Identification and Hierarchical Leveling of the Components of a Meritocracy-Based Human Resource Recruitment Model Using Interpretive Structural Modeling (ISM)

Abstract

The establishment of a meritocracy system in the public sector, particularly in service-oriented institutions characterized by specific cultural and contextual requirements, necessitates a transition from traditional approaches toward indigenous and data-driven models. The present study aimed to identify and hierarchically level the components of a meritocracy-based human resource recruitment model in Qom Municipality. In terms of purpose, this study was applied, and in terms of its nature and methodology, it employed a mixed-methods (qualitative–quantitative) design with an exploratory sequential approach. In the qualitative phase, data were collected through semi-structured interviews with 15 experts in public and urban management who held doctoral degrees and had managerial experience. Interviews continued until theoretical saturation was achieved, and the data were analyzed using Braun and Clarke’s six-phase thematic analysis. In the quantitative phase, the interrelationships, causal precedence, and structural dynamics among the 16 final components were examined using Interpretive Structural Modeling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. The qualitative findings resulted in the identification of 64 basic themes, 15 organizing themes, and six overarching themes. The quantitative findings demonstrated that the components could be classified into a seven-level hierarchical structure. The variables “reforming structural and legal foundations,” “data-driven management and institutional monitoring,” “inclusion, diversity, and monitoring,” and “leadership and organizational culture” were positioned at the deepest levels of the model (Levels 6 and 7) and were identified as fundamental drivers because of their high driving power. Performance appraisal, training, and assessment-center-related components occupied the intermediate or linkage levels, whereas “design and implementation of a competency-based recruitment system,” “equality of opportunity,” and “reward and career advancement system” were positioned at the upper levels of the model as dependent and outcome variables. Achieving effective merit-based selection in Qom Municipality is therefore not merely a technical or single-factor process; rather, it requires prior revision of employment regulations, elimination of relationship-based bottlenecks, and establishment of transparent, data-driven systems, which should subsequently be complemented through multidimensional assessment centers and integration with retention and succession-planning cycles. The proposed model provides urban management decision-makers with an operational and scientific roadmap for enhancing organizational productivity and public trust.