BACKGROUND AND OBJECTIVES: Technological advances and the expansion of its application in urban communities have led to extensive changes in conceptual dimensions, strategic importance and geographical concentration of urban services. Today, cities are at the highest level of need to use new methods and technologies of service. Utilizing the numerous capabilities of technology in the field of urban management also has tremendous consequences, and its development in the form of intelligent municipal services requires the proper management of human resources. With the advent of the Fourth Revolution and the development of a new paradigm called digital human resource management, various areas of the human resource management process, including human resource performance management, need to be revised and updated based on this approach. Therefore, the purpose of this study is to identify the factors affecting human resource performance management with emphasis on the digital city and the prioritization of factors in the Municipality of Tehran.
METHOD: This research is applied in terms of purpose, descriptive-survey in terms of method. In order to extract the research background the library method and for data collection purposes the field method, and questionnaire tools were used. After applying the selection criteria, 10 articles were selected for information extraction. After extracting the initial indicators using Delphi technique, 10 experts were interviewed. In order to analyze the data, confirmatory factor analysis and structural equations using partial least squares method have been used. The perspective of 11 employees of Municipality of Tehran using pairwise comparison questionnaire and their aggregation (with geometric mean) and analytic technique network process were performed and factors were prioritized with Super Decisions software.
RESULTS: All items had a t-statistic greater than 1.96; therefore, none of the items were removed from the model and in total, all coefficients were significant at the 95% level. The relative weight of technological factor was 0.537, organizational 0.045, behavioral 0.078 and environmental 0.340 and since IR > 0.1=0.07, then there is consistency in pairwise comparisons. With the formation of a limit super matrix through software, the values of technological factors with 0.133, organizational 0.124, behavioral 0.086 and environmental 0.071, respectively, had the first to fourth priorities for human resource performance management with emphasis on the role of digital city.
CONCLUSION: According to the obtained indicators, four factors affecting the management of human resource performance including technological, organizational, behavioral, and environmental factors were obtained. Findings from network analysis among all the factors, technological factor had the most impact and organizational factor had the least impact on human resource performance management with emphasis on the role of the digital city.
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