Asia pacific journal of information systems

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

DOI QR Code

Factors Influencing Work-Related Use of Smartphones: An Empirical Investigation

  • JaeSung Park (Business Incubating Center, Chonnam National University) ;
  • HeeOck Rho (Policy Planning Department, Gwangju Institute of Green-Car Advancement) ;
  • Joon Koh (College of Business Administration, Chonnam National University)
  • Received : 2018.04.11
  • Accepted : 2018.09.27
  • Published : 2018.09.29
Download PDF
⟨ Previous Next ⟩

Abstract

This paper touches the limitations of existing theories related to technology acceptance, which mainly focus on users' perceived ease of use and usefulness, and proposes the role for sensory capabilities and enjoyment in understanding smartphone use. Furthermore, we develop a model that explains smartphone usage and intention to use it for a task and analyzes 442 questionnaire survey responses of smartphone users. First, perceived usefulness, perceived sensory capability, and perceived enjoyment influenced smartphone usage. Second, we found that both perceived usefulness and smartphone use were significantly associated with users' intention to utilize the smartphone for their job-related tasks. Finally, both perceived sensory capability and enjoyment were found to be more powerful factors than ease of use in explaining smartphone use. From the study findings, implications and future research directions are also discussed.

Keywords

References

  1. Agarwal, R., and Karahanna, E. (2000). Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.  https://doi.org/10.2307/3250951
  2. Alderman, R. B. (1974). Psychological behavior in sport. Saunders. 
  3. Beaudry, A., and Pinsonneault, A. (2010). The other side of acceptance: studying the direct and indirect effects of emotions on information technology use. MIS Quarterly, 34(4), 689-710.  https://doi.org/10.2307/25750701
  4. Bloomberg (2012). Apple sues samsung over smartphones in widening patent infringement claims. Retrieved from http://www.bloomberg.com/news/2012-02-12/apple-expands-number-of-patent-claims-against-samsung-in-latest-lawsuit.html 
  5. Castaneda, J. A., Munoz-Leiva, F., and Luque, T. (2007). Web acceptance model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384-396.  https://doi.org/10.1016/j.im.2007.02.003
  6. Chen, K., and Yen, D. C. (2004). Improving the quality of online presence through interactivity. Information & Management, 42(1), 217-226.  https://doi.org/10.1016/j.im.2004.01.005
  7. Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology, Sloan School of Management. 
  8. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.  https://doi.org/10.2307/249008
  9. Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.  https://doi.org/10.1287/mnsc.35.8.982
  10. Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.  https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
  11. Deci, E. L. (1975). Intrinsic motivation: Perspectives in social psychology. Plenum Press. 
  12. Desmet, P., and Hekkert, P. (2002). The basis of product emotions, Pleasure with Products, beyond Usability (pp. 60-68). Taylor & Francis, London 
  13. Fishbein, M. (1967). Attitude and the prediction of behavior. Readings in Attitude Theory and Measurement (pp. 477-492). 
  14. Fishbein, M., and Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley. 
  15. Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.  https://doi.org/10.1177/002224378101800104
  16. Gartner (2012). Gartner says worldwide sales of mobile phones declined 2 percent in first quarter of 2012; previous year-over-year decline occurred in second quarter of 2009. 
  17. Hassenzahl, M., and Tractinsky, N. (2006). User experience-a research agenda. Behaviour & Information Technology, 25(2), 91-97.  https://doi.org/10.1080/01449290500330331
  18. Hennig-Thurau, T., Groth, M., Paul, M., and Gremler, D. D. (2006). Are all smiles created equal? How emotional contagion and emotional labor affect service relationships. Journal of Marketing, 70(3), 58-73.  https://doi.org/10.1509/jmkg.70.3.058
  19. Hoffman, D. L., and Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: conceptual foundations. Journal of Marketing, 60(3), 50-68.  https://doi.org/10.1177/002224299606000304
  20. Hsu, C. L., and Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868.  https://doi.org/10.1016/j.im.2003.08.014
  21. Igbaria, M., Zinatelli, N., Cragg, P., and Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: a structural equation model. MIS Quarterly, 21(3), 279-305.  https://doi.org/10.2307/249498
  22. Jeon, E., and Park, H. A. (2015). Factors affecting acceptance of smartphone application for management of obesity. Healthcare Informatics Research, 21(2), 74-82.  https://doi.org/10.4258/hir.2015.21.2.74
  23. Jin, B. S., Ji, Y. G., Choi, K., and Cho, G. (2009). Development of a usability evaluation framework with quality function deployment: From customer sensibility to product design. Human Factors and Ergonomics in Manufacturing & Service Industries, 19(2), 177-194.  https://doi.org/10.1002/hfm.20145
  24. Jordan, P. W. (2002). Designing pleasurable products: An introduction to the new human factors. CRC Press. 
  25. Kim, S. S., Ko, E. J., and Kim S. Y. (2018). The role of ICT in smart-work continuance. Asia Pacific Journal of Information Systems, 28(1), 1-18.  https://doi.org/10.14329/apjis.2018.28.1.1
  26. Kim, S., and Koh, J. (2007). The effect of e-scape on internet shopper's cognition, emotion, and behavior response. The 28th International Conference of Information Systems, Montreal, Canada. 
  27. Kotler, P., Kartajaya, H., and Setiawan, I. (2010). Future model for marketing 3.0. Wiley. 
  28. Laudon, J. P., and Laudon, K. C. (2006). Essentials of business information systems. Prentice-Hall. 
  29. Lavie, T., and Tractinsky, N. (2004). Assessing dimensions of perceived visual aesthetics of web sites. International Journal of Human-Computer Studies, 60(3), 269-298.  https://doi.org/10.1016/j.ijhcs.2003.09.002
  30. Lee, K. Y., Lee, M., and Kim, K. (2017). The differential impacts of 'communication' and 'computing' functions in smartphones on individuals' performance and the moderating role of organizational roles. Asia Pacific Journal of Information Systems, 27(4), 191-215.  https://doi.org/10.14329/apjis.2017.27.4.191
  31. Li, L., and Lin, T. T. C. (2016). Exploring work-related smartphone dependency among young working adults in China: A qualitative approach. International Journal of Communication, 10, 1-19. 
  32. Lin, C. S., Wu, S., and Tsai, R. J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information & Management, 42(5), 683-693.  https://doi.org/10.1016/j.im.2004.04.003
  33. Mahlke, S. (2008). User experience of interaction with technical systems. Technischn Universitat Berlin. 
  34. Malhotra, Y., and Galletta, D. F. (1999). Extending the technology acceptance model to account for social influence: theoretical bases and empirical validation. 32th Hawaii International Conference on System Science, Maui, HI. 
  35. Marks, D. F. (1996). Health psychology in context. Journal of Health Psychology, 1, 7-21.  https://doi.org/10.1177/135910539600100102
  36. Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.  https://doi.org/10.1287/isre.2.3.173
  37. Milosevic, M., Shrove, M. T., and Jovanov, E. (2011). Applications of smartphones for ubiquitous health monitoring and wellbeing management. Journal of Information Technology and Applications, 1(1), 7-15. 
  38. Moon, J. W., and Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.  https://doi.org/10.1016/S0378-7206(00)00061-6
  39. Nunnally, J. C. (1978). Psychometric theory. McGraw-Hill. 
  40. Ohly, S., and Latour, A. (2014). Work-related smartphone use and well-being in the evening: The role of autonomous and controlled motivation. Journal of Personnel Psychology, 13(4), 174-183.  https://doi.org/10.1027/1866-5888/a000114
  41. Park, J., and Choi, Y. (2013). The ecosystem of the smartphone industry in Korea: Perspectives on its sustainable growth. Information Systems Review, 15(1), 25-43.  https://doi.org/10.14329/isr.2016.18.1.025
  42. Petri, H. L. (1996). Motivation: Theory, research, and applications. Thomson Brooks/Cole. 
  43. Rafaeli, A., and Vilnai-Yavetz, I. (2004). Emotion as a connection of physical artifacts and organizations. Organization Science, 15(6), 671-686.  https://doi.org/10.1287/orsc.1040.0083
  44. Saade, R., and Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information & Management, 42(2), 317-327.  https://doi.org/10.1016/j.im.2003.12.013
  45. Shin, D. H. (2009). Determinants of customer acceptance of multi-service network: An implication for IP-based technologies. Information & Management, 46(1), 16-22.  https://doi.org/10.1016/j.im.2008.05.004
  46. Straub, D., Limayem, M., and Karahanna-Evaristo, E. (1995). Measuring system usage: Implications for IS theory testing. Management Science, 41(8), 1328-1342.  https://doi.org/10.1287/mnsc.41.8.1328
  47. Sutton, S. (1998). Predicting and explaining intentions and behavior: How well are we doing? Journal of Applied Social Psychology, 28(15), 1317-1338.  https://doi.org/10.1111/j.1559-1816.1998.tb01679.x
  48. Taylor, S., and Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570.  https://doi.org/10.2307/249633
  49. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.  https://doi.org/10.1287/isre.11.4.342.11872
  50. Venkatesh, V., and Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.  https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
  51. Venkatesh, V., and Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.  https://doi.org/10.1287/mnsc.46.2.186.11926
  52. Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.  https://doi.org/10.2307/30036540
  53. Wu, J., and Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. MIS Quarterly, 33(2), 419-432.  https://doi.org/10.2307/20650298
  54. Zhou, R., and Feng, C. (2017). Difference between leisure and work contexts: The roles of perceived enjoyment and perceived usefulness in predicting mobile video calling use acceptance. Frontiers in Psychology, 8, 350-368. https://doi.org/10.3389/fpsyg.2017.00350