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作 者:宋伟[1] 王天宇 张学和[1] SONG Wei;WANG Tianyu;ZHANG Xuehe(School of Public Affairs,University of Science and Technology of China,Hefei Anhui 230000,China)
机构地区:[1]中国科学技术大学公共事务学院,安徽合肥230026
出 处:《北京理工大学学报(社会科学版)》2024年第1期195-207,共13页Journal of Beijing Institute of Technology:Social Sciences Edition
基 金:安徽省社会科学基金(AHSKF2021D11)。
摘 要:公共服务动机的研究不断发展繁荣,理论研究成果颇丰,是公共管理研究的前沿热点。但公共服务动机如何转化为公共服务绩效在理论机制方面尚未清晰,遑论纳入公共管理人力资源实践中。基于Apriori算法对相关主题文献进行了无监督机器学习挖掘,发现公共服务动机转化的研究不足之处。基于此,在社会认知理论视角下系统性厘清了公共服务动机、公共服务行为、公共服务绩效三者关系,打通了三者相互链接转化的逻辑框架。并以逻辑转化路径为基础,基于系统网络层面搭建起“公共服务动机—公共服务行为—公共服务绩效”三元交互发展的逻辑分析模型,以期发展和完善公共服务动机理论,从而达到将公共服务动机理论成功转化为实践的目的。The study of public service motivation has been flourishing and evolving,yielding significant theoretical advancements,making it a prominent frontier in public management research.However,the mechanisms through which public service motivation translates into public service performance remain unclear,necessitating further investigation in the realm of human resource practices in public administration.In this study,employing the Apriori algorithm,machine learning unsupervised mining on relevant literature was conducted to uncover research gaps in the transformation of public service motivation.Based on this,from the perspective of social cognitive theory,the interrelationship among public service motivation,public service behavior,and public service performance,was systematically elucidated,establishing a logical framework that explores the interconnectedness and transformation between these three constructs.Finally,based on the logical transformation pathway,a creative analytical model was constructed at systemic network level,namely the“public service motivation-public service behavior-public service performance”triadic interactive development model,which aims to further develop and refine the theory of public service motivation,facilitating successful translation of theoretical insights into practical implementation within public service contexts.
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