How e-WOM influences consumers' purchase intention towards private label brands on e-commerce platforms: investigation through IAM (Information Adoption Model) and ELM (Elaboration Likelihood Model) Models - Institut Mines-Télécom Business School Accéder directement au contenu
Article Dans Une Revue Technological Forecasting and Social Change Année : 2023

How e-WOM influences consumers' purchase intention towards private label brands on e-commerce platforms: investigation through IAM (Information Adoption Model) and ELM (Elaboration Likelihood Model) Models

Résumé

The rapid growth of technology has given rise to a form of communication unknown to the business world i.e. “electronic word of mouth” (e-WOM), which is considered to be an ideal and the most effective way of communicating. However, as e-WOM progresses online, the factors contributing may differ from those of traditional WOM. The current study attempts to analyze the effect of e-WOM on consumer's purchase intention towards private label brands (PLB) offered by the e-tailers in India. A self-executed questionnaire was the tool to survey and extract data from 437 respondents on platforms of social media. The study brings forth a new framework integrating the models- ELM (Elaborative Likelihood Model) and IAM (Information Adoption Model) along with store image to assess the consumer's PLB purchase intention. The data was analyzed with the help of Structural Equation modeling (SEM). The outcome of the research will help the managers, marketers, e-tailers on the significance of e-WOM in making appropriate strategies to attract more and more e-shoppers. Theoretical and practical implications as well as the limitations of the study are further discussed.
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Dates et versions

hal-03992649 , version 1 (16-02-2023)

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Sumit Kumar, Gyan Prakash, Bhumika Gupta, Giuseppe Cappiello. How e-WOM influences consumers' purchase intention towards private label brands on e-commerce platforms: investigation through IAM (Information Adoption Model) and ELM (Elaboration Likelihood Model) Models. Technological Forecasting and Social Change, 2023, 187, pp.122199. ⟨10.1016/j.techfore.2022.122199⟩. ⟨hal-03992649⟩
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