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Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana.

A total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model.

The model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%.

To the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.

Major maintenance projects are often regarded as maintenance activities regardless of the projects' complexity and scale. Consequently, very scarce research attention has hitherto been paid to the critical skills required when undertaking these projects. More specifically, the body of relevant knowledge is deprived of a study focusing on maintenance projects within the energy sector. In view of this shortcoming, this research aims to examine the critical project management (PM) skills required to deliver major maintenance projects within the energy sector.

Based on a quantitative research strategy, this study addressed the knowledge gap through a cross-sectional survey of professionals involved in the delivery of major maintenance projects in the United Kingdom's (UK) energy sector. Data obtained were analyzed via descriptive (e.g. frequencies, mean and standard deviation [SD]) and inferential statistical analyses (One sample t-test and exploratory factor analysis (EFA)).

Out of the 45 PM skills identified in the literature and examined by the respondents, the results obtained from the One sample t-test (based on p (1-tailed) = 0.05) showed that 37 were considered to be at least “important,” accounting for 80.4% of all the skills identified. EFA revealed a clustering of the PM skills items into seven components: “skills related to work scheduling and coordination”; “communication, risk, safety and stakeholder management skills”; “quality assurance skills”; “people management skills”; “skills related to forecasting scope and duration of outage”; “implementation of processes and time management skills” and “technical/engineering skills and experience pertaining to the outage and local site knowledge.”

This study has identified and contributed to the limited state-of-the-art skills project managers must possess to manage major maintenance projects in the energy sector successfully. The findings would be useful to organizations within the energy sector in ensuring that the organizations have suitable personnel in place to deliver major maintenance projects on the organizations' assets.

China–Pakistan Economic Corridor (CPEC) is a framework of regional connectivity in which employees have to work in a cross-cultural environment. This study has extended the leader-member exchange theory by investigating the mediating role of employee commitment (EC) between the relationship of leader-member exchange (LMX) and employee's work-related behaviors.

PLS-SEM technique was used to test the model by utilizing a multi-wave/two-source data collected from employees and their supervisors (n = 500) working in different energy projects of CPEC.

According to the results/findings, LMX has a significant positive impact on employee commitment, employee performance (EP) and open-minded discussions, but insignificant impact on innovative work behaviour (IWB). Mediating role of employee commitment was significant between the relationship of LMX with EP and open-minded discussions, but insignificant with the IWB.

The study contributes empirical evidence to understanding the leader-member exchange relationship among Chinese managers and Pakistani workers. It also contributes to the LMX theory literature by investigating the effect of LMX on followers' outcomes (employee performance, IWB, open-minded discussions) through employee commitment.

The purpose of this study is to propose an improved framework for managing Private Participation in Infrastructure ICT (PPI-ICT) projects in the context of developing countries as the requirements to manage them are different in several aspects.

The framework has been proposed based on an exhaustive literature review and statistical analysis of the PPI-ICT projects’ data set using logistic regression, F-test and student’s t-test. The proposed framework was also applied to the PPI-ICT projects.

The framework is an extension to NTCP (novelty, technology, complexity and pace) approach by including extrinsic factors such as income of the country, climate risk, religious diversity, political stability, regularity quality and control of corruption. The proposed framework was used to analyze project characteristics and their external conditions in the context of developing countries. Based on the analyses, the authors have presented a detailed set of recommendations for project managers, practitioners and governments to improve the success rate of these projects.

The major contribution of this study is the framework, which encompasses the NTCP model as well as extrinsic characteristics of PPI-ICT projects. The proposed framework is meant to assist the project managers to comprehend the project characteristics and its external environment to identify an adequate approach for managing projects successfully.

The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.

The construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.

An ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.

The research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries.

This study aimed to address a gap in subcontractor management by focusing on previously unexplored complexities surrounding subcontractor management in developing countries. While past studies concentrated on selection and relationships, this study delved into how effective subcontractor management impacts project success.

This study used the Bayesian Network analysis approach, through a meticulously developed questionnaire survey refined through a piloting stage involving experienced industry professionals. The survey was ultimately distributed among participants based in Accra, Ghana, resulting in a response rate of approximately 63%.

The research identified diverse components contributing to subcontractor disruptions, highlighted the necessity of a clear regulatory framework, emphasized the impact of financial and leadership assessments on performance, and underscored the crucial role of main contractors in Integrated Project and Labour Cost Management with Subcontractor Oversight and Coordination.

Previous studies have not considered the challenges subcontractors face in projects. This investigation bridges this gap from multiple perspectives, using Bayesian network analysis to enhance subcontractor management, thereby contributing to the successful completion of construction projects.

Demand for private investment in infrastructure, notably in the power sector remains high, and this is anticipated to expand with the passage of time. Very little research currently exists on the power sector and specifically the private sector influencing factors (PSIFs) for entering into public–private partnerships (PPPs). The purpose of this study is to explore influencing factors for private sector participation in PPP power projects in Ghana.

Using purposive and snowball sampling techniques, questionnaires were used to gather responses from experts in the PPP power sector domain in a two-round Delphi survey. Reliability analysis was conducted using Cronbach’s alpha coefficient and level of agreement tested using Kendall’s concordance. Mean score ranking, analysis of variance (ANOVA) and Chi-square test were the main analysis conducted on the influencing factors.

The most significant PSIFs were: obtaining of investment support; improvement in private sector’s international image; synergy with public sector; sharing of risks; and gaining of profits. From ANOVA results, all the influencing factors had no significant different perception between the number of years in PPP practice and the motivations for the private sector entering into PPP power projects. Using Chi-square, the association between the variables indicated they were statistically significant.

The findings in this study are significant for multinational power generation firms that seek to enter the Ghanaian energy sector to help fill the generation gap and deficit.

The output of this research contributes to the checklist of influencing factors for private sector participation in PPP power projects and enhances the development of PPP practice.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

The purpose of the article is to identify relevant criteria for decision support in the implementation of waste-to-energy (WtE)-based systems.

The methodology is a simple case study with a qualitative approach. Five experts involved in the project of a thermoelectric power plant qualitatively evaluated, on a Likert scale, a decision model with 15 indicators derived from recent studies. The research object was the first stage of a project to implement a thermoelectric plant employing municipal solid waste (MSW) in southern Brazil.

The study identified 15 criteria supporting the decision-making process regarding WtE implementation for MSW in a mid-sized city in southern Brazil. The study identified that compliance with MSW legislation, compliance with energy legislation, initial investment and public health impact are the most influential criteria. The study offered two models for decision processes: a simplified one and a complete one, with ten and fifteen indicators, respectively.

The study concerns mid-sized municipalities in southern Brazil.

Municipal public managers have now a methodology based on qualitative evaluation that admits multiple perspectives, such as technical, economic, environmental and social, to support decision-making processes on WtE technologies for MSW.

MSW management initiatives can yield jobs and revenues for vulnerable populations and provide a correct destination for MSW, mainly in developing countries.

The main originality is that now municipal public decision-makers have a structured model based on four constructs (technical, economic, environmental and social) deployed in 15 indicators to support decision-making processes involving WtE and MSW management.

This paper seeks to understand kaizen in practice as it travels through time and space in the organisational setting.

A qualitative case study was carried out at a multinational company using mainly interviews for the data collection that were analysed from an actor-network theory (ANT) perspective.

This paper finds that the company deals with a series of paradoxes while managing the kaizen process. Efficiency and quality paradoxes are the basis for starting kaizen projects. Furthermore, intrinsic, and extrinsic motivation, emerge in these processes, and paradoxes relate to how spontaneous ideas emerge in a deliberated context of cost-saving objectives. The supply chain finance team coordinates kaizen projects with the collaboration of plant managers, promoting the paradox of autonomy and control. In addition, as kaizen mobilises and enrols the actors, some trials of strength emerge, showing actors who oppose the kaizen network and create competing networks that mutually exist in the firm.

This study presents valuable insights for professionals to successfully implement kaizen methodologies that take advantage of developing a network for problem-solving in organizations.

This study highlights the supply chain finance team's role in enrolling the actors within a network built by practitioners engaged in kaizen projects. Usually, engineers, quality, or manufacturing teams lead kaizen projects, and only occasionally, accounting and financial teams participate, including multidisciplinary teams.