Liao G, Wang J, Zhang Q, Ding X. The quality of crowdsourcing virtual community and users' voice behavior: An analysis of stimulus-organism-response framework among Chinese users.
Heliyon 2024;
10:e26881. [PMID:
38434368 PMCID:
PMC10904280 DOI:
10.1016/j.heliyon.2024.e26881]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/10/2024] [Accepted: 02/21/2024] [Indexed: 03/05/2024] Open
Abstract
The quality of a crowdsourcing virtual community is an essential factor that stimulates users' perceptions of belonging and attachment to the community, thereby influencing their behavior. As a prerequisite for the development of "creative crowdsourcing," it is particularly important to study how users' voice behavior can be promoted in virtual communities. Drawing on the Stimulus-Organism-Response (SOR) framework and the Social Identification Theory, this study developed a conceptual model that investigates the impact of crowdsourcing virtual communities in system, information, interaction, and service quality on users' voice behavior. Furthermore, we introduce community identification and self-disclosure to further analyze the influencing mechanism between these two variables. Data were collected through 672 survey questionnaires from participants in well-known crowdsourcing virtual communities such as Xiaohongshu, Bilibili, Haier Hope, Test Baidu, and Test China. Using hierarchical regression and bootstrap analysis, we found a positive correlation between the quality of the crowdsourcing virtual community and users' voice behavior, with community identification acting as a mediator. Furthermore, self-disclosure showed a significant moderating effect on the relationship between community identification and voice behavior. These findings significantly contribute to the theoretical landscape by advancing the SOR framework within a virtual community. This not only deepens the understanding of the quality of the crowdsourcing virtual community, but also provides theoretical and practical implications for managers and users on how to promote voice behavior.
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