E-service quality and customer loyalty in the e-commerce market, South West, Nigeria: Post-COVID-19

  • Received January 7, 2023;
    Accepted March 14, 2023;
    Published September 6, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.19(3).2023.10
  • Article Info
    Volume 19 2023, Issue #3, pp. 114-122
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In today’s fiercely competitive e-commerce arena, online service providers are compelled to focus on improving quality service delivery to remain competitive. The e-commerce market in Nigeria has experienced low patronage due to factors such as establishing cost, accessibility, credit card threat, information privacy, data security, and network reliability. Thus, the study explored the impact of quality service delivery on customer loyalty. A survey research design was used to seek information about the phenomenon of interest from the sampled respondents through an online platform, mobile device, and mail. The study used copies of the questionnaire as an instrument to gather data from 385 customers of Jumia and Konga who are engaged in e-business service delivery. The data were analyzed using SPSS version 25. The results indicated that the computed t values and the associated significant probabilities of responsiveness, privacy, fulfillment, compensation, insistence action by customers, switching restraint by customers, repeat purchase by customers, customer satisfaction and customers loyalty were 16.08 (P < 0.001), 26.33 (P < 0.001), 12.97 (P < 0.001), 6.75 (P < 0.001), 10.60 (P < 0.001), 7.35 (P < 0.001), 15.75 (P < 0.001), 13.74 (P < 0.001), and 11.92 (P < 0.001), respectively. Given the foregoing, it is evident that respondents perceive a firm’s responsiveness, privacy, and compensation to be significant at the ninety-nine percent confidence level. Furthermore, insistence action by customers, switching restraint by customers, repeat purchase by customers, customer satisfaction, and customer loyalty are perceived to be significant at the ninety-nine percent confidence level.

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    • Table 1. Significance test for independent and dependent variables
    • Table 2. Model summary
    • Table 3. ANOVA
    • Table 4. Coefficients
    • Conceptualization
      Peter Fred Ojochide, Adeniyi Mojisola Mubo, Peter Adeshola Oluwaseyi
    • Data curation
      Peter Fred Ojochide, Adeniyi Mojisola Mubo, Decster Lydia Ineba
    • Funding acquisition
      Peter Fred Ojochide, Peter Adeshola Oluwaseyi
    • Investigation
      Peter Fred Ojochide, Adeoti Sarah Bunmi
    • Writing – original draft
      Peter Fred Ojochide
    • Resources
      Adeniyi Mojisola Mubo, Peter Adeshola Oluwaseyi, Adeoti Sarah Bunmi, Decster Lydia Ineba
    • Writing – review & editing
      Adeniyi Mojisola Mubo, Adeoti Sarah Bunmi, Decster Lydia Ineba
    • Methodology
      Peter Adeshola Oluwaseyi
    • Software
      Peter Adeshola Oluwaseyi, Adeoti Sarah Bunmi
    • Project administration
      Adeoti Sarah Bunmi, Decster Lydia Ineba