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Showing 3 results for Emami
Investigating the Relationship of Work-Related Rumination with Work-Family Conflict and Work-Family Enrichment
Simindokht Kalani, Mandana Katebi, Farzin Emamifar,
Volume 13, Issue 2 (Iranian Journal of Ergonomics 2025)
Abstract
Objectives: The interaction between work and family roles can result in various outcomes, including work-family conflict or enrichment. The way individuals manage the boundaries between these two domains plays an essential role in shaping the quality of this interaction, with work-related rumination being a common manifestation of role integration. The present study aimed to assess the relationship of work-related rumination with work-family conflict and enrichment.
Methods: This cross-sectional study included 330 employees from an industrial organization in Isfahan, selected via convenience sampling. Participants completed questionnaires measuring work-family conflict, work-family enrichment, work-related rumination, positive and negative work reflection, the Irritation scale, as well as the subscales of excessive commitment and Wok Obsession/Inability to Recover. Data were analyzed using stepwise regression analysis.
Results: Among the nine types of work-related rumination, cognitive Irritation (P<0.001), affective rumination (P<0.001), and negative reflection (P<0.001) predicted work-family conflict and together explained 56% of its variance. Problem-solving pondering (P<0.001), positive reflection (P<0.001), and negative reflection (P=0.003) predicted work-family enrichment and explained 12% of its variance.
Conclusion: Work-related rumination does not necessarily have a negative impact on work–family relations and may lead to different outcomes depending on its nature. Certain types of rumination may facilitate the transfer of beneficial work experiences to the family domain. These results highlight the importance of examining the consequences of specific forms of work-home integration rather than broadly rejecting any integration.

Designing a Sociotechnical Model Based on Macroergonomic Principles to Enhance Cybersecurity Resilience and Reduce Financial Risk in the Digital Banking Industry
Nabi Omidi, Mohammad Reza Omidi, Mohsen Emami, Mohammad Reza Omidi,
Volume 13, Issue 4 (Iranian Journal of Ergonomics-In Press 2026)
Abstract
Background and Objective: With the increasing expansion of digital banking, cyber threats have become a major financial and operational risk. This study aimed to design a model based on macro-ergonomic principles to strengthen cybersecurity resilience in order to reduce financial risk in the digital banking industry.

Methods: This study was conducted with a mixed approach. In the qualitative phase, 15 experts were interviewed and the data were examined with thematic analysis. In the quantitative phase, the resulting conceptual model was tested through a researcher-made questionnaire on a sample of 387 bank employees. Data analysis and evaluation of the final model were performed using structural equation modeling (SEM) in LISREL software.

Results: The qualitative analysis led to the identification of 5 main themes and 32 sub-themes that formed the dimensions of the model: technical-instrumental subsystem, human-psychological, organizational-structural, environmental-supervisory factors, and cybersecurity resilience (consequence). The results of the quantitative model test showed that the model has a good fit (CMIN/DF = 2.41, GFI = 0.92, CFI = 0.94, RMSEA = 0.061, SRMR = 0.057). All four macroergonomic dimensions had a positive and significant effect on cybersecurity resilience. Among them, the “organizational-structural subsystem” with a standardized path coefficient of 0.48 had the greatest effect and was identified as the strongest predictor.

Conclusion: The sociological-technical model based on macroergonomics provides an efficient framework for analyzing and strengthening cybersecurity resilience in digital banking; in such a way that increasing cyber resilience is expected to also help reduce financial risks. This result emphasizes the need to transition from purely technical approaches to a systemic and interactive approach between humans, technology, and organizational structure.

The Relationship Between Employees' Attitudes Toward Artificial Intelligence and Occupational Depression: The Mediating Role of Perceived Job Insecurity and Perceived Job Fit
Farzin Emamifar, Simindokht Kalani,
Volume 13, Issue 4 (Iranian Journal of Ergonomics-In Press 2026)
Abstract
Objectives: The rapid integration of artificial intelligence in workplace environments has transformed job structures, automated tasks, and altered employees’ work experiences. The present study aimed to examine the relationship between employees’ attitudes toward artificial intelligence and occupational depression, with the mediating roles of perceived job insecurity and perceived job fit.
Methods: In this descriptive–correlational study, 261 employees of the Telecommunication Company of Kerman Province were selected using convenience sampling and completed the Schepman & Rodwav (2020) Attitudes Toward Artificial Intelligence Scale, Nassasira (2020) Job Insecurity Questionnaire, Shafi Abadi and Rezaei (1997) Occupational Self-Concept Questionnaire, and Bianchi and Schonfeld (2020) Occupational Depression Inventory. The conceptual model was tested using partial least squares structural equation modeling.
Results: A positive attitude toward artificial intelligence was associated with a significant reduction in occupational depression (b=-0.12, p=0.038) decreased job insecurity (b=-0.501, p<0.001), and increased job fit (b=0.471, p<0.001). Job insecurity showed a positive relationship with occupational depression (b=0.417, p<0.001), whereas job fit showed a negative relationship (b=-0.243, p<0.001). Job insecurity (b=-0.209, p<0.001) and job fit (b=-0.114, p=0.002) mediated the relationship between attitudes toward artificial intelligence and occupational depression.

Conclusion: A positive attitude toward artificial intelligence reduces occupational depression by decreasing job insecurity and increasing job fit. The findings highlight the importance of fostering positive attitudes toward artificial intelligence through training, role redesign, and transparent communication within organizations to strengthen employees’ psychological security and perceived job fit

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