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There is a clear gap in the literature regarding the factors that determine social conductivity (extent of interactions) in project relationships. This study aims to use social capital theory to answer the research question – What factors determine social conductivity in project relationships?

In the study, the authors use fuzzy synthetic evaluation based on the findings from a survey of 203 project practitioners to quantify the impacts of three principal components of factors determining social conductivity in project relationships.

The study findings reveal the structural, relational and cognitive dimensions of project social capital are all significant (impact levels exceeding 3.50) for determining social conductivity in project relationships. However, the study’s main finding reveals – issues relating to the cognitive dimension of project social capital are the most critical factors determining social conductivity in project relationships (a criticality index of 4.326).

This study provides evidence of varieties of ways social capital can boost the conductivity of project relationships.

The key contributions of this study are linked to the manner in which project social capital determines social conductivity in project relationships. The findings add to previous research by extending the dimensions of the factors that increase social conductivity from relational project social capital to include two new dimensions (the cognitive and structural dimensions of project social capital).

Incipient detection of pavement deterioration (such as crack identification) is critical to optimizing road maintenance because it enables preventative steps to be implemented to mitigate damage and possible failure. Traditional visual inspection has been largely superseded by semi-automatic/automatic procedures given significant advancements in image processing. Therefore, there is a need to develop automated tools to detect and classify cracks.

The literature review is employed to evaluate existing attempts to use Hough transform algorithm and highlight issues that should be improved. Then, developing a simple low-cost crack detection method based on the Hough transform algorithm for pavement crack detection and classification.

Analysis results reveal that model accuracy reaches 92.14% for vertical cracks, 93.03% for diagonal cracks and 95.61% for horizontal cracks. The time lapse for detecting the crack type for one image is circa 0.98 s for vertical cracks, 0.79 s for horizontal cracks and 0.83 s for diagonal cracks. Ensuing discourse serves to illustrate the inherent potential of a simple low-cost image processing method in automated pavement crack detection. Moreover, this method provides direct guidance for long-term pavement optimal maintenance decisions.

The outcome of this research can help highway agencies to detect and classify cracks accurately for a very long highway without a need for manual inspection, which can significantly minimize cost.

Hough transform algorithm was tested in terms of detect and classify a large dataset of highway images, and the accuracy reaches 92.14%, which can be considered as a very accurate percentage regarding automated cracks and distresses classification.

Traditional paper-based contracts are document-intensive, insecure, susceptible to forgery and errors, detrimental to productivity improvement and require multiple intermediaries. Addressing these challenges requires computerised construction to modernise the way modern construction projects are procured with blockchain-enabled smart contracts. Smart contracts could replace paper-based contracts by improving transparency and security and automating contractual terms, processes and transacting activities. However, smart contracts are an emerging technology with limited adoption in construction projects, and the issues influencing its widespread adoption remain unclear and unexplored. Hence, this study aims at exploring and understanding the important obstacles to adoption of smart contracts in construction projects.

Using an international questionnaire survey, the study draws on experienced construction practitioners with direct involvement and knowledge in blockchain technology and smart contract initiatives and activities. Descriptive statistics and fuzzy logic techniques were used to analyse and model the quantitative survey data to establish the critical barriers to smart contracts adoption.

Organisational and external characteristics, personal characteristics and technology characteristics constitute major obstacles to the successful adoption of smart contracts. Construction practitioners’ limited knowledge of smart contracts, resistance to technology change, insufficiently digitalised construction industry and lack of or weak governmental support are critical to smart contracts adoption.

The research contributes to the body of knowledge on diffusing cutting-edge technology by advancing the understanding of practitioners’ perspectives on the primary obstacles to smart contracts adoption. Understanding the obstacles provides industry stakeholders (policymakers, leaders and practitioners) with underpinning knowledge with which to develop and implement corrective actions.

Previous studies have postulated that an advance payment system (APS) positively impacts the contractor's working capital and is paramount to ensuring an efficient and effective project cash flow process. However, scant research has been undertaken to empirically establish the cash flow performance and domino effect of APS on project and organisational performance.

The epistemological design adopted a positivist philosophical stance augmented by deductive reasoning to explore the phenomena under investigation. Primary quantitative data were collected from 504 Construction Industry Development Board (CIDB) registered contractors (within the grade bandings 1–9) in South Africa. A five-point Likert scale was utilised, and subsequent data accrued were analysed using structural equation modelling (SEM).

Emergent findings reveal that the mandatory use of an APS does not guarantee a positive project cash flow, an improvement in organisational performance or an improvement in project performance.

The ensuing discussion reveals the contributory influence of APS on positive cash flow and organisational performance, although APS implementation alone will not achieve these objectives. Practically, the research accentuates the need for various measures to be concurrently adopted (including APS) towards ensuring a positive project cash flow and improved organisational and project performance.

There is limited empirical research on cash flow performance and the domino effect of APS on project and organisational performance in South Africa, nor indeed, the wider geographical location of Africa as a continent. This study addresses this gap in the prevailing body of knowledge.

The purpose of this paper is to present a quantified model for influential factors in the collaboration process in Building Information Modelling (BIM). BIM-based Construction Networks (BbCNs), which comprise teams of specialist organisations engaged to execute BIM-related activities, have become the centrepiece of collaboration in construction projects. In BbCNs, however, a lack of effective collaboration among teams remains a major barrier to receiving the full benefits of BIM. Despite this importance, the role of influential factors in collaboration in BbCNs has remained somewhat esoteric in nature in various previous studies, in which the present study attempts to address this gap.

To develop the quantified model for collaboration in BbCNs, primary empirical data was collected from a questionnaire survey of BIM experts in the construction industry. This data was subsequently analysed through the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique using SmartPLS software as a viable and robust package for PLS-SEM analysis.

Quantification of associations to collaboration in BbCNs reveals that unlike the common beliefs espoused in previous studies on collaboration in BbCNs, the lack of BIM-related tools and technologies is no longer the key concern of effective collaboration in BbCNs. Instead, ethical and managerial factors including “ethical approaches”, “liabilities” and “BIM manager role” were found to be in need of more attention for effective collaboration in BbCNs.

Through presenting the first quantified model for collaboration in BbCNs, findings provide a point of reference for practitioners for coaching and managing teams. So too, the findings can be translated into a set of guiding principles for the world of practice for enhancing collaboration in BbCNs.

This paper makes a significant contribution to the field by quantifying the factors that impact collaboration within BbCNs settings. It meticulously assesses the degree of influence wielded by these factors and provides empirical numerical evidence to demonstrate that the lack of BIM tools and software is comparatively less concerning in fostering collaboration within BbCNs when contrasted with human-related factors. This original contribution surpasses prior qualitative evaluations by introducing a systematic framework for ranking and comparing other influential factors, thereby advancing relevant theoretical constructs into the realm of quantitative analysis.

The purpose of this paper was to first identify and then model the impact of critical success factors (CSFs) of public–private partnership (PPP) power projects.

Review of empirical literature came out with 20 CSFs which were ranked by experts and industry practitioners through a two-round Delphi questionnaire survey.

These CSFs were grouped into CSF groups (CSFGs) using component analysis, and they served as the input variables for fuzzy analysis. The six components were collaboration and transparency, guarantee and permits, socio-political support, expected profitability, technical feasibility and risk allocation (RA). Overall success index of PPP power projects in Ghana was 5.966 and showed there is high impact of CSFGs on project success. Fuzzy analysis also confirmed RA as the most significant CSFG.

The model developed can serve as a multi-dimension CSF framework that can be used as a success attainment tool for PPP power projects. For policy developers and stakeholders, the model serves as a pointer to issues which the government/public sector must focus on to attract huge investments from the private sector in the power sector.

In comparison to other countries, power generation in Sub-Sahara Africa is poor. Public–private partnership (PPP) model has become increasingly popular for addressing infrastructural challenges, especially in the power sector. The purpose of this study is to evaluate and classify the factors that influence public sector involvement in Ghanaian PPP power projects.

Using purposive and snowball sampling techniques, questionnaires were used to gather responses from experts in the PPP power sector in a two round Delphi survey. Analytical tools adopted were descriptive statistics, mean score ranking, Cronbach’s alpha and factor analysis.

The most significant factors that influence public sector involvement in PPP power projects were: achieving improved value for money; access to additional capital; increased certainty of projects; greater efficiency of project delivery services; and improved ability to deliver new infrastructure. From factor analysis, the four components were: value for money and efficiency; capital and skills; innovation and technology; and project delivery.

Government bodies in the power sector will benefit from the findings, as it would aid them develop policies that would strengthen regulatory structures as well as institutions.

Given the expansion of cities and urbanization, developing efficient and reliable transportation infrastructure, especially urban tunnels, is essential. Failure to maintain such complex construction facilities with intelligent equipment systems could result in human losses and impose huge costs on governments. Therefore, it is necessary to have practical maintenance plans and operational safety monitoring for urban tunnels, which leads to their long lifespan, increases users’ safety and reduces operation risks.

Hence, this research aims to evaluate the maintenance risks of urban tunnel lighting systems (UTLS) using a hybrid risk-based maintenance (RBM) approach. In this vein, three rounds of a fuzzy Delphi survey were conducted to consolidate the specific operation criteria and maintenance risk factors to the circumstances of Iran and UTLS. Furthermore, the fuzzy DEMATEL method was applied to determine the cause-and-effect relationships among the identified critical operation criteria. The identified risks associated with maintenance in UTLS were then analyzed and ranked using a combination of fuzzy ANP-VIKOR techniques.

The ranking of the various risks revealed that the “poor performance of switchboards in power supply due to faults in switchboard equipment” risk was ranked first, followed by the “poor performance of panels in the power supply due to unfavorable environmental conditions,” “The poor performance of panels in the power supply due to problems with switches (key failure)” and “The poor performance of panels in power supply due to burning fuses due to unauthorized current” risks. The findings of this study indicate that this hybrid maintenance method, developed as a risk-based network, provides reliability for maintaining urban tunnel lighting systems (UTLS).

It is anticipated that the findings of this research will considerably contribute to improving UTLS maintenance management while enhancing different stakeholders’ understanding of the most critical risks in maintenance, particularly toward the UTLS in Iran. An RBM management program can result in preparing and formulating policies, comprehensive guidelines or regulations for the maintenance of urban tunnels that are recommended for future research.

The purpose of the study is to demonstrate the influences of three dimensions of social capital (the structural, relational and cognitive dimensions) on five situated learning processes (institutionalization, socialization, knowledge articulation, experience accumulation and knowledge reuse) in projects.

Drawing on a cross sectional survey, data were drawn from 203 construction professionals in Ghana who have hands-on experience in managing projects. Partial least square structural equation modeling was used to conduct both confirmatory factor analysis and path analysis of the structural model of the relationship between these two constructs.

In relation to the research questions, all three dimensions of social capital have effects of the situating learning processes. However, the research’s key finding is that the relational dimension of social capital exerts much influence on the situated learning processes in projects, with the structural and cognitive dimensions of social capital exerting medium and small effects, respectively.

The study’s key finding implies that – addressing the “relational” conditioners that moderate project participants’ behaviour in social relationships is critical for increasing situated learning activity in projects. These must, however, be complemented by both structural and cognitive factors.

The research findings expand existing frontiers of knowledge by addressing the gap in the literature on the lack of practical demonstration of the influences exerted by the various dimensions of social capital on a situated learning activity in projects.

This study aims to investigate the effects of moral hazard on quality and satisfaction of public–private–partnership (PPP) construction projects in Ghana.

After undertaking a literature review, questionnaires were used to elicit responses from respondents. Population consisted of quantity surveyors, project managers, procurement officers, consultants, public agency officers involved in PPP projects, private partners and contractors. A total of 211 questionnaires were received from 250 distributed. Purposive and snowballing sampling techniques were adopted. Analytical tools were Cronbach’s alpha for testing reliability, regression, mean score ranking and relative importance index.

Reduced mutual trust and respect, poor clarity of project objectives; consequence on decision-making; less effective construction process; and increased construction risks were the significant effects of moral hazard on satisfaction of PPP construction projects. Value-based effects; manufacturer-based effects; product-based effects; user-based effects; and transcendent-based effects were the significant effects of moral hazard on quality of PPP construction projects.

Construction stakeholders involved in delivering PPP projects ought to take note of the findings and recommendations arising. Further studies should explore the effects on other project performance indicators apart from satisfaction and quality.

This paper extends knowledge in the area of exploring the effects of moral hazard on PPP project satisfaction and quality. The findings are beneficial to both academia and industry practitioners.