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Articles

Factors affecting the adoption of fashion mobile shopping applications

影响使用时尚类手机购物APP的因素

ORCID Icon, &
Pages 358-376 | Received 01 Jul 2018, Accepted 24 Jul 2019, Published online: 30 Aug 2019

References

  • Aarts, H., Verplanken, B., & Knippenberg, A. V. (1998). Predicting behaviour from actions in the past: Repeated decision making or a matter of habit? Journal of Applied Social Psychology, 28(15), 1355–1374.
  • Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
  • Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211.
  • Ajzen, I., & Fischbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood-Cliffs. NJ: Prentice-Hall.
  • Arbuckle, J. L. (2009). Amos 18 user’s guide. Chicago, IL: Amos Development Corporation.
  • Babin, B., & Attaway, J. (2000). Atmospheric affect as a tool for creating value and gaining share of customer. Journal of Business Research, 49(2), 91–99.
  • Bairakimova, K., & Arkvik, I. (2010). Marketing and facebook. Saarbrü cken, Germany: Lap Lambert Academic Pub.
  • Bakewell, C., Mitchell, V.-W., & Rothwell, M. (2006). UK generation Y male fashion consciousness. Journal of Fashion Marketing and Management: an International Journal, 10(2), 169–180.
  • Chong, A. (2013). A two-staged sem-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Systems with Applications, 40(4), 1240–1247.
  • Compeau, D. R., & Higgins, C. A. (1995). Computer selfefficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Davis, F. D., Bagozzi, R. P, & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science 36(8), 982–1003.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of Applied Social Psychology, 22(14), 1111–1132.
  • Diep, V. C. S., & Sweeney, J. C. (2008). Shopping trip value: Do stores and products matter? Journal of Retailing and Consumer Services, 15(5), 399–409.
  • Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers. Journal of Marketing Research, 28(3), 307–319.
  • emarketer (2016). Retail mcommerce sales in India, 2015-2020 [online]. Retrieved from http://www.emarketer.com/Chart/Retail-Mcommerce-Sales-India-2015-2020-billions-of-retail-ecommerce-sales/201685
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
  • Gefen, D. (2003). TAM or just plain habit: A look at experienced online shoppers. Journal of End User Computing, 15(3), 1–13.
  • Groß, M. (2015a). Mobile shopping: A classification framework and literature review. International Journal of Retail & Distribution Management, 43, 221–241. doi:10.1108/IJRDM-06-2013-0119.
  • Gutman, J., & Mills, M. K. (1982). Fashion life style, self-concept, shopping orientation, and store patronage: An integrative analysis. Journal of Retailing, 58(2), 64–87.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. 7th ed. Upper Saddle River: Prentice Hall.
  • Harsono, L. D., & Suryana, L. A. (2014). Factor affecting the user behavior of social media using UTAUT2 model. In Proceedings of the first Asia- Pacific conference on global business, economics, finance and social sciences. Singapore.
  • Heath, T., Chatterjee, S., & France, K. (1995). Mental accounting and changes in price: The frame dependence of reference dependence. Journal of Consumer Research, 22, 90–97. doi: 10.1086/209437
  • Hew, J., Lee, V., Ooi, K., & Wei, J. (2015). What catalyses mobile apps usage intention: An empirical analysis. Industr Mngmnt& Data Systems, 115(7), 12691–291.
  • Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9(2), 132–140.
  • Huang, C.-Y., & Kao, Y.-S. (2015).UTAUT2 based predictions of factors influencing the technology acceptance of phablets by DNP. Mathematical Problems in Engineering, 2015, Article ID 603747.
  • Hung, M. C., Yang, S. T., & Hsieh, T. C. (2012). An examination of the determinants of mobile shopping continuance. International Journal of Electronic Business Management, 10, 29–37.
  • Islam, M. Z., Low, P. K. C., & Hasan, I. (2013). Intention to use advanced mobile phone services (AMPS). Management Decision, 51(4), 824–838.
  • Jianlin, W., & Qi, D. (2010, May 7-9). Moderating effect of personal innovativeness in the model for E-store Loyalty. International conference on e-business and e-government, ICEE 2010, 2065–2068, Guangzhou, China, .
  • Kermeen, J.-M. (2012). Initiating change to make and break habits. International Coach Academy. Retrieved from https://coachcampus.com/coach-portfolios/research-papers/jean-mariekermeen-initiating-change-to-make-and-break-habits/
  • Khalaf, S. (2015). Shopping, productivity and messaging give mobile another stunning growth year [online]. Flurry Insights Blog. Retrieved from http://flurrymobile.tumblr.com/post/115194992530/shoppingproductivity-and-messaging-givemobile
  • Kim, C., Li, W., & Kim, D. J. (2015). An empirical analysis of factors influencing M-Shopping use. International Journal of Human-computer Interaction, 31(12), 974–994.
  • Kim, S. C., Yoon, D., & Han, E. K. (2016). Antecedents of mobile app usage among smartphone users. Journal of Marketing Communications, 22, 653–670. doi: 10.1080/13527266.2014.951065.
  • Lai, J.-Y., Debbarma, S., & Ulhas, K. R. (2012). An empirical study of consumer switching behaviour towards mobile shopping: A push-pull-mooring model. International Journal of Mobile Communications, 10(4), 386–404.
  • Langlois, J. H., Kalakanis, L., Rubenstein, A. J., Larson, A., Hallam, M., & Smoot, M. (2000). Maxims or myths of beauty? A meta-analytic and theoretical review. Psychological Bulletin, 126, 390–423.
  • Leung, L., & Wei, R. (1998). The gratifications of pager use: Sociability, information seeking, entertainment, utility, and fashion and status. Telematics and Informatics, 15(4), 253–264.
  • Liao, C., Palvia, P., & Lin, H. (2006). The roles of habit and web site quality in E-Commerce. International Journal of Information Management, 26, 469–483.
  • Limayem, M., & Hirt, S. G. (2003). Force of habit and information systems usage: Theory and initial validation. Journal of the AIS, 4(1), 65–97.
  • Limayem, M., & Hirt, S. G. & Cheung, C. M. (2007). How habit limits the predictive power of intention.The case of information systems continuance, 705–737.
  • Lu, H-P., & Yu-Jen Su, P. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19, 442–458. doi: 10.1108/10662240910981399
  • Lu, J., Yao, J. E., & Yu, C-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268. do:10.1016/j.jsis.2005.07.003
  • Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25, 29–39.
  • Magrath, V., & McCormick, H. (2013). Marketing design elements of mobile fashion retail apps. Journal of Fashion Marketing and Management: an International Journal, 17(1), 115–134.
  • Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The Concept and its Measurement. Journal of Consumer Research, 4(2), 229–242.
  • Miladinovic, J., & Hong, X. (2016). A Study on factors affecting the behavioral intention to use mobile shopping fashion apps in Sweden (Dissertation). Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-30245
  • Monsuwé, T. P., Dellaert, B. G., & De Ruyter, K. (2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management, 15(1), 102–121.
  • Moore, G., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.
  • Morgan Stanley (2017). India’s digital leap: The multi-trillion-dollar opportunity. Morgan Stanley website. Retrieved from: https://www.morganstanley.com/ideas/digital-india
  • Morris, L. (2016). Which mobile fashion retail app has the best UX? Retrieved from https://www.clickz.com/2015/11/06/whichmobile-fashion-retail-app-has-the-best-ux
  • Mort, G., & Drennan, J. (2002). Mobile digital technology: Emerging issue for marketing. Journal of Database Marketing & Customer Strategy Management, 10(1).
  • Nielsen Informate Mobile Insights’ Mobile Shoppers Turn App-Happy. (2015). Retrieved from http://sci-hub.hk/http://rai.net.in/images/Report_Repository/pdf/nielsen-featured-insights.pdf
  • Olstrom, J. M. (1971). Satisfaction with clothing and personal appearance related tos self-esteem and participation in actitities among full-time homemakers. Corvallis,OR: Oregon State University.
  • Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 54–74.
  • Pelet, J.-É., & Papadopoulou, P. (2015). Social media and m-commerce. International Journal of Internet Marketing and Advertising, 9(Issue), 1.
  • PWC (PricewaterhouseCoopers). (2015). Total retail 2015: Retailers and the age of disruption [Online], Retrieved from https://www.pwc.com/sg/en/publications/assets/total-retail-2015.pdf
  • Rogers, E. M. (2010). Diffusion of Innovations (4th ed.). New York: Simon and Schuster.
  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.
  • Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325–343.
  • Statista. (2016). Number of digital buyers in India from 2014 to 2020 (in millions). Retrieved from https://www.statista.com/statistics/251631/number-of-digital-buyers-in-india/
  • Statista. (2019). Mobile phone internet user penetration in India from 2015 to 2023. Retrieved from https://www.statista.com/statistics/309019/india-mobile-phone-internet-user-penetration/
  • Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87(2), 245–251.
  • Tak, P., & Panwar, S. (2017). Using UTAUT 2 model to predict mobile app based shopping: Evidences from india". Journal of Indian Business Research, 9(3), 248–264.
  • Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(4).
  • Teller, C., Thomas, R., & Peter, S. (2008). Hedonic and utilitarian shopper types in evolved and created retail agglomerations. International review of retail. Distribution and Consumer Research, 18(3), 283–309.
  • Thompson, R. L., & Higgins, C. A. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125.
  • Tsu Wei, T., Marthandan, G., Yee-Loong Chong, A., Ooi, K., & Arumugam, S. (2009). What drives malaysian adoption? An empirical analysis. Industrmngmnt& Data Systems, 109(3), 370–388.
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186–204.
  • Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
  • Wang, Y., Lin, H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16, 157–179.
  • Yang, H. (2013). Bon appétit for apps: Young American consumers' acceptance of mobile applications. Journal of Computer Information Systems, 53(3), 85–96.
  • Yang, K. (2010). Determinants of US consumer mobile shopping services adoption: Implications for designing mobile shopping services. Journal of Consumer Marketing, 27(3), 262–270.
  • Yang, Y-H., & Kim, J-K. (2012). A Literature Review of Compassion Fatigue in Nursing. Korean Journal of Adult Nursing, 24. doi:10.7475/kjan.2012.24.1.38.
  • Zhou, L., & Wong, A. 2004. Consumer impulse buying and in-store stimuli in Chinese supermarkets. Journal of International Consumer Marketing, 16, 37–53, doi: 10.1300/J046v16n02_03

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