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研究生:Davaajargal Munkhzul
研究生(外文):Davaajargal Munkhzul
論文名稱:Factors Affecting Consumer’s Intentions of Online Shopping Intention for Clothes in Mongolia
論文名稱(外文):Factors Affecting Consumer’s Intentions of Online Shopping Intention for Clothes in Mongolia
指導教授:陳筱華陳筱華引用關係
指導教授(外文):Sheau-Hwa Chen
口試委員:Kuo-Hsun LiaoYi-Ting Chen
口試委員(外文):Kuo-Hsun LiaoYi-Ting Chen
口試日期:2020-07-30
學位類別:碩士
校院名稱:國立東華大學
系所名稱:企業管理學系
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:77
外文關鍵詞:Technology application model (TAM)Intention behaviorOnline shoppingMongolian customer
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The objectives of this study are to explore factors that affect the online shopping behavior of customers in Mongolia and to help develop online shopping platforms and meet the needs of customers. The main approach of this study is based on a quantitative survey. 400 questionnaires were sent to customers in total with 350 answered and returned. The effective 324 questionnaires among the 350 were input into SPSS software.
This study is conducted by applying the TAM model to analyze 324 customers with their questionnaires. The result shows that two factors in the model have a positive correlation with behavior intention of customers in using online shopping for Clothes in Mongolia and the degree in order as follows: Perceived usefulness (β = -.055), Perceived Ease to use (β =.472), Shipping (β =-.054), Customer service (β =.407), and Web design (β =.005)

Keywords: Technology application model (TAM), Intention behavior, Online shopping, Mongolian customer
Chapter 1: Introduction 1
1.1 Research background 1
1.1.1 Online shopping in Mongolia 3
1.2 Research purpose 8
1.3 Research questions: 9
1.4 Research contribution 9
1.5 Outline 10
Chapter 2 Literature Review 11
2.1 Brief of Consumer Behavior 11
2.2 E-commerce and online shopping 13
2.2.1 E-commerce 13
2.2.2 Online shopping 13
2.3 Theory of Reasoned Action 14
2.4 Technology Acceptance Model (TAM) 15
2.4.1 TAM Application and extension studies 19
2.5 Relationships among variables and hypothesis development 19
2.5.1 Web Design 20
2.5.2 Shipping 21
2.5.3 Customer service 22
2.5.4 Perceived Ease to use 22
2.5.5 Perceived Usefulness 23
Chapter 3 Research methodology 24
3.1 Research framework and hypothesis 24
3.2 Variable definition and source 25
3.3 Research procedure 29
3.4 Questionnaire design 30
3.5 Sampling technique and data collection 30
3.6 Data analysis procedure 30
3.6.1 Descriptive statistic analysis 30
3.6.2 Reliability Test 30
3.6.3 Pearson correlation 31
3.6.4 Linear regression analysis 31
Chapter 4 Results 33
4.1 Descriptive statistics 33
4.1.1 Participant information 33
4.1.2 Study variables 35
4.3 Reliability analysis 38
4.4 Pearson’s Correlation Analysis 40
4.5 Simple linear regression 41
4.6 Multiple regression analysis 45
Chapter 5 Conclusion 46
5.1 Conclusion 46
5.2 Research recommendations 47
5.3 Research contribution 48
5.4 Research limitation 48
References 50
Appendix 1 53
Appendix 2 57
Illustration1 Online shopping websites 61
Illustration2 Online shopping websites 62
Illustration3 Online shopping websites 63
Fishbein & Ajzen. (1975). Belief. Attitude, Intention and Behavior: An Introduction to Theory and Research Reading. Boston: Addison-Wesley.
Liao & Cheung. (2002). Internet-based e-banking and consumer attitudes: an empirical study. Information & Management, 4(39), 283-295.
Abbasi, Bigham & Sarencheh. (2011). Good’s history and trust in electronic commerce. Procedia Computer Science, 3, 827-832.
Adams & Schvaneveldt. (1985). Understanding research methods . London: Longman Publishing Group.
Ajzen. (1991). The theory of planned behavior. Organizational behavior and human decision processe, 2(50), 179-211.
Albarracin, Johnson & Zanna. (2014). The handbook of attitudes. London: Psychology Press.
Baier & Stüber. (2010). Acceptance of recommendations to buy in online retailing. Journal of Retailing and Consumer Services, 3(17), 173-180.
Childers, Carr, Peck & Carson. (2002). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of retailing, 4(77), 511-535.
Cho & Park. (2001). Development of electronic commerce user-consumer satisfaction index (ECUSI) for Internet shopping. Industrial Management & Data Systems, 400-406.
Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Davis. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man-machine studies, 3(38), 475-487.
Davis, Bagozzi & Warshaw. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 8(35), 982-1003.
Delger, O. &. (2020). Current State of E-Commerce in Mongolia. Advances in Intelligent Information Hiding and Multimedia Signal Processing, Smart Innovation, Systems and Technologies 156. 156, p. 296. Springer Nature Singapore Pte Ltd. doi:https://doi.org/10.1007/978-981-13-9714-1_32
eMarketer. (2019). Global Ecommerce 2019. Retrieved from eMarketer: https://www.emarketer.com/content/global-ecommerce-2019
Endo, Yang & Park. (2012). The investigation on dimensions of e-satisfaction for online shoes retailing. Journal of Retailing and Consumer Services, 4(19), 398-405.
Ganbat, Selenge, & Odonchimeg. (2012). An empirical study. mongolian online consumer attitude towards web advertisement MUST-Conference-Doctorate (p. 10). Ulaanbaatar: Admon.
Gefen & Straub. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model . MIS quarterly, 389-400.
Gefen, K. &. (2003). Trust and TAM in online shopping: An integrated mode. MIS quarterly, 1(27), 51-90.
Hsu & Bayarsaikhan. (2012). Factors influencing on online shopping attitude and intention of Mongolian consumers. The Journal of International Management Studies, 2(7), 167-176.
King, Lee, Liang, & Turban. (2008). Electronic commerce: A managerial and social networks perspective. New York: Springer.
Klein, Astrachan & Smyrnios. (2005). The F‐PEC scale of family influence: Construction, validation, and further implication for theory. Entrepreneurship Theory and Practice, 3(29), 321-339.
Kling, McKim, & King. (2003). A bit more to it: scholarly communication forums as socio‐technical interaction networks. Journal of the Association for Information Science and Technology, 1(54), 47-67.
Koufaris. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 2(13), 205-223.
Lee & Lin. (2005). Customer perceptions of e-service quality in online shopping. Internationa. Journal of Retail & Distribution Management, 2(33), 161-176.
McCloskey. (2004). Evaluating electronic commerce acceptance with the technology acceptance model. Journal of Computer Information Systems, 2(44), 49-57.
Meeker, M. (2019). Internet Trends. San Francisco, USA: BOND capital.
Meeker, M. (2019). Internet Trends. San Francisco, USA: BOND Capital. Retrieved from https://www.bondcap.com/report/itr19/#view/title
Ministry of Law of Mongolia. (2010, April). ХӨДӨЛМӨРИЙН ХӨЛСНИЙ ДООД ХЭМЖЭЭНИЙ ТУХАЙ, Regulation of minimum wages.
National Statistic Office of Mongolia. (2020, July). Retrieved from 1212.MN
Nunnally, J. C. (1978). Psychometric Theory. New York: McGraw-Hill Book Co.
Park, Roman, Lee, & Chung. (2009). User acceptance of a digital library system in developing countries: An application of the Technology Acceptance Model. International journal of information management, 3(29), 196-209.
Robertson & Kassarjian. (1991). Handbook of consumer behavior. New Jersey: Prentice Hall.
Rohm & Swaminathan. (2004). A typology of online shoppers based on shopping motivations. Journal of business research, 7(57), 748-757.
Rosen & Howard. (2000). E-retail: Gold rush or fool's gold? (Vol. 3). California: California management review.
Sakarya & Soyer. (2013). Cultural differences in online shopping behavior: Turkey and the United Kingdom. International Journal of Electronic Commerce Studies, 2(4), 213.
Salehi, Abdollahbeigi, Langroudi & Salehi. (2012). The impact of website information convenience on e-commerce success of companies. Procedia-Social and Behavioral Sciences(57), 381-387.
United Nations. (2016). Building e-Resilience in Mongolia Enhancing the Role of Information and Communications Technology for Disaster Risk Management Building e-Resilience in Mongolia Enhancing the Role of Information and Communications Technology for Disaster Risk Management. United Nations.
Venkatesh & Davis. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 3(27), 451-481.
Venkatesh & Davis. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 2(46), 186-204.
Vijayasarathy. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & management, 6(41), 747-762.
Wolfinbarger & Gilly. (2003). eTailQ: dimensionalizing, measuring and predicting etail quality. Journal of retailing, 3(79), 183-198.
WTO. (2020). E-COMMERCE, TRADE AND THE COVID-19 PANDEMIC. Genève,Switzerland: WTO.
Б.Анхтуяа. (2019, Aipril 2). 70 percent of Mongolians use Facebook. Retrieved from News Mongolia: https://news.mn/en/787103/
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