A STUDY ON THE INFLUENCE OF MOBILE FOODIE APPLICATIONS ON RESTAURANT SELECTION DECISIONS BY MISTER ANUSORN PHOPIPAT AN INDEPENDENT STUDY SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE PROGRAM IN MARKETING (INTERNATIONAL PROGRAM) FACULTY OF COMMERCE AND ACCOUNTANCY THAMMASAT UNIVERSITY ACADEMIC YEAR 2017 COPYRIGHT OF THAMMASAT UNIVERSITY Ref. code: 25605902040483CGF A STUDY ON THE INFLUENCE OF MOBILE FOODIE APPLICATIONS ON RESTAURANT SELECTION DECISIONS BY MISTER ANUSORN PHOPIPAT AN INDEPENDENT STUDY SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE PROGRAM IN MARKETING (INTERNATIONAL PROGRAM) FACULTY OF COMMERCE AND ACCOUNTANCY THAMMASAT UNIVERSITY ACADEMIC YEAR 2017 COPYRIGHT OF THAMMASAT UNIVERSITY Ref. code: 25605902040483CGF (1) Independent Study Title A STUDY ON THE INFLUENCE OF MOBILE FOODIE APPLICATIONS ON RESTAURANT SELECTION DECISIONS Author Mister Anusorn Phopipat Degree Master of Science Program in Marketing (International Program) Major Field/Faculty/University Faculty of Commerce and Accountancy Thammasat University Independent Study Advisor Professor Malcolm C. Smith, Ph.D. Academic Year 2017 ABSTRACT Online food delivery competition in Thailand is fierce. Public behavior has changed from eating out at restaurants to ordering food from various online providers. Social media allows users/customers to generate on-line content and share their experiences with the online community. This study of “The influence of mobile foodie applications on restaurant selection decisions” is an independent research exercise focusing on the contemporary topic of technological issues regarding applied marketing in Thailand. There are four primary research were to 1) To identify customer profiles and then classify them into the segments, 2) To determine consumer restaurant selection behavior and experience, 3) To determine consumer price perception toward online order fees, and 4) To identify key application features needed by customers. Ref. code: 25605902040483CGF (2) Exploratory research was conducted through a secondary data reviews and ten in-depth interviews. Descriptive research was conducted by an online social media survey using Facebook, LINE chat application, and e-mail. Target respondents were males or females aged between 18 to 60 years old who had access to the internet and had used a foodie application in the past three months. Data gathered from 265 respondents were analyzed using the Statistical Package for the Social Sciences (SPSS) by Analysis of Variance (ANOVA), Chi-square, frequencies, percentages, factor analysis, cluster analysis, and price sensitivity measurements. Main findings from the quantitative research indicate that customers who used online delivery food applications can be divided into four segments as achiever, perfectionist, extrovert, and outdoor enthusiast. Top three restaurant selection criteria for all respondents were speed of service, location, and value for money. The three features respondents perceived to be important when using an application were booking, payment option, and promotional information features. In term of awareness, LINEMAN was ranked as number one followed by foodpanda, UberEat, and Grabfood. Interestingly, the current online delivery fee is perceived to be acceptable by respondents, and there is room to increase the service fee if needed. The recommendation for the marketer is to focus on the achiever segment because they are the heavy users of online food delivery services. This segment can be engaged via online channels. Therefore, marketers should try to prevent this segment from switching to other service providers. For developers, the top three features of foodie applications to focus on are booking, payment option, and Ref. code: 25605902040483CGF (3) promotional information features. Also, the contents section of the application is another important aspect to focus on. This research will enable restaurant managers and application developers to better understand changing customer behaviors better. Furthermore, the findings will aid managers to design strategies to entice more customers to use their restaurants and applications. Keywords: Restaurant selections, food application, online delivery Ref. code: 25605902040483CGF (4) ACKNOWLEDGMENTS Firstly, I would like to express my sincere appreciation and gratitude to Prof. Malcolm C. Smith, my supportive advisor, for his valuable recommendations throughout the entire independent study course. Prof. Malcolm C. Smith was always accessible during his visits to Thailand. Without his support, comments, and advice, this research would not have been completed. Secondly, I would like to express my sincere gratitude to all the respondents for giving their valuable time to participate in the in-depth interviews, complete the surveys, and contribute to a significant part of this research. I would also like to thank all the Professors from every course I have taken during my two years at Thammasat University. Lastly, I would like to thank my family, friends, and colleagues for their understanding concerning my time devoted to the completion of this master’s degree at Thammasat University. Mister Anusorn Phopipat Ref. code: 25605902040483CGF (5) TABLE OF CONTENTS Page ABSTRACT (1) ACKNOWLEDGEMENTS (4) LIST OF TABLES (9) LIST OF FIGURES (10) CHAPTER 1 INTRODUCTION 1 1.1 Introduction to the study 1 1.2 Research objectives 3 CHAPTER 2 REVIEW OF LITERATURE 4 2.1 Restaurant delivery system 4 2.2 Thailand internet usage and customer changing behavior 4 2.3 Online spending in Thailand 4 2.4 Online food delivery service providers in Thailand 5 2.5 Customer decision-making process 5 2.6 Social Media, user-generated content and its effects 6 on purchase intention 2.7 Summary 7 CHAPTER 3 RESEARCH DESIGN 8 3.1 Research Methodology 8 Ref. code: 25605902040483CGF (6) 3.1.1 Exploratory Research Design 8 3.1.2 Secondary Data Research 8 3.1.3 In-depth interviews 8 3.2 Descriptive Research Design 8 3.2.1 Questionnaire survey 9 3.3 Data collection 9 3.3.1 Qualitative data 9 3.3.2 Quantitative data 9 3.4 Data Analysis 9 3.5 Theoretical Framework 10 3.6 Limitations of the study 10 CHAPTER 4 RESULTS AND DISCUSSION 11 4.1 Key findings from Secondary Research 11 4.2 Key findings from In-depth Interviews 11 4.3 Key findings from the questionnaire survey 13 4.3.1 General Profile of Respondents 13 4.3.2 Respondents’ Demographic profiles 13 4.3.3 Foodie application users’ segmentation 15 4.3.4 Customer segments 16 4.3.5 General Profile of each Customer Segment 17 4.3.6 Psychographic profile by segment 19 4.3.7 Restaurant Selection behavior by customer’s segments 20 4.3.8 Restaurant selection criteria 21 4.3.9 Key attributes that stimulates usage decision 22 of foodie applications 4.3.10 Key usage decision attributes by customer segments 23 4.3.11 Restaurant selection criteria via foodie application 23 4.3.12 Mean comparison of key restaurant selection criteria 24 via applications by customer segments 4.3.13 Importance of application features 25 Ref. code: 25605902040483CGF (7) 4.3.14 Mean comparison of key application features 25 by customer segments 4.3.15 Respondents’ awareness of online delivery 26 application in the market 4.3.16 Respondent’s perception on each application 26 4.3.16.1 LINEMAN Application’s Perception 26 4.3.16.2 GrabFood Application’s Perception 27 4.3.16.3 UBER EATS Application’s Perception 28 4.3.16.4 foodpanda Application’s Perception 28 4.3.17 Respondents’ perceptions toward fees charged 29 by online food delivery applications 4.3.18 Price sensitivity Measurement 30 4.3.19 Impact of price promotion on consumer 31 purchase intentions for foodie applications 4.3.20 Mean comparison of price promotion impact on 31 purchase intent by customer segments CHAPTER 5 SUMMARY AND CONCLUSIONS 32 5.1 Research Summary 32 5.1.1 Customer Segmentation based on psychological factors 32 5.1.2 Consumer restaurant selection behavior 32 5.1.3 Consumer perception toward application’s features 32 5.1.4 Consumer perception toward each brand in the market 33 5.1.5 Consumer perception toward online delivery service fee 33 5.2 Recommendations 34 REFERENCES 36 APPENDICES APPENDIX A: In-depth Interview’s questions 38 Ref. code: 25605902040483CGF (8) APPENDIX B: Online questionnaire’s questions 39 APPENDIX C: Respondent’s profile and segmentation 52 APPENDIX D: Restaurant selection behavior 55 APPENDIX E: User’s perception on foodie application 65 APPENDIX F: Price perception toward online order fee 70 BIOGRAPHY 71 Ref. code: 25605902040483CGF (9) LIST OF TABLES Tables Page 4.1: All respondents’ demographic profile by frequency and percentage 13 4.2: Factor Analysis from psychological attributes 15 4.3: Number of respondents in each segment by frequency 16 4.4: Each customer segments by demographic profile 17 4.5: ANOVA test on restaurant selection behavior on 21 customer’s segments 4.6: All respondents' usage decision attributes for foodie application 23 by mean score 4.7: All Respondents' restaurant selection criteria via applications 24 by mean score 4.8: All Respondents' key application features by mean score 25 4.9: Online delivery application awareness by frequency and percentage 26 4.10: LINEMAN application’s perception by mean score 27 4.11: GrabFood application’s perception by mean score 27 4.12: UBER EATS application’s perception by mean score 28 4.13: foodpanda application’s perception by mean score 29 4.14: Respondents’ perception toward fees charged by mean score 29 4.15: Price promotion impact on purchase intent by mean score 31 Ref. code: 25605902040483CGF (10) LIST OF FIGURES Figures Page 2.1 The marketing Funnel 6 3.1 Research’s framework 10 4.1 Price sensitivity measurement 30 Ref. code: 25605902040483CGF 1 CHAPTER 1 INTRODUCTION 1.1 Introduction to the study Restaurants are critical businesses in Thailand as they are related to the travel and tourism industry which accounted for 20.6% of the country’s GPD in 2016 and is expected to rise by 9.4% to 21.9% in 2017 (World travel & Tourism council, 2017).