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Works procurement performance is critical to successful project delivery. However, early supplier involvement (ESI) has been touted in other industries to impact procurement performance positively. Works procurement has been attracting significant attention from major players due to poor performance characterized by poor performance, budget overruns and incompetence. Hence, the purpose of this study was to assess the impact of ESI on public works procurement performance.

Based on a thorough review of the literature for a pilot survey, the main questionnaires were administered to 103 public procurement officers. To assess the impact of ESI on public works procurement performance, three constructs that served as factors for implementing ESI and five that measure works procurement performance were validated using partial least square structural equation modelling (PLS-SEM).

The outcome of this study shows a significant positive impact of ESI on works procurement performance. This included communication, trust and supplier capabilities. The study further showed that even though cost, schedule, quality, health and safety are essential, sustainability measures are also crucial for work procurement.

The results of this study could help firms make better decisions regarding public works procurement by encouraging ESI. This will likely significantly impact the successful project delivery and preservation of sustainability and efficiency objectives.

The application of PLS-SEM analysis in this study provides insights into how ESI can impact the procurement of public works in Ghana.

This study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.

The structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.

Results indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.

This study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.

Construction material management is an important process in supporting construction operations that affect project performance. Previous studies attempt to identify factors influencing material management in different stages such as procurement, transportation and utilization. However, they lack a model to explain the relationship between influential factors and the effectiveness of material management. Therefore, this study aims to validate the variables and key factors influencing the effectiveness of material management processes.

A total of 42 variables were reviewed from literature in different stages of material management process. Survey questionnaires were used to collect data about participants' perceptions on these variables. The respondents were 200 project engineers and project managers from construction sites and offices in Vietnam. Then factor analysis techniques were undertaken to validate the structure of factor groups. Two methods of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were, respectively, performed to evaluate and verify the model's fit.

Factors influencing the effectiveness of material management were grouped into nine main factors, which are procurement issues, site conditions, planning and handling on site, industrial environments, contractual issues, quality control, suppliers and manufacturers' issues, transportation in and out site and security on site.

The paper has several implications for theory and methodology related to material management. It features influential factors in association with the material management effectiveness. Therefore, senior managers can more fully understand the errors in their works and propose timely solutions to limit the unwanted risks.

This research contributes on theoretical development on factors influencing effectiveness of material management processes. The key findings on influential factors can be applied to measure the effectiveness of material management processes.

The unitized curtain wall system (UCWS), a symbol of modern architecture, is gaining popularity among prefabricated components. Previous studies have focused on both construction technology advances and material selection strategies to facilitate the UCWS. However, the topic of client satisfaction, which drives industry development by targeting clients' demands, has gone unnoticed. Therefore, the current study aims to investigate client satisfaction with UCWS products in Hong Kong by finding its influential factors.

A systematic review was employed to first identify the influential factors. A semi-structured interview was employed to validate the reliability of the extracted factors. The machine learning algorithm Extreme Gradient Boosting (XGBoost) and the Pearson correlation were then employed to rank the importance and correlation of factors based on the 1–5 Likert scale scores obtained through a questionnaire survey.

The findings revealed that “reduction in construction time” and “reduction in construction waste” are the most important factors and have a strong positive influence on client satisfaction.

Unlike previous studies, the present study focused on a novel research topic and introduces an objective analysis process using machine learning algorithms. The findings contribute to narrowing the knowledge gap regarding client preference for UCWS products from both individual and collaborative perspectives, providing decision-makers with an objective, quantitative and thorough reference before making investments in the curtain wall management development.

The design documents are products of a process that aims to provide sufficient details to enable the contractor to efficiently implement the project at a realistic cost. Accordingly, it is expected that these design documents must be of high quality to engender the attainment of the desired project objectives. The purpose of this study is to analyze the factors that affect the quality of design documentation in construction projects in the context of a developing country.

This study used a descriptive research design involving professionals from firms offering services in areas of design and documentation, mainly architectural, quantity surveying and engineering. A total of 80 out of 84 questionnaires were received and analyzed using IBM SPSS Statistics Version 25, and a factor analysis approach was used to categorize the factors into smaller five groups.

The factors were subsequently categorized according to size, time, staff, quality and training-related factors. Collectively, large size of the project, inadequate supervision of junior design staff, low professional fees, procurement process and system, failure to adopt quality management systems and allocation or assigning of staff to more than one project at the same time have high influence (component loading of 700) in respective groups.

The reliance on data to analyze the factors of design documents in construction projects in developing economies context, using a Tanzanian exemplar, is considered a limitation. Developing countries with similar economic characteristics, procurement systems and cultural setup could benefit from the results of this study.

The study of factors affecting quality of design and documents in construction projects serves as a guide for built environment firms in Tanzania in conducting effective business and ensuring quality design documents, hence improved project performance. Understanding the nature of relationship between the design and construction teams as well as the impact of design documents on project performance is of great importance for the design teams of future projects and other decision-makers to pay attention when preparing design and related documents, especially during design stage of construction projects in developing countries.

The study contributes the knowledge by providing useful insights on the subject through a categorization of the factors affecting the quality of design documentation and exploring the nature of relationship between the design and construction teams in construction projects within a previously unexplored Tanzanian context focusing on a traditional procurement system for future improvement of project delivery, hence project success.

The nature of construction works has a negative impact on physical, mental and emotional well-being and makes it difficult for the construction industry to attack and retain its workforce. The current study seeks to integrate the current knowledge focused on work–life balance (WLB) in the industry into an understandable whole.

An interpretivist philosophical approach was adopted using a bibliometric review and a narrative review of existing studies from both Scopus and Google databases. The Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps from the bibliographic data garnered.

The study reveals that the prominent factors influencing the WLB of the construction workforce are organizational culture, salary earned, heavy workload, long working hours and inflexible working time. The recent WLB discourse is on organisational commitment, job satisfaction and workplace dynamics. While WLB areas for further exploration are job stress, safety performance, employee attrition and an ageing workforce. Meanwhile, Africa and South America are still lagging in WLB research.

The findings reported here will assist stakeholders in identifying appropriate WLB initiatives that can be used to improve the well-being of the construction workforce. Also, the gaps in knowledge for further research were highlighted.

The findings reveal current trends and a road map for future studies on WLB in construction. It also reveals prominent factors influencing the WLB of workers in the construction industry.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

This paper aims to identify the unidimensionality and reliability of 84 factors that influence the performance of construction projects and develop a confirmatory factor analysis (CFA) model.

The study adopted a deductive research approach and started by identifying the positive factors that influence construction project performance. This was followed by the modification of the identified factors. After that, a questionnaire was developed out of the factors for data collection. Exploratory factor analysis was used to establish the factor structure of the positive factors, and this was verified using CFA afterwards. A model fit analysis was performed to determine the goodness of fit of the hypothesised model, followed by the development of the confirmatory model.

The study demonstrated substantial correlation in the data, sufficient unidimensionality and internal reliability. In addition, the estimated fit indices suggested that the postulated model adequately described the sample data.

The paper revealed that performance can be enhanced if stakeholders identify and leverage the positive factors influencing performance. The paper suggests that project stakeholders, particularly government, project owners, consultants and construction firms, can improve project performance by critically examining economic and financial systems (EFS), regulation and policy-making systems (RPS), effective management practices (EMP) and project implementation strategies (PIS).

The contribution of this paper to the present literature is identifying the positive factors and developing the confirmatory factor model. The model comprised 42 positive variables under four indicators: EMP, RPS, PIS and EFS.

Several factors influence OSC adoption, but extant literature did not articulate the dominant barriers or drivers influencing adoption. Therefore, this research has not only ventured into analyzing the core influencing factors but has also employed one of the best-known predictive means, Machine Learning, to identify the most influencing OSC adoption factors.

The research approach is deductive in nature, focusing on finding out the most critical factors through literature review and reinforcing — the factors through a 5- point Likert scale survey questionnaire. The responses received were tested for reliability before being run through Machine Learning algorithms to determine the most influencing OSC factors within the Nigerian Construction Industry (NCI).

The research outcome identifies seven (7) best-performing algorithms for predicting OSC adoption: Decision Tree, Random Forest, K-Nearest Neighbour, Extra-Trees, AdaBoost, Support Vector Machine and Artificial Neural Network. It also reported finance, awareness, use of Building Information Modeling (BIM) and belief in OSC as the main influencing factors.

Data were primarily collected among the NCI professionals/workers and the whole exercise was Nigeria region-based. The research outcome, however, provides a foundation for OSC adoption potential within Nigeria, Africa and beyond.

The research concluded that with detailed attention paid to the identified factors, OSC usage could find its footing in Nigeria and, consequently, Africa. The models can also serve as a template for other regions where OSC adoption is being considered.

The research establishes the most effective algorithms for the prediction of OSC adoption possibilities as well as critical influencing factors to successfully adopting OSC within the NCI as a means to surmount its housing shortage.

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.