چکیده مقاله
Human Resource Management HRM plays a vital role within organizations, encompassing a range of functions aimed at maximizing employee performance while aligning with overall strategic objectives The expansion of global business operations poses significant challenges for human resource management HRM , including recruiting qualified candidates, retaining talent, and providing adequate training To address these issues, this study employs Transformer Based Predictive model which can effectively capture complex patterns in sequential and textual HR data to enhance predictive analytics in HRM processes In this study, we utilize the IBM HR Analytics Employee Attrition & Performance dataset, to evaluate the effectiveness of our transformer based method The performance of our approach is compared against existing baseline methods such as RNN, LSTM, BiLSTM and CNN to demonstrate improvements in predicting employee performance, recruitment outcomes, and retention The proposed transformer based approach surpasses traditional methods by providing a deeper understanding of employee behavior and strengthening decision making processes within human resource management This study emphasizes the strategic value of advanced analytics in HRM, illustrating how data driven insights contribute to cultivating a motivated and high performing workforce, thereby enabling organizations to maintain a competitive advantage in dynamic business environments
کلیدواژهها
نویسندگان
شیوه ارجاع
Sabzevari, Amir Abbas and Torkzadeh, Vahid,1404,Transformer-Based Predictive Model for Strategic Human Resource Management: Applications in Performance, Recruitment, and Retention,1th national conference on challenges of human capital management in large scale organizations,Mashhad
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مجموعه مقالات اولین کنفرانس ملی چالش های مدیریت سرمایه انسانی در سازمان های بزرگ مقیاس23 مهر 1404 · مشهد