The influence of social Q&A systems on consumers' purchase intention: an empirical study based on Taobao's “Ask Everyone”

信息系统 可靠性 一致性(知识库) 答辩人 感知 价值(数学) 社会影响力 社会化媒体 独创性 信息质量 实证研究 社会制度 结构方程建模 营销 计算机科学 心理学 业务 社会心理学 万维网 数学 统计 人工智能 神经科学 机器学习 政治学 法学 电气工程 创造力 工程类
作者
Ruiqian Yang,Shizhong Ai,Na Li,Rong Du,Weiguo Fan
出处
期刊:Information Technology & People [Emerald Publishing Limited]
卷期号:36 (2): 477-499 被引量:6
标识
DOI:10.1108/itp-10-2019-0568
摘要

Purpose Social question and answer (Q&A) systems have been rapidly developed on many e-commerce websites. The purpose of this paper is to explore how social Q&A systems influence consumers' information processing and purchase intention. Design/methodology/approach The authors design this research based on the information adoption model (IAM). First, the auhors consider the impacts of the central route (information factor) and peripheral route (social factor) on consumers' perception of information usefulness in Q&A systems. Then, the authors verify the influence of information and social aspects on purchase intention and empirically test the model with structural equation modelling (SEM) using 428 effective data samples. Findings On the whole, the authors prove that purchase intention is influenced by information and social aspects, which are two paths in Q&A systems. Specifically, both answer quality and social presence positively influence information usefulness. Interestingly, respondent credibility and answer consistency do not significantly impact information usefulness. Moreover, information usefulness positively affects information adoption, which positively affects consumer purchase intention. Practical implications This paper provides insights on social Q&A system mechanism design. Originality/value First, this paper is a useful complement to the research on social Q&A systems on e-commerce websites. Second, the authors provide a new theoretical lens through which the impacts of social Q&A systems on e-commerce websites are understood by extending the IAM. Third, the authors add answer consistency into original information process routes, which obtains a finding that is different from those of prior research.

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