Determining the Direct and Moderator Effect of Covid-19 Risk Perception: Research Over Technology Acceptance Model Variables

Year 2021, Volume: 5 Issue: 3, 902 - 917, 18.09.2021

Safak Altay

https://doi.org/10.25295/fsecon.952399

Abstract

The Covid-19 virus, which had an impact on people’s lives, has become pandemic since its emergence in 2020 and has affected the world. During the Pandemic process, individuals try to leverage technology to avoid lagging in areas such as education and fulfill their duties. The use of technology opportunities has become a necessity due to individual preferences and risk-creating situations. This study aims to identify the ease-of-use and usability perceptions of individuals with the Technology Acceptance Model (TAM) variables for distance education systems and determine the effects of Covid-19 risk perception on these perceptions. Also, the research aims to determine whether existing risk perceptions have moderator effect between usefulness and ease of use. The research was conducted through the sample of academicians from Ardahan University which were selected from among the universities that use the distance learning system. The partial least squares structural equation modeling (PL-SEM) was used in the analysis of the data. It has been determined that the risk perception of Covid-19 has partial effects on TAM variables and has no moderator effects.

Keywords

Covid-19, Risk Perception, TAM, Moderator Effect

Covid-19 Risk Algısının Doğrudan ve Düzenleyici Etkilerinin Belirlenmesi: Teknoloji Kabul Modeli Değişkenleri Üzerinden Bir Araştırma

Abstract

İnsanların hayatları üzerinde etkileri olan Covid-19 virüsü, 2020 yılında ortaya çıktığı zamandan itibaren pandemi halini alarak bütün dünyayı etkilemiştir. Pandemi sürecinde bireyler eğitim gibi alanlarda geri kalmamak ve görevlerini yerine getirmek için teknolojilerden faydalanmaya çalışmaktadırlar. Teknoloji olanaklarının kullanımı hem bireysel tercihlerden hem de risk oluşturan durumlardan dolayı bir zorunluluk halini almıştır. Bu çalışmada bireylerin uzaktan eğitim sistemlerine yönelik Teknoloji Kabul Modeli (TAM) değişkenleri olan kullanım kolaylığı ile kullanışlılık algılarının belirlenmesi ve Covid-19 risk algısının bu algılar üzerindeki etkilerini belirlemek amaçlanmaktadır. Ayrıca mevcut risk algılarının kullanışlılık ve kullanım kolaylığı arasında düzenleyici etkisinin olup olmadığının belirlenmesi de araştırma amaçları arasında yer almaktadır. Araştırma uzaktan eğitim sistemini kullanan üniversiteler arasından seçilen Ardahan Üniversitesi akademisyenleri örneklemi üzerinden yapılmıştır. Verilerin analizinde kısmı en küçük kareler yapısal eşitlik modellemesi (PL-SEM) kullanılmıştır. Covid-19 risk algısının TAM değişkenleri üzerinde kısmı etkilerinin olduğu, düzenleyici etkilerinin ise bulunmadığı belirlenmiştir.

Keywords

Covid-19, Risk Algısı, TAM, Düzenleyici Etki

References

• Agarwal, R., and Karahanna, E. (2000). “Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage.” MIS Quarterly, 665–694.
• Al-Maroof, R. S., Salloum, S. A., Hassanien, A. E., and Shaalan, K. (2020). “Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic.” Interactive Learning Environments, 1–16. https://doi.org/10.1080/10494820.2020.1830121
• Bagozzi, R. P., and Yi, Y. (1988). “On the evaluation of structural equation models.” Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327
• Barrios, J. M., and Hochberg, Y. (2020). Risk perception through the lens of politics in the time of the covid-19 pandemic. National Bureau of Economic Research.
• Brewer, N. T., Chapman, G. B., Gibbons, F. X., Gerrard, M., McCaul, K. D., and Weinstein, N. D. (2007). “Meta-analysis of the relationship between risk perception and health behavior: The example of vaccination.” Health Psychology, 26(2), 136–145. https://doi.org/10.1037/0278-6133.26.2.136
• Bults, M., Beaujean, D. J. M. A., de Zwart, O., Kok, G., van Empelen, P., van Steenbergen, J. E., … Voeten, H. A. C. M. (2011). “Perceived risk, anxiety, and behavioural responses of the general public during the early phase of the Influenza A (H1N1) pandemic in the Netherlands: results of three consecutive online surveys.” BMC Public Health, 11(1), 1–13.
• Carter, L., and Bélanger, F. (2005). “The utilization of e‐government services: citizen trust, innovation and acceptance factors.” Information Systems Journal, 15(1), 5–25.
• Cassel, C., Hackl, P., and Westlund, A. H. (1999). “Robustness of partial least-squares method for estimating latent variable quality structures.” Journal of Applied Statistics, 26(4), 435–446. https://doi.org/10.1080/02664769922322
• Chen, H.-R., and Tseng, H.-F. (2012). “Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan.” Evaluation and Program Planning, 35(3), 398–406. https://doi.org/https://doi.org/10.1016/j.evalprogplan.2011.11.007
• Chin, W. W. (1998). “The partial least squares approach to structural equation modeling.” Modern Methods for Business Research, 295(2), 295–336.
• Cori, L., Bianchi, F., Cadum, E., and Anthonj, C. (2020). “Risk Perception and COVID-19.” International Journal of Environmental Research and Public Health, 17(9), 3114. https://doi.org/10.3390/ijerph17093114
• Davis, F. D. (1989). “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
• 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
• Groot, S. (2018). Effect of perceived risks, naturalness, usefulness and ease of use on the consumer acceptance of 3D food printing.
• 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.
• Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). “A new criterion for assessing discriminant validity in variance-based structural equation modeling.” Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
• Humayoun, M. S. A. A., and Khan, Z. (2010). “Risk perception and adoption of technology: An empirical study of personal computer use for Pakistani managers.” African Journal of Business Management, 4(14), 3080–3085.
• Huynh, T. L. (2020). “The COVID-19 risk perception: A survey on socioeconomics and media attention.” Econ. Bull, 40(1), 758–764.
• İKÇÜ. (2021). “İKÇÜ Üniversite Bilgi Yönetim Sistemi.” Accessed Tarihi: February 17, 2021, https://ikcuubys.ikcu.edu.tr/
• Iriani, S. S., and Andjarwati, A. L. (2020). “Analysıs of perceıved usefulness, perceıved ease of use, and perceıved rısk toward onlıne shoppıng ın the era of covıd-19 pandemıc.” Systematic Reviews in Pharmacy, 11(12), 313–320.
• Kamal, S. A., Shafiq, M., and Kakria, P. (2020). “Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM).” Technology in Society, 60, 101212. https://doi.org/10.1016/j.techsoc.2019.101212
• Long, N. N., and Khoi, B. H. (2020). “The Intention to Study Using Zoom During the SARS-CoV-2 Pandemic.” International Journal of Emerging Technologies in Learning (IJET), 15(21), 195. https://doi.org/10.3991/ijet.v15i21.16777
• Marco, H., Markus, B., Christian, B., Wenjiao, Z. R., Vincent, K., and René, R. (2019). “The influence of acceptance and adoption drivers on smart home usage.” European Journal of Marketing, 53(6), 1073–1098. https://doi.org/10.1108/EJM-12-2016-0794
• Paek, H.-J., and Hove, T. (2017). “Risk Perceptions and Risk Characteristics.” In Oxford Research Encyclopedia of Communication. https://doi.org/10.1093/acrefore/9780190228613.013.283
• Pal, D., and Vanijja, V. (2020). “Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India.” Children and Youth Services Review, 119. https://doi.org/10.1016/j.childyouth.2020.105535
• Perlusz, S., GattikerR, U., and Wıckramasınghe, N. (2003). “RISK AND THE ADOPTION OF NEW TECHNOLOGIES: A FIELD STUDY.” Academy of Management Proceedings, 2003(1), D1–D6. Academy of Management Briarcliff Manor, NY 10510.
• Priest, S. (2007). The British Empiricists. https://doi.org/10.4324/9780203003107 Ramírez Anormaliza, R. I., Sabaté i Garriga, F., and Llinàs Audet, F. J. (2016). “The acceptance and use of the e-learning systems among the university teachers in Ecuador.” EDULEARN16 Proceedings, 3666–3674.
• Rosa, E. A. (2003). “The logical structure of the social amplification of risk framework (SARF): Metatheoretical foundations and policy implications.” The Social Amplification of Risk, 47, 47–49.
• Saglık.gov.tr. (2020). “COVID-19 BİLGİLENDİRME SAYFASI.” Accessed Tarihi: https://covid19.saglik.gov.tr/TR-66300/covid-19-nedir-.html S eale, H., Heywood, A. E., McLaws, M.-L., Ward, K. F., Lowbridge, C. P., Van, D., and MacIntyre, C. R. (2010). “Why do I need it? I am not at risk! Public perceptions towards the pandemic (H1N1) 2009 vaccine.” BMC Infectious Diseases, 10(1), 99. https://doi.org/10.1186/1471-2334-10-99
• Sjöberg, L., Moen, B.-E., and Rundmo, T. (2004). “Explaining risk perception.” An Evaluation of the Psychometric Paradigm in Risk Perception Research, 10(2), 612–665.
• Slovic, P. (1990). “Perception of risk: Reflections on the psychometric paradigm.” In D. Golding & K. S. (Eds.), Theories of Risk. New York: Praeger.
• Slovic, P., and Peters, E. (2006). “Risk perception and affect.” Current Directions in Psychological Science, 15(6), 322–325.
• Thakur, R., and Srivastava, M. (2015). “A study on the impact of consumer risk perception and innovativeness on online shopping in India.” International Journal of Retail & Distribution Management.
• UCLG. (2020). Digital Technologies and the COVID19 pandemic. Accessed Tarihi: https://www.uclg.org/sites/default/files/eng_briefing_technology_final_x.pdf.
• Vargo, D., Zhu, L., Benwell, B., and Yan, Z. (2021). “Digital technology use during COVID-19 pandemic: A rapidreview.” Human Behavior and Emerging Technologies, 3(1), 13–24. https://doi.org/10.1002/hbe2.242
• WHO. (2021). “WHO Coronavirus Disease (COVID-19) Dashboard.” Accessed Tarihi: March 5, 2021, https://covid19.who.int/
• Wiederhold, B. K. (2020). “Connecting Through Technology During the Coronavirus Disease 2019 Pandemic: Avoiding ‘Zoom Fatigue.’” Cyberpsychology, Behavior, and Social Networking, 23(7), 437–438. https://doi.org/10.1089/cyber.2020.29188.bkw
• Wise, T., Zbozinek, T. D., Michelini, G., Hagan, C. C., and Mobbs, D. (2020). “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, 7(9), 200742. https://doi.org/10.1098/rsos.200742
• YÖK. (2021). “Yükseköğretim Bilgi Yönetim Sistemi.” Accessed Tarihi: April 21, 2021, https://istatistik.yok.gov.tr/
• Yuen, A. H. K., and Ma, W. W. K. (2008). “Exploring teacher acceptance of e‐learning technology.” Asia‐Pacific Journal of Teacher Education, 36(3), 229–243.