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Market segmentation of online shoppers: a Bayesian approach

Author

Listed:
  • Manit Mishra
  • Snigdha Mohapatra

Abstract

Trust among online shoppers is an essential prerequisite for a flourishing e-retail. This study identifies trust-based segments among online shoppers in India. The antecedent constructs of trust in e-retailing context are theorised and a response-based segmentation is carried out using Bayesian latent structure regression (BLSR) with variable selection. BLSR is run on survey response from 263 respondents to extract the segments. The findings are validated by a focus group discussion involving 12 online shoppers. The study makes four unique contributions. First, there are no universal drivers of trust in e-retail. Second, Indian online shoppers can be segmented based on trust into - 'inner-directed' and 'outer-directed' shoppers. Third, trust levels of inner-directed shoppers are influenced by their technology-savvy characteristics and brand knowledge. And fourth, trust levels of outer-directed shoppers are shaped by e-retailer's care. The findings provide e-retailers with segment-level, strategic market interventions for trust formation among online shoppers.

Suggested Citation

  • Manit Mishra & Snigdha Mohapatra, 2023. "Market segmentation of online shoppers: a Bayesian approach," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 32(1), pages 81-96.
    • Handle: RePEc:ids:ijbire:v:32:y:2023:i:1:p:81-96
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