Title: The factors driving buyers to post their online feedback - ordered logistic regression analysis

Authors: Xubo Zhang; Yanbin Tu; KeKe Zhong

Addresses: School of Economics, Wuhan Polytechnic University, No. 36 Huanhu Middle Road, Dongxihu District, Wuhan, Hubei, China ' Rockwell School of Business, Robert Morris University, Moon Township, PA 15108, USA ' College of Business, Central Washington University, Lynnwood, WA 98036, USA

Abstract: Reputation is vital for sellers to survive and grow at online auction marketplaces. Positive feedback ratings from buyers help sellers build such a reputation. In this study, we explore the factors that affect feedback ratings from buyers at online auction marketplaces. We try to identify the factors related to three types of feedback (+, 0, -) posted by buyers. We also study the effects of sellers' first move to post their feedback to buyers on the counter-feedback from buyers. We find that characteristics of sellers and products, selling strategies, auction outcomes, and the first mover strategy are significantly associated with feedback posted from buyers. More specifically, sellers' first move to post their positive feedback to buyers helps them receive positive counter-feedback from buyers. Our study contributes to the literature by exploring the determinants of online feedback posted from buyers and providing empirical evidence on the effects of sellers' first mover strategy.

Keywords: online auction; buyer's feedback; first mover strategy; marketing analytics.

DOI: 10.1504/IJIDS.2025.149304

International Journal of Information and Decision Sciences, 2025 Vol.17 No.3, pp.308 - 325

Received: 15 Jul 2022
Accepted: 12 Oct 2023
Published online: 24 Oct 2025 *

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