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Due to the recent increase in unexpected events that negatively affect projects, the concept of resilience has grasped the attention of researchers, as risk management alone fails to address unpredicted events. This study aims to identify resilience dimensions and their designated factors and then construct a comprehensive definition for resilience in construction projects.

This paper adopted a qualitative research design through content analysis of semi-structured interviews with project engineers on behalf of their construction project; 26 interviews were analyzed via ATLAS.ti.

The results demonstrate that resilience in construction projects consists of four main dimensions: preparation, absorption, recovery and adaptation; each dimension comprises separate factors. The evidence from this study demonstrates that the resilience of the organization, project team and project manager supports the construction project when facing unpredicted or abnormal conditions.

The results of this paper will help construction project managers to enhance the resilience of their projects by providing different resilience factors.

The resilience concept in projects is novel and has limited knowledge available, especially in construction projects therefore, it requires additional comprehensive discussion and validation. The findings of this paper will serve as a cornerstone for the development of the resilience field and enrich the indigent literature on resilience in the construction industry.

The purpose of this paper is to analyze and evaluate bidding competitiveness and success rate of contractors bidding for public construction projects (PCPs). Additionally, this research determines the effect of work sector, contractor’s classification category (experience), project size and number of bidders on contractors’ bidding competitiveness, and the influence of work sector and classification category on their success rate.

The data were collected through 2,296 bidding attempts for 289 tender projects that were announced by the Government Tenders Department in Jordan between 2013 and 2016. The research uses bid competitiveness percentage (BCP) to evaluate contractors’ bidding competitiveness. Pearson correlation is used to investigate the correlation among variables. Hypothesis testing using ANOVA was conducted to evaluate the effect of the abovementioned factors on contractors’ bidding competitiveness, and their success rate.

The results of the analysis indicate that contractors’ average BCP and success rate in Jordanian PCPs are 83.8% and 13.3%, respectively. The analysis also reveals that work sector, contractor’s classification category, project size and number of bidders significantly affect contractors’ bidding competitiveness, whereas classification category and work sector do not affect bidding success rate. Therefore, experience of contractors affects their bidding competitiveness, but does not affect their success rate.

The present research uses contractors’ bidding success rate as a measure to evaluate their bidding competitiveness for PCPs. The novel model of this research can be applied in any country, after considering local regulations, to measure and evaluate contractors’ bidding competitiveness, and success rate when bidding for PCPs. Also, contractors cannot depend on their experience (i.e. classification category) or increasing bidding attempts to win bids and improve bidding success rate, rather than enhance their bidding strategy.

Cost estimating process is an important element within the project life cycle. Comprehensive information, expanded knowledge, considerable expertise, and continuous improvement are needed to obtain accurate cost estimation. The purpose of this paper is to identify the critical factors that affect accuracy of cost estimation and evaluate the degree to which these factors are important from contractors’ and consultants’ viewpoints.

Qualitative and quantitative research approaches were adopted in collecting and analyzing the data, and testing the hypotheses. Based on the literature review, a questionnaire was prepared and then was modified according to the results of face-to-face open-ended interviews conducted with 11 project managers. The final version of the questionnaire was distributed to a random sample of 265 respondents. For analyzing the collected data Kendall’s and Mann-Whitney tests were conducted.

The analysis revealed that there is a strong agreement between contractors and consultants in the ranking of the factors related to consultant, contractor, design parameters, and information. A slightly weak agreement between contractors and consultants was noted regarding the factors related to market conditions (external factors) and factors related to project characteristics. Furthermore, the results show that the top ten factors affecting the accuracy of cost estimate are clear and detail drawings and specification, pricing experience of construction projects, perception of estimation importance, equipment (cost/availability/performance), project complexity, clear scope definition, accuracy and reliability of cost information, site constraints (access, storage, services), material availability, financial capabilities of the client, and availability of database of bids on similar project (historical data).

Offers an original view of the concept of accuracy of cost estimates as it relates to the efficiency of the project relying on both literature review and empirical evidence.

The present research aims to investigate how lean project management (LPM) and agile project management (APM) affect project performance outcomes in the construction sector in Jordan. This study focuses on six key project performance outcomes, namely cost, time, quality, client satisfaction, innovation and responsiveness.

The present study employed a quantitative approach to achieve the research objectives. Accordingly, a multi-item survey questionnaire was prepared to gather data from 392 project managers from construction companies in Jordan. The study’s model showed acceptable levels regarding reliability, validity, fit indices and discriminant validity. In order to test the hypotheses of this study, path analysis was employed using Amos 24.0 software.

LPM demonstrated a remarkably high positive impact on cost performance. It also positively affected quality performance and client satisfaction. However, LPM insignificantly affected time, innovation and responsiveness performance measures. On the other hand, APM showed a notably high positive impact on innovation and responsiveness. The findings also revealed that APM positively impacted quality performance and client satisfaction. In addition, APM negatively impacted cost performance and insignificantly impacted time performance.

This study is one of the first comprehensive studies to empirically examine the impact of both LPM and APM on various project performance outcomes in the construction industry in the context of a developing country. It reveals some similarities and differences between LPM and APM with regard to their impacts on project management outcomes. The findings are expected to guide managers in selecting the appropriate project management approach based on the desired performance outcomes. Accordingly, it offers important implications for project managers in construction companies.

Though widely recognized as essential for improving work performance across various domains, self-efficacy’s specific role in managing construction workforces remains understudied. This knowledge gap restricts our ability to uncover new factors that enhance workforce management effectiveness and ultimately boost construction labor productivity (CLP). To address this, our study proposes and tests a novel model. This model explores the impact mechanism of self-efficacy on CLP by investigating the mediating role of work motivation. By delving into this crucial yet underexplored area, we aim to provide valuable insights for construction project managers and researchers alike, paving the way for more effective workforce management strategies and consequently, improved CLP.

This study utilizes a mixed-method approach, incorporating both qualitative and quantitative methodologies. Data from 112 rebar workers at five construction sites in Vietnam underwent analysis using Cronbach’s alpha, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) to examine the novel research model.

The results indicate a positive and significant association between self-efficacy and CLP. Additionally, work motivation emerged as a full mediator in the relationship between self-efficacy and CLP. Specifically, individuals with higher self-efficacy set ambitious goals and invest more effort in their pursuit, leading to increased work motivation and, ultimately, heightened productivity levels.

The significant implications of the current study extend to construction managers and policymakers alike. Construction managers can leverage the findings to devise targeted interventions aimed at enhancing the self-efficacy and work motivation of their workforce, potentially resulting in noteworthy enhancements in CLP. Policymakers, too, can benefit from these findings by formulating policies that actively support the cultivation of self-efficacy and work motivation among construction workers. Such policies have the potential to foster a more productive and efficient construction industry, aligning with the broader goals of workforce development and industry enhancement.

This study expands existing knowledge by identifying the important role of self-efficacy in work performance enhancement and the mediating role of work motivation in terms of these relationships.

Construction projects, and particularly highway infrastructures, are known to be major contributors to the socio-economic growth of developing countries. However, these types of projects are infamous for being highly risky due to the interplay of numerous risk factors. This study aims to explore the key risk factors impacting on the performance of highway infrastructure projects in Nigeria from the contextual viewpoint of key industry stakeholders.

Qualitative data was collected using semi-structured interviews. Specifically, 17 in-depth expert interviews were conducted with experienced stakeholders in the highway sector of the Nigerian construction industry. The collected data was transcribed and analysed using an established coding framework (grounded on case study approach, principles of thematic analysis and saliency analysis).

Overall, 17 key risks were identified from the data analysis process, and 6 risks were recognised as the most significant, based on the combination of prevalence of occurrence and significance of the coded information. The six top risks were: change in government, corruption, cost of construction materials, inflation, project funding issues and construction project delay. However, the first two of these risks (change in government and corruption) are politically related, which is specific and unique to the setting of Nigeria and thus might be seen as discouraging indicators that could have an impact on attracting foreign investors/contractors to Nigeria.

The study addressed the gap related with identifying context-specific risk factors impeding the performance of highway projects in Nigeria from the viewpoints of industry experts. It is expected that the findings will provide a better insight into the various risk factors and thus aid relevant policymakers to provide context-specific mitigating strategies.

This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

Construction cost management is one of the important processes that should be achieved effectively and accurately for successful project delivery. Modern-day construction cost management demands a high level of spatial skills. Augmented reality (AR) can potentially increase the stakeholders’ spatial skills as a supportive technology to traditional cost management tools and techniques. AR is a breakthrough technology that could considerably ease execution in various industries, but AR applicability in cost management has not been studied extensively. Thus, this study aims to explore the use of AR in construction cost management tools and techniques.

Data were collected using a qualitative approach consisting of two rounds of the Delphi technique. A total of 22 experts in the construction and information technology fields were interviewed using a purposive sampling technique. The manual content analysis helped analyse data.

The study identified AR features with the potential to increase the usage of cost management tools and techniques. AR can enable spatial skills (abilities, thinking and tasks) in most cost management tools and techniques. However, technical, cultural and technical and cultural barriers obstruct the use of AR in the construction industry.

The usage of AR in construction cost management tools and techniques has not been examined in detail until now. Thus, the study was developed to meet the industry needs and fill the literature gap to investigate the potential use of AR in construction cost management tools and techniques.