A Causal Configuration Analysis of Payment Decision Drivers in Paid Q&A

Wenyu Chen, Yan Cheng, Jia Li
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引用次数: 2

Abstract

Abstract Purpose This paper examines factors of payment decision as well as the role each factor plays in casual configurations leading to high payment intention under systematic and heuristic information processing routes. Design/methodology/approach Based on heuristic-systematic model (HSM), we propose a configurational analytic framework to investigate complex casual relationships between influencing factors and payment decision. In line with this approach, we use fuzzy-set qualitative comparative analysis (fsQCA) to analyze data crawled from Zhihu.com. Findings The number of previous consultations is a necessary element in all five equivalent configurations which lead to high intention in payment decision. The heuristic processing route plays a core role while the systematic processing route plays a peripheral role in payment decision-making process. Research limitations Research is limited in that moderating effect of professional fields has not been considered in the framework. Practical implications Configurations in results can assist managers of knowledge communities and paid Q&A service providers in the management of information elements to motivate more payment decision. Originality/value This paper is one of the few studies to apply HSM theory and fsQCA method with respect to the payment decision in paid Q&A.
付费问答中付费决策驱动因素的因果配置分析
摘要目的研究系统启发式信息处理路径下的支付决策因素,以及各因素在导致高支付意愿的随机配置中的作用。设计/方法/方法基于启发式系统模型(HSM),我们提出了一个配置分析框架来研究影响因素与支付决策之间复杂的因果关系。根据这种方法,我们使用模糊集定性比较分析(fsQCA)来分析从知乎网抓取的数据。调查结果以前的咨询次数是所有五种等效配置的必要因素,导致支付决策的高意愿。在支付决策过程中,启发式处理路径起核心作用,系统性处理路径起外围作用。研究的局限性在于框架中没有考虑专业领域的调节作用。结果中的配置可以帮助知识社区的管理者和付费问答服务提供商管理信息元素,以激励更多的付费决策。本文是为数不多的将HSM理论和fsQCA方法应用于付费问答支付决策的研究之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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