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Failures of public–private partnership (PPP) projects are often ascribed to the agency problem, which arise under conditions of inadequate and asymmetric information when a principal (the client) hires an agent (the contractor). This paper aims to identify the causes and effects of moral hazard and adverse selection on PPP construction projects using a synthesis of extant literature (to determine key variables) and analysis of survey questionnaire data collected.

Mean score ranking was used to rank the causes and effects of moral hazard and adverse selection problems in PPP construction projects. One sample t-test was conducted to establish the relative significance of these variables.

Effort dimensions (which are not verifiable), low transfer of risk, lack of accurate information about project conditions, wrong party chosen to execute project and renegotiation of contracts were the most significant causes of moral hazard and adverse selection problems in PPP construction projects. In addition, reduction of competition, high transaction costs, consequences on profitability of project, siphoning of funds and negative implications on enforceability of contract were the most significant effects of moral hazard and adverse selection problems in PPP construction projects.

Application of these findings will help mitigating moral hazard and adverse selection problems occurring when undertaking PPP construction projects.

Research findings provide guidance to construction stakeholders in the PPP sector on the different causes and effects of adverse selection and moral hazard. This pioneering study is the first to conduct an empirical assessment of the causes and effects of moral hazard and adverse selection of PPP construction projects in a developing country.

With the growth of entrepreneurship education adoption in higher education institutions (HEIs), the importance of assessments as a tool to gauge and enhance learning is of utmost importance. The purpose of this paper is to examine the influence and appropriateness of current assessment methods for engineering and technology students in Nigerian and British HEIs.

The study employs a qualitative research method with a case study approach to investigate the impact and suitability of assessment methods currently used within entrepreneurship education in Nigeria and England.

The results reveal that lecturers across both countries believed that assessment methods currently in use were appropriate, but were not uniform in its influence on learning. However, students were unanimous in that most assessment methods currently used were not effective at enhancing their learning, not very appropriate, and were not a good judge of their work and effort. The results were used in building a framework to understand the importance of assessment methods in entrepreneurship education.

In light of the inadequate literature, this paper covers an acute gap in the field. This will allow policymakers and different interested parties to reassess the development of suitable assessment methods to involve students as key stakeholders.

The purpose of this paper was to assess the causal relationship(s) between moral hazard and adverse selection of public–private partnership (PPP) construction projects. Structural equation modelling (SEM) was used to explore the cause and effect relationship between moral hazard and adverse selection problems in PPP construction projects in Ghana. The study produced a framework to predict, estimate and depict the complex causal relationships (i.e. the directionality) between moral hazard and adverse selection.

To test the proposed framework, a quantitative methodology was used, in which, data were collected using research questionnaires that targeted a sample of 280 PPP stakeholders in Ghana. In total, 210 useable questionnaires were retrieved, representing a response rate of 75 per cent.

The interrelationships between the eight causes and the nine effects of moral hazard and adverse selection were established using the model. The tested framework showed the degree of association and isolation of the unobserved variables on the indicator factors. Confirmatory factor analysis (CFA) was used to evaluate the fit of items to latent constructs. Because the fit of each model was good and the item loadings were adequate, it was assumed that the indicators of the different variables factors were fitting. Furthermore, a diagnostic fit analysis was conducted using the robust maximum likelihood method to test the statistical significance of the parameter estimates.

This novel research is one of the few studies investigating the causal relationships between moral hazard and adverse selection of PPP construction projects. The research concluded with future studies that seek to validate the model developed in other countries and/or other industries.

The research findings will serve as a guide for construction stakeholders in the PPP sector on the causes and effects of adverse selection and moral hazard and how to mitigate these.

The UK government has elaborated the effect of late payment on the economy, with its impact on the construction sector being particularly pronounced. This paper aims to evaluate the late payment epidemic that persists within the construction industry, specifically analysing the effectiveness of government-led voluntary payment initiatives.

A mixed philosophical lens is adopted that incorporates both pragmatism and post-positivism to examine the late payment phenomena. Couched within deductive reasoning and a case study strategy, a questionnaire survey was conducted to elicit responses from one-hundred construction professionals. Elucidating upon respondents’ perceptions of the UK’s late payment epidemic, a comparative analysis was undertaken of upstream (main contractor) and downstream (subcontractors/suppliers) contractors through Cronbach’s alpha, descriptive statistics, independence chi-square test, Kruskal–Wallis test and Mann–Whitney U test.

Emergent findings reveal that in practice, the monitoring and enforcement of government-led voluntary payment initiatives has been unprosperous with numerous contractors being forced to adopt indefensibly poor and punitive payment practices. Survey responses and extant literature substantiate and underscore the industry’s need to strengthen voluntary government-led payment initiatives. To create a responsible payment culture, any future code created should be mandatory and enforceable as a self-regulating approach has failed dismally. The work concludes with practical additional measures that could be introduced to create a responsible payment culture and promote ethical trading within the UK construction industry.

This paper constitutes a novel vignette of, and reflection upon, contemporary practice in this area of construction finance and serves to emphasise that very little has changes in the sector despite numerous UK government led reports and interventions.

The growing interest in the development of entrepreneurial intention (EI) that has increased the importance of theories that explain and anticipate the tendency among individuals to start a new business. However, most of these theories focus on the relationship between entrepreneurs perceptions and their intention and ignore the cognitive and psychological characteristics that might configure their perceptions. Therefore, the purpose of this paper is to integrate the theory of planned behaviour (TPB) with the entrepreneurial event model (EEM) and to extend the combined model to include the personality characteristics of an entrepreneur that might shape the perceptions and intentions.

This study uses a sample of 688 senior university students (Emirati nationals, 91.2 per cent and expatriates, 8.8 per cent) and employs positivist research with a quantitative approach, adopting a survey strategy through questionnaires and structural equation modelling.

The results demonstrate the relevance and robustness of the suggested combined and extended model in the prediction of intention on the part of senior university students to become entrepreneurs (explained variance=73.3 per cent) based on survey data (2017; n = 688).

The main contribution of this paper lies not only in the integration of the TPB and the EEM, but also in extending the two theories on which it is based through adding entrepreneurial personality characteristics and an explanation of the mechanism through which entrepreneurial perceptions and EI develop.

Housing completions in the UK have fallen to 125,000 annually, while government targets have risen to 300,000. This dramatic shortfall raises concerns as to whether current traditional construction approaches remain appropriate. This study aims to compare the traditional approach with modular construction, with a view to assessing whether a shift in construction systems offers the potential to alleviate the UK's domestic housing crisis.

A comprehensive interpretivist review of the available relevant literature is undertaken on construction methods within the UK; advantages and disadvantages. A bibliometric analysis is conducted to extract trends and findings relevant to the comparison at hand. The database is Web of Science; the analysis software is the VOS viewer.

The research illustrates that the UK housing market is in a state of crisis. A toxic combination of a rising UK population combined falling rates of housing delivery has resulted in an ever-widening housing supply gap. The construction industry’s capacity to meet this observed dearth in supply is further exacerbated by a number of chronic factors such as: falling participation in the construction sector workforce; lowering skill levels; reducing profitability; time to delivery pressures; and cost blow-outs.

While much information on the various construction methods are available, including comparative material, this study is the first to assemble the various comparative parameters regarding traditional and modular UK residential construction in one place. Thus, this study provides a definitive assessment of the relative advantages and disadvantages of these forms of construction.

A comprehensive literature review of performance management within the Dutch steel processing industry is presented. The purpose of this paper is to analyse the motives for companies to become excellent performers in their field of expertise. These internal and external motives (refined by quantitative analysis of bibliographic data) sought to reveal the common factors that impact company performance.

Inductive reasoning was adopted using an interpretivist philosophical stance to generate new theoretical insight. A mixed-methods analysis of pertinent extant literature afforded greater synthesis of the research problem domain and generated more valid and reliable findings. The software visualisation of similarities viewer was used to conduct a qualitative bibliographic analysis of extant literature to yield greater clarification on the phenomena under investigation.

Four thematic groups of past research endeavours emerged from the analysis and were assigned appropriate nomenclature, namely: industry internal motives; industry external motives; excellent performer and incremental working method. To further expand upon the continuous improvement process (CIP – embodied within performance management), the paper describes the virtuous cycle of improvement, which consists of the consecutive steps of “planning”, “doing”, “checking” and ultimately of “acting” accordingly to the previous steps. It can be concluded that a high-performing company acts according to its mission, plans in line with the vision do as defined in the strategy and checks by reflection.

This unique study provides invaluable insight into the performance management of Dutch steel processing companies. Although the research context was narrowly defined, the findings presented are equally applicable to clients, contractors and sub-contractors active in other sectors of the construction industry. The research concludes by prescribing factors of mitigation strategies to support chief executive officers to focus on the optimum distribution of their scarce resources.

Credit market development requires appropriate credit assessment and default policies. This paper aims to examine the impact of household characteristics on mortgage default, using survey data collected from Ghanaian financial institutions.

Data were gathered using semi-structured questionnaires from customers of five universal banks in Ghana. A logistic regression was used to model the determinants of credit default propensity.

Contrary to established knowledge, the study shows that females are more likely to default on credit than their male counterparts. This is even more likely if the female is older, unmarried, divorced and financially illiterate and has lower educational attainments. These factors are associated with lower earning capacity, which increases default tendencies. The findings confirm that price instability (typified by excessive movements in inflation and exchange rates in addition to low national savings rate) are adversely linked to credit defaults. Borrower’s perception of constraints to credit access (such as collateral requirements, interest rate and loan size) influence credit default. Banks should be encouraged to invest in the financial literacy skills development of their customers to mitigate credit default tendencies.

The study is of practical value to credit officers and the development of the credit market in Ghana. A novel model is presented for assessing credit applications and developing credit default policies.

The research findings have not only expanded the frontiers of literature but also empirically examined the determinants of credit default propensity, which provides a basis for developing and improving credit default policy in the credit market.

This paper aims to explore the emerging relationship between Industry 4.0 (I4.0) digital technologies (e.g. blockchain, Internet of Things (IoT) and artificial intelligence (AI)) and the construction industry’s gradual transition into a circular economy (CE) system to foster the adoption of circular economy in the construction industry.

A critical and thematic analysis conducted on 115 scientific papers reveals a noticeable growth in adopting digital technologies to leverage a CE system. Moreover, a conceptual framework is developed to show the interrelationship between different I4.0 technologies to foster the implantation of CE in the construction industry.

Most of the existing bodies of research provide conceptual solutions rather than developing workable applications and the future of smart cities. Moreover, the coalescence of different technologies is highly recommended to enable tracking of building assets’ and components’ (e.g. fixtures and fittings and structural components) performance, which enables users to optimize the salvage value of components reusing or recycling them just in time and extending assets’ operating lifetime. Finally, circular supply chain management must be adopted for both new and existing buildings to realise the industry's CE ambitions. Hence, further applied research is required to foster CE adoption for existing cities and infrastructure that connects them.

This paper investigates the interrelationships between most emerging digital technologies and circular economy and concludes with the development of a conceptual digital ecosystem to integrate IoT, blockchain and AI into the operation of assets to direct future practical research applications

Using a discrete choice experiment (DCE), this study aims to better understand the job preference of postgraduate students studying at the Kwame Nkrumah University of Science and Technology-Institute of Distance Learning, Ghana and also rank the attributes of a job they deem important.

The research adopted a positivist epistemological design contextualised within a deductive approach and case study strategy. Primary survey data was collected from a stratified random sample of 128 postgraduate students with multi-sectorial career prospects. Sample students were subjected to a DCE in which their stated preferences were collected using closed-ended questionnaires with 28 pairs of hypothetical job profiles. Respondents’ preferences from the DCE data were then modelled using the conditional logit.

The research reveals that: salary in the range GHC 2,800.00 to GHC 3,400.00 ($1 = GHS 5.3); supportive management; very challenging jobs; and jobs located in the city were the top attributes that were significant and had the most impact in increasing the utility of selecting a particular job. Interestingly, jobs with no extra hours workload were not significant hence, had a negative impact upon student preferences.

This novel research is the first to use a DCE to better elicit preference and trade-offs of postgraduate students in a developing country towards varying job characteristics that have an impact on their future employment decisions. Knowledge advancements made provide invaluable insight to employers and policymakers on the key criteria that should be implemented to retain the best candidate.