The correlations between big data analytics and financial performance empirical investigation in the vietnamese banking sector

1 THE STATE BANK OF VIETNAM MINISTRY OF EDUCATION AND TRAINING BANKING UNIVERSITY OF HO CHI MINH CITY CHU VIET HONG THE CAPABILITIES OF BIG DATA ANALYTICS INFLUENCE ON FINANCIAL PERFORMANCE: EMPIRICAL INVESTIGATION IN BANKING SECTOR AT HO CHI MINH CITY THESIS PROPOSAL BUSINESS ADMINISTRATON CODE: 7340101 Advisor by DANG TRUONG THANH NHAN, MBA HO CHI MINH, 2021 THE STATE BANK OF VIETNAM MINISTRY OF EDUCATION AND TRAINING BANKING UNIVERSITY OF HO CHI MINH CITY CHU VIET HONG THE CAPABILITIES OF BIG DATA ANALYTICS INFLUENCE ON FINANCIAL PERFORMANCE: EMPIRICAL INVESTIGATION IN BANKING SECTOR AT HO CHI MINH CITY THESIS PROPOSAL BUSINESS ADMINISTRATON CODE: 7340101 Advisor by DANG TRUONG THANH NHAN, MBA HO CHI MINH, 2021 i ABSTRACT This study presents a big data analytics capability (BDAC) model based on the resource-based approach and the literature on big data analytics (BDA), information system (IS) success, and the commercial value of information technology (IT) The study expands on the previous research by looking at the direct impacts of BDAC on financial performance at banks (FPER), as well as the effects of technological capacity, talent capability, management, and bank performance on the link between big data analysis and FPER We utilized an online survey to collect data from 250 Vietnamese IT managers and business and finance analysts with big data and business analytic experience at banks in Ho Chi Minh City to evaluate our suggested research methodology The findings confirm the value of the entanglement conceptualization of the hierarchical BDA model, which has both direct and indirect impacts on FPER As a result, this study examines the relationship between Vietnamese banks' big data analysis and their financial indicators to determine if a focus on big data analysis can be applied to assist improve the banking sector's financial performance The research study was conducted in order to: (1) Identify BDA measures influencing BDA capability in the Vietnamese banking sector; (2) evaluate the relationship between BDA measures and BDA capability in the Vietnamese banking industry; (3) examine the correlation between BDA capability and financial performance The study began with a reference to theories and results of previous studies on experience in using and working with big data at banks in Ho Chi Minh City recent years, the author proposed a theoretical model of factors’ BDA affecting financial performance including factors: BDA management capability (BDAMC), BDA technology capability (BDATEC), BDA talent capability (BDATLC), BDA capability (BDAC) and bank performance (BPER) with 20 variables of observation and each factor with variables The formal study was carried out utilizing quantitative research approaches such as consumer survey techniques and comprehensive questionnaires The sample size ii was 250 people SPSS 20 statistical software was used to process the obtained data Cronbach's alpha reliability coefficient was used to assess the scale's preliminary reliability, and the EFA exploratory factor analysis was used to test it The suggested research model was originally calibrated based on the analysis outcomes The author next used the features of the redesigned research model to the linear regression analysis Based on the findings of this investigation, the author's choice with observed variables and the basic model of five component factors with 20 observation variables remained unaltered iii DECLARATION This thesis is the author's own research work, the research results are honest, in which there are no previously published contents or content made by others except for the cited references full source in the thesis iv ACKNOWLEDGEMENTS During my thesis time, I got loads of backings and supportive gestures from numerous people This thesis would not have been accomplished without those valuable input, support, counsel, and advice First and foremost, I would like to express my deepest acknowledge to my advisor MBA Dang Truong Thanh Nhan – lecturer at Banking University of Ho Chi Minh City for her unbelievable and unreserved help, valuable advices and recommendation Thanks for her effort and wide knowledge to make my topic possible, her suggestions, direction and advices are always highly appreciated and greatly contributing to the success of this thesis I would also like to express my sincere appreciation to the professors and lecturers for their guidance during my academic years at the University of Banking The knowledge and skills that I have learned, have assisted me in the completing of this thesis Last but not least, honestly the most supported ones are my family Words fail me to express my thankfulness for my parents for their endless love To all the above, and so many more, I just simply want to say again “Thank you for all your encouragement, support, and love” v TABLE OF CONTENTS ASTRACT i DECLARATION iii ACKNOWLEDGEMENTS iv LIST OF ABBREVIATIONS viii LIST OF TABLES ix LIST OF FIGURES x LIST OF DIAGRAMS x CHAPTER OVERVIEW OF THESIS 1.1 Research Background 1.2 Research objectives 1.3 Research questions 1.4 Research subject and scope 1.4.1 Research subject 1.4.2 Research scope 1.4.3 Research respondents 1.5 Significant of study 1.5.1 Practical significance 1.5.2 Scientific significance 1.6 Research Method 1.6.1 Expected layout of the thesis 1.6.2 Proposed thesis structure 1.7 Conclusion CHAPTER LITERATURE REVIEW AND REVIEW RESEARCH MODEL 2.1.The Big Data Analytics 2.2 Navigating BDAs in the Financial Sector 11 2.3 The theoretical background 12 2.3.1 The Resources-based view theory (RBT) 13 vi 2.3.2 Institutional theory 14 2.3.3 The management theory 15 2.3.4 The organizational culture 16 2.4 Theoretical Model and Hypotheses 22 2.4.1 BDA Management Capability (BDAMC) 22 2.4.2 BDA Technology Capability (BDATEC) 23 2.4.3 BDA Talent Capability (BDATLC) 24 2.4.4 Big Data Analytics Capability (BDAC) and Financial Performance (FPER) 26 2.4.5 Bank Performance (BPER) and Financial Performance (FPER) 27 2.4.5.1 Bank Performance (BPER) 27 2.4.5.2 Financial Performance (FPER) 29 2.5 Conclusion 31 CHAPTER RESEARCH METHODOLOGY 32 3.1 Research Process 32 3.1.1 Quantitative Research 32 3.2 Adjust the Scale 33 3.3 Data Processing Methods 38 3.3.1 Cronbach's Alpha Analysis 38 3.3.2 EFA Analysis 39 3.3.3 Regression and Anova Analysis 40 3.3 Conclusion 41 CHAPTER RESULT AND DISCUSSION 43 4.1 Overview of the research samples 43 4.1.1 Descriptive statistics for variables 43 4.1.2 Descriptive statistics for independent variables 45 4.2 Cronbach’s Alpha Analysis 47 4.2.1 Evaluate Independent Variable Scale 47 4.2.2 Evaluate Dependent Variable Scale 49 vii 4.3 Exploratory Factor Analysis (EFA) 49 4.3.1 EFA analysis for Independent Variable Scale 49 4.3.2 EFA analysis for Dependent Variable Scale 52 4.4 Linear Regression and ANOVA Analysis 54 4.4.1 Linear Regression 54 4.4.2 ANOVA Analysis 54 4.5 Hypothesises testing 55 4.6 Determining the differences according to the characteristics of the research object 57 4.6.1 Difference in Type of Bank 57 4.6.2 Difference in Data usage frequency 58 4.7 Theoretical contributions 60 4.8 BDA practices of different types of banks 61 4.9 Challenges related to BDA in the banking sector in Vietnam 64 4.10 Reflection on findings based on proposed conceptual framework 66 4.11 Conclusion 67 CHAPTER CONCLUSIONS AND RECOMMENDATION 69 5.1 Conclusions 69 5.2 Implications 70 5.2.1 BDA capability 70 5.2.2 BDA talent capability 71 5.2.3 Bank performance 71 5.2.4 BDA technology capability 73 5.3 Limitations and Recommendation for Future Research 74 5.4 Final reflection 75 REFERENCE 77 APPENDICES 91 viii LIST OF ABBREVIATIONS BDA Big data analystics BDAC Big data analytics capability BDAMC BDA management capability BDATEC BDA technology capability BDATLC BDA talent capability BPER Bank performance FPER Financial performance IS Information system IT Information technology RBT Resource-based view theory 80 Davenport, T 2018, 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Organizations as Actors in Social Systems, In Zucker, LG ed, Institutional Patterns and Organizations; Culture and Environment, Ballinger, Cambridge, MA, pp 23-49 91 APPENDICES Appendice The questionaire of thesis Part 1 Which bank are you currently working at? What part of the bank are you working in? Is your bank a domestic or a foreign bank? A Domestic bank B International bank How often you work with data and handle them? A Not use B Occasionally C Having used but not handled D Not used but having handled E Having used and having handled 92 Part Please indicate your level of agreement on the following statements by crossing the box that you think is most appropriate in accordance with the following convention: Strongly disagree Disagress Partially agree Agree Strongly agree The BDA Management Capability scale (BDAMC) We BDAMC1 continuously innovative examine opportunities for the the 5 5 strategic use of big data analytics When we make big data analytics investment decisions, we consider and BDAMC2 project about how much these options will help end-users make quicker decisions In our organization, business analysts BDAMC3 and line people meet frequently to discuss important issues both formally and informally We are confident that big data analytics BDAMC4 project proposals are properly appraised The BDA Technology Capability scale (BDATEC) Compared to rivals within our industry, BDATEC1 our organization has the foremost available analytics systems 93 All remote, branch, and mobile offices BDATEC2 are connected to the central office for 5 analytics Software applications can be easily BDATEC3 transported and used across multiple analytics platforms Reusable software modules are widely BDATEC4 used in new analytics model development The BDA Talent Capability scale (BDATLC) Our analytics personnel are very BDATLC1 capable in terms of programming 5 5 5 skills BDATLC2 Our analytics personnel show superior understanding of technological trends Our analytics personnel understand our BDATLC3 organization’s policies and plans at a very high level Our analytics personnel are very BDATLC4 capable in terms of planning, organizing, and leading projects The BDA Capability scale (BDAC) We perform big data analytics planning BDAC1 processes in systematic and formalized ways We frequently adjust big data analytics BDAC2 plans to better adapt to changing conditions 94 In our organization, business analysts BDAC3 and line people coordinate their efforts 5 harmoniously BDAC4 Our analytics department is clear about its performance criteria The Bank Performance scale (BPER) Bank performance (BPER): Using analytics improved during the last years relative to competitors: BPER1 We have entered new markets more quickly than our competitors 5 5 We have introduced new products BPER2 or services to the market faster than our competitors Our success rate of new products BPER3 or services has been higher than our competitors BPER4 Our market share has exceeded that of our competitors The Financial Performance scale (FPER) Financial performance (FPER): Using analytics improved during the last years relative to competitors: FPER1 Customer retention FPER2 Profitability FPER3 _Return on investment 5 FPER4 Overall financial performance Appreciate Your Participation In My Survey! ... discussed in the article This article aims to elucidate whether big data mining and big data investment could improve the financial sector output of the financial sector by looking at the Vietnamese. .. financial performance, the challenges associated with BDA application in the banking industry, and the relationship between BDA and financial performance The ideas and features of BDA inside the industry... Discussion of research findings The quantitative study findings were the emphasis of this chapter The findings of the quantitative investigation on the link between BDA and financial performance were