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國國國國國國國國國國國國國國國國國國 Department of Tropical Agriculture and Internatonal Cooperaton Natonal Pingtung University of Science and Technology 國國國國國國 Ph.D Dissertaton 國國國國國國國國國國國國國國國國國國國國國國國國國 Applying Big Data Analytcs in E-commerce: Aspects of Business and Customer 國國國國 Advisor: 國國國國國(Shu-Yi Liaw, Ph.D.) 國國國 Student: 國國國 (Le Thi Mai) 國國國國 107 國 06 國 01 國 June 1, 2018 國國 國國國P10322019 國國國國國國國國國國國國國國國國國國國國國國國國國國國國 國國 國國國國151 國 國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國 國國國國國國國國國106 國國國國 國國 國國國國國國國國 國國國國國國國 國國國國國國國國 國國 國國國國國國國 國國國國國國國國國國國國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國 國國國國國國國國國國國國1國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國國國國國國2國國國國國國國國國 國國國國國國國國國國國國國國國國國國國 國國國國3國國國國國國國 國國國國國國國國國國國國國國4國國國國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國國國國國國國國國國國國國國國國 349 國國國國國國國國國國國國國國國國國國國國國國國國國國國國國 國國國國國國國 國1國國國國國國國國國國國國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國國 國國國國國國國國國 國國國國國國國國國國國國國國國國國國國國國國 國國國國國國國國 國國國國國國國國國國國國國國國國國國國國國國國 國國國國國國國國國國國國國國國國國國國國國國國國國國國國 國國國 國國國國國國國國國國國國國國國國國國國國國國 I 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University of Science and Technology Graduate Date: June 1, 2018 Degree Conferred: Doctoral Degree Name of Student: Le Thi Mai Advisor: Liaw, Shu-Yi, Ph.D The Contents of Abstract in This Dissertation: The era of Big Data analytcs (BDA) has begun in most industries within developing and developed countries This new analytics tool has raised motivaton for experts and researchers to study its impacts to business values and challenges However, there is shortage of studies which evaluate the applicatons of BDA under business view and help to understand customers’ views towards the applicatons of Big Data analytic This research aims to (1) draw on a systematic review of the literature about definiton, distnctve characteristics, business values and challenges of a company when applying Big Data analytics, (2) explore and determine the pros and cons of applying Big Data analytics that affects customers’ responses in an ecommerce environment, perceived (3) evaluate the mediaton effect of value’s dimensions and perceived risk, (4) determine the moderation effect of trust propensity Data analyses were conducted by using the statistcal package for social sciences and analysis of moment structures software in useful sample of 349 respondents in Vietnam Two aspects as business and customer views are reviewed, explored, discussed in this study III III The major findings include: (1) The study synthesized diverse BDA concepts that provide deeper insight about applicaton of BDA for e-commerce firms It is highlight that the increase in interest related to BDA in e-commerce in recent years BDA applicatons in e-commerce can be divided into five aspects like as creatng transparency, discovering needs and improving performance, segmentng market, better decision making, new product or business model innovation These applicatons bring many business values but also raise some challenges when e-firms want to apply BDA (2) The findings found that information search, recommendation system, dynamic pricing, and customer services had different significant positive effects on customers’ responses Specifically, information search had a highest improved significant customers’ influence behavior on customers’ Following by intention dynamic and pricing, recommendation system and customers’ service also had significant impact on customers’ intention but decreased customers’ behavior On another hand, privacy and security, shopping addiction, and group influences were found to have different significant negative effects on customers’ responses Specifically, shopping addiction had a drastic change from intenton to behavior compared to group influences and privacy and security It cannot be denied that customers receive positve and negatve factors at the same time (3) The results confirmed that functonal and emotional values play mediating roles between positve of applying BDA and consumers’ responses However, there weren’t significant different between mediator effect of functional value and emotonal value This finding highlights the notificaton that customers nowadays not only find their products or services but also seek enjoyment when online shopping under Big Data era Therefore, efirms should increase perceived value based on creasing equally functonal and emotional values IV IV (4) The study found out that perceived risk don’t act mediate the relatonship between negative of applying BDA and consumers’ responses Besides, customers’ trust propensity was found to moderate the relation of negative factor of applying BDA to customers’ responses and perceived risk to customers’ responses High trust propensity partcipants reported stronger responses than those with low trust propensity It due to customers’ trust on new applications of BDA, hence, it is easy to influence on customers as their negative response when negative factor and perceived risk are rising This study contributes to improve understanding of applicatons of Big Data Analytics under business view and customer view This could play an important role to develop sustainable consumers market E-vendors can rely on Big Data analytics but over usage may have some negatve applicatons Besides that, the research also broader discussion regarding future research opportunites, challenges in theory and practice Keywords: E-commerce, Big Data Analytics, Customers’ Responses, Perceived Value, Perceived Risk, Trust Propensity V V ACKNOWLEDGEMENTS This study has been carried out at the Department of Tropical Agriculture and Internatonal Cooperation (DTAIC), National Pingtung University of Science and Technology (NPUST), Taiwan This is the outcome of knowledge that I received from this university, my contnuous efforts to learning, and consistent guidance of my advisor Firstly, I would like to express my sincere grattude to my advisor, Professor Shu-Yi Liaw for contnuous support of my Ph.D study and related research He has given me valuable guideline, patence, assistance, motvaton and inspiration during Ph.D time His intellectual directon and critical reviews of research works helps me all the time and find a right tract towards the successfully competton of this dissertaton He is the best teacher I have met Besides my advisor, I would like to thank the rest of my advisory committee: Dr Shi-Jer Lou, Dr Rong-Fang Chen, Dr Shih-Wei Chou, and Dr Pei-Chen Sun, for their insightul comments and encouragement My sincere thanks also goes to Dr Nguyen Tuan Anh who encourage me to join Ph.D program Many thanks to Dr Joey Lee, Dr Henry Chen and other faculties who provided for their encouragement and supports during my study I would like to thank Barbara, Sylvia (OIA), Sophia, Joanna and all DTAIC staff, Yang Ya-Chu, Lin Yi-Ru and other staff of computer center for their assistants I thank my fellow classmates for the discussions and fun time we had Also thank my internatonal friends Mediana Purnamasari (Indonesia), Mr Chuang-Yeh Huang (Johnson), Mr Edgardo, Caleb Milk Breria (P&G), Miguel, Michael Qwanafia Bilau (Solomon Islands), Rudra (Nepal), Stanley, Jimmy, Adam, Guo Wei-Peng and other my friends for their support during VI VI the entre study Thanks to Vietnamese student associaton members and the time we have fun activites together I would like to thank NPUST and Chung Hwa Rotary Education Foundation for providing me the scholarship to pursue my doctoral degree Last but not the least, I extremely grateful to my family, my boyfriend and my relatives who have always given me encouragement and support to finalize my study in abroad VII TABLE OF CONTENTS 國國 I ABSTRACT III ACKNOWLEDGEMENTS VI TABLE OF CONTENTS VIII LIST OF TABLES XII LIST OF FIGURES XIV CHAPTER I INTRODUCTION 1.1 Background of the Study 1.2 Statement of the Problem 1.3 Objectives of the Study 1.4 Contributon of the Study 1.5 Definiton of the Operation Terms 1.6 Research Flowchart 1.7 Research Systematic Discussion CHAPTER II LITERATURE REVIEW 11 2.1 Concept of Big Data in E-commerce Environment 11 2.1.1 Big Data Analytics in the E-Commerce Environment 11 2.1.2 Big Data’s Distinctve Characteristics 13 VIII VIIIV 2.1.3 Types of Big Data Used in E-commerce 18 2.2 Big data analytics in E-commerce: Aspect of business 22 2.2.1 Literature Review Research Approach 23 IXI XIX Appendix B QUESTIONNAIRE (English Version) Number: DISSERTATION RESEARCH Pros and Cons of Applying Big Data Analytcs for Business and Customer in E-commerce context Dear Respondent, I am undertaking a research project to determine the effects on e-commerce users’ perception when e-vendors use Big Data analytics application I kindly request you can complete the following questionnaire regarding your feeling, thinking, preferences and your attitudes towards e-commerce service The following part is instruction to complete this survey Step Looking through the survey to ensure that you know what will you have to complete for survey This survey will ask you some factors: Recommendation system, Information Search, Dynamic Price, Customer Service, Perceived value, Privacy and Security, Shopping Addiction, Group influences, Perceived Risk, and Customers’ responses Each factor we will explain what meaning, example is and how to measure your feeling Please pay attenton Step Navigate to the Amazon website (www.amazon.com) which is one of famous websites using big data analytics applicaton This action is required to at least times on computer and goes through the procedure of buying any product on the website, but not actually purchase Step Complete the survey Your partcipation is vital to scientific research and is greatly appreciated Thank you very much in advance! Yours sincerely, Le Thi Mai Ph.D Student Supervisor: Dr Shu-Yi Liaw Associate Professor of College Management Natonal Pingtung University of Science and Technology Fill the blank with (X) sign on the answer you think most appropriate Demographic/ Personal Data  Gender: Male Female  How many times last month you access e-commerce website?  Not at all  1-2 tmes  3-4 times  more than times  Kind of product was chosen for interacton with Amazon website  (1) Lightweight on-Ear Headphones – White  (2) Halston Heritage Women's Strapless Dress with Flared Skirt Please circle your response for each of the following items based on the following scale: Strongly Disagree disagree Disagree somewha Agree Neutral Agree somewha Strongly Agree Part A Based on your vendor website, percepton or ideas after you feel the positve interaction with e- applications of Big Data analytcs, using following statements as your consideraton or your thinking So please No I am able to search the useful information in IS1 the e-shopping website The information I search in the e-shopping IS2 site are detailed and completed Search result is provided quickly and fit to IS3 my need Search result is provided by shopping IS4 website is very realistic RS1 Shopping website can recommend substtute goods for thewebsite product I want can to buy recommend RS2 Shopping 7 7 7 RS3 RS4 PD1 PD2 PD3 PD4 CS1 CS2 CS3 CS4 complementary goods for the product I want to buy website can recommend for you Shopping some products may be you like or best sellers of website I believe that the recommendation information is an act of kindness Providing different prices for individual customers at the same time Offer different prices at different times Providing different prices with different substtute products Providing different prices with different conditons on the same product The website can provide channels to support customers I expect that I am able to track my order 7 7 7 7 The shopping website which provides virtual experience can let me choose more suitable goods I can refer to the reviews of customers who bought the products before 141 Part B Based on your percepton or ideas after interaction with e- vendor website, you feel the negatve applications of Big Data analytics, using following statements as your consideraton or your thinking So please No PS1 PS2 PS3 PS4 SA1 SA2 SA3 SA4 SA5 Statement Online retailers may disclose my personal information (e.g email address, mailing address) to other companies Attracting a great deal of attention from cyber criminals Customer’s personal information will be stolen My information about payment method will be stolen Spending a lot of time to review products GI2 GI3 GI4 7 7 I have often bought a product that it is not my intention As soon as I enter a shopping website, I have an irresistble urge to go into a shop and buy something I have felt somewhat guilty after buying a product, because it seems unreasonable There were some products that I bought, but I not show them to anyone for fear of GI1 being perceived as irratonal in my buying When I buy a product online, the reviews behavior presented on the website are helpful for my decision making Reviews posted on the website affect my purchase decision Rating about usefulness of reviewers affects my purchase decision Presentation of the reviews affects my purchase decision 142 7 7 Part C Based on your percepton after interaction with e-vendor website, using following statements as your consideraton or your thinking So please give your agreement level for the following statements No Statement PV1 Information obtained from e-vendor website are PV2 I can buy product which I want from shopping website PV3 When using the shopping website, I feel relaxed and enjoy my time PV4 I feel I can save time to buy product on this evendor website 7 7 Part D Based on your percepton after interaction with e-vendor website, using following statements as your consideraton or your thinking So please give your agreement level for the following statements No Statement PR1 I am afraid that online purchase is risky because the product/service may fail to meet my expectaton PR2 I believe that online purchases are risky because I will spend more money to buy other products PR3 I believe that online purchases are risky because I have to spend more time to view substitute and complementary products PR4 I believe that online purchases are risky because my personal informaton and credit information will be stolen 143 7 7 Please choose level of your trust propensity on something/someone Low High Part E Please indicate your agreement level with each of the following statements CA1 The applications on website catches my attention CA2 I had trying to read that information CI1 Continuously pay attention CI2 I want to get more information CD1 I want to buy the product CD2 I will continue to use this webpage for shopping CA3 I will have action to buy CA4 I will introduce this webpage to my friends and family 144 Appendix C QUESTIONNAIRE (Vietnamese Version) Số phiếu: Xin chào anh chị, Nhằm đánh giá tác động tích cực têu cực ứng dụng phân tích liệu lớn vào dịch vụ thương mại điện tử Anh/Chị vui lòng dành chút thời gian quý báu trả lời câu hỏi Xin chân thành cảm ơn! Hướng dẫn thực hiện: Bước Trước trả lời câu hỏi điều tra anh chị ý hỏi câu hỏi liên quan đến yếu tố tích cực như: Informaton Search(thơng tn tìm kiếm), Recommendaton System (hệ thống giới thiệu), Price Dynamics (giá động), Customers Services (dịch vụ khách hàng), giá trị nhận (Perceived Value), xu hướng tn tưởng (Trust propensity), lòng tin (Customer Trust) ; yếu tố têu cực như: Privacy and Data Security (Tính riêng tư bảo mật liệu), Shopping Addicton (Gây nghiện mua sắm), Group influences (Ảnh hưởng nhóm), rủi ro nhận (Perceived Risk), Sự nghi ngờ (Customer distrust) từ đưa phản ứng khách hàng (Customers’ Responses) Bước Thực tương tác với trang web Amazon (www.amazon.com) sau: Lựa chọn sản phẩm (1) Lightweight on-Ear Headphones – White (2) Halston Heritage Women's Strapless Dress with Flared Skirt Thực tương tác việc tìm kiếm sản phẩm trang web Amazon đến tận bước cuối toán tền hàng khơng thực tốn ý đến ứng dụng có liên quan đến thơng tn tìm kiếm, giới thiệu, giá cả, dịch vụ khách hàng Và từ suy nghĩ liệu có tác động tiêu cực không Giả định rằng: bạn có ý định tìm kiếm mua sản phẩm có riêng khoản tài để mua Bước Hồn thành câu hỏi Hãy khoanh tròn câu trả lời bạn cho mục sau dựa thang điểm sau: 145 Rất không đồng ý Không đồng ý Không đồng ý phần Trung lập Đồng ý phần Đồng ý Rất đồng ý Phần Yếu tố tích cực việc ứng dụng phân tích liệu lớn Thơng tin tìm kiếm IS1 Tơi tìm kiếm thơng tn hữu ích trang web IS2 Các thơng tin tìm kiếm cụ thể đầy đủ IS3 Kết cung cấp nhanh phù hợp với nhu cầu IS4 Kết cung cấp thực tế 7 Hệ thống giới thiệu RS1 Trang web giới thiệu sản phẩm thay cho sản phẩm tơi muốn mua RS2 Trang web giới thiệu sản phẩm bổ sung cho sản phẩm muốn mua RS3 Trang web giới thiệu số sản phẩm tơi thích bán tốt trang web RS4 Tôi tn tưởng thơng tin giới thiệu hành động lòng tốt 7 7 Giá động PD1 Cung cấp giá khác cho đối tượng khách hàng cá nhân thời điểm PD2 Cung cấp giá khác thời điểm khác PD3 Cung cấp giá khác sản phẩm thay khác PD4 Cung cấp giá khác cho sản phẩm với điều kiện khác 146 7 7 Dịch vụ khách hàng Trang web cung cấp kênh để hỗ trợ khách CS1 hàng CS2 Tơi mong muốn theo dõi đặt hàng CS3 Trang web mua sắm cung cấp trải nghiệm ảo giúp chọn hàng hóa phù hợp CS4 Tơi tham khảo ý kiến khách hàng mua sản phẩm trước 7 7 Giá trị nhận PV1 Thông tn có từ trang web nhà cung cấp dễ hiểu hữu ích PV2 Tơi mua sản phẩm mà muốn từ trang web mua sắm PV3 Khi sử dụng trang web mua sắm cảm thấy thư giãn tận hưởng sống PV4 Tơi cảm thấy tết kiệm thời gian mua sắm 7 7 Xu hướng tin tưởng Vui lòng lựa cho mực độ xu hướng tn tưởng bạn vào người điều TP Thấp Cao 147 Phần Yếu tố tiêu cực việc ứng dụng phân tích liệu lớn Tính riêng tư bảo mật liệu PS1 Các nhà bán lẻ trực tuyến tết lộ thơng tn cá nhân tơi (ví dụ địa email, địa gửi thư) cho PS2 Thu hút nhiều ý từ giới tội phạm mạng PS3 Thông tin cá nhân khách hàng bị đánh cắp PS4 Thơng tn việc tốn bị đánh cắp 7 Gây nghiện mua sắm SA1 Dành nhiều thời gian để xem xét sản phẩm SA2 Tôi thường mua sản phẩm mà thực không cần cần thiết SA3 7 Ngay sau tơi nhập vào trang web mua sắm, tơi có thúc cưỡng lại để vào SA4 Tôi cảm thấy chưa thực thích đáng sau mua sản phẩm, khơng hợp lý Ảnh hưởng nhóm GI1 Khi tơi mua sản phẩm trực tuyến, ý kiến sản phẩm trình bày trang web hữu ích GI2 Nhận xét đăng trang web ảnh hưởng đến định mua hàng GI3 Xếp hạng khách hàng hữu dụng ảnh hưởng đến định mua hàng GI4 Sự có mặt đánh giá ảnh hưởng đến định mua hàng 148 7 Rủi ro nhận PR1 Tơi e mua hàng trực tuyến mạo hiểm sản phẩm /dịch vụ khơng đáp ứng mong PR2 Tôi tn mua hàng trực tuyến mạo hiểm tơi dành nhiều tền để mua thêm sản phẩm PR3 Tôi tn mua hàng trực tuyến mạo hiểm tơi phải dành nhiều thời gian để xem thay bổ sung sản phẩm PR4 Tôi cho mua hàng trực tuyến mạo hiểm thơng tin cá nhân tơi thông tn tốn bị đánh cắp Phần Phản hồi khách hàng CA1 Những ứng dụng trang web nhận ý CA2 Tôi cố đọc thông tin cung cấp CI1 Tiếp tục ý tới thông tn ứng dụng CI2 Tôi mong muốn nhận thêm thông tn CD1 Tơi có mong muốn mua sản phẩm CD2 Tôi tếp tục sử dụng trang web để mua sắm CA3 Tơi có hành động mua sản phẩm CA4 Tôi giới thiệu trang web cho bạn bè gia đình Điền vào chỗ trống với (X) dấu hiệu câu trả lời bạn nghĩ thích hợp Giới tính: Nam Nữ Khác Có lần tháng trước bạn truy cập trang web thương mại điện tử?  Không  1-2 lần  3-4 lần  nhiều lần Sản phẩm bạn lựa chọn để tương tác với trang web Amazon  (1) Lightweight on-Ear Headphones – White  (2) Halston Heritage Women's Strapless Dress with Flared Skirt 149 Biographical Sketch I Personal Information Name in Full: LE THI MAI Gender: Female Date of Birth: September 14, 1989 Place of Birth: Ha Tinh, Vietnam Areas of Studying and Researching: Accountng, Marketing, Big Data Applications Department: Department of Tropical Agriculture and Internatonal Cooperation Email: lemai.istnu@gmail.com II Education Ph.D Degree in Business and Management Natonal Pingtung University of Science and Technology, Taiwan (20152018) Master of Business Administraton Southern Luzon University, Philippines and Thai Nguyen University, Vietnam (2012-2014) Bachelor of Accounting & Auditing Banking Academy, Vietnam (2007-2011) III Professional Experience and Positon Held 2011-2012: Collaborator at auditng of ACA group 2011-2012: Accountant at Maritme Bank (MSB) 2012-2015: Managing Staff at Academic Affairs and International Cooperation- International School-Thai Nguyen University- Vietnam 2012-2015: Teaching Assistant and Lecturer of Economic and Management Department - Internatonal School University,Vietnam IV Professional Training Programs Banking (2011) - Topica Founder Instituton, Vietnam 150 - Thai Nguyen Epage Website Constructon (2014) – Computer Centre, NPUST, Taiwan 151 V Publications Le, T.M.; Liaw, S.-Y., (2017) Effects of Pros and Cons of Applying Big Data Analytics to Consumers’ Responses in an E-Commerce Context Sustainability, 9, 798 Le, T.M.; Liaw, S.-Y., (2016) How Certificaton Label and Website Language Affect on Purchase Intenton? A Cross-culture Comparison The Internatonal Journal of Business & Management, (6) Liaw, S.-Y & Le, T M., (2017) Comparing Mediaton Effect of Functional and Emotional Value in the Relationship between Pros of Applying Big Data Analytics and Consumers’ Responses International Journal of Marketing Studies, 9(4) Liaw, S.-Y & Le, T M., (2017) Under Interruptve Effects of Rarity and Mental Accountng, Whether the Online Purchase Intention Can Stll Be Enhanced Even with Higher Search Costs and Perceived Risk Internatonal Journal of Business and Management; 12(8) Le, T M; Hediasri,Nur A D & Liaw, S.-Y (2018) A Cross-cultural Comparison in E bank based on Multple Mediaton of Trust Contemporary Management Research – ISSN: 1813-5498 Accepted VI Internatonal Conference Effects of Certficaton Label and Language Choice of Webpage on Purchase Intenton Internatonal Conference on “Business, Economics, Social Science & Humanites-BESSH-2016 Seoul, Korea (02-03/07/2016) A Study of the Multple Mediation of Trust in E-bank From a Crosscultural Comparison between Indonesia and Taiwan NETs 2017 International Conference on Internet Studies Bali Indonesia (14-16/07/2017) 151 ... responses and perceived risk to customers’ responses High trust propensity partcipants reported stronger responses than those with low trust propensity It due to customers’ trust on new applications
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