An affordance lens for wearable information systems

References

• Allen, D. K., Brown, A., Karanasios, S., & Norman, A. (2013). How should technology- mediated organizational change be explained? A comparison of the contributions of critical realism and activity theory. MIS Quarterly, 37(3), 835–854.
   Web of Science ®Google Scholar
• Altenhoff, B., Vaigneur, H., & Caine, K. (2015). One step forward, two steps back: The key to wearables in the field is the app. PervasiveHealth '15 Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare, 241–244.
   Google Scholar
• Barki, H., Titah, R., & Boffo, C. (2007). Information system use-related activity: An expanded behavioral conceptualization of individual-level information system use. Information Systems Research, 18(2), 173–192.
   Web of Science ®Google Scholar
• Baskerville, R. (2011, July) Design theorizing individual information systems. Proceedings of the Americas Conference in Information Systems (PACIS), Brisbane, Australia., Vol. 25.
   Google Scholar
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
   Google Scholar
• Chen, R., Sharman, R., Rao, H. R., & Upadhyaya, S. J. (2013). Data model development for fire related extreme events: An activity theory approach. MIS Quarterly, 37(1), 125–147.
   Web of Science ®Google Scholar
• Engeström, Y. (1987). Learning by expanding. In An activity-theoretical approach to developmental research. Helsinki, Finland: Orienta-Konsultit Oy.
   Google Scholar
• Etkin, J. (2016). The hidden cost of personal quantification. Journal of Consumer Research, 42(6), 967–984.
   Web of Science ®Google Scholar
• Fernando, A. (2015) Interoperability: 4 Keys to safe successful wearable technology use. Medical Design Technology, Retrieved 2015, July 9from https://www.mdtmag.com/article/2015/07/interoperability-4-keys-safe-successful-wearable-technology-use
   Google Scholar
• Fritz, T., Huang, E. M., Murphy, G. C., & Zimmermann, T. (2014, April). Persuasive technology in the real world: A study of long-term use of activity sensing devices for fitness. CHI'14- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Toronto, Ontario, Canada (pp. 487–496). New York, NY: ACM.
   Google Scholar
• Gagliordi, N. (2016) Fitbit leads wearables market as apple watch sales decline. ZDNet. Retrieved from http://www.zdnet.com/article/fitbit-leads-wearables-market-as-apple-watch-sales-decline/
   Google Scholar
• Ghose, A., & Ipeirotis, P. G. (2011). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE Trans-actions on Knowledge and Data Engineering, 23(10), 1498–1512.
   Web of Science ®Google Scholar
• Gibson, J. J. (1986). The ecological approach to visual perception. Hillsdale, NJ: Lawrence Earlbaum.
   Google Scholar
• Gilmore, J. N. (2015). Everywear: The quantified self and wearable fitness technologies. New Media & Society, 18(11), 2524–2539.
   Web of Science ®Google Scholar
• Gleasure, R., & Morgan, L. (2018). The pastoral crowd: Exploring self‐hosted crowdfunding using activity theory and social capital. Information Systems Journal, 28(3), 489–515.
   Web of Science ®Google Scholar
• Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642.
   Web of Science ®Google Scholar
• Hartson, H. R. (2003). Cognitive, physical, sensory, and functional affordances in interaction design. Behavior & Information Technology, 22(5), 315–338.
   Web of Science ®Google Scholar
• Hasan, H., & Kazlauskas, A. (2014). Activity theory: Who is doing what, why and how. In H. Hasan (Ed.), Being practical with theory: A window into business research (pp. 9–14). Wollongong: THEORI. http://eurekaconnection.files.wordpress.com/2014/02/p-09-14-activity-theory-theori-ebook-2014.pdf
   Google Scholar
• Hindman, D. (2015). Designing for the internet of wearable things: Five principles. Retrieved from https://www.fjordnet.com/conversations/designing-for-the-internet-of-wearable-things/
   Google Scholar
• Hutchby, I. (2001). Technologies, texts and affordances. Sociology, 35(2), 441–456.
   Google Scholar
• IDC. (2017, June 21). Worldwide quarterly wearables device tracker. Retrieved from http://www.idc.com/
   Google Scholar
• James, T. L., Wallace, L., & Deane, J. K. (in press). Using organistic integration theory to explore the association between users’ exercise motivations and fitness technology feature set use. MIS Quarterly.
   Google Scholar
• Johnston, C. (2013, July 30) The great fitness band shootout: The jawbone up, fitbit flex, and nike fuelband—Which is best? Ars Technica. Retrieved from http://arstechnica.com/gadgets/2013/07/the-great-fitness-band-shootout/3/
   Google Scholar
• Kaptelinin, V. (1996). Activity theory: Implications for human-computer interaction. In B. A. Nardi (Ed.), Context and consciousness (pp. 53–59). Cambridge, MA: MIT press.
   Google Scholar
• Kaptelinin, V. (2005). Activity theory. In Encyclopaedia of human computer interaction (2nd ed.). Retrieved from https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/activity-theory
   Google Scholar
• Kaptelinin, V., & Nardi, B. (2012, May 5–10). Affordances in HCI: Toward a mediated action perspective. CHI '12 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Austin, TX: ACM.
   Google Scholar
• Karahanna, E., Xu, S. X., Xu, Y., & Zhang, N. (in press). The Needs-Affordances Features (NAF) perspective for the use of social media. MIS Quarterly.
   Google Scholar
• Karanasios, S. (2018). Toward a unified view of technology and activity: The contribution of activity theory to information systems research. Information Technology & People 31(1), 134-155.
   Web of Science ®Google Scholar
• Karanasios, S., & Allen, D. (2014). Mobile technology in mobile work: Contradictions and congruencies in activity systems. European Journal of Information Systems, 23, 529–542.
   Web of Science ®Google Scholar
• Kietzmann, J. (2008). Interactive innovation of technology for mobile work. European Journal of Information Systems, 17(3), 305–331.
   Web of Science ®Google Scholar
• Krippendorff, K. (2004). Content analysis: An introduction to its methodology. Thousand Oaks, CA: Sage.
   Google Scholar
• Kuutti, K. (1991). Activity theory and its applications to information systems research and development. In H. -E. Nissen, H. K. Klein and R. Hirschheim (Eds.), Information systems research arena of the 90's (pp. 529–549). Amsterdam: North Holland.
   Google Scholar
• Lee, J. -M., Kim, Y., & Welk, G. (2014). Validity of consumer-based physical activity monitors. Medicine & Science in Sports & Exercise, 46(9), 1840–1848.
   PubMed Web of Science ®Google Scholar
• Leonardi, P. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147–167.
   Web of Science ®Google Scholar
• Leont’ev, A. N. (1978). Activity, consciousness, and personality. Englewood Cliffs, NJ: Prentice Hall.
   Google Scholar
• Lombard, M., Snyder-Duch, J., & Bracken, C. C. (2004). A call for standardization in content analysis reliability. Human Communication Research, 30, 434–437.
   Web of Science ®Google Scholar
• Mackinlay, M. (2013). Phases of accuracy diagnosis: (In)visibility of system status in the fitbit. Intersect: the Stanford Journal of Science, Technology and Society, 6(2), 1–9.
   Google Scholar
• Mann, S. (2005). Wearable computing. In Encyclopaedia of human computer interaction (2nd ed.). Denmark: Interaction Design Foundation. https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/wearable-computing
   Google Scholar
• Markus, M. L., & Silver, M. S. (2008). A foundation for the study of IT effects: A new look at DeSanctis and Poole’s concepts of structural features and spirit. Journal of the Association for Information Systems, 9(10/11), 609–632.
   Web of Science ®Google Scholar
• Mcauley, J., & Yang, A. (2016, April 11–15) Addressing complex and subjective product-related queries with customer reviews. World Wide Web WWW 2016, Montréal, Canada.
   Google Scholar
• Mudambi, S. M., & Schuff, D. (2010). Research note: What makes a helpful online review? A Study of customer reviews on Amazon.com. MIS Quarterly, 34(1), 185–200.
   Web of Science ®Google Scholar
• Nardi, B. A. (1996). Studying context: A comparison of activity theory, situated action models and distributed cognition. In B. A. Nardi (Ed.), Context and consciousness (pp. 69–102). Cambridge, MA: MIT press.
   Google Scholar
• Norman, D. A. (1988). The psychology of everyday things. New York: Basic Books.
   Google Scholar
• Norman, D. A. (1999, May/June). Affordances, conventions, and design. Interactions, 6, 38–42.
   Google Scholar
• Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable devices as facilitators, not drivers, of health behavior change. Journal of the American Medical Association, 313(5), 459–460.
   PubMed Web of Science ®Google Scholar
• Prasopoulou, E. (2017). A half-moon on my skin: A memoir on life with an activity tracker. European Journal of Information Systems, 26(3), 287–297.
   Web of Science ®Google Scholar
• Pressman, A. (2017, November 30) Fitbit is back on top of wearables, but apple is growing faster. Fortune.
   Google Scholar
• Rettner, R. (2013) Tracker craze: Fitness wristbands’ popularity will continue to grow. Live Science. Retrieved from http://www.livescience.com/42144-activity-monitors-popularity.html
   Google Scholar
• Ruckriem, G. (2009). Digital technology and mediation — A challenge to activity theory. In A. Sannino, H. Daniels, & K. D. Gutiérrez (Eds.), Learning and expanding with activity theory. Cambridge: Cambridge University Press.
   Google Scholar
• Ryan, G. W., & Bernard, H. R. (2003). Techniques to identify themes. Field Methods, 15(1), 85–109.
   Google Scholar
• Ryu, C., Jin, K.-Y., Chaudhury, A., & Rao, H. R. (2005). Knowledge acquisition via three learning processes in enterprise information portals: Learning-by-investment, learning-by- doing, and learning-from-others. MIS Quarterly, 29(2), 245–278.
   Web of Science ®Google Scholar
• Schüll, N. D. (2016). Data for life: Wearable technologies and the design of self-care. Biosocieties, 11(3), 317–333.
   Web of Science ®Google Scholar
• Swan, M. (2013). The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), 85–99.
   PubMed Web of Science ®Google Scholar
• Vella, M. (2013, January 29) Making the wearable tech revolution a reality. Fortune. Retrieved from http://fortune.com/2013/01/29/making-the-wearable-tech-revolution-a-reality/
   Google Scholar
• Vyas, D., Chisalita, C., & Dix, A. (2017). Organizational affordances: A structuration theory approach to affordances. Interacting with Computers, 29(2), 117–131.
   Web of Science ®Google Scholar
• Vygotsky, L. S. (1978). Mind and society. Cambridge, MA: Harvard University Press.
   Google Scholar
• Yoo, Y. (2010). Computing in everyday life: A call for research on experiential computing. MIS Quarterly, 34(2), 213–231.
   Web of Science ®Google Scholar
• Zhang, P. (2008). Motivational affordances: Reasons for ICT design and use. Communications of the ACM, 51(11), 145–147.
   Web of Science ®Google Scholar