Volume 18, Issue 1 (1-2026)                   jorar 2026, 18(1): 3-7 | Back to browse issues page

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Khoundabi B, Mahmoudi B, Emamian M, Khalafi M, Gholami S. Cluster Analysis of Iranian Provinces Based on Islamic Work Ethics, Organizational Commitment and Job Satisfaction among Aid Workers of the Red Crescent Society. jorar 2026; 18 (1) :3-7
URL: http://jorar.ir/article-1-1069-en.html
Iran Helal Institute of Applied Science and Technology, Iranian Red Crescent Society, Tehran, Iran
Abstract:   (12 Views)
INTRODUCTION: Islamic work ethics constitute a fundamental component of organizational culture within relief organizations. Higher levels of work ethics appear to promote both organizational commitment and job satisfaction among aid workers. Examining inter-provincial variations in these indicators may provide strategic insights for human resource policymaking and performance enhancement within the Iranian Red Crescent Society (IRCS).
METHODS: A cross-sectional study was conducted among aid workers of the IRCS across all provinces of Iran in 2024. Islamic work ethics, organizational commitment, and job satisfaction were assessed using validated and widely applied standardized questionnaires including: Golparvar and Nadi Islamic work ethics (2011), Allen and Meyer organizational commitment (1993), and Brayfield and Rothe job satisfaction (1951). K-means clustering was employed to identify distinct provincial groupings based on aggregated mean scores for each indicator at the provincial level. The optimal number was determined through iterative model testing and evaluation of clustering stability.  
FINDINGS: The findings indicated that among the 3,399 respondents, 2,221 (65.3%) were male and 1,178 (34.7%) were female, with a mean age of 36.9 years. The mean scores for Islamic work ethics, organizational commitment, and job satisfaction were 4.23 ± 0.42, 3.54 ± 0.40, and 3.82 ± 0.40, respectively. Based on the inflection point of the elbow plot and the K-means clustering results such as Purity index equals to 0.73, a three-cluster solution was identified as the most appropriate classification. Cluster 1 comprised 12 provinces with moderate levels across all three indicators. Cluster 2 included 9 provinces and demonstrated the highest overall scores, whereas Cluster 3 consisted of 8 provinces and exhibited the lowest levels across all indicators.
CONCLUSION: According to the results, the three clusters were labeled as Moderate (Cluster 1), High (Cluster 2), and Developing (Cluster 3) to reflect their relative performance across the three indicators. The hypothesis is that provinces located in the high cluster have more effective management and more supportive work environments. In contrast, provinces located in the developing cluster need targeted interventions to strengthen employee engagement and improve organizational outcomes.
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