Reisi, R. and Ghoddousi, P. (2025) The influence of emotional intelligence on job satisfaction and organizational commitment in tehran's construction industry: A structural equation modeling approach. Engineering, Construction and Architectural Management, 33(5), pp. 3718-3736. ISSN 0969-9988
Abstract
Purpose – The purpose of the study was to examine the role of emotional intelligence (EI) in enhancing job satisfaction (JS) and organizational commitment (OC) among construction project employees. This research aimed to uncover the direct and indirect effects of EI on JS and OC as well as the mediating role of JS, thus contributing to a deeper understanding of the interplay between these variables within the construction industry context. Design/methodology/approach – In this study, the relationship between emotional intelligence (EI), job satisfaction (JS), and organizational commitment (OC) was evaluated in the construction projects. The total of 424 employees were invited to participate in the research through email and face-to-face methods from top-rated construction companies in Tehran, Iran. The final 362 responses were collected and analyzed using Smart PLS 3 through structural equation modeling (SEM). The results showed a significant positive effect of EI on both JS (0.945) and OC (0.925), while JS had a moderate positive impact on OC (0.073). The study also highlighted the mediating role of JS in the relationship between EI and OC, with a total indirect effect of 0.069. These findings suggest the significant role of EI in the decisive satisfaction and commitment of employees within the distinctive environment of the construction industry. Findings – The study employed a quantitative research methodology, utilizing a survey-based approach to collect data from construction project employees. Structural equation modeling (SEM) was used to analyze the relationships between EI, JS, and OC, providing robust statistical evidence on both the direct and indirect effects of EI on JS and OC. The findings revealed that EI has a significant positive effect on both JS and OC, with coefficients of 0.945 and 0.925, respectively. Additionally, job satisfaction (JS) was found to have a moderate positive impact on OC with a coefficient of 0.073. The study also highlighted the mediating role of JS in the relationship between EI and OC, with a total indirect effect of 0.069. Research limitations/implications – The research is limited to the construction industry in Tehran, Iran, which may restrict the generalizability of the findings to other regions or industries. Additionally, the study relied on self-reported measures, which could introduce bias. Practical implications – For construction companies, the findings suggest the value of developing and implementing programs aimed at enhancing employees' emotional intelligence. Such initiatives could lead to increased job satisfaction and organizational commitment, ultimately improving overall organizational performance. Social implications – Improving emotional intelligence within the workforce has broader social implications, as it can contribute to better work environments and enhanced employee well-being. A workforce that is more emotionally intelligent and satisfied is likely to experience lower turnover rates, leading to greater organizational stability. Originality/value – The results of the research demonstrated that emotional intelligence has a significant influence on organizational commitment and job satisfaction of construction project employees. Additionally, the test results indicated that all EI dimensions, including self-awareness, self-management, social awareness, and relationship management, significantly affect organizational commitment and its components, namely, continuance commitment, affective commitment, and normative commitment. EI had the greatest impact on continuance commitment. Furthermore, considering JS as a mediating factor, the results revealed a significant effect on OC.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | construction projects; emotional intelligence; job satisfaction; organizational commitment; Tehran |
| Index terms: | satisfaction, construction industry, face, program, dimension, quantitative research, work environment, bias, organizational commitment, commitment, construction company, Tehran, construction project, emotional intelligence, organizational performance, evidence, indirect effect, well-being, relationship management, structural equation modelling, turnover, stability, survey, methodology, job satisfaction |
| Subjects: | health monitoring assessment and metrics, structural engineering, organization, statistical analysis, analytical methods, production management, psychology, mental health and wellbeing, probability and distributions, Geography, management, industry analysis, research methods, evaluation and assessment methods, business management, software systems, project delivery, data collection methods, performance measurement, sociology, data analysis and analytics |
| Topics: | Human Resources, Engineering Principles, Business Strategy, Organizational Design, Health and Safety, Geographical Context, Quality Management, Research Practice, Digital Applications, Project Management |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here