Asia pacific journal of information systems

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

DOI QR Code

Analyzing Factors Influencing COVID-19 Contact-Tracing Application Users' Mobile Location Service Settings: A Perspective of Information-Motivation-Behavioral Skills Model and Implementation Intention

  • Jongki Kim (Department of Business Administration, School of Business, Pusan National University) ;
  • Jianbo Wang (Department of Business Administration, Pusan National University) ;
  • Wei Zhang (School of Information, Central University of Finance and Economics)
  • Received : 2023.07.05
  • Accepted : 2024.03.26
  • Published : 2024.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Contact-tracing applications have significantly contributed to mitigating the spread of coronavirus disease 2019 (COVID-19), yet the extensive use of these location-based applications raises serious privacy concerns. Drawing on the Information-Motivation-Behavioral (IMB) skills model, our study investigated factors that influence users' protective behaviors toward location privacy, elucidating the privacy paradox and the mediating role of implementation intention. Through an online survey conducted in China with 311 participants, we found that privacy concerns and privacy awareness positively affected the use of mobile location service settings, with privacy concerns mediating the relationship between privacy awareness and the intention to protect privacy. Furthermore, our study demonstrated the privacy paradox, revealing the pivotal mediating role of implementation intentions in bridging the gap between users' intentions and their actual behaviors. This study offers new perspectives on the privacy paradox, particularly through the lens of implementation intention, and provides valuable insights for motivating greater use of contact-tracing applications. It offers both theoretical and practical guidance for stakeholders to address privacy concerns during global pandemics like COVID-19, thereby encouraging a more widespread and responsible engagement with technology in public health.

Keywords

References

  1. Acikgoz, Y., and Sumer, H. C. (2019). Implementation intentions as a predictor of applicant withdrawal. Military Psychology, 31(5), 347-354. https://doi.org/10.1080/08995605.2019.1637208 
  2. Acquisti, A., and Grossklags, J. (2005). Privacy and rationality in individual decision making. IEEE Security & Privacy, 3(1), 26-33. https://doi.org/10.1109/MSP.2005.22 
  3. Adriaanse, M. A., Oettingen, G., Gollwitzer, P. M., Hennes, E. P., de Ridder, D. T. D., and de Wit, J. B. F. (2010). When planning is not enough: Fighting unhealthy snacking habits by mental contrasting with implementation intentions (MCII). European Journal of Social Psychology, 40(7), 1277-1293. https://doi.org/10.1002/ejsp.730 
  4. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.  https://doi.org/10.1016/0749-5978(91)90020-T
  5. Alshawi, A., Al-Razgan, M., AlKallas, F. H., Suhaim, R. A. B., Al-Tamimi, R., Alharbi, N., and AlSaif, S. O. (2022). Data privacy during pandemics: A systematic literature review of COVID-19 smartphone applications. PeerJ Computer Science, 8, e826. https://doi.org/10.7717/peerj-cs.826 
  6. Ang, V., and Shar, L. K. (2021). Covid-19 one year on-security and privacy review of contact tracing mobile apps. IEEE Pervasive Computing, 20(4), 61-70. https://doi.org/10.1109/MPRV.2021.3115478 
  7. Awad, N. F., and Krishnan, M. S. (2006). The personalization privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quarterly, 13-28. 
  8. Bagozzi, R. P., Dholakia, U. M., and Basuroy, S. (2003). How effortful decisions get enacted: The motivating role of decision processes, desires, and anticipated emotions. Journal of Behavioral Decision Making, 16(4), 273-295. https://doi.org/10.1002/bdm.446 
  9. Baker-Eveleth, L., Stone, R., and Eveleth, D. (2022). Understanding social media users' privacy-protection behaviors. Information & Computer Security, 30(3), 324-345. https://doi.org/10.1108/ICS-07-2021-0099 
  10. Bandara, R., Fernando, M., and Akter, S. (2020). Explicating the privacy paradox: A qualitative inquiry of online shopping consumers. Journal of Retailing and Consumer Services, 52, 101947. https://doi.org/10.1016/j.jretconser.2019.101947 
  11. Barth, S., and De Jong, M. D. (2017). The privacy paradox-Investigating discrepancies between expressed privacy concerns and actual online behavior-A systematic literature review. Telematics and Informatics, 34(7), 1038-1058. https://doi.org/10.1016/j.tele.2017.04.013 
  12. Barth, S., de Jong, M. D., Junger, M., Hartel, P. H., and Roppelt, J. C. (2019). Putting the privacy paradox to the test: Online privacy and security behaviors among users with technical knowledge, privacy awareness, and financial resources. Telematics and Informatics, 41, 55-69. https://doi.org/10.1016/J.TELE.2019.03.003 
  13. Bieleke, M., Legrand, E., Mignon, A., and Gollwitzer, P. M. (2018). More than planned: Implementation intention effects in non-planned situations. Acta Psychologica, 184, 64-74. https://doi.org/10.1016/j.actpsy.2017.06.003 
  14. Chan, E. Y., and Saqib, N. U. (2021). Privacy concerns can explain unwillingness to download and use contact tracing apps when COVID-19 concerns are high. Computers in Human Behavior, 119, 106718. https://doi.org/10.1016/j.chb.2021.106718 
  15. Chang, S. J., Choi, S., Kim, S. A., and Song, M. (2014). Intervention strategies based on information-motivation-behavioral skills model for health behavior change: A systematic review. Asian Nursing Research, 8(3), 172-181. https://doi.org/10.1016/j.anr.2014.08.002 
  16. Chen, H. T., and Chen, W. (2015). Couldn't or wouldn't? The influence of privacy concerns and self-efficacy in privacy management on privacy protection. Cyberpsychology, Behavior, and Social Networking, 18(1), 13-19. https://doi.org/10.1089/cyber.2014.0456 
  17. Cohen, J. (1988). Statistical Power Analysis for The Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum. 
  18. Collado-Borrell, R., Escudero-Vilaplana, V., Villanueva-Bueno, C., Herranz-Alonso, A., and Sanjurjo-Saez, M. (2020). Features and functionalities of smartphone apps related to COVID-19: Systematic search in app stores and content analysis. Journal of Medical Internet Research, 22(8), e20334. https://doi.org/10.2196/20334 
  19. Crossler, R. E., and Belanger, F. (2017). The mobile privacy-security knowledge gap model: Understanding behaviors. In Proceedings of the 50th Hawaii International Conference on System Sciences (pp. 4071-4080). Retrieved from http://hdl.handle.net/10919/81983 
  20. Crossler, R. E., and Belanger, F. (2019). Why would I use location-protective settings on my smartphone? Motivating protective behaviors and the existence of the privacy knowledge-belief gap. Information Systems Research, 30(3), 995-1006. https://doi.org/10.1287/isre.2019.0846 
  21. Dienlin, T., and Metzger, M. J. (2016). An extended privacy calculus model for SNSs: Analyzing self-disclosure and self-withdrawal in a representative US sample. Journal of Computer-Mediated Communication, 21(5), 368-383. https://doi.org/10.1111/jcc4.12163 
  22. DiMoia, J. P. (2020). Contact tracing and COVID-19: The South Korean context for public health enforcement. East Asian Science, Technology and Society: An International Journal, 14(4), 657-665. https://doi.org/10.1215/18752160-8771448 
  23. Ermakova, T., Fabian, B., and Zarnekow, R. (2014). Acceptance of health clouds-a privacy calculus perspective. In Proceedings of the European Conference on Information Systems (ECIS). Retrieved from http://aisel.aisnet.org/ecis2014/proceedings/track09/11 
  24. Fahey, R. A., and Hino, A. (2020). COVID-19, digital privacy, and the social limits on data-focused public health responses. International Journal of Information Management, 55, 102181. https://doi.org/10.1016/j.ijinfomgt.2020.102181 
  25. Farooq, A., Jeske, D., and Isoaho, J. (2019). Predicting students' security behavior using information-motivation-behavioral skills model. In ICT Systems Security and Privacy Protection. SEC 2019. IFIP Advances in Information and Communication Technology, 562. Springer, Cham. https://doi.org/10.1007/978-3-030-22312-0_17 
  26. Ferretti, L., Wymant, C., Kendall, M., Zhao, L., Nurtay, A., Abeler-Dorner, L., ... and Fraser, C. (2020). Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science, 368(6491), eabb6936. https://doi.org/10.1126/science.abb6936 
  27. Feyisa, H. L. (2020). The world economy at COVID-19 quarantine: Contemporary review. International Journal of Economics, Finance and Management Sciences, 8(2), 63-74. https://doi.org/0.11648/j.ijefm.20200802.11  https://doi.org/10.11648/j.ijefm.20200802.11
  28. Fisher, J. D., and Fisher, W. A. (2000). Theoretical approaches to individual-level change in HIV risk behavior. In Handbook of HIV Prevention (pp. 3-55). Springer. 
  29. Fisher, J. D., Fisher, W. A., Amico, K. R., and Harman, J. J. (2006). An information-motivation- behavioral skills model of adherence to antiretroviral therapy. Health Psychology, 25(4), 462-473. https://doi.org/10.1037/0278-6133.25.4.462 
  30. Fisher, W. A., Fisher, J. D., and Harman, J. (2003). The information-motivation-behavioral skills model: A general social psychological approach to understanding and promoting health behavior. Social Psychological Foundations of Health and Illness, 22(4), 82-106. https://doi.org/10.1002/9780470753552.ch4 
  31. Fox, G., and Connolly, R. (2018). Mobile health technology adoption across generations: Narrowing the digital divide. Information Systems Journal, 28(6), 995-1019. https://doi.org/10.1111/isj.12179 
  32. Fraser, C. (2020, April 16). Digital contact tracing can slow or even stop coronavirus transmission and ease us out of lockdown. Oxford University's Big Data Institute. Retrieved from https://www.research.ox.ac.uk/Article/2020-04-16-digital-contact-tracing-can-slow-oreven-stop-coronavirus-trans mission-and-ease-us-out-of-lockdown 
  33. Gerber, N., Gerber, P., and Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers & Security, 77, 226-261. https://doi.org/10.1016/j.cose.2018.04.002 
  34. Gollwitzer, P. M. (1993). Goal achievement: The role of intentions. European Review of Social Psychology, 4(1), 141-185. https://doi.org/10.1080/14792779343000059 
  35. Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist, 54(7), 493-503. https://doi.org/10.1037/0003-066X.54.7.493 
  36. Gollwitzer, P. M., and Sheeran, P. (2006). Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in Experimental Social Psychology, 38, 69-119. https://doi.org/10.1016/S0065-2601(06)38002-1 
  37. Hair Jr, J. F., Hult, G. T. M., Ringle, C., and Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications. 
  38. Hoffmann, C. P., and Lutz, C. (2021). Digital divides in political participation: The mediating role of social media self-efficacy and privacy concerns. Policy & Internet, 13(1), 6-29. https://doi.org/10.1002/poi3.225 
  39. Hoffmann, C. P., Lutz, C., and Ranzini, G. (2016). Privacy cynicism: A new approach to the privacy paradox. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 10(4), Article 7. https://doi.org/10.5817/CP2016-4-7 
  40. Jahari, S. A., Hass, A., Hass, D., and Joseph, M. (2022). Navigating privacy concerns through societal benefits: A case of digital contact tracing applications. Journal of Consumer Behaviour, 21(3), 625-638. https://doi.org/10.1002/cb.2029 
  41. Johnston, A. C., and Warkentin, M. (2010). Fear Appeals and Information Security Behaviors: An Empirical Study. MIS Quarterly, 34(3), 549-566. https://doi.org/10.2307/25750691 
  42. Juneau, C. E., Briand, A. S., Collazzo, P., Siebert, U., and Pueyo, T. (2023). Effective contact tracing for COVID-19: A systematic review. Global Epidemiology, 5, 100103. https://doi.org/10.1016/j.gloepi.2023.100103 
  43. Jung, Y., and Park, J. (2018). An investigation of relationships among privacy concerns, affective responses, and coping behaviors in location-based services. International Journal of Information Management, 43, 15-24. https://doi.org/10.1016/j.ijinfomgt.2018.05.007 
  44. Kim, J., and Kwan, M. P. (2021). An examination of people's privacy concerns, perceptions of social benefits, and acceptance of COVID-19 mitigation measures that harness location information: A comparative study of the US and South Korea. ISPRS International Journal of Geo-Information, 10(1), 25. https://doi.org/10.3390/ijgi10010025 
  45. Kim, J., and Wang, J. (2020). Examining factors that determine the use of social media privacy settings: Focused on the mediating effect of implementation intention to use privacy settings. Asia Pacific Journal of Information Systems, 30(4), 919-945.  https://doi.org/10.14329/apjis.2020.30.4.919
  46. Kim, J., and Wang, J. (2022). Investigating the use of COVID-19 contact tracing applications in South Korea and China: An agency theory perspective. The Journal of Internet Electronic Commerce Research, 22(5), 1-24. https://doi.org/10.37272/JIECR.2022.10.22.5.1 
  47. Kondylakis, H., Katehakis, D. G., Kouroubali, A., Logothetidis, F., Triantafyllidis, A., Kalamaras, I., ... and Tzovaras, D. (2020). COVID-19 mobile apps: A systematic review of the literature. Journal of Medical Internet Research, 22(12), e23170. https://doi.org/10.2196/23170 
  48. Lee, D., and Lee, J. (2020). Testing on the move: South Korea's rapid response to the COVID-19 pandemic. Transportation Research Interdisciplinary Perspectives, 5, 100111. https://doi.org/10.1016/j.trip.2020.100111 
  49. Liang, F. (2020). COVID-19 and Health Code: How digital platforms tackle the pandemic in China. Social Media+ Society, 6(3), 2056305120947657. https://doi.org/10.1177/2056305120947657 
  50. Liang, H., and Xue, Y. L. (2010). Understanding security behaviors in personal computer usage: A threat avoidance perspective. Journal of the Association for Information Systems, 11(7). https://doi.org/10.17705/1jais.00232 
  51. Nguyen, V. M., Bell, C., Berseth, V., Cvitanovic, C., Darwent, R., Falconer, M., Hutchen, J., Kapoor, T., Klenk, N., and Young, N. (2023). Promises and pitfalls of digital knowledge exchange resulting from the COVID-19 pandemic. Socio-Ecological Practice Research, Preprints, 3, 427-439. https://doi.org/10.1007/s42532-021-00097-0 
  52. Norberg, P. A., Horne, D. R., and Horne, D. A. (2007). The privacy paradox: Personal information disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100-126. https://doi.org/10.1111/j.1745-6606.2006.00070.x 
  53. Nunnally J., and Bernstein, I. (1994). Psychometric Theory. New York: McGraw Hill. 
  54. Osmanlliu, E., Rafie, E., Bedard, S., Paquette, J., Gore, G., and Pomey, M. P. (2021). Considerations for the design and implementation of COVID-19 contact tracing apps: Scoping review. JMIR mHealth and uHealth, 9(6), e27102. https://doi.org/10.2196/27102 
  55. Roberts, T. H. (2012). A cross-disciplined approach to exploring the privacy paradox: Explaining disclosure behaviour using the theory of planned behaviour. UK Academy for Information Systems Conference Proceedings. https://aisel.aisnet.org/ukais2012/7 
  56. Rowe, F. (2020). Contact tracing apps and values dilemmas: A privacy paradox in a neo-liberal world. International Journal of Information Management, 55, 102178. https://doi.org/10.1016/j.ijinfomgt.2020.102178 
  57. Rubens, M., Attonito, J., Saxena, A., Shehadeh, N., Ramamoorthy, V., and Nair, R. R. (2015). Health promotion and disease prevention strategies for today's physicians. The American Journal of the Medical Sciences, 349(1), 73-79. https://doi.org/10.1097/MAJ.0000000000000320 
  58. Shahroz, M., Ahmad, F., Younis, M. S., Ahmad, N., Boulos, M. N. K., Vinuesa, R., and Qadir, J. (2021). COVID-19 digital contact tracing applications and techniques: A review post initial deployments. Transportation Engineering, 5, 100072. https://doi.org/10.48550/arXiv.2103.01766 
  59. Sheehan, K. B., and Hoy, M. G. (2000). Dimensions of privacy concern among online consumers. Journal of Public Policy & Marketing, 19(1), 62-73. https://doi.org/10.1509/jppm.19.1.62.16949 
  60. Sheeran, P. (2002). Intention-behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12(1), 1-36. https://doi.org/10.1080/14792772143000003 
  61. Sheeran, P., and Orbell, S. (2000). Using implementation intentions to increase attendance for cervical cancer screening. Health Psychology, 19(3), 283-289. https://doi.org/10.1037//0278-6133.19.3.283 
  62. Sheeran, P., Webb, T. L., and Gollwitzer, P. M. (2005). The interplay between goal intentions and implementation intentions. Personality and Social Psychology Bulletin, 31(1), 87-98. https://doi.org/10.1177/0146167204271308 
  63. Singh, H. J. L., Couch, D., and Yap, K. (2020). Mobile health apps that help with COVID-19 management: Scoping review. JMIR Nursing, 3(1), e20596. https://doi.org/10.2196/20596 
  64. Taddicken, M. (2014). The 'privacy paradox' in the social web: The impact of privacy concerns, individual characteristics, and the perceived social relevance on different forms of self-disclosure. Journal of Computer-mediated Communication, 19(2), 248-273. https://doi.org/10.1111/jcc4.12052 
  65. Thompson, R., Barclay, D. W., and Higgins, C. A. (1995). The partial least squares approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies: Special Issue on Research Methodology, 2(2), 284-324. 
  66. Trestian, R., Celeste, E., Xie, G., Lohar, P., Bendechache, M., Brennan, R., and Ta, I. (2022). The privacy paradox-investigating people's attitude towards privacy in a time of COVID-19. In 2022 14th International Conference on Communications (COMM) (pp. 1-6). Retrieved from https://ieeexplore.ieee.org/document/9817170 
  67. Valentino-DeVries, J., Singer, N., Keller, M. H., and Krolik, A. (2018, December 10). Your apps know where you were last night, and they're not keeping it secret. The New York Times, Retrieved from https://www.nytimes.com/interactive/2018/12/10/business/location-data-privacy-apps.html 
  68. Van Gelderen, M., Kautonen, T., Wincent, J., and Biniari, M. (2018). Implementation intentions in the entrepreneurial process: Concept, empirical findings, and research agenda. Small Business Economics, 51, 923-941. https://doi.org/10.1007/s11187-017-9971-6 
  69. Vitak, J., and Zimmer, M. (2020). More than just privacy: Using contextual integrity to evaluate the long-term risks from COVID-19 surveillance technologies. Social Media+ Society, 6(3), 2056305120948250. https://doi.org/10.1177/2056305120948250 
  70. Walrave, M., Waeterloos, C., and Ponnet, K. (2020). Adoption of a contact tracing app for containing COVID-19: A health belief model approach. JMIR Public Health and Surveillance, 6(3), e20572. 
  71. Xu, H., Dinev, T., Smith, J., and Hart, P. (2011). Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems, 12(12), 1. https://doi.org/10.17705/1jais.00281 
  72. Xu, H., Luo, X. R., Carroll, J. M., and Rosson, M. B. (2011). The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing. Decision Support Systems, 51(1), 42-52. https://doi.org/10.1016/j.dss.2010.11.017 
  73. Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. Industrial Management & Data Systems, 111(2), 212-226. https://doi.org/10.1108/02635571111115146