Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
권호 표지
DOI QR코드

DOI QR Code

Sustaining the Use of Quantified-Self Technology: A Theoretical Extension and Empirical Test

  • Ayoung Suh (School of Creative Media and Department of Information Systems, City University of Hong Kong)
  • Received : 2018.02.09
  • Accepted : 2018.04.13
  • Published : 2018.06.29
Download PDF
⟨ Previous Next ⟩

Abstract

Quantified-self technologies (QSTs) provide functions for users to collect, track, and monitor personal data for self-reflection and acquisition of self-knowledge. Although QSTs require prolonged use to reap the attendant benefits, many users stop using their devices or tracking within weeks or months. To address this issue, this study seeks to determine ways to sustain the use of QSTs. Combining motivational affordance theory with technology continuance theory, this study develops a theoretical model that accounts for an individual's continued intention to use a QST. Within the proposed model, unique QST affordances were identified as antecedents of individual motivation in relation to technology continuance, and their different roles in stimulating hedonic, utilitarian, and eudaimonic motivations were examined. The model was tested using data collected from 180 QST users. Results demonstrate that although utilitarian and eudaimonic motivations are complementary forces in determining continuance intention, hedonic motivation loses its predictive power in favor of eudaimonic motivation. Tracking, visualizing, and sharing affordances play different roles in elevating user motivations. The sharing affordance does not influence utilitarian and eudaimonic motivations, but it positively influences hedonic motivation. This research contributes to the literature on technology continuance by shifting scholarly attention from hedonic-utilitarian duality to eudaimonic motivation, characterized by meaning, self-growth, and pursuit of excellence.

Keywords

Acknowledgement

This research was supported by Grant No. CityU 6391221 from the University Grants Committee (UGC) of the Hong Kong SAR.

References

  1. Anderson, J. C., and Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.  https://doi.org/10.1037/0033-2909.103.3.411
  2. Baek, H., Kim, J. H., and Kim, Y. J. (2013). An Analysis for Deriving New Convergent Service of Mobile Learning: The Case of Social Network Analysis and Association Rule. Information Systems Review, 15(3), 1-37. 
  3. Bakardjieva, M. (2005). Internet society: The Internet in everyday life. Sage. 
  4. Barclay, D., Higgins, C., and Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2, 285-309. 
  5. Bollen, K., and Lennox, R. (1991). Conventional wisdom on measurement: A structural equation perspective. Psychological Bulletin, 110(2), 305-314.  https://doi.org/10.1037/0033-2909.110.2.305
  6. Chamberlain, A., Poole, E., Munson, S., Danis, C., and Churchill, E. (2015). Moving beyond e-health and the quantified self: the role of CSCW in collaboration, community and practice for technologically-supported proactive health and wellbeing. Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing. ACM, 273-276. 
  7. Chin, W. W., Marcolin, B. L., and Newsted, P. R. (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.  https://doi.org/10.1287/isre.14.2.189.16018
  8. Choe ,E. K., Lee, N. B., Lee, B., Pratt, W., and Kientz, J. A. (2014). Understanding quantified-selfers' practices in collecting and exploring personal data. Proceedings of the 32nd annual ACM conference on Human factors in computing systems. ACM, 1143-1152. 
  9. Chun, H., Lee, H., and Kim, D. (2012). The integrated model of smartphone adoption: Hedonic and utilitarian value perceptions of smartphones among Korean college students. Cyberpsychology, Behavior, and Social Networking, 15(9), 473-479.  https://doi.org/10.1089/cyber.2012.0140
  10. Consolvo, S., Klasnja, P., McDonald, D. W., and Landay, J. A. (2009). Goal-setting considerations for persuasive technologies that encourage physical activity. Proceedings of the 4th international Conference on Persuasive Technology. ACM. 
  11. Coorevits, L., and Coenen, T. (2016). The rise and fall of wearable fitness trackers. Annual Meeting of the Academy of Management. Anaheim, California. 
  12. Cyr, D., Head, M., and Ivanov, A. (2006). Design aesthetics leading to m-loyalty in mobile commerce. Information & Management, 43(8), 950-963.  https://doi.org/10.1016/j.im.2006.08.009
  13. Deterding, S. (2014). Eudaimonic design, or: Six invitations to rethink gamification, Niklas Schrape. Luneburg: Meson press 2014. Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2466374 
  14. Epstein, D. A., Avrahami, D., and Biehl, J. T. (2016a). Taking 5: Work-breaks, productivity, and opportunities for personal informatics for knowledge workers. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 673-684. 
  15. Epstein, D. A., Borning, A., and Fogarty, J. (2013). Fine-grained sharing of sensed physical activity: a value sensitive approach. Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. ACM, 489-498. 
  16. Epstein, D. A., Jacobson, B. H., Bales, E., McDonald, D. W., and Munson, S. A. (2015). From nobody cares to way to go!: A Design Framework for Social Sharing in Personal Informatics. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing. Canada: ACM, 1622-1636. 
  17. Epstein, D. A., Kang, J. H., Pina, L. R., Fogarty, J., and Munson, S. A. (2016b). Reconsidering the device in the drawer: lapses as a design opportunity in personal informatics. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 829-840. 
  18. Fornell, C., and Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440-452.  https://doi.org/10.1177/002224378201900406
  19. Fritz, T., Huang, E. M., Murphy, G. C., and Zimmermann, T. (2014). Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 487-496. 
  20. Gottschalg, O., and Zollo, M. (2007). Interest alignment and competitive advantage. Academy of Management Review, 32(2), 418-437.  https://doi.org/10.5465/amr.2007.24351356
  21. Grgecic, D., Holten, R., and Rosenkranz, C. (2015). The Impact of Functional Affordances and Symbolic Expressions on the Formation of Beliefs. Journal of the Association for Information Systems, 16(7), 580-607.  https://doi.org/10.17705/1jais.00402
  22. Gu, J.-C., Fan, L., Suh, Y. H., and Lee, S.-C. (2010). Comparing utilitarian and hedonic usefulness to user intention in multipurpose information systems. Cyberpsychology, Behavior, and Social Networking, 13(3), 287-297.  https://doi.org/10.1089/cyber.2009.0167
  23. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., and Tatham, R. L. (2006). Multivariate data analysis. Pearson Prentice Hall Upper Saddle River, NJ. 
  24. Harter, J. K., Schmidt, F. L., and Hayes, T. L. (2002). Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: a meta-analysis. Journal of Applied Psychology, 87(2), 268-279.  https://doi.org/10.1037/0021-9010.87.2.268
  25. Jia, Y., Xu, B., Karanam, Y., and Voida, S. (2016). Personality-targeted Gamification: A Survey Study on Personality Traits and Motivational Affordances. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 2001-2013. 
  26. Jun, J. G., Lee, T. M., and Park, C. (2015). Utilization of Mobile Information and Perceptions of Society : A Comparison of Korea, China, U.S.A and Japan. Information Systems Review, 17(3), 19-38.  https://doi.org/10.14329/isr.2015.17.3.019
  27. Jung, J., Schneider, C., and Valacich, J. (2010). Enhancing the motivational affordance of information systems: The effects of real-time performance feedback and goal setting in group collaboration environments. Management Science, 56(4), 724-742.  https://doi.org/10.1287/mnsc.1090.1129
  28. Kaptelinin, V., and Nardi ,B. (2012). Affordances in HCI: toward a mediated action perspective. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 967-976. 
  29. Ke, W., Tan, C.-H., Sia, C.-L., and Wei, K.-K. (2012). Inducing intrinsic motivation to explore the enterprise system: The supremacy of organizational levers. Journal of Management Information Systems, 29(3), 257-290.  https://doi.org/10.2753/MIS0742-1222290308
  30. Kim ,Y.-H., Jeon, J. H., Choe, E. K., Lee, B., Kim, K., and Seo, J. (2016b). TimeAware: Leveraging framing effects to enhance personal productivity. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 272-283. 
  31. Kim, D.-J., Lee, Y., Rho, S., and Lim, Y.-K. (2016a). Design Opportunities in Three Stages of Relationship Development between Users and Self-Tracking Devices. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 699-703. 
  32. Kim, K. J. (2016). Round or Square? How Screen Shape Affects Utilitarian and Hedonic Motivations for Smartwatch Adoption. Cyberpsychology, Behavior, and Social Networking, 19(12), 733-739.  https://doi.org/10.1089/cyber.2016.0136
  33. Leonardi, P. M. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147-167.  https://doi.org/10.2307/23043493
  34. Leonardi, P. M. (2014). Social media, knowledge sharing, and innovation: Toward a theory of communication visibility. Information Systems Research, 25(4), 796-816.  https://doi.org/10.1287/isre.2014.0536
  35. Li, I., Dey, A. K., and Forlizzi, J. (2011). Understanding my data, myself: supporting self-reflection with ubicomp technologies. Proceedings of the 13th international conference on Ubiquitous computing. ACM, 405-414. 
  36. Li, I., Dey, A., and Forlizzi, J. (2010). A stage-based model of personal informatics systems. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 557-566. 
  37. Lomborg, S., and Frandsen, K. (2016). Self-tracking as communication. Information, Communication & Society, 19(7), 1015-1027.  https://doi.org/10.1080/1369118X.2015.1067710
  38. Lou, L., and Koh, J. (2017). Enhancing Fan Participation in Social Media Based Virtual Brand Communities: The Case of Like, Comment, and Share Activities. Asia Pacific Journal of Information Systems, 27(1), 54-76.  https://doi.org/10.14329/apjis.2017.27.1.54
  39. Ma, M., and Agarwal, R. (2007). Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities. Information Systems Research, 18(1), 42-67.  https://doi.org/10.1287/isre.1070.0113
  40. McGrenere, J., and Ho, W. (2000). Affordances: Clarifying and evolving a concept. Graphics Interface, 179-186. 
  41. Mekler, E. D., and Hornbaek, K. (2016). Momentary Pleasure or Lasting Meaning?: Distinguishing Eudaimonic and Hedonic User Experiences. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 4509-4520. 
  42. Munson, S. A., and Consolvo, S. (2012). Exploring goal-setting, rewards, self-monitoring, and sharing to motivate physical activity. Pervasive computing technologies for healthcare (Pervasive Health), 2012 6th international conference on. IEEE, 25-32. 
  43. Munson, S. A., Krupka, E., Richardson, C., and Resnick, P. (2015). Effects of public commitments and accountability in a technology-supported physical activity intervention. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 1135-1144. 
  44. Newman, M. W., Lauterbach, D., Munson, S. A., Resnick, P., and Morris, M. E. (2011). It's not that i don't have problems, i'm just not putting them on facebook: challenges and opportunities in using online social networks for health. Proceedings of the ACM 2011 conference on Computer supported cooperative work. ACM, 341-350. 
  45. Norman, D. A. (1988). The psychology of everyday things. Basic books. 
  46. Park, C. (2003). Online Hedonic-Experiential Value in Internet Shopping: Antecedents and Consequences. Asia Pacific Journal of Information Systems, 13(4), 73-96. 
  47. Patel, M. S., Asch, D. A., and Volpp, K. G. (2015). Wearable devices as facilitators, not drivers, of health behavior change. JAMA, 313(5), 459-460.  https://doi.org/10.1001/jama.2014.14781
  48. Podsakoff, P. M., and Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531-544.  https://doi.org/10.1177/014920638601200408
  49. Rapp, A., and Cena, F. (2015). Affordances for self-tracking wearable devices. Proceedings of the 2015 ACM International Symposium on Wearable Computers. ACM, 141-142. 
  50. Rivera-Pelayo, V., Zacharias, V., Muller, L., and Braun, S. (2012). Applying quantified self approaches to support reflective learning. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge. ACM, 111-114. 
  51. Rooksby, J., Rost, M., Morrison, A., and Chalmers, M. C. (2014). Personal tracking as lived informatics. Proceedings of the 32nd annual ACM conference on Human factors in computing systems. Toronto, Canada: ACM, 1163-1172. 
  52. Ryan, R. M., Rigby, C. S., and Przybylski, A. (2006). The motivational pull of video games: A self-determination theory approach. Motivation and Emotion, 30(4), 344-360.  https://doi.org/10.1007/s11031-006-9051-8
  53. Shin, D.-H. (2017). Conceptualizing and measuring quality of experience of the internet of things: Exploring how quality is perceived by users. Information & Management, http://dx.doi.org/10.1016/j.im.2017.02.006. 
  54. Suh, A., and Cheung, C. M. (2017). Beyond Hedonic Enjoyment: Conceptualizing Eudaimonic Motivation for Personal Informatics Technology Usage. HCI International 2017. Vancouver, Canada. 
  55. Suh, A., Cheung, C. M., Ahuja, M., and Wagner, C. (2017). Gamification in the Workplace: The Central Role of the Aesthetic Experience. Journal of Management Information Systems, 34(1), 268-305.  https://doi.org/10.1080/07421222.2017.1297642
  56. Toscos, T., Faber, A., An, S., and Gandhi, M. P. (2006). Chick clique: persuasive technology to motivate teenage girls to exercise. CHI'06 extended abstracts on Human factors in computing systems. ACM, 1873-1878. 
  57. Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS quarterly, 28(4), 695-704.  https://doi.org/10.2307/25148660
  58. Van Vugt, H. C., Hoorn, J. F., Konijn, E. A., and de Bie Dimitriadou, A. (2006). Affective affordances: improving interface character engagement through interaction. International Journal of Human-Computer Studies, 64(9), 874-888.  https://doi.org/10.1016/j.ijhcs.2006.04.008
  59. Waterman, A. S. (2011). Eudaimonic identity theory: Identity as self-discovery. Handbook of identity theory and research. Springer, 357-379. 
  60. Waterman, A. S., Schwartz, S. J., and Conti, R. (2008). The implications of two conceptions of happiness (hedonic enjoyment and eudaimonia) for the understanding of intrinsic motivation. Journal of Happiness Studies, 9(1), 41-79.  https://doi.org/10.1007/s10902-006-9020-7
  61. Zhang, P. (2008a). Motivational affordances: reasons for ICT design and use. Communications of the ACM, 51(11), 145-147.  https://doi.org/10.1145/1400214.1400244
  62. Zhang, P. (2008b). Technical opinion Motivational affordances: reasons for ICT design and use. Communications of the ACM, 51(11), 145-147. https://doi.org/10.1145/1400214.1400244