International Journal of Internet, Broadcasting and Communication

  • 제14권2호
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  • Pages.1-9
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  • 2022
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  • 2288-4920(pISSN)
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  • 2288-4939(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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Testing the Mediating Role of Perceived Risk of COVID-19 and the Moderating Role of Age in the Relationship between COVID-19 related Information Sensitivity and Personal Preventive Behaviors

  • Hong, Kyung-Wan (Major in Tourism Management, College of Business Administration, Keimyung University) ;
  • Kim, Hyeon-Cheol (School of Business Administration, College of Business and Economics, Chung-Ang University)
  • 투고 : 2022.04.30
  • 심사 : 2022.05.09
  • 발행 : 2022.05.31
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초록

The influence of information sensitivity during the COVID-19 pandemic on perceived risk and personal preventive behaviors of consumers in China had been investigated. The participants were Chinese individuals experiencing the pandemic as it happened. Participants voluntarily completed an online questionnaire to provide their COVID-19 information sensitivity, their perceived COVID-19 risk, preventive behavior and their respective age. Our study discovered that COVID-19 information sensitivity positively influence perceived risk and preventive behavior. Moreover, young individuals show higher levels of online information sensitivity, which influenced their personal protective behavior when compared to that of middle-aged and elderly participants. Furthermore, Perceived risk significantly affected preventive behaviors. The results of this study may assist the government and marketeers in comprehending information sensitivity which can affect consumers' protective behavior toward reducing COVID-19 infections.

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참고문헌

  1. WHO. https://www.who.int/emergencies/diseases/novel-coronavirus-2019
  2. Center for Disease Control and Prevention. https://www.chinacdc.cn/
  3. Wise, T., Zbozinek, T. D., Michelini, G., Hagan, C. C., & Mobbs, D. "Changes in risk perception and self-reported protective behaviour during the first week of the COVID-19 pandemic in the United States." Royal Society Open Science, Vol. 7, No. 9, pp. 200742, Sep 2020. DOI: https://doi.org/10.31234/osf.io/dz428
  4. Zhang, K. Z. K., Cheung, C. M. K., & Lee, M. K. O. "Examining the moderating effect of inconsistent reviews and its gender differences on consumers' online shopping decision." International Journal of Information Management, Vol. 34, No. 2, pp. 89-98, April 2014. DOI: http://doi.org/10.1016/j.ijinfomgt.2013.12.001.
  5. Schomakers, E. M., Lidynia, C., Mullmann, D., & Ziefle, M. "Internet users' perceptions of information sensitivity-insights from Germany." International Journal of Information Management, Vol. 46, pp. 142-150, June 2019. DOI: https://doi.org/10.1016/j.ijinfomgt.2018.11.018.
  6. Zimmer, J. C., Arsal, R., Al-Marzouq, M., Moore, D., & Grover, V. "Knowing your customers: Using a reciprocal relationship to enhance voluntary information disclosure." Decision Support Systems, Vol. 48, No. 2, pp. 395-406, Jan 2010. DOI: https://doi.org/10.1016/j.dss.2009.10.003
  7. Mothersbaugh, D. L., Foxx, W. K., Beatty, S. E., & Wang, S. "Disclosure antecedents in an online service context: The role of sensitivity of information." Journal of Service Research, Vol. 15, No. 1, pp. 76-98, 2012. DOI: 10.1177/1094670511424924
  8. Liu, P. L. "COVID-19 information seeking on digital media and preventive behaviors: The mediation role of worry." Cyberpsychology, Behavior, and Social Networking, Vol. 23, No. 10. pp. 677-682, 2020. DOI: https://doi.org/10.1089/cyber.2020.0250.
  9. Guo, X., Zhang, X., & Sun, Y. "The privacy-personalization paradox in mHealth services acceptance of different age groups." Electronic Commerce Research and Applications, Vol. 16, pp. 55-65, Mar-April 2016. D OI: https://doi.org/10.1016/j.elerap.2015.11.001.
  10. Campbell, M. C., & Goodstein, R. C. (2001). "The moderating effect of perceived risk on consumers' evaluations of product incongruity: Preference for the norm." Journal of Consumer Research, Vol. 28, No. 3, pp. 439-449, Dec 2001. DOI: https://doi.org/10.1086/323731
  11. Liao, C., Lin, H. N., & Liu, Y. P. "Predicting the use of pirated software: A contingency model integrating perceived risk with the theory of planned behavior." Journal of Business Ethics, Vol. 91, No. 2, pp. 237-252, April 2010. DOI: https://doi.org/10.1007/s10551-009-0081-5.
  12. Pavlou, P. A. "Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model." International Journal of Electronic Commerce, Vol. 7, No, 3, pp. 101-134, Dec 2014. DOI: https://doi.org/10.1080/10864415.2003.11044275.
  13. Liu, B. F., & Kim, S. "How organizations framed the 2009 H1N1 pandemic via social and traditional media: Implications for US health communicators." Public Relations Review, Vol. 37, No, 3, pp. 233-244, Sep 2011. DOI: http://dx.doi.org/10.1016/j.pubrev.2011.03.005.
  14. Yoo, W., Choi, D. H., & Park, K. "The effects of SNS communication: How expressing and receiving information predict MERS-preventive behavioral intentions in South Korea." Computers in Human Behavior, Vol. 62, pp. 34-43, Sep 2016. DOI: https://doi.org/10.1016/j.chb.2016.03.058.
  15. Oh, S. H., Lee, S. Y., & Han, C. "The effects of social media use on preventive behaviors during infectious disease outbreaks: The mediating role of self-relevant emotions and public risk perception." Health Communication, Vol. 36, No. 8, pp. 1-10, Feb 2020. DOI: https://doi.org/10.1080/10410236.2020.1724639.
  16. Bilgihan, A., Peng, C., & Kandampully, J. "Generation Y's dining information seeking and sharing behavior on social networking sites." International Journal of Contemporary Hospitality Management, Vol. 26, No. 3, pp. 346-399, April 2014. DOI: https://doi.org/10.1108/ijchm-11-2012-0220.
  17. Dhir, A., & Torsheim, T. "Age and gender differences in photo tagging gratifications." Computers in Human Behavior, Vol. 63, pp. 630-638, Oct 2016. DOI: https://doi.org/10.1016/j.chb.2016.05.044.
  18. Yang, Y. T., Horneffer, M., & DiLisio, N. "Mining social media and web searches for disease detection." Journal of Public Health Research, Vol. 2, No. 1, pp. 17-21, May 2013. DOI: https://doi.org/10.4081/jphr.2013.e4.
  19. Huang, Y. Y., & Handfield, R. B. (2015). "Measuring the benefits of ERP on supply management maturity model: a "big data" method." International Journal of Operations & Production Management, Vol. 35, No. 1, pp. 2-25. Jan 2015. DOI: https://doi.org/10.1108/IJOPM-07-2013-0341
  20. Sheppard, B. H., Hartwick, J., & Warshaw, P. R. "The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research." Journal of Consumer Research, Vol. 15, No. 3, pp. 325-343, 1988. DOI: 10.1086/209170.
  21. Davidson, A. R., Yantis, S., Norwood, M., & Montano, D. E. "Amount of information about the attitude-behavior consistency." Journal of Personality and Social Psychology, Vol. 49, No. 5, pp. 1184-1198, 1985. DOI: https://doi.org/10.1037/0022-3514.49.5.1184.
  22. Sato, K., Viswanath, K., Hayashi, H., Ishikawa, Y., Kondo, K., Shirai, K., . . . and Kawachi, I. "Associati on between exposure to health information and mortality: Reduced mortality among women exposed to information via TV programs." Social Science and Medicine, Vol. 221, pp. 124-131, 2019. DOI: https://doi.org/10.1016/j.socscimed.2018.12.019.
  23. Mou, Y., & Lin, C. A. "Communicating food safety via the social media: The role of knowledge and emotions on risk perception and prevention." Science Communication, Vol. 36, No. 5, pp. 593-616, Sep 2014. DOI: http://dx.doi.org/10.1177/1075547014549480.
  24. Zhao, Y., Ni, Q., & Zhou, R. "What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age." International Journal of Information Management, Vol. 43, pp. 342-350, Dec 2018. DOI: https://doi.org/10.1016/j.ijinfomgt.2017.08.006.
  25. Murray, T., & Lewis, V. "Gender-role conflict and men's body satisfaction: The moderating role of age." Psychology of Men and Masculinity, Vol. 15, No. 1, pp. 40-48, Jan 2014. DOI: https://doi.org/10.1037/a0030959.
  26. Bansal, G., & Gefen, D. "The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online." Decision support systems, Vol. 49, No. 2, pp. 138-150, May 2010. DOI: https://doi.org/10.1016/j.dss.2010.01.010.
  27. Kim, S., & Kim, S. "Exploring the determinants of perceived risk of middle East respiratory syndrome(MERS) in Korea." International Journal of Environmental Research and Public Health, Vol. 15, No. 6, pp. 1 168-1179, 2018. DOI: https://doi.org/10.3390/ijerph15061168.
  28. Hansen, J. M., Saridakis, G., & Benson, V. "Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers' use of social media for transactions." Computers in Human Behavior, Vol. 80, pp. 197-206, Mar 2018. DOI: https://doi.org/10.1016/j.chb.2017.11.010.