Engaging consumers in multichannel online retail environment

Shekhar Singh · Sandeep Kumar Srivastava

44 citations0/0 files storedJournal of Modelling in Management

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Consumer Retail Behavior Studies Digital Marketing and Social Media Technology Adoption and User Behaviour

Abstract

Purpose With India becoming world’s second largest user of smartphones (Ming, 2017) and with more users adopting mobile devices for online shopping, Indian online retailers now have to manage mobile channel in addition to existing traditional channel (of computers). Hence, the purpose of this study is to investigate the mapping of product characteristics with individual channel capabilities and its effect on online consumer behaviour, so that e-tailers can create enhanced online shopping experience for consumers. Design/methodology/approach A comprehensive research model is developed on the basis of the knowledge gained from multichannel retailing and e-commerce literature. Then, the model is empirically tested, with primary data collected from 344 customers, using structural equation modelling. The data are collected from customers across two product categories: electronics and fashion. Findings The results reveal that perceived usefulness, perceived risk and perceived self-efficacy are important drivers of online consumer behaviour for continued usage. The multi-group analysis confirms the moderation influence of platform type for some relationships across electronics and fashion. Practical implications The findings underline the importance of multichannel complementarity across electronics and fashion. The preference of mobile devices for fashion and traditional devices such as computers for electronics provides valuable insights for online retailers towards management of multichannel e-commerce ecosystem. Originality/value In Indian context, this is the first empirical research on online multichannel retail setting, studying the impact of diverse channel formats on different product categories. The study’s findings give empirical basis to online retailers to look out for right product–channel fit strategy for engaging consumers in the long run.

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References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 1991The theory of planned behavior 1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 1977Self-efficacy: Toward a unifying theory of behavioral change.1977Self-efficacy: Toward a unifying theory of behavioral change.1988Structural equation modeling in practice: A review and recommended two-step approach.1998Principles and Practice of Structural Equation Modeling

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