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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.

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 Traditional visual inspection has been largely superseded by semi-automatic/automatic procedures given significant advancements in image processing.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.

This study aims to assess the usability of augmented reality (AR) based mobile app for excavation and earthmoving processes using a novel tool entitled Excavator Augmented Reality (EAR).

A mixed-methods research approach was used through conducting experimentation to collect qualitative and quantitative data collected from the Sri Lankan construction sector. EAR app was used for experimentation in outdoor areas examining how a 360° tracked hydraulic excavator can be navigated in different physical environments similar to the real prospected job.

The findings reveal that EAR could make a considerable impact on enhancing productivity, safety and training processes. However, the developed EAR App subjected to assessment demonstrated the highest satisfaction gap for the auditory aspects. Among the remaining criterion, the satisfaction met user expectations for comfortability and no-risk practice. An analysis of strengths, weaknesses, opportunities and threats (SWOT analysis) conducted revealed that visualising the excavator activities and the requirements of improved features were the highest agreed strengths and weaknesses of the EAR. Among the opportunities for improvement, the necessity of improving emergency and safety reached the highest agreement. Moreover, the study presented the challenges in introducing mobile augmented reality (MAR) to the construction sector under the political, economic, sociocultural, technological, environmental and legal (PESTEL) model along with solutions to be taken.

This study provides a novel approach to addressing the safety, productivity and training concerns in heavy mobile plants and machinery on construction sites which remains to be unexplored to this end.

The concept of working capital management (WCM) has been a fundamental financial accounting term that has evolved in financial theory for centuries. Given that the construction industry (CI) is financially dynamic, there is an imperative need to understand its WCM practices. The call for the industry players to adhere to efficient financial management practices as a result of a huge financing gap requires consented effort. This study aims to explore the trend of practices of WCM in the CI and elicit a broader polemic dialogue about this crucial theme.

The source of information for the study was secondary mainly from referenced journals and international conference papers published on WCM relating to the CI. A three-step sample selection strategy was adopted to identify the range and scope of publications on WCM in the CI based on the systematic literature review method.

The CI cannot boost of enough empirical WCM research to gain in-depth understanding of its practical trend. The developing economies are failing to produce insightful peer-reviewed papers on WCM to assist in bridging the infrastructural financing gap through apposite strategies. Gaining appropriate knowledge of the short-term financial operations through a conceptualization of WCM practices in the CI may lead to better strategies formulated for smooth operations.

This is a pioneering paper in developing economies that have taken stock of WCM knowledge of the practical trend in the CI. Future research prospects in which WCM matters can use it as a reference point.

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.

This study aims to identify the critical success factors of public private partnership (PPP) power projects in Ghana and further evaluates the most significant critical success factors (CSFs) influencing both the public and private sector participation in PPP power projects.

Ranking-type Delphi survey in two rounds was conducted to establish a comprehensive list of critical success factors of PPP power projects. Using purposive and snowball sampling techniques, experts were targeted for the Delphi survey. Mean score ranking, Cronbach’s alpha coefficient and Kendall’s concordance were used for analysis.

From the list of 37 critical success factors, 9 CSFs were deemed to be extremely significant. The five topmost CSFs were as follows: shared authority, trust and communication between public and private sectors; necessity of power project; debt guarantee to enable private partner to raise funds from the local or international financial markets; appropriate risk allocation and risk sharing; and thorough and realistic assessment of cost, projections and benefits.

The CSFs identified and prioritized in this study have the propensity to trigger policy development towards the PPP power sector in Ghana and developing countries that shares similar context. This is because the study has wide implications for financing, politics, procurement, regulations, legal and capacity building.

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.

This paper presents an historical reconstruction of the radicalisation of Alan Fox, the industrial sociologist and a detailed analysis of his early historical and sociological writing in the classical pluralist phase.

An intellectual history, including detailed discussion of key Fox texts, supported by interviews with Fox and other Biographical sources.

Fox’s radicalisation was incomplete, as he carried over from his industrial relations (IR) pluralist mentors, Allan Flanders and Hugh Clegg, a suspicion of political Marxism, a sense of historical contingency and an awareness of the fragmented nature of industrial conflict.

Recent academic attention has centred on Fox’s later radical pluralism with its “structural” approach to the employment relationship. This paper revisits his early, neglected classical pluralist writing. It also illuminates his transition from institutional IR to a broader sociology of work, influenced by AH Halsey, John Goldthorpe and others and the complex nature of his radicalisation.

The 50th anniversary of Fox's Beyond Contract and Man Mismanagement coincides with another vital contribution to the sociology of work from 1974: Braverman's Labor and Monopoly Capital. This article analyses these two scholars' complementary approaches to job design and the extent to which Fox's ideas influenced subsequent labour process thought.

The article's methodological approach is a historiographical reading of Fox and Braverman's thought in the context of their times and later scholarship.

The article demonstrates that despite some noteworthy overlap with Braverman concerning scientific management, Fox's insights were marginal to later iterations of labour process analysis. It delves into the reasons for this relative neglect, providing an understanding of the dynamics at play.

This paper's value lies in its combined industrial relations and labour process historiography. It offers a fresh perspective on Alan Fox's relationship to the latter field of study.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.