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The authors investigated how emotional intelligence (EI) affects the relationship between project managers' (PMgs) expertise and experience and project success for both the team and client.

This study collected 290 valid responses from IT project managers. The results were analyzed using an ordinary least squares (OLS) regression, with Process v4.0 procedure and the Johnson-Neyman (JN) technique to assess the moderating effect of the level of EI.

Results showed that moderate levels of EI can enhance the impact of PMgs' experience on the project client, while higher levels of EI are necessary to positively impact the team. Moderate levels of EI can improve PMgs' expertise impact on the project team, increasing their effectiveness in interactions with clients and other stakeholders.

It is recommended to consider emotional intelligence alongside technical skills when selecting project managers to address emotional labor, stress, stakeholder management and agility. Providing EI training and experiential learning opportunities internally can improve project managers' emotional intelligence.

This study contributes to the literature on emotional intelligence and project management, highlighting the relationship between technical skills and emotional intelligence levels of PMgs. This research emphasizes the significance of experience and EI in project management, particularly in overseeing complex projects. Additionally, moderate levels of EI enhance PMgs' effectiveness in engaging with stakeholders closely involved in projects.

The complex interaction of politics and the economy is a critical factor for the sustainable growth and development of the construction sector (CNS). This study aims to investigate the effects of type of political administration including democracy and military on the performance of CNS using the Nigerian Construction Sector (NCS) as a case study.

A 48 year (1970–2017) time series data (TSD) on the NCS and the gross domestic product (GDP) based on 2010 constant USD were extracted from the United Nations Statistical Department database. Analysis of variance (ANOVA) and analysis of covariance (ANCOVA) models were used to analyze the TSD. The ANCOVA model includes the GDP as correlational variable or covariate.

The estimates of the ANOVA model indicate that democratic administration is significantly better than military administration in construction performance. However, the ANCOVA model indicates that the GDP is more important than political administration in the performance of the CNS. The study recommends for a new national construction policy, favourable fiscal and monetary policy, local content development policy and construction credit guaranty scheme for the rapid growth and development of the NCS.

Hitherto, little is known about the influence of political administration on the performance of the CNS. This study provides empirical evidence from a developing economy perspective. It presents the relationships and highlights recommendations for driving growth in the construction industry.