Perceived health risk, online retail ethics, and consumer behavior within online shopping during the COVID-19 pandemic

  • Received February 23, 2021;
    Accepted June 22, 2021;
    Published July 9, 2021
  • Author(s)
  • DOI
  • Article Info
    Volume 17 2021, Issue #3, pp. 17-29
  • Cited by
    27 articles

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The risk of virus contracting during the COVID-19 pandemic has changed consumer preference for online shopping to meet their daily needs than shopping in brick-and-mortar stores. Online shopping presents a different environment, atmosphere, and experience. The possibility of ethical violations is higher during online than face-to-face transactions. Therefore, this study was conducted to investigate the influence of perceived health risk and customer perception of online retail ethics on consumer online shopping behavior during the COVID-19 pandemic, involving seven variables, namely perceived health risk, security, privacy, non-deception, reliability fulfillment, service recovery, and online shopping behavior. The data were collected through an online survey by employing the purposive sampling technique to a consumer who has shopped online during the COVID-19 pandemic in Indonesia. 315 valid responses were obtained and analyzed through quantitative method using SEM-Amos. The results showed that perceived health risk and four variables of online retail ethics including security, privacy, reliability fulfillment, and service recovery affected online shopping behavior. Meanwhile, non-deception was found to have an insignificant effect. The coefficient value proved perceived health risk to be more dominant in influencing online shopping behavior than the variables of online retail ethics. Thus, consumers pay more concern for their health during online shopping. However, positive consumer perceptions of the behavior of online retail websites in providing services also can encourage consumers to shop online during this pandemic.

view full abstract hide full abstract
    • Figure 1. The model
    • Table 1. Demographic profile of the respondents
    • Table 2. Reliability and validity result
    • Table 3. Structural parameter estimates
    • Table A1. Questionnaire items
    • Conceptualization
      Yuniarti Fihartini, Arief Helmi, Meydia Hassan, Yevis Marty Oesman
    • Data curation
      Yuniarti Fihartini, Arief Helmi, Meydia Hassan, Yevis Marty Oesman
    • Formal Analysis
      Yuniarti Fihartini, Arief Helmi, Meydia Hassan, Yevis Marty Oesman
    • Writing – original draft
      Yuniarti Fihartini, Arief Helmi
    • Writing – review & editing
      Yuniarti Fihartini
    • Supervision
      Arief Helmi
    • Validation
      Arief Helmi, Meydia Hassan, Yevis Marty Oesman
    • Methodology
      Meydia Hassan, Yevis Marty Oesman