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The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews

Authors:

Sara KimAuthors Info & Claims

Electronic Commerce Research and Applications, Volume 7, Issue 4

Pages 399 - 410

https://doi.org/10.1016/j.elerap.2007.12.001

Published: 01 December 2008 Publication History

Abstract

This paper investigates one type of electronic word-of-mouth (eWOM), the online consumer review. The study considers two components of review structure: the type and the number of reviews. Using the cognitive fit theory, we show that the type of reviews can be a key moderating variable to explain the inconsistent relationship between consumer expertise and WOM in previous research. This study examines which type of reviews cognitively fits consumers with a high (low) level of expertise. Using the elaboration likelihood model (ELM), we also investigate that the effects of the type of reviews and the number of reviews. The hypotheses were tested using a 2 (levels of expertise)x2 (types of reviews)x2 (number of reviews) mixed design including two control conditions. The results show that the effect of cognitive fit (the type of reviews) on purchase intention is stronger for experts than for novices while the effect of the number of reviews on purchase intention is stronger for novices than experts. This paper delivers managerial implications for online sellers providing consumer created reviews along with advertisements.

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The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews

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Published In

cover image Electronic Commerce Research and Applications

Electronic Commerce Research and Applications Volume 7, Issue 4

December, 2008

94 pages

ISSN:1567-4223

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2008.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2008

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Cited By

Khern-am-nuai WGhasemkhani HQiao DKannan K(2024)The Impact of Online Q&As on Product SalesInformation Systems Research10.1287/isre.2023.123335:2(747-765)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1287/isre.2023.1233
Zhang CSinha AWang Y(2024)When to Target Customers for Helpful Reviews: The Evolution of Consumers’ Product Evaluations with Product ExposureInformation Systems Frontiers10.1007/s10796-023-10414-526:3(1183-1199)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10796-023-10414-5
Peng GTalaei-Khoei AYang ALiu C(2023)Valuing Your Patient's OpinionJournal of Global Information Management10.4018/JGIM.32452031:1(1-24)Online publication date: 9-Jun-2023
https://dl.acm.org/doi/10.4018/JGIM.324520
Changchit CKlaus TPham L(2023)Factors Influencing Intention to Use Online Consumer ReviewsJournal of Global Information Management10.4018/JGIM.32164231:1(1-22)Online publication date: 14-Apr-2023
https://dl.acm.org/doi/10.4018/JGIM.321642
St-Vincent Villeneuve APlaisent M(2023)Framework for Choosing a Supervised Machine Learning Method for Classification Based on Object Categories : Classifying Subjectivity of Online Comments by Product CategoriesProceedings of the 13th International Conference on Advances in Information Technology10.1145/3628454.3630041(1-5)Online publication date: 6-Dec-2023
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Meng J(2022)How Far Can the Message Go Through Online CommunicationJournal of Global Information Management10.4018/JGIM.29932330:1(1-22)Online publication date: 11-Mar-2022
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Srivastava GBag S(2022)Antecedents of Buying Behavior Patterns of E-ConsumersJournal of Electronic Commerce in Organizations10.4018/JECO.30030020:2(1-23)Online publication date: 26-Aug-2022
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Meng J(2022)The more we know, the more likely we may agree?Telematics and Informatics10.1016/j.tele.2022.10180770:COnline publication date: 1-May-2022
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Parameswaran SMukherjee PValecha R(2022)I Like My Anonymity: An Empirical Investigation of the Effect of Multidimensional Review Text and Role Anonymity on Helpfulness of Employer ReviewsInformation Systems Frontiers10.1007/s10796-022-10268-325:2(853-870)Online publication date: 5-Apr-2022
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Kundu SChakraborti S(2022)A comparative study of online consumer reviews of Apple iPhone across Amazon, Twitter and MouthShut platformsElectronic Commerce Research10.1007/s10660-020-09429-w22:3(925-950)Online publication date: 1-Sep-2022
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