Knowledge Management in Relationship Among Abusive Management, Self-Efficacy, and Corporate Performance Under Artificial Intelligence

作     者：Li, Moye Shang, XianFa Liu, Na Pan, Xingchen Han, Fanshen 

作者机构：Minist Culture & Tourism Lab Isl Tourism Resource Data Min & Monitoring Sanya Peoples R China Gachon Univ Seongnam South Korea Liaocheng Univ Liaocheng Shandong Peoples R China Gansu Univ Polit Sci & Law Business Sch Lanzhou Gansu Peoples R China 

出 版 物：《JOURNAL OF GLOBAL INFORMATION MANAGEMENT》 (全球信息管理杂志)

年 卷 期：2022年第30卷第11期

页      面：1-26页

核心收录：

学科分类：1205[管理学-图书情报与档案管理] 12[管理学] 120501[管理学-图书馆学] 120502[管理学-情报学] 

基　　金：The Open Access Processing fee for this article was covered in full by the authors 

主　　题：Abusive Management Artificial Intelligence BP Neural Network Enterprise Performance Human-Computer Interaction Technology Knowledge Management Self-Efficacy Support Vector Machine 

摘      要：The purpose of this paper is to explore the application potential of HCI (human-computer interaction) technology under AI (artificial intelligence) in enterprise performance evaluation and the influence of abusive management and self-efficacy on enterprise performance. Guided by psychological theory, employees from a listed real estate enterprise are selected, and the research themes of abusive management, self-efficacy, and employee performance are assumed. Afterward, the employee job satisfaction and performance evaluation model and system interface based on deep learning BPNN (back propagation neural network), SVM (support vector machine) regression, and HCI are innovatively proposed. The results show that the HCI interface can be accessed accurately according to the employee s verbal instructions. BPNN model has reached the best performance at the iteration of 70 times, and all indexes have reached the expected employee satisfaction.