Browse by author
Lookup NU author(s): Professor Matthew GortonORCiD, Dr Gu Pang
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
Purpose: To understand how users of online marketplaces process market signals in their decision making and whether this depends on if the good is of high or low involvement. Design/methodology/approach: The paper employs a mixed methods approach. Study 1 draws on an analysis of interviews with online marketplace users using hypothetical eBay purchases as stimuli, understanding how users conceptualize specific market signals and whether their importance varies depending on the type of purchase (high versus low involvement good). Study 2 tests hypotheses derived from signaling theory, using an eye tracking experiment. Findings: Price and photographs act as “fast and frugal” signals for inclusion in consideration sets for low involvement purchases, but consumers deem them insufficient for high involvement purchases where high-cost signals that help establish seller credibility are far more salient. Users pay relatively greater attention to costly market signals, which are beyond sellers’ direct control, for high involvement goods. Practical implications: The paper offers insights for sellers regarding the presentation of quality cues and strategies online marketplaces can employ to reduce information asymmetry. Originality/value: Drawing on and extending signaling theory, the paper introduces and confirms hypotheses for understanding users’ attention to market signals when making purchase decisions on online marketplaces. It identifies how the degree of involvement of a product affects the processing of market signals:
Author(s): Gorton M, Marek-Andrzejewska E, Pang G, Andrzejewski W, Lin Y
Publication type: Article
Publication status: Published
Journal: Electronic Commerce Research and Applications
Year: 2024
Volume: 65
Print publication date: 01/05/2024
Online publication date: 18/03/2024
Acceptance date: 15/03/2024
Date deposited: 03/04/2024
ISSN (print): 1567-4223
ISSN (electronic): 1873-7846
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.elerap.2024.101382
DOI: 10.1016/j.elerap.2024.101382
Data Access Statement: Data will be made available on request.
Altmetrics provided by Altmetric
