مطهره كامراني شهري

Companies' human resource management (HRM) strategies for managing people in domestic and international organizations are being incorporated with AI and other AI-based applications. The proliferation of AI-based HRM applications over the past ten years has sparked an exciting new field of research on AI's social presence, the effects of AI adoption on individual and business outcomes, and how to eva‎luate AI-enabled HRM practices. Computerized reasoning can possibly change the eventual fate of human assets executives (HRM). Scholars from various fields have contributed to AI in HRM, but there hasn't been enough cross-fertilization, which has resulted in a fragmented body of knowledge. On the other hand, in recent years, researchers have begun to pay attention to the tool known as social network analysis as a means of analyzing and researching large-scale social phenomena. The study of scientific co-authorship networks is one application of social network analysis. The goal of this study is to identify the main components of the network and look into the trends in these networks. Using indicators from social network analysis, the current study looked into the AI&HRM co-authorship network. The coauthorship network of this field, which consists of 43,789 members and 81,891 scientific collaborations, was analyzed in this study after articles related to AI&HRM published between 2000 and 2023 were extracted from the WOS citation database. Using centrality measures (degree, closeness, betweenness, and special vector), the most important members of the "AI&HRM" co-authorship network were investigated in this study. The TOPSIS method was used to identify 20 prominent researchers in this field. In addition, the keywords "AI&HRM" and the scientific cooperation network of nations, universities, and communities have been examined and described in this study.

هوش مصنوعي , مديريت منابع انساني , تحليل هم نويسندگي , تجزيه و تحليل شبكه هاي اجتماعي , اندازه گيري مركزيت

artificial intelligence , human resource management , co-Authorship , social network analysis , Centrality measure

motahareh kamrani

rahim khanizad