Designing a Conceptual Model for Human Resource Performance Evaluation Indicators in the Banking Industry with Emphasis on the Fourth Industrial Revolution
Keywords:
Performance evaluation, Human resources, Fourth Industrial Revolution, Banking industryAbstract
The Fourth Industrial Revolution has not only introduced profound technological transformations but also brought about significant changes in business models and customer demands. In this context, human resources, as the most critical asset of organizations, play a key role in achieving these new objectives. Consequently, evaluating human resource performance has become one of the most crucial areas of organizational focus. This study aimed to design a conceptual model of human resource performance evaluation indicators in the banking industry, with a specific emphasis on the Fourth Industrial Revolution. The statistical population of this research was divided into two groups: fifteen subject-matter experts familiar with the research topic, and all senior, middle, and junior managers at various management levels within Bank Melli Iran. A sample of 335 individuals was selected from this population. Data were collected using three separate questionnaires. To analyze the data, fuzzy screening methods, exploratory factor analysis, and Interpretive Structural Modeling (ISM) were employed. The results of the fuzzy screening indicated that out of a total of 49 human resource performance evaluation indicators, 8 were eliminated, and 41 were confirmed by the experts. Moreover, the findings from the exploratory factor analysis showed that the 41 confirmed indicators could be categorized into seven main components. Finally, the results of the ISM phase revealed that flexibility and continuous learning constitute the foundation of the human resource performance evaluation model with an emphasis on the Fourth Industrial Revolution and are considered the most influential components within the model. In contrast, the component of quantitative and qualitative performance was identified as the most affected component in the structure of the proposed model.
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