Determinants of customer loyalty in mobile shopping apps: Extending expectation-confirmation theory in the Indian context

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Type of the article: Research Article

Abstract
The study explores the evolving role of customer loyalty within mobile shopping applications in the context of the Indian market, where the rapid growing penetration of smart phones and mobile commerce adoption poses more challenges and opportunities to mobile commerce companies. Therefore, this study aimed to investigate the effect of confirmation, hedonic motivation, and price saving orientation on perceived usefulness, customer satisfaction, and eventually loyalty by integrating Expectation-Confirmation Theory (ECT) and Technology Acceptance Model (TAM). Data were collected through an online survey of 535 Indian smartphone users who had prior mobile shopping experience. Utilizing partial least squares structural equation modelling, this study examines the relationships among confirmation, perceived usefulness, customer satisfaction, and loyalty. The results show that perceived usefulness and satisfaction are important mediators in the confirmation of (β = 0.188, p < 0.001), hedonic motivation (β = 0.134, p < 0.001), and price-saving orientation β = 0.291, p < 0.001) towards customer loyalty. Customer satisfaction (β = 0.457, p < 0.001) was the most crucial determinant of loyalty among the predictors tested. Price-saving orientation showed significant impact on both satisfaction (β = 0.390, p < 0.001) and the perceived usefulness (β = 0.271, p < 0.001), reflecting Indian consumer’s economic nature. In contrast, hedonic motivation (β = 0.012, p = 0.389) was not significant as a predictor of satisfaction, but it had an indirect impact on loyalty via perceived usefulness, indicating the conjoined effect of emotional and utilitarian motives. These findings enhance the theoretical understanding by extending Expectation-Confirmation Theory within the context of mobile commerce and provide actionable insights for developers and marketers striving for user retention by aligning customer expectations and offering both value and enjoyment through the app.

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    • Figure 1. Conceptual model
    • Figure 2. Results of structural model
    • Figure 3. Visual representation of hypothesized relationships among latent variables using standardized scores. Subfigures 3a–3i provide scatterplots and best-fitting curves for each bivariate relationship, illustrating the strength and direction of hypot
    • Table 1. Profile of respondents
    • Table 2. Validity, reliability, and multicollinearity
    • Table 3. Discriminant validity results for the constructs
    • Table 4. HTMT ratios
    • Table 5. Model fit indices
    • Table 6. Path coefficients and p-values
    • Table 7. Direct, indirect, and total effects related to customer loyalty.
    • Conceptualization
      S. Saibaba
    • Data curation
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    • Formal Analysis
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    • Investigation
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    • Methodology
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    • Project administration
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    • Supervision
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    • Validation
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    • Visualization
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    • Writing – original draft
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    • Writing – review & editing
      S. Saibaba