Project Managers Selection in the Construction Industry: Towards the Integration with Artificial Emotional Intelligence and Technology

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Abstract

Emotional intelligence (EI) comes almost automatically to humans when we respond instinctively. This basic level of intelligence tells us how to behave in certain scenarios. However, can this understanding be used with the help of technology in selecting efficient managers in the construction industry where the rate of increase in costs and delays in the construction project never ends and even increases? This conceptual paper proposes a study exploring the theory of artificial emotional intelligence in the construction industry to reduce the increase in cost and time overrun in the project using mixed-method research. The indicators of construction project management success were collected from the literature. The questionnaire was prepared for the second phase, and sample data will be collected from construction project managers nationwide through an online survey to form the new model. Finally, the data will be tested and analysed to see the relationship between construction project managers' EI and project success using artificial intelligence technology. Later, they will be validated with a group of certified project managers in an appropriate workshop. This study will conclude whether selecting an excellent project manager can be achieved with the help of artificial intelligence, characterised by emotional intelligence theory. The study will also verify if there is a significant correlation between the performance of construction project managers with elements in the EI theory by using artificial technology and the success of construction projects.

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APA

Hanafi, A. G., Nawi, M. N. M., Abdul Rahim, M. K. I., Nifa, F. A. A., Omar, M. F., & Mohamed, O. (2022). Project Managers Selection in the Construction Industry: Towards the Integration with Artificial Emotional Intelligence and Technology. Journal of Advanced Research in Applied Sciences and Engineering Technology, 29(1), 160–176. https://doi.org/10.37934/araset.29.1.160176

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