Behavioral profiling in personnel management: a typological model of behavioral vectors

The paper presents a review of the literature and advances a set of propositions concerning the employees’ perceptions on the relationship between human resource management and organizational performance. The study is aimed at filling the gap in the literature on the employees’ perception regarding human resource policies and the relationship to organizational performance. Social information processing theory is used to advance the insights on how employees’ performance about human resource policies may influence the organizational performance. The review indicated that there is a positive relationship between the employees’ perceptions of human resource policies and overall performance of a given organization. A positive perception of the implemented policies influences various individual outcomes such as commitment, engagement, and satisfaction, amongst others. Shared perceptions among the employees are also considered to have a considerable impact on the organizational performance. Nevertheless, there is a need for further research to explore the relationship between human resource management and organizational performance in more detail.

The rapid digital transformation of public systems has improved interactions between governments and citizens. In Morocco, while efforts to digitalize public administration continue, the integration of artificial intelligence presents new challenges due to structural and technical limitations. This study explores the openness of Moroccan civil servants to adopting artificial intelligence solutions and examines the role of change management in facilitating this process. A quantitative approach was employed, with 129 civil servants from key ministries – Education, Finance, and Health – completing an online questionnaire. These ministries were selected due to their critical importance in the public system and their frequent interactions with citizens. Furthermore, they played a central role in the National Administrative Reform Plan (2018–2022), which emphasized digital transformation as a key pillar in advancing e-government. The collected data were analyzed using SPSS, enabling a comprehensive analysis of the factors influencing AI adoption. The findings reveal that while younger civil servants are more open to AI, over 40% of respondents pointed to insufficient digital skills as a major barrier to artificial intelligence integration. The study underscores the importance of effective change management strategies, highlighting that strong leadership and clear communication are essential in promoting artificial intelligence receptiveness and ensuring seamless integration within Morocco’s public sector.

The “new normal” era has made remote work the new standard, making the use of artificial intelligence (AI) increasingly important. Therefore, this study aims to investigate employee perceptions of change leadership in the application of AI that affects employee engagement and productivity according to the resource-based view (RBV). Of the 467 respondents who worked in the banking industry in West Sumatra province, Indonesia, only 359 met the eligibility requirements. The partial least squares (PLS) analysis shows a direct relationship between AI and employee engagement (p < 0.05) and productivity (p < 0.05), as well as employee engagement and employee productivity (p < 0.05). The effect of AI on employee productivity is mediated by employee engagement (p < 0.05), but the moderating effect provided by change leadership is not significant (p > 0.05) in increasing employee productivity. These findings will help managers create a positive work environment through the application of AI, resulting in higher employee engagement and productivity. Specifically, these findings help organizations integrate AI more effectively and provide managers with a comprehensive understanding of the considerations needed to increase productivity through employee engagement for organizational competitiveness.

Acknowledgment
The authors thank Universitas Negeri Padang for helping finish this article. We also appreciate the cooperation and support of each member.