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Exploring the Factors That Influence Unexpected Change of E-Customer Behaviour and Perceived Cybercrime Risk during COVID-19 in Saudi Arabia

  • Ibrahim, Rehab (Department of Computer Science and Information Technology, La Trobe University) ;
  • Li, Alice (Department of Management, Sport and Tourism, La Trobe University) ;
  • Soh, Ben (Department of Computer Science and Information Technology, La Trobe University)
  • Received : 2021.12.05
  • Published : 2021.12.30

Abstract

Cybercrimes are the biggest threat that can influence the future of e-commerce, particularly in difficult times such as the COVID-19 pandemic. This pandemic has resulted in noticeable changes in e-customer behaviour represented in three types: spending rates, types of goods bought, and the number of purchasing times. Moreover, the percentage of cybercrime in many countries, including Saudi Arabia, has increased during the pandemic. The increase in the number of cybercrimes during the COVID-19 crisis and the changes in consumer behaviour shows that there is an urgent need to conduct research on the factors that have led to this. This study will explore the most significant factors that have an effect on the unexpected change of customer behaviour and cybercrime perceived risk during the COVID-19 pandemic in Saudi Arabia. The finding of the study will hopefully contribute to attempts in finding safer methods for shopping online during COVID-19 and similar crisis.

Keywords

References

  1. WHO. WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020. 2020; Available from: https://www.who.int/dg/speeches/detail/who-directorgeneral-s-opening-remarks-at-the-media-briefing-on-covid19---11-march-2020.
  2. WHO. Coronavirus disease (COVID-19) pandemic. 2020; Available from: https://www.who.int/emergencies/diseases/novelcoronavirus-2019.
  3. The Maritime Executive. The Impact of the Covid-19 Pandemic on Shipping,. 2020; Available from: https://www.maritime-executive.com/editorials/the-impactof-the-covid-19-pandemic-on-shipping.
  4. Kim, R.Y., The Impact of COVID-19 on Consumers: Preparing for Digital Sales. IEEE Engineering Management Review, 2020.
  5. Neger, M. and B. Uddin, Factors Affecting Consumers' Internet Shopping Behavior During the COVID-19 Pandemic: Evidence From Bangladesh. Chinese Business Review, 2020. 19(3): p. 91-104.
  6. Hall, M.C., et al., Beyond panic buying: consumption displacement and COVID-19. Journal of Service Management, 2020.
  7. Mckinsey&Company. The COVID-19 recovery will be digital: A plan for the first 90 days. 2020 [cited 2020 19/09]; Available from: https://www.mckinsey.com/business-functions/mckinseydigital/our-insights/the-covid-19-recovery-will-be-digital-aplan-for-the-first-90-days.
  8. Al-Moarki, F., International companies to "Riyadh": The Corona pandemic raised the demand for e-commerce, in AlRiyadh. 2020.
  9. NEWS, A. Identity theft soars during COVID-19 as scammers target government payments, superannuation. 2020; Available from: https://www.abc.net.au/news/2020-08-17/identity-theft-soars-with-coronavirus-scams-acccreports/12558622.
  10. SPA, S.P.A. COVID-19 Committee Holds 93rd Meeting. 2020; Available from: https://www.spa.gov.sa/2090514.
  11. Roca, J.C., J.J. Garcia, and J.J. De La Vega, The importance of perceived trust, security and privacy in online trading systems. Information Management & Computer Security, 2009.
  12. Chang, H.H., C.S. Fu, and H.T. Jain, Modifying UTAUT and innovation diffusion theory to reveal online shopping behavior: Familiarity and perceived risk as mediators. Information Development, 2016. 32(5): p. 1757-1773. https://doi.org/10.1177/0266666915623317
  13. Slade, E.L., et al., Modeling consumers' adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing, 2015. 32(8): p. 860-873. https://doi.org/10.1002/mar.20823
  14. Davis, F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 1989: p. 319-340.
  15. Venkatesh, V., et al., User acceptance of information technology: Toward a unified view. MIS quarterly, 2003: p. 425-478.
  16. Ganesan, S., Determinants of long-term orientation in buyer-seller relationships. Journal of marketing, 1994. 58(2): p. 1-19. https://doi.org/10.2307/1252265
  17. Al-maghrabi, T. and C. Dennis, Driving online shopping: Spending and behavioral differences among women in Saudi Arabia. International Journal of Business Science & Applied Management (IJBSAM), 2010. 5(1): p. 30-47.
  18. Al-Debei, M.M., M.N. Akroush, and M.I. Ashouri, Consumer attitudes towards online shopping: the effects of trust, perceived benefits, and perceived web quality. Internet Research, 2015.
  19. Yazdanifard, R., N.A.-H. Edres, and A.P. Seyedi. Security and privacy issues as a potential risk for further ecommerce development. in International Conference on Information Communication and Management-IPCSIT. 2011.
  20. Srikanth, V. and D.R. Dhanapal, E-commerce online security and trust marks. International Journal of Computer Engineering and Technology, 2012. 3(2): p. 238-255. https://doi.org/10.24297/ijct.v3i2a.2813
  21. Okamoto, T., J. Yatsuhashi, and N. Mizutani. Young People's Purchase Intentions in Online Flea Market. in Proceedings of the 5th Multidisciplinary International Social Networks Conference. 2018.
  22. Niranjanamurthy, M. and D. Chahar, The study of e-commerce security issues and solutions. International Journal of Advanced Research in Computer and Communication Engineering, 2013. 2(7): p. 2885-2895.
  23. Sattar, A. and T. Lorenzen, Develop a shopping mart web application, in Working group reports on ITiCSE on Innovation and technology in computer science education. 2006. p. 68-70.
  24. Almarashdeh, I., et al., The difference between shopping online using mobile apps and website shopping: A case study of service convenience. International Journal of Computer Information Systems and Industrial Management Applications, 2019. 11: p. 151-160.
  25. Liang, Y. and C. Liu, Comparison of consumers' acceptance of online apparel mass customization across web and mobile channels. Journal of Global Fashion Marketing, 2019. 10(3): p. 228-245. https://doi.org/10.1080/20932685.2019.1619469
  26. Okamoto, T., J. Yatsuhashi, and N. Mizutani. University Students' Priorities for Smartphone Applications in Online Purchasing. in Proceedings of the 4th Multidisciplinary International Social Networks Conference. 2017.
  27. Moore, T., R. Clayton, and R. Anderson, The economics of online crime. Journal of Economic Perspectives, 2009. 23(3): p. 3-20. https://doi.org/10.1257/jep.23.3.3
  28. Hunton, P., The growing phenomenon of crime and the internet: A cybercrime execution and analysis model. Computer Law & Security Review, 2009. 25(6): p. 528-535. https://doi.org/10.1016/j.clsr.2009.09.005
  29. Khan, N.A., S.N. Brohi, and N. Zaman, Ten Deadly Cyber Security Threats Amid COVID-19 Pandemic. 2020.
  30. Riek, M., R. Bohme, and T. Moore, Measuring the influence of perceived cybercrime risk on online service avoidance. IEEE Transactions on Dependable and Secure Computing, 2015. 13(2): p. 261-273. https://doi.org/10.1109/TDSC.2015.2410795