Impacts of User Personality Traits on Their Contributions in Idea Implementation: A Moderated Mediation Model

开放的体验 尽责 五大性格特征 人格 心理学 调解 知识管理 特质 激励 社会心理学 计算机科学 认知心理学 社会学 外向与内向 微观经济学 经济 社会科学 程序设计语言
作者
Xuejiao Mi,Huiying Zhang,Fei Qu
出处
期刊:Behavioral sciences [MDPI AG]
卷期号:14 (3): 210-210 被引量:2
标识
DOI:10.3390/bs14030210
摘要

In the realm of open innovation, users have emerged as a significant external source of innovation that enterprises cannot afford to overlook. Implemented ideas play a pivotal role in driving the iterative innovation of products within enterprises. However, the existing literature still lacks an exploration of specific impact mechanisms on contributions in idea implementation. This study presents a model that delineates the impact of user personality traits on idea implementation contributions, drawing upon theories such as personality trait theory, user engagement perspective, and trait activation theory. Empirical research was carried out by utilizing user data obtained from the Chinese high-tech company Xiaomi’s MIUI community. Personality trait indicators were developed through the application of text mining and machine learning techniques. To evaluate the models, a negative binomial regression model, which is well-suited for handling discrete data, was employed. The findings of this study indicate that user openness and conscientiousness positively influence their idea implementation contribution, whereas neuroticism has a negative impact on implementation contribution. Additionally, it is observed that user engagement plays a partial mediating role in the relationship between openness, conscientiousness, neuroticism, and idea implementation contribution. Community incentives can positively moderate the impact of user engagement on the relationship between conscientious personality and idea implementation contribution. This study expands the analysis of the impact mechanism of user idea implementation contributions, which has important theoretical guidance and practical implications for accurately identifying leading users in open innovation communities and enhancing user innovation contributions.
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