Future Consequences, Perceived Risk and Security and Continuance Intention to Use Mobile Commerce: Proposal Model

Author(s)

Thanh Long Vu , Thi Chuyen Hoang , Thi Nguyet Minh Nguyen ,

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Volume 10 - January 2021 (01)

Abstract

The effort is put into doing a literature review to clarify the research gap which provides clearer arguments for investigating if and how the perception of risks and security are related to continuance intention to use mobile commerce under the influence of consideration of future consequences.

Keywords

Consideration of future consequences; perceived risk and security; continuance intention;

References

        i.            Aaker, J.L., A.Y. Lee, 2006. Understanding regulatory fit. Journal of Marketing Research, 43(1): 15-19.

      ii.            Adams, J., 2012. Consideration of immediate and future consequences, smoking status, and body mass index. Health Psychology, 31(2): 260-263.

    iii.            Adams, J., D. Nettle, 2009. Time perspective, personality and smoking, body mass, and physical activity: an empirical study. British Journal of Health Psychology, 14(1): 83-105.

     iv.            Agarwal, R., M. Ahuja, P.E. Carter and M. Gans 1998. Early and late adopters of IT innovations: extensions to innovation diffusion theory. Proceedings of the DIGIT Conference.

       v.            Agarwal, R., J. Prasad, 1998. A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2): 204–215.

     vi.            Aiken, L.S., S.G. West and R.R. Reno 1991. Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage Publications.

   vii.            Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2): 179-211.

 viii.            Ajzen, I., 2012. Martin Fishbein’s legacy: The reasoned action approach. The Annals of the American Academy of Political and Social Science, 640(1): 11-27.

     ix.            Ajzen, I., M. Fishbein 1980. Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice-Hall.

       x.            Albarracin, D., B.T. Johnson, M. Fishbein and P.A. Muellerleile, 2001. Theories of reasoned action and planned behavior as models of condom use: a meta-analysis. Psychological Bulletin, 127(1): 142-161.

     xi.            Aldás-Manzano, J., C. Lassala-Navarré, C. Ruiz-Mafé and S. Sanz-Blas, 2009a. The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27(1): 53–75.

   xii.            Aldás-Manzano, J., C. Ruiz-Mafe and S. Sanz-Blas, 2009b. Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109(6): 739-757.

 xiii.            Anderson, J.C., D.W. Gerbing, 1988. Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3): 411–423.

 xiv.            Andersson, U., A. Cuervo-Cazurra and B.B. Nielsen, 2014. From the Editors: Explaining interaction effects within and across levels of analysis. Journal of International Business Studies, 45(9): 1063-1071.

   xv.            Anil, S., L.T. Ting, L.H. Moe and G.P.G. Jonathan, 2003. Overcoming barriers to the successful adoption of mobile commerce in Singapore. International Journal of Mobile Communications, 1(1-2): 194-231.

 xvi.            Arnocky, S., T.L. Milfont and J.R. Nicol, 2013. Time perspective and sustainable behavior. Environment and Behavior, 46(5): 556-582.

xvii.            Ashraf, A.R., M.A. Razzaque and N. Thongpapanl, 2016. The role of customer regulatory orientation and fit in online shopping across cultural contexts. Journal of Business Research, 69(12): 6040-6047.

xviii.            Avnet, T., E.T. Higgins, 2006. How regulatory fit affects value in consumer choices and opinions. Journal of Marketing Research, 43(1): 1-10.

 xix.            Azizli, N., B.E. Atkinson, H.M. Baughman and E.A. Giammarco, 2015. Relationships between general self-efficacy, planning for the future, and life satisfaction. Personality and Individual Differences, 82: 58-60.

   xx.            Babin, B.J., W.R. Darden and M. Griffin, 1994. Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4): 644-656.

 xxi.            Bagozzi, R.P., 2007. The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of The Association for Information Systems, 8(4): 244-254.

xxii.            Bandura, A. 1986. Social foundation of thought and action: A social-cognitive view. New

xxiii.            Chin, W.W., B.L. Marcolin and P.R. Newsted, 2003. A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2): 189-217.

xxiv.            Chiu, C.-M., E.T.G. Wang, Y.-H. Fang and H.-Y. Huang, 2014. Understanding customers' repeat purchase intentions in B2C e-commerce: the roles of utilitarian value, hedonic value and perceived risk. Information Systems Journal, 24(1): 85-114.

xxv.            Choi, Y., D.Q. Mai, 2018. The sustainable role of the e-trust in the B2C e-commerce of Vietnam. Sustainability, 10(2): 1-18.

xxvi.            Choi, Y.K., J.W. Totten, 2012. Self-construal's role in mobile TV acceptance: Extension of TAM across cultures. Journal of Business Research, 65(11): 1525-1533.

xxvii.            Chong, A. Y. -L., F.T. Chan and Ooi, K. -B., 2012. Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems, 53(1): 34-43.

xxviii.            Chong, A.Y.-L., 2015. Understanding mobile commerce continuance intentions: An empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4): 22–30.

xxix.            Citrin, A.V., D.E. Sprott, S.N. Silverman and D.E. Stem, 2000. Adoption of Internet shopping: the role of consumer innovativeness. Industrial Management & Data Systems, 100(7): 294–300.

xxx.            Cohen, J., 1992. A power primer. Psychological Bulletin, 112(1): 155-159.

xxxi.            Costa, P.T., R.R. McCrae, 1992. Four ways five factors are basic. Personality and Individual Differences, 13(6): 653-665.

xxxii.            Cozzarin, B.P., S. Dimitrov, 2015. Mobile commerce and device specific perceived risk. Electronic Commerce Research, 16(3): 335-354.

xxxiii.            Cunningham, L.F., J.H. Gerlach, M.D. Harper and C.E. Young, 2005. Perceived risk and the consumer buying process: internet airline reservations. International Journal of Service Industry Management, 16(4): 357-372.

xxxiv.            D'Arcy, J., A. Hovav and D. Galletta, 2009. User awareness of security countermeasures and its impact on information systems misuse: A deterrence approach. Information Systems Research, 20(1): 79-98.

xxxv.            Dassen, F.C., K. Houben and A. Jansen, 2015. Time orientation and eating behavior: Unhealthy eaters consider immediate consequences, while healthy eaters focus on future health. Appetite, 91: 13-19.

xxxvi.            Dassen, F.C.M., A. Jansen, C. Nederkoorn and K. Houben, 2016. Focus on the future: Episodic future thinking reduces discount rate and snacking. Appetite, 96: 327-332.

xxxvii.            Davis, F.D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3): 319-340.

xxxviii.            DeLone, W.H., E.R. McLean, 1992. Information systems success: The quest for the dependent variable. Information Systems Research, 3(1): 60-95.

xxxix.            Delone, W.H., E.R. McLean, 2003. The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4): 9-30.

     xl.            Devaraj, S., R.F. Easley and J.M. Crant, 2008. Research note-how does personality matter? Relating the five-factor model to technology acceptance and use. Information Systems Research, 19(1): 93-105.

   xli.            Dinh, V.S., H.V. Nguyen and T.N. Nguyen, 2018. Cash or cashless? Strategic Direction, 34(1): 1-4.

 xlii.            Faqih, K.M.S., M.-I.R.M. Jaradat, 2015. Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective. Journal of Retailing and Consumer Services, 22: 37-52.

xliii.            Featherman, M.S., P.A. Pavlou, 2003. Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4): 451-474.

xliv.            Fessel, F., 2010. Increasing level of aspiration by matching construal level and temporal distance. Social Psychological and Personality Science, 2(1): 103-111.

 xlv.            Fishbein, M., I. Ajzen, 1977. Belief, attitude, intention, and behavior: An introduction to theory and research. Philosophy & Rhetoric, 10(2): 132-132.

xlvi.            Fishbein, M., I. Ajzen 2011. Predicting and Changing Behavior: The Reasoned Action Approach. New York, NY: Taylor and Francis.

xlvii.            Flavián, C., M. Guinalíu, 2006. Consumer trust, perceived security and privacy policy. Industrial Management & Data Systems, 106(5): 601-620.

xlviii.            Fornell, C., D.F. Larcker, 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1): 39-50.

xlix.            Geers, A.L., J.A. Wellman, L.D. Seligman, L.A. Wuyek and L.A. Neff, 2010. Dispositional optimism, goals, and engagement in health treatment programs. Journal of Behavioral Medicine, 33(2): 123-134.

        l.            Gerpott, T.J., S. Thomas, 2014. Empirical research on mobile Internet usage: A meta-analysis of the literature. Telecommunications Policy, 38(3): 291-310.

      li.            Gilovich, T., M. Kerr and V.H. Medvec, 1993. Effect of temporal perspective on subjective confidence. Journal of Personality and Social Psychology, 64(4): 552-560.

    lii.            Glover, S., I. Benbasat, 2014. A comprehensive model of perceived risk of e-commerce transactions. International Journal of Electronic Commerce, 15(2): 47-78.

  liii.            Goodhue, D.L., R.L. Thompson, 1995. Task-technology fit and individual performance. MIS Quarterly, 19(2): 213-236.

   liv.            Graso, M., T.M. Probst, 2012. The Effect of Consideration of Future Consequences on Quality and Quantity Aspects of Job Performance1. Journal of Applied Social Psychology, 42(6): 1335-1352.

     lv.            Grewal, D., J. Gotlieb and H. Marmorstein, 1994. The moderating effects of message framing and source credibility on the price-perceived risk relationship. Journal of

   lvi.            Im, H., Y. Ha, 2012. Who are the users of mobile coupons? A profile of US consumers. Journal of Research in Interactive Marketing, 6(3): 215-232.

 lvii.            Jarvis, C.B., S.B. MacKenzie and P.M. Podsakoff, 2003. A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2): 199-218.

lviii.            Joireman, J., D. Balliet, D. Sprott, E. Spangenberg and J. Schultz, 2008. Consideration of future consequences, ego-depletion, and self-control: Support for distinguishing between CFC-Immediate and CFC-Future sub-scales. Personality and Individual Differences, 45(1): 15-21.

   lix.            Joireman, J., J. Kees and D. Sprott, 2010. Concern with immediate consequences magnifies the impact of compulsive buying tendencies on college students' credit card debt. Journal of Consumer Affairs, 44(1): 155-178.

     lx.            Joireman, J., S. King, 2016. Individual differences in the consideration of future and (more) immediate consequences: A review and directions for future research. Social and Personality Psychology Compass, 10(5): 313-326.

   lxi.            Joireman, J., M.J. Shaffer, D. Balliet and A. Strathman, 2012. Promotion orientation explains why future-oriented people exercise and eat healthy: evidence from the two-factor consideration of future consequences-14 scale. Personality and Social Psychology Bulletin, 38(10): 1272-1287.

 lxii.            Joireman, J., D.E. Sprott and E.R. Spangenberg, 2005. Fiscal responsibility and the consideration of future consequences. Personality and Individual Differences, 39(6): 1159-1168.

lxiii.            Joireman, J., A. Strathman and D.P. Balliet, 2006. Considering future consequences: An integrative model. In L. J. Sanna and E. C. Chang eds.2006. Judgments over time: The interplay of thoughts, feelings, and behaviors. New York, NY, US, Oxford University Press. pp. 82-99.

lxiv.            Jung, Y., B. Perez-Mira and S. Wiley-Patton, 2009. Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1): 123-129.

 lxv.            Junglas, I.A., N.A. Johnson and C. Spitzmüller, 2008. Personality traits and concern for privacy: an empirical study in the context of location-based services. European Journal of Information Systems, 17(4): 387-402.

lxvi.            Kalinic, Z., V. Marinkovic, 2015. Determinants of users’ intention to adopt m-commerce: an empirical analysis. Information Systems and e-Business Management, 14(2): 367-387.

lxvii.            Kees, J., S. Burton and A.H. Tangari, 2010. The impact of regulatory focus, temporal orientation, and fit on consumer responses to health-related advertising. Journal of Advertising, 39(1): 19-34.

lxviii.            Khalifa, M., S.K. Cheng and K.N. Shen, 2012. Adoption of mobile commerce: a confidence model. Journal of Computer Information Systems, 53(1): 14-22.

lxix.            Khalifa, M., K.N. Shen, 2008a. Drivers for transactional B2C m-commerce adoption: extended theory of planned behavior. Journal of Computer Information Systems, 48(3): 111-117.

 lxx.            Khalifa, M., K.N. Shen, 2008b. Explaining the adoption of transactional B2C mobile commerce. Journal of Enterprise Information Management, 21(2): 110-124.

lxxi.            Khoi, N.H., H.H. Tuu and S.O. Olsen, 2018. The role of perceived values in explaining Vietnamese consumers’ attitude and intention to adopt mobile commerce. Asia Pacific Journal of Marketing and Logistics, 30(4): 1112-1134.

lxxii.            Kijsanayotin, B., S. Pannarunothai and S.M. Speedie, 2009. Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model. International Journal of Medical Informatics, 78(6): 404-416.

lxxiii.            Kim, C., M. Mirusmonov and I. Lee, 2010a. An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3): 310-322.

lxxiv.            Kim, D.J., D.L. Ferrin and H.R. Rao, 2008. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2): 544-564.

lxxv.            Phuong, D., N. Ngoc and T.T. Dai Trang, 2018. Repurchase intention: The effect of service quality, system quality, information quality, and customer satisfaction as mediating role: A PLS approach of m-commerce ride hailing service in Vietnam. Marketing and Branding Research, 5: 78-91.

lxxvi.            Podsakoff, P.M., S.B. MacKenzie, J.-Y. Lee and N.P. Podsakoff, 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5): 879-903.

lxxvii.            Pozolotina, T., S.O. Olsen, 2019. Present and future temporal profiles and their relationship to health intentions and behaviors: A test on a Norwegian general population sample. Scandinavian Journal of Psychology, 60(1): 36-42.

lxxviii.            Probst, T.M., M. Graso, A.X. Estrada and S. Greer, 2013. Consideration of future safety consequences: a new predictor of employee safety. Accident Analysis & Prevention, 55: 124-134.

lxxix.            Rappange, D.R., W.B. Brouwer and N.J. van Exel, 2009. Back to the Consideration of Future Consequences Scale: time to reconsider? The Journal of Social Psychology, 149(5): 562-584.

lxxx.            Rasmussen, H.N., C. Wrosch, M.F. Scheier and C.S. Carver, 2006. Self-regulation processes and health: the importance of optimism and goal adjustment. Journal of Personality, 74(6): 1721-1747.

lxxxi.            Rigdon, E.E., C.M. Ringle and M. Sarstedt, 2010. Structural modeling of heterogeneous data with partial least squares.2010. Review of Marketing Research. pp. 255-296.

lxxxii.            Rodríguez-Entrena, M., F. Schuberth and C. Gelhard, 2018. Assessing statistical differences between parameters estimates in Partial Least Squares path modeling. Quality & Quantity, 52(1): 57-69.

lxxxiii.            Rogers, E.M. 1995. Diffusion of innovations. New York: Free Press.

lxxxiv.            Salisbury, W.D., R.A. Pearson, A.W. Pearson and D.W. Miller, 2001. Perceived security and World Wide Web purchase intention. Industrial Management & Data Systems, 101(4): 165-177.

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