The Continuance Usage Of Physical Activity Tracking Technology With Social Media: Connecting The Dots For Singapore

  • Authors

    • Nittee Wanichavorapong
    • Ab Razak Che Hussin
    • Ahmad Fadhil Yusof
    • Halina Mohamed Dahlan
    2018-12-03
    https://doi.org/10.14419/ijet.v7i4.38.27900
  • ECM(expectation confirmation Model), IS Continuance, fitness tracker, social media, wearability, Quantified Self, personal informatics
  • Physical activity (PA) tracking technology can assist individual in monitoring physical activities in eHealth while gaining popularity and enjoying a flourishing market. Social media (SM) offers huge advantages to PA tracking technology (PATT). Yet, the continuance usage is the cornerstone of IT goods and services; otherwise failed. The limited knowledge of IS continuance in PATT-SM is the motive. Our purpose is to analyze the factors that drive users to continue using PATT-SM. This study demonstrated the use of expectation confirmation model (ECM) and value factors to predict CI in a variety of perspectives including social, economics, behavior, and cognitive. Through data collection, a survey method was conducted in Singapore (n=201). The proposed model has been assessed for reliability and validity. The PLS-SEM method was used to investigate the cause-effect relationship between the constructs in a multi-linear regression style. The results exhibited that the all constructs of ECM constructs had a statistically significant impact on continuance intention (CI); in addition, usefulness has an impact on CI. However, perceived influence had rather a negative impact on CI. Social value received no significant association with CI. Then, network size and complementarity had also positive and statistical significance on perceived influence whereas complementarity yielded less impact.

     

  • References

    1. [1] Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370.

      [2] Bhattacherjee, A., & Barfar, A. (2011). Information technology continuance research: current state and future directions. Asia Pacific Journal of Information Systems, 21(2), 1-18.

      [3] Chiu, C. M., Cheng, H. L., Huang, H. Y., & Chen, C. F. (2013). Exploring individuals’ subjective well-being and loyalty towards social network sites from The Facebookcase. International Journal of Information Management, 33(3), 539-552.

      [4] Chung, A. E., Skinner, A. C., Hasty, S. E., & Perrin, E. M. (2017). Tweeting to health: a novel mHealth intervention using Fitbits and Twitter to foster healthy lifestyles. Clinical pediatrics, 56(1), 26-32.

      [5] Cooper, R. B., & Zmud, R. W. (1990). Information technology implementation research: a technological diffusion approach. Management science, 36(2), 123-139.

      [6] 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.An example appendix

      [7] Gouveia, R., Karapanos, E., & Hassenzahl, M. (2015, September). How do we engage with activity trackers?: a longitudinal study of Habito. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1305-1316). ACM.

      [8] Hallowell, R. (1996). The relationships of customer satisfaction, customer loyalty, and profitability: an empirical study. International journal of service industry management, 7(4), 27-42.

      [9] Karapanos, E. (2015). Sustaining user engagement with behavior-change tools. interactions, 22(4), 48-52.

      [10] Kim, B., & Han, I. (2011). The role of utilitarian and hedonic values and their antecedents in a mobile data service environment. Expert Systems with Applications, 38(3), 2311-2318.

      [11] Kim, H. W., Chan, H. C., & Chan, Y. P. (2007). A balanced thinking–feelings model of information systems continuance. International Journal of Human-Computer Studies, 65(6), 511-525.

      [12] Lazar, A., Koehler, C., Tanenbaum, J., & Nguyen, D. H. (2015, September). Why we use and abandon smart devices. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 635-646). ACM.

      [13] Lupton, D. (2014). Self-tracking modes: Reflexive self-monitoring and data practices.

      [14] Lyytinen, K., & Hirschheim, R. (1988). Information systems as rational discourse: An application of Habermas's theory of communicative action. Scandinavian Journal of Management, 4(1), 19-30.

      [15] Middelweerd, A., van der Laan, D. M., van Stralen, M. M., Mollee, J. S., Stuij, M., te Velde, S. J., & Brug, J. (2015). What features do Dutch university students prefer in a smartphone application for promotion of physical activity? A qualitative approach. International Journal of Behavioral Nutrition and Physical Activity, 12(1), 31.

      [16] Perloff, R. M. (2002). The third-person effect. Tudor-Locke, C., Hatano, Y., Pangrazi, R. P., & Kang, M. (2008). Revisiting" how many steps are enough?". Medicine & Science in Sports & Exercise, 40(7), S537-S543.

      [17] Rintamäki, T., Kanto, A., Kuusela, H., & Spence, M. T. (2006). Decomposing the value of department store shopping into utilitarian, hedonic and social dimensions: Evidence from Finland. International Journal of Retail & Distribution Management, 34(1), 6-24.

      [18] Saga, V. L., & Zmud, R. W. (1993, October). The nature and determinants of IT acceptance, routinization, and infusion. In Proceedings of the IFIP TC8 working conference on diffusion, transfer and implementation of information technology (pp. 67-86). Elsevier Science Inc..

      [19] Shapiro, C., & Varian, H. R. (1998). Information rules: a strategic guide to the network economy. Harvard Business Press.

      [20] Sullivan, A. N., & Lachman, M. E. (2017). Behavior change with fitness technology in sedentary adults: A review of the evidence for increasing physical activity. Frontiers in public health, 4, 289.

      [21] Zhang, C. B., Li, Y. N., Wu, B., & Li, D. J. (2017). How WeChat can retain users: Roles of network externalities, social interaction ties, and perceived values in building continuance intention. computers in Human Behavior, 69, 284 29

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    Wanichavorapong, N., Razak Che Hussin, A., Fadhil Yusof, A., & Mohamed Dahlan, H. (2018). The Continuance Usage Of Physical Activity Tracking Technology With Social Media: Connecting The Dots For Singapore. International Journal of Engineering & Technology, 7(4.38), 1457-1460. https://doi.org/10.14419/ijet.v7i4.38.27900