1 0.7 0.3 0.4 0.1 (0.1) (0.3) Commercial Banks 1.3 2.0 2.2 1.6 0.8 1.1 1.0 1.0 0.9 Specialized Banks (0.8) (1.2) (1.8) 0.7 1.8 2.4 1.9 (0.6) 0.6 All Banks 1.2 1.9 2.1 1.5 0.8 1.1 1.0 0.9 0.9 ROE (Avg. Equity& Surplus) (Before Tax) Public Sector Commercial Banks 30.8 30.7 32.4 27.2 5.2 14.7 9.5 12.8 13.2 Local Private Banks 28.8 40.1 36.2 20.4 12.9 18.1 17.8 16.4 15.2 Foreign Banks 26.7 38.9 30.0 13.1 0.0 6.7 2.8 0.4 (2.1) Commercial Banks 29.0 37.2 34.7 21.8 10.6 16.8 15.2 14.7 13.9 Specialized Banks ------All Banks 30.5 38.2 35.2 22.6 11.4 17.7 16.0 15.1 14.5 ROE (Avg. Equity &Surplus) (After Tax) Public Sector Commercial Banks 17.2 20.9 21.7 19.5 4.4 7.8 5.3 8.4 8.0 Local Private Banks 20.2 27.2 25.0 13.8 8.5 11.3 11.0 10.0 9.4 Foreign Banks 21.5 27.1 20.4 6.0 2.2 2.8 0.5 (0.9) (2.0) Commercial Banks 19.6 25.4 23.7 15.0 7.3 10.1 9.2 9.1 8.5 Specialized Banks ------All Bank s 20.3 25.8 23.8 15.4 7.8 10.7 9.7 9.0 8.6 NII/Gross Income Public Sector Commercial Banks 63.7 71.3 69.5 65.9 65.4 68.6 70.0 68.2 62.6 Local Private Banks 62.0 73.0 73.5 70.7 73.3 78.9 75.9 75.7 75.8 Foreign Banks 57.7 61.5 65.8 59.1 61.3 54.8 57.2 60.6 64.4 Commercial Banks 61.9 71.3 72.1 69.2 71.3 76.1 74.1 73.8 73.1 Specialized Banks 81.9 87.7 40.1 42.8 46.6 65.9 41.3 48.2 47.9 All Banks 62.8 72.0 70.9 68.2 70.4 75.8 73.0 73.1 72.3 Cost / Income Ratio Public Sector Commercial Banks 39.5 34.3 31.8 30.2 39.1 48.1 48.4 45.7 49.3 Local Private Banks 56.2 43.1 40.7 45.4 51.8 49.2 48.6 49.3 50.5 Foreign Banks 49.0 42.2 49.8 57.0 69.6 58.6 63.6 69.9 77.5 Commercial Banks 51.7 41.2 39.4 42.8 50.2 49.5 49.3 49.7 51.5 Specialized Banks 57.8 47.8 62.6 53.2 52.1 60.4 70.6 63.7 55.4 All Ban ks 52.0 41.5 40.3 43.2 50.3 49.9 50.1 50.1 51.6 LIQUIDITY Liquid Assets/Total Assets Public S ector Commercial Banks 43.9 35.6 33.9 37.0 30.5 31.4 30.2 29.3 29.8 Local Private Banks 34.3 32.4 31.1 32.5 27.4 29.5 30.5 30.9 32.2 Foreign Banks 39.8 41.8 41.0 41.6 45.3 49.6 54.7 57.2 54.7 Commercial Banks 37.0 33.9 32.2 33.8 28.7 30.7 31.5 31.6 32.6 Specialized Banks 25.3 25.8 23.0 27.9 24.5 21.6 22.2 19.0 19.0 All Banks 36.6 33.7 31.9 33.6 28.6 30.5 31.2 31.4 32.3 Liquid Assets/Total Deposits Public Sector Commercial Banks 52.6 44.7 42.6 47.1 38.8 40.3 38.6 38.7 38.4 Local Private Banks 42.3 40.3 40.6 42.9 35.7 39.3 39.9 41.2 43.4 Foreign Banks 53.4 57.9 61.1 61.1 71.9 79.6 84.2 83.3 82.2 Commercial Banks 45.7 42.7 42.0 44.3 37.6 41.0 41.2 42.3 43.7 Specialized Banks 154.1 183.2 205.4 247.7 229.4 243.7 206.9 193.5 155.3 All Banks 46.5 43.5 42.7 45.1 38.2 41.5 41.7 42.7 44.1 Advances/Deposi ts Public Sector Commercial Banks 49.7 59.8 64.6 60.0 68.4 65.2 65.0 67.0 65.1 Local Private Banks 67.3 70.8 74.5 70.1 75.4 71.4 69.2 68.8 66.9 Foreign Banks 70.1 68.7 80.1 75.2 69.1 65.1 57.5 50.2 56.3 Commercial Banks 63.6 68.4 72.7 73.8 73.8 69.9 67.9 67.8 66.2 Specialized Banks 370.5 400.7 528.4 507.3 577.0 721.3 597.2 683.3 544.9 All Banks 65.8 70.2 74.6 69.7 75.5 71.7 69.6 69.6 67.9 *Source: (State Bank of Pakistan, 2009)

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