Motivation impulses customers' online shopping intention via cashback and rewards mobile applications
Article Sidebar
Main Article Content
صندلی اداریAbstract
The field of cashback and rewards applications is still a relatively new platform in the e-commerce platform that has not had many research papers pay attention to. The purpose of this study is to identify and analyze the factors that contribute to customers' impulsive online purchasing intentions when using cashback and rewards applications (apps) in Ho Chi Minh City. Using the theory of behavioral intention (TRA, TPB, TAM, UTAUT1,2) of Ajzen and Fishbein (1975, 1980), Ajzen (1985, 1991), Davis (1989) and Venkatesh, Thong and Xu (2012), and the Motivation Model - MM of Davis, Bagozzi and Warshaw (1992) as the foundation for proposing a research model, this research was conducted. Thus, six factors influence consumers' online purchasing intentions via cashback and rewards apps: Perceived Usefulness, Perceived Convenience Social Influence, Price Value, Trust, and Perceived Enjoyment. These factors are considered under two aspects: extrinsic and intrinsic motivation. Official quantitative research conducted in Ho Chi Minh City surveyed 220 consumers. According to Cronbach's Alpha, EFA factor analysis, and regression correlation, the six factors that suggest studying consumers' online shopping intentions via cashback and rewards apps in Ho Chi Minh City in the same direction are Price Value, Social Influence, Trust, Perceived Usefulness, Perceived Convenience, and Perceived Enjoyment, in order of strength. In general, when factors are classified as intrinsic or extrinsic motivations, research indicates that extrinsic motivations have a greater influence on users' intention for using. Additionally, the research reveals no differences in online shopping intention via cashback and rewards apps based on income or age, but did discover differences based on gender. Since then, proposing some governance implications for Vietnamese online shopping businesses in order to provide solutions for future sales growth. As a result, the company may consider segmenting its users according to gender in order to prioritize the creation of extrinsic influences in addition to intrinsic motivational stimuli. It will effectively promote customers' consumption behavior.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
1. Proposal of Policy for Free Access Periodics
Authors whom publish in this magazine should agree to the following terms:
a. Authors should keep the copyrights and grant to the magazine the right of the first publication, with the work simultaneously permitted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 that allows the sharing of the work with recognition of the authorship of the work and initial publication in this magazine.
b. Authors should have authorization for assuming additional contracts separately, for non-exclusive distribution of the version of the work published in this magazine (e.g.: to publish in an institutional repository or as book chapter), with recognition of authorship and initial publication in this magazine.
c. Authors should have permission and should be stimulated to publish and to distribute its work online (e.g.: in institutional repositories or its personal page) to any point before or during the publishing process, since this can generate productive alterations, as well as increasing the impact and the citation of the published work (See The Effect of Free Access).
Proposal of Policy for Periodic that offer Postponed Free Access
Authors whom publish in this magazine should agree to the following terms:
a. Authors should keep the copyrights and grant to the magazine the right of the first publication, with the work simultaneously permitted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 [SPECIFY TIME HERE] after the publication, allowing the sharing of the work with recognition of the authorship of the work and initial publication in this magazine.
b. Authors should have authorization for assuming additional contracts separately, for non-exclusive distribution of the version of the work published in this magazine (e.g.: to publish in institutional repository or as book chapter), with recognition of authorship and initial publication in this magazine.
c. Authors should have permission and should be stimulated to publish and to distribute its work online (e.g.: in institutional repositories or its personal page) to any point before or during the publishing process, since this can generate productive alterations, as well as increasing the impact and the citation of the published work (See The Effect of Free Access).
d. They allow some kind of open dissemination. Authors can disseminate their articles in open access, but with specific conditions imposed by the editor that are related to:
Version of the article that can be deposited in the repository:
Pre-print: before being reviewed by pairs.
Post-print: once reviewed by pairs, which can be:
The version of the author that has been accepted for publication.
The editor's version, that is, the article published in the magazine.
At which point the article can be made accessible in an open manner: before it is published in the magazine, immediately afterwards or if a period of seizure is required, which can range from six months to several years.
Where to leave open: on the author's personal web page, only departmental websites, the repository of the institution, the file of the research funding agency, among others.
References
Ajzen, I., & Fishbein, M. (1975). Belief, Attitude, Intention and Behavior: An Introduction to theory and research. Addition-Wesley, Reading, MA.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior: Attitudes, intentions, and perceived behavioral control. Englewood Cliffs, NJ: Prentice Hall.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Heidelberg: Springer.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211. DOI: 10.1016/0749-5978(91)90020-T.
Akbari, M., Ardekani, Z. F., Pino, G., & Maleksaeidi, H. (2019). An extended model of Theory of Planned Behavior to investigate highly-educated iranian consumers’ intentions towards consuming genetically modified foods. Journal of Cleaner Production. DOI:10.1016/j.jclepro.2019.04.246
Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society. doi:10.1016/j.techsoc.2018.06.007.
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110.
Bhatla, S. (2020). Why You Should Invest in Vietnam’s E-commerce Industry. Available: https://www.vietnam-briefing.com/news/why-you-should-invest-vietnams-e-commerce-industry.html/. Access: 24th May, 2021.
Cao, X., Yu, L., Liu, Z., Gong, M., & Adeel, L. (2018). Understanding mobile payment users’ continuance intention: a trust transfer perspective, Internet Research, 28(2), 456-476. DOI: 10.1108/IntR-11-2016-0359.
Chen, H. (2012). The Influence of Perceived Value and Trust on Online Buying Intention’. Journal of Computers, 7(7), 618 - 635
Cheng, Y-C., & Yeh, H-T. (2009). From concepts of motivation to its application in instructional design: Reconsidering motivation from an instructional design perspective. British Journal of Educational Technology, 40(4), 597–605. DOI:10.1111/j.1467-8535.2008.00857.x
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77, 511–535.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. DOI:10.2307/24900
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. DOI:10.1287/mnsc.35.8.982
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111-1132. DOI: 10.1111/j.1559-1816.1992.tb00945.x
Delafrooz, N., Paim, L., & Khatibi, A. (2011). Understanding consumer's internet purchase intention in Malaysia. African Journal of Business Management, 5(3), 2837-2846.
Dellote (2019). Retail in Vietnam 2019 - Navigating the digital retail landscape. Available: https://www2.deloitte.com/content/dam/Deloitte/vn/Documents/consumer-business/vn-cb-vietnam-consumer-retail-2019.pdf. Access: 6th April, 2021.
Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51-90.
Grace, K., Salvatier, J., Dafoe, A., Zhang, B., & Evans, O. (2018). Viewpoint: When Will AI Exceed Human Performance? Evidence from AI Experts. Journal of Artificial Intelligence Research, 62, 729-754.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.
Hasslinger, A., Hodzic, S., & Obazo, C. (2007). Consumer behaviour in online shopping. Kristianstaad University Department of Business Studies.
Mcknight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: a trust building model. The Journal of Strategic Information Systems, 11(3-4), 297–323. DOI:10.1016/s0963-8687(02)00020-3
Hofacker, C. F. (2001). Internet Marketing. 3rd Edition, John Wiley and Sons, Inc., New York.
Hoffman L., Gorbea, C., & Rechsteiner, M. (1999). Identification, molecular cloning, and characterization of subunit 11 of the human 26S proteasome. FEBS Letters, 449(1), 88-92
Hossein, R. D., Seyede, N. A., & Faeze, K. Z. (2011). Considering factors that affect users' online purchase intentions with using structural equation modeling. Linterdisciplinary Journal of contemporaty reseach in business, 3(8), 463–471. Available: https://journal-archieves13.webs.com/463-471.pdf. Access: 16th April, 2021.
Iyer, P., Davari, A., & Mukherjee, A. (2018). Investigating the effectiveness of retailers’ mobile applications in determining customer satisfaction and repatronage intentions? A congruency perspective. Journal of Retailing and Consumer Services, 44), 235–243.
Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (1999). Consumer Trust in an Internet Store. Information Technology and Management, 1(12), 45-71.
Jarvenpaa, S. L., & Todd, P. A. (1997). Consumer Reactions to Electronic Shopping on the World Wide Web. International Journal of Electronic Commerce, 1, 59-88.
Jiang, P., & Rosenbloom, B. (2005). Customer intention to return online: price perception, attribute‐level performance, and satisfaction unfolding over time. European Journal of Marketing, 39(1/2), 150–174. DOI:10.1108/03090560510572061
Joines, J., Scherer, C., & Scheufele, D. (2003). Exploring Motivations for Consumer Web Use and Their Implications for E-Commerce. Journal of Consumer Marketing, 20(2), 90-109.
Kalinic, Z., Marinkovic, V., Molinillo, S., & Liébana-Cabanillas, F. (2019). A multi-analytical approach to peer-to-peer mobile payment acceptance prediction. Journal of Retailing and Consumer Services, 49, 143–153. DOI:10.1016/j.jretconser.2019.03.016
Kawet, O., Pangemanan, S. S., & Tumiwa, J. (2017). Analyzing the effect of perceived value and trust on purchase intention (Case Study of Zalora). Jurnal EMBA, 5(2 ), 773-783
Keller, K., & Kotler, P. (2006). Marketing Management (12th Edition). Retrieved from Researchgate: https://www.researchgate.net/publication/225084026_Marketing_Management
Khalilzadeh, J., Ozturk, A. B., & Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460-474.
Kim, H. W., Kankanhalli, A., & Lee, H. L. (2016). Investigating decision factors in mobile application purchase: A mixed-methods approach. Information and Management, 53(6), 727-739.
Kim, H. W., & Gupta, S. (2009). A comparison of purchase decision calculus between potential and repeat customers of an online store. Decision Support Systems, 47, n.4), 477–487.
Kwateng, K. O., Atiemo, K. A. O., & Appiah, C. (2018). Acceptance and use of mobile banking: an application of UTAUT2. Journal of Enterprise Information Management, 32(11). DOI:10.1108/jeim-03-2018-0055
Laroche, M., Kim, C., & Zhou, L. (1996). Brand familiarity and confidence as determinants of purchase intention: An empirical test in a multiple brand context. Journal Of Business Research, 37(2), 115-120. Available: https://econpapers.repec.org/article/eeejbrese/v_3a37_3ay_3a1996_3ai_3a2_3ap_3a115-120.htm. Access: 25th May, 2021.
Liu, C., Marchewka, J. T., Lu, J., & Yu, C. S. (2004). Beyond concern: A privacy–trust–behavioral intention model of electronic commerce. Information & Management, 42(1), 127-142. DOI: 10.1016/j.im.2004.01.003
Lin, J. C-C., & Lu, H. (2000). Towards an understanding of the behavioural intention to use a web site. International Journal of Information Management, 20(3), 197–208. DOI:10.1016/s0268-4012(00)00005-0
Mayer, R. C., Davis, J. H., & David, F. S. (1995). An Integrative Model of Organizational Trust. The Academy of Management Review, 20(3), 709-734.
Moon, J. -W., & Kim, Y. -G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217–230. DOI:10.1016/s0378-7206(00)00061-6.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.
Oliveira, A. S., Schlink, B. S., Hairston, W. D., König, P., & Ferris, P. D. (2016). Induction and separation of motion artifacts in EEG data using a mobile phantom head device. Journal of Neural Engineering, 13(3), 1-14
Park, E., Baek, S., Ohm, J., & Chang, H. J. (2014). Determinants of player acceptance of mobile social network games: An application of extended technology acceptance model. Telematics and Informatics, 31(1), 3–15. DOI:10.1016/j.tele.2013.07.001
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7, 101-134.
Pavlou, P., & Chai, L. (2002). What Drives Electronic Commerce across Cultures? Across-Cultural Empirical Investigation of the Theory of Planned Behavior, 3(4), 47–59.
Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS quarterly, 30(1), 115-143.
Sanayei, A., & Bahmani, E. (2012). Integrating TAM and TPB with Perceived Risk to Measure Customers’ Acceptance of Internet Banking. International Journal of Information Science and Management, Special Issue (ECDC 2012)), 25-37.
Salisbury, W. D., Pearson, R. A., Pearson, A. W., & Miller, D. W. (2001). Perceived security and World Wide Web purchase intention. Industrial Management & Data Systems, 101(4), 165-177. DOI:10.1108/02635570110390071
Segal, T. (2020). CashBack. Available: https://www.investopedia.com/terms/c/cash-back.asp. Access: 6th May, 2021.
Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling consumers' adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing, 32(8), 860–873.
Taylor, S., & Todd, P.A. (1995). Understanding Information Technology Usage: A Test of Competing Models. v. 6(2), 144-176.
To, P.-L., Liao, C., & Lin, T.-H. (2007). Shopping motivations on Internet: A study based on utilitarian and hedonic value. Technovation, 27(12), 774–787. doi:10.1016/j.technovation.2007.01.001
Vana, P., Lambrecht, A., & Bertini, M. (2018). Cashback Is Cash Forward: Delaying a Discount to Entice Future Spending. Journal of Marketing Research, 55(6), 852–868. DOI:10.1177/0022243718811853
Vallerand, R. J. (1997). Toward A Hierarchical Model of Intrinsic and Extrinsic Motivation. Advances in Experimental Social Psychology, 29, 271–360. DOI:10.1016/s0065-2601(08)60019-2.
Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. Organizational Behavior and Human Decision Processes, 83(1), 33–60. DOI:10.1006/obhd.2000.2896
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425 - 478.
Venkatesh, V., Thong, J. Y. L., & 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. Available: https://www.jstor.org/stable/41410412. Access: 15th May, 2021. DOI:10.2307/41410412
Wolfinbarger, M., & Gilly, M. (2001). Shopping Online for Freedom, Control, and Fun. California Management Review, 43(2), 34-56.
Yeo, C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD). services. Journal of Retailing and Consumer Services, 35), 150–162. DOI:10.1016/j.jretconser.2016.12.013
Zeithaml, A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52(3), 2–22. DOI:10.1177/002224298805200302
Zhou, L., Dai, L., & Zhang, D. (2007). Online shopping acceptance model - A critical survey of consumer factors in online shopping. Journal of Electronic Commerce Research, 8(1), 41–62. Available: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.93.4939&rep=rep1&type=pdf. Access: 15th May, 2021.