Journalartikel

Are longer reviews always more helpful? Disentangling the interplay between review length and line of argumentation


AutorenlisteLutz, Bernhard; Pröllochs, Nicolas; Neumann, Dirk

Jahr der Veröffentlichung2022

Seiten888-901

ZeitschriftJournal of Business Research

Bandnummer144

ISSN0148-2963

eISSN1873-7978

DOI Linkhttps://doi.org/10.1016/j.jbusres.2022.02.010

VerlagElsevier


Abstract
An overwhelming majority of previous works find longer product reviews to be more helpful than short reviews. In this paper, we build upon information overload theory and propose that longer reviews should not be assumed to be uniformly more helpful; instead, we argue that the effect depends on the complexity of the line of argumentation. To test this idea, we implement state-of-the-art machine learning methods that allow us to study the line of argumentation in reviews at the sentence-level. Our empirical analysis based on a dataset of Amazon customer reviews suggests that line of argumentation and review length are closely intertwined such that longer reviews with frequent changes between positive and negative arguments are perceived as less helpful. Our work has important implications for marketing professionals and retailer platforms that can utilize our results to optimize their customer feedback systems, enhance reviewer guidelines, and include more useful product reviews.



Autoren/Herausgeber




Zitierstile

Harvard-ZitierstilLutz, B., Pröllochs, N. and Neumann, D. (2022) Are longer reviews always more helpful? Disentangling the interplay between review length and line of argumentation, Journal of Business Research, 144, pp. 888-901. https://doi.org/10.1016/j.jbusres.2022.02.010

APA-ZitierstilLutz, B., Pröllochs, N., & Neumann, D. (2022). Are longer reviews always more helpful? Disentangling the interplay between review length and line of argumentation. Journal of Business Research. 144, 888-901. https://doi.org/10.1016/j.jbusres.2022.02.010



Schlagwörter


Argumentation patternsConsumer reviewsCREDIBILITYData-driven decision-makingINFORMATION OVERLOADMODERATING ROLENatural language processingONLINE CONSUMER REVIEWSOnline word-of-mouthPRODUCT REVIEWSPurchase intentionSALESWORD-OF-MOUTH

Zuletzt aktualisiert 2025-22-05 um 14:17