Exploring Latent Characteristics of Fake Reviews and Their Intermediary Role in Persuading Buying Decisions

Rahul Kumar, Shubhadeep Mukherjee, Nripendra P. Rana*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Online reviews play a significant role in shaping consumer purchase decisions. Accordingly, emergence of fake reviews has proliferated as an instrument to manipulate customers’ buying preferences. Such manifestation, however, lacks theoretical grounding and remains under researched due to two notable challenges: first, absence of conceptual underpinnings between consumers’ writing style and recommendation behavior. Second, little knowledge about the role of product characteristics underlying fake reviews and their influence on nudging product preferences. Through the lens of environmental psychology, this study uses an empirical investigation utilizing natural language processing (NLP) to uncover latent product-specific features underlying customer reviews and their impact on persuading buying preferences. As a major finding, we observe that characteristics underlying fake reviews, as opposed to genuine ones, fail to influence product recommendation or discouragement. Accordingly, we suggest firms permitting fake reviews on their portals to be aware of the limited economic advantages of such practices.

Original languageEnglish
JournalInformation Systems Frontiers
Early online date24 May 2023
DOIs
Publication statusE-pub ahead of print - 24 May 2023

Bibliographical note

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Keywords

  • E-commerce
  • Online reviews
  • Product discouragement
  • Product recommendation
  • Purchase decisions
  • Review manipulation
  • Text mining

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