Impact of COVID-19 on unorganized Indian retail markets

  • Received February 24, 2021;
    Accepted August 18, 2021;
    Published August 27, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.17(3).2021.08
  • Article Info
    Volume 17 2021, Issue #3, pp. 99-108
  • TO CITE АНОТАЦІЯ
  • Cited by
    3 articles
  • 2382 Views
  • 764 Downloads

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

As informal workers struggle to survive the current crisis, there is reason to believe that more strain would also be exerted on the already fragile sector in the post-crisis era. The implications of the COVID-19 outbreak for the informal economy will continue. Faced with a long crisis, the global economy would likely shrink demand for informal goods and services. The primary goal of this paper is to study consumer behavior during the pandemic, investigate government-implemented Standard Operating Procedures (SOPs) for the unorganized retail sector, and determine if consumers prefer to have goods delivered to their homes rather than visit retail stores. This paper collected information from a number of Indian customers who made unorganized retail transactions in New Delhi and NCR Region. The sample was taken from 700 citizens of New Delhi, India. The study found that product variety, digital payment, scheduling, free delivery and lower speed have a significant effect on customer behavior. In addition, SOPs do not influence consumer behavior. The main reasons for choosing a specific channel are simple availability, security, less hassle, and compliance with all laws. The pandemic led to a renewed trust in the local Kirana shop, with new clients visiting metro and non-metro shops locally. The system in Kirana has changed from physical sales to digital aviation because of the pandemic.

view full abstract hide full abstract
    • Figure 1. Regression model
    • Table 1. Respondent profile
    • Table 2. KMO and Bartlett’s Test
    • Table 3. Factor loading
    • Table 4. Reliability and validity
    • Table 5. Model fit
    • Table 6. Regression results
    • Conceptualization
      Amgad S.D. Khaled, Mohammad Ahmad Al-Omari
    • Investigation
      Amgad S.D. Khaled, Mohammad Azmi Khan
    • Methodology
      Amgad S.D. Khaled, Mosab I. Tabash, Mohammad Ahmad Al-Omari
    • Resources
      Amgad S.D. Khaled
    • Writing – original draft
      Amgad S.D. Khaled, Mohammad Ahmad Al-Omari
    • Writing – review & editing
      Amgad S.D. Khaled, Mosab I. Tabash, Mohammad Azmi Khan
    • Data curation
      Khaled Ismail Alshaketheep
    • Formal Analysis
      Khaled Ismail Alshaketheep, Mosab I. Tabash
    • Funding acquisition
      Khaled Ismail Alshaketheep, Mohammad Azmi Khan
    • Project administration
      Khaled Ismail Alshaketheep
    • Software
      Khaled Ismail Alshaketheep
    • Validation
      Khaled Ismail Alshaketheep
    • Visualization
      Khaled Ismail Alshaketheep
    • Supervision
      Mosab I. Tabash, Mohammad Azmi Khan, Mohammad Ahmad Al-Omari