Journal of Structural and Construction Engineering

Journal of Structural and Construction Engineering

An Investigation into the Emotional Intelligence of Construction Project Managers with Emphasis on Conflict Management in Construction Settings Using a Neural Network Approach

Document Type : Original Article

Authors
1 Master's in Construction Management, Faculty of Engineering, Department of Civil Engineering, Qa.C, Islamic Azad University, Qazvin,Iran..
2 Assistant Professor, Faculty of Engineering, Department of Civil Engineering, Qa.C, Islamic Azad University, Qazvin,Iran.
Abstract
Emotional intelligence (EI) in construction project managers refers to a set of cognitive and behavioral skills that enable them to recognize, understand, regulate, and constructively manage their own emotions and those of others in complex and high-pressure project environments. The importance of EI in improving project management performance, particularly in handling crises and conflicts, has gained increasing attention in construction management research and practice.

This study investigates the effect of EI on conflict management strategies among construction project managers using an Artificial Neural Network (ANN) modeling approach. Data were collected through two standardized instruments: the Petrides and Furnham Emotional Intelligence Questionnaire (2006) and the Robbins Conflict Management Styles Questionnaire (1994). The study population comprised managers actively involved in decision-making and conflict resolution in construction projects. Using convenience sampling, 30 experienced managers were selected. Data analysis and modeling of relationships between EI components and conflict management styles were conducted in MATLAB. The ANN model consisted of four hidden layers with 18 neurons each, enabling accurate simulation of nonlinear relationships among variables.

Results showed that higher EI levels, particularly in emotional regulation and interpersonal skills, significantly improved the effectiveness of conflict management strategies in construction projects. The ANN model predicted EI with an overall correlation coefficient of 0.974 and a very low Mean Squared Error (MSE ≈ 2.465×10⁻⁵), indicating high reliability and generalizability. These findings suggest that the proposed analytical framework can serve as an effective tool for rapid, cost-efficient, and accurate assessment of managerial competencies, reducing organizational risks and enhancing project outcomes in the construction sector.
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  • Receive Date 27 April 2025
  • Revise Date 17 August 2025
  • Accept Date 02 September 2025