Interpretive Structural Modeling of the Drivers of Non-Elite Selection in Iranian Governmental Organizations - Mohammadpour, Enayat; Zahedi, Shams Sadat; Montazeri, Mohammad (Future of Work and Digital Management Journal, 2026)
The objective of the present study is to develop an interpretive structural model of the drivers of non-elite selection in Iranian governmental organizations. This study falls within the category of mixed-methods research designs. In terms of purpose, the research is applied, and with respect to data collection, it is descriptive, employing a qualitative–quantitative approach. Initially, a list of drivers was identified through content analysis and semi-structured interviews with experts, then screened using the Delphi method, and subsequently stratified using the interpretive structural modeling (ISM) approach. The participants in the thematic analysis phase consisted of 15 academic experts and managers of governmental organizations. In the Delphi analysis and interpretive structural modeling phase, 12 academic experts and human resource managers from governmental organizations participated, who were selected using purposive sampling. The instrument used in the qualitative phase was semi-structured interviews; in the Delphi phase, an expert-based questionnaire was employed; and in the interpretive structural modeling phase, an ISM questionnaire was utilized. In this study, 15 key factors were identified and classified into six hierarchical levels: Level 1 (outcome factors: elite migration and intra-organizational distrust), Level 2 (elite-averse managerial fear and resistance to change), Level 3 (weak evaluation system, preference for personal relationships, and anti-elite managerial attitudes), Level 4 (inefficient employment structure and traditional recruitment processes), Level 5 (influence of powerful interest groups, lack of meritocracy, and centralized decision-making), and Level 6 (root factors: weak governance support, anti-elite public culture, and external political pressures). This model illustrates the causal relationships among these factors, and its innovation compared to previous studies lies in integrating internal and external factors to support comprehensive policymaking.