Impact of review narrativity on sales in a competitive environment

Soumya Mukhopadhyay, V Kumar, Amalesh Sharma and Tuck Siong Chung

Production and Operations Management, 2022, vol. 31, issue 6, 2538-2556

Abstract: Online user‐generated reviews have received significant importance in the literature as they help consumers make consumption decisions. However, despite significant developments in this domain in the past decade, little attention has been paid to how narrative aspects of reviews affect consumers’ consumption decisions and, consequently, influence sales. A narrative can be defined as a sequentially structured discourse that provides an understanding of the events that unfold around the narrator. Relying on the literature on narrative transportation, we examine the role of review narrativity in determining firm sales, the contingency effect of the competitive environment, and review polarity. Specifically, we propose that review narrativity has an asymmetric U‐shaped (or, J‐shaped) relationship with sales; the impact of review narrativity on sales would have significant positive interaction with the polarity of the review text; and that under high (low) competitive agglomeration, review narrativity would have a significant (insignificant) positive impact on sales. Operationalizing review narrativity using three different measures from a unique and rich dataset collected from OpenTable and using a Bayesian framework, consistent with our hypotheses, we find that the narrativity of textual reviews exerts a significant nonlinear impact on sales contingent on their polarity. Enriching the relatively nascent empirical literature on the effects of competitive context on eWOM, the current paper further offers clear empirical evidence that the impact of review narrativity on sales is significantly higher (lower) under a high (low) competitive agglomeration. The paper makes a methodological contribution by developing a flexible framework to identify the proposed relationships better while accounting for heterogeneity, endogeneity, and temporal patterns in the context of dynamic panels.

Date: 2022
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