Abstract

Online retail sector in India has witnessed a phenomenal growth in recent times. Online shopping has also become a popular trend among the younger generation in India. Increasing number of shoppers visit online retailer websites and read online reviews before making their purchase decision. The online reviews or electronic word of mouth (eWOM) becomes an important guiding tool for the online shoppers with its intrinsic product information and evaluation characteristics. The present study aims to analyze the effects of various eWOM antecedents on online sales by considering the effects of positive and mixed-neutral eWOM (MNWOM) valence (stimuli) on sales. It also explores the role of market-level eWOM factors, such as price, on online sales of security products like antivirus software. The confirmatory bias of these factors was noted, while the elaboration likelihood model (ELL) has been used to understand the relative importance of these factors in influencing customers’ purchase decision and sales. Further, a content analysis method supplemented by a multiple regression method was used to analyze 205 real-time online sales (reviews from verified purchasers) data pertaining to popular and top-selling antivirus products taken from two leading e-commerce websites. The study contributes as a pioneering effort in the domain with the use of innovative methodology of capturing real-time online data with a subsequent kappa statistics validation. The results showed a new insightful perspective of eWOM valence and price on sales, and provided further research directions.

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