Abstract

A help-seeking message is composed of abundant types of content; therefore, it is unsuitable for analysis by the traditional methods that assume that variables are independent of one another. To address this problem, we introduced qualitative comparative analysis (QCA) to explore the synergistic effects of help-seeking message content on online charitable behavior. Crisp-set QCA and fuzzy-set QCA were both used to analyze qualitative and quantitative data from 40 Waterdrop projects. To analyze the qualitative data, three members of our research team intensively and separately read a large number of help-seeking messages, analyzed and summarized the main content referring to previous studies on charitable donation, extracted rational appeals, positive emotions, negative emotions, moral appeals, and the economic condition as condition variables, and finally determined the coding rules collaboratively. The necessity analysis results show that moral appeals and rational appeals are necessary conditions for online charitable behavior. The sufficiency analysis results show that there are three configurations impacting online charitable behavior. This study can help inspire future studies shifting from a traditional perspective to a configuration perspective and help seekers obtain more charitable donations.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call