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Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

The innovativeness of dressmakers is a concern to respondents to satisfy their clothing needs. The purpose of this study is to determine the criteria that respondents use to judge the quality of clothing and its influences on the innovative ability of dressmakers in the clothing manufacturing industries.

Three hundred and ninety-seven (397) respondents in the Takoradi Metropolis of Ghana filled out a questionnaire, and the results were used to compile data for the study. The sample size was calculated using Miller and Brewer formula. The data was analysed using structural equational modelling with the SmartPLS v.4 software.

The results showed that respondents are very interested in the calibre of clothing produced by their dressmakers. However, the study revealed that when evaluating the quality of a garment, respondents do not simply accept what has been sewn for them but also consider the performance, appearance, fit and shape of the garment. Findings revealed that there was a significant relationship between garment appearance quality (t = 2.605; p < 0.05), garment performance quality (t = 3.915; p < 0.05), garment shape quality (t = 6.248; p <0.05) and fashion innovations. Subsequently, the evaluation of garment fit quality by respondents revealed it does not bring about innovations (t = 1.310; p > 0.05).

The continuous evaluation of custom-made clothing from customers will go a long way towards highlighting the relative criteria they use to evaluate the innovation of dressmakers. This will help improve the creativity of the dressmakers since such feedback will help them understand and innovate their production skills to meet the preferences of customers.

The present study provides an in-depth understanding of how garment quality evaluation by customers influences the innovation of dressmakers in Takoradi, Ghana. The constructs were developed for the study to capture the appropriate data from customers for the study. This presents an evaluation criterion on four garment quality variables imperative for use or modification by other studies.

The concept of distributed leadership (DL) has been widely advocated within higher education (HE). Yet, there have been few empirical investigations and little theory development outside Western contexts to date. This study presents a unique conceptualisation of DL and tests it empirically in India.

This study tests a moderated-mediation model by exploring the antecedents and consequences of DL in HE. Standardised questionnaires were drawn from literature and completed by a sample of 269 respondents from six top-ranked (elite) Indian higher education institutions (HEIs). Structural equation modelling (SEM) and multi-group analysis techniques were used to analyse the data.

Results demonstrated that empowering power structure (EPS) is positively related to DL, whilst participation in decision-making (PDM) strengthened this relationship. Further, it is also noted that DL mediates the relationship between EPS and behavioural outcomes of employee voice and silence.

The findings suggest that a DL approach can be effective at enhancing employee voice and reducing employee silence within HEIs in (and perhaps beyond) India. The research also suggests that where institutions implement EPS alongside opportunities for PDM, this can help foster and sustain DL.

By exploring antecedents (EPS and PDM) and consequences (voice and silence), this paper presents a novel approach to studying DL. The focus on Indian HE offers a more nuanced empirical understanding of DL in a non-Western context.

Although (tele)work is increasingly being adopted and employees’ behavior is recognized to be key for organizational outcomes (e.g. performance), the current literature on counterproductive work behaviors (CWB) in telework settings is fragmented, and a valid measurement instrument is lacking. This study aims to address this gap and starts by presenting a review of the current literature on counterproductive work behavior in flexible work arrangements (i.e. telework). Based on this study, eight categories of work behavior that appear to be frequent under telework settings were identified.

Next, four studies aimed at developing and validating a measurement instrument that captures employee counterproductive work behavior when teleworking: the counterproductive [tele]work behavior scale (CTwBS).

In Study 1, the CTwBS was created, and in Study 2, its factorial validity was examined (N = 350). In Study 3, using a sample of teleworkers (N = 289), the convergent and discriminant validity of the CTwBS was tested using self-ratings of (positive and negative) affect, attitudes toward telework and frequency of CWB in general. In Study 4, a daily-diary study across five workdays (N = 232 × 5 = 1,160) examined the criterion validity of the CTwBS.

The results indicated that the CTwBS is a valid and reliable instrument for capturing employee counterproductive work behavior in telework settings. Theoretical and practical implications are discussed.

To the best of the authors’ knowledge, CTwBS is the first measure aimed at assessing counterproductive work behavior in telework settings.

This paper explored the socioeconomic factors affecting green cities development. Extant literature have highlighted green cities as a major path towards sustainability in the construction industry but very little is known on the socioeconomic aspect of green cities and its bid in promoting sustainability in the construction industry; hence, the premise of this study which highlights the socioeconomic factors affecting green cities development in Ghana.

A comprehensive literature review was conducted to identify the socioeconomic factors affecting green cities. A quantitative research strategy was adopted to collect primary data from respondents who have the requisite understanding and knowledge in green cities using questionnaires. The data gathered was then analysed using descriptive statistics and exploratory factor analysis viz principal component analysis.

The socioeconomic factors affecting green city development comprised: Green support mechanisms (i.e. innovation and technology, green city planning (urban planning), stakeholder engagement, awareness, city planning (transportation) and environmental regulations); green inhibitors (i.e. population, culture, housing and policy implementation); green market and finance (i.e. digital finance, green market mechanism, green investment finance, risks and uncertainties, income levels of clients). It was evident that socioeconomic factors are significant to the development of green cities in Ghana and hence policy makers and various stakeholders should prioritize socioeconomic factors in the bid to achieve sustainability through green cities in the construction industry.

This paper presents a foremost and comprehensive study on the socioeconomic factors affecting green cities in Ghana. The study results showed that even though the path to sustainability in green cities has pivoted mainly on environmental factors, socioeconomic factors are also significant to green city development, hence, policy makers and the construction industry should keenly consider the socioeconomic factors affecting green city development in the bid towards sustainability for cities.

This paper posits the need for English language arts (ELA) teachers to foster students’ use of languaging about their relations with ecosystems and peers, leading to their engaging in collective action to critique and transform status-quo systems impacting the climate crisis.

This paper reviews the current theory of languaging theory and research that focuses on the use of languaging to enact relations with ecosystems and others and voice emotions for transforming communities and reducing emissions contributing to climate change.

This review of languaging theory/research leads to identifying examples of teachers having students critique the use of languaging constituting status quo energy and community/transportation systems, respond to examples of characters using languaging in literary texts, using languaging in discussing or writing about the need to address climate change, critiquing languaging in media promoting consumption, using media to interact with audiences and using languaging through engaging in role-play activities.

This focus on languaging in ELA classrooms is a unique perspective application of languaging theory, leading students to engage in collective, communal action to address the climate crisis.

Prior research from transaction costs economics argued that central firms perform better because they have superior access to information to discipline their alliance partners. Central firms may also, however, face higher costs and risks of unintentional learning and weaken their competence through structural inertia. We propose that these costs and risks are influenced by the learning capacities of the firms in the network and can explain different outcomes for focal firm performance.

To test our predictions, we use instrumental variable–generalized method of moments estimation techniques on 15,517 firm-year observations from equity alliance portfolios in the global food industry across a 21-year window.

We find support for our predictions and show that the relationship between network degree centrality and firm performance is negatively influenced by partners’ learning capacity and positively influenced by focal firms’ learning capacity, while firms with low network degree centrality benefit less from their learning capacity.

Future developments in transaction cost economics may consider partner and focal firms’ learning capacity as moderators of the network degree centrality – firm performance relationship.

In alliance decisions, managers must consider that the combination of high network degree centrality and partners’ learning capacity can lead to high costs, risks of unintentional learning, and structural inertia, all of which have negative consequences for performance. In concentrated industries where network positions are controlled by a few large firms, policymakers must acknowledge that firms may face substantial barriers to collaboration with learning-intensive firms.

This study is the first to develop and test a comprehensive transaction cost analysis of the central firm’s unintended knowledge flows and structural inertia in alliance networks. It is also the first to incorporate theoretically and empirically the hazards of complex and unintended information flows on the relationship of network degree centrality to performance in equity alliance portfolios.

Megaproject knowledge innovation (MKI) is perceived as a critical strategy for engineering value co-creation and industrial chain upgrading. Ascertaining the impact mechanism of MKI is a crucial initial step towards improving management practices. Within the framework of complex systems in megaprojects, factors exhibit intricate interdependencies. However, the current domain of knowledge has either overlooked or oversimplified this relationship and therefore cannot propose pragmatic and efficacious strategies for enhancing MKI. To close this gap, this study develops a Bayesian network (BN) model aiming to investigate the interdependencies among MKI-related factors and their impact on MKI.

First, this study implements literature review, expert interview and field investigation to identify the influencing factor nodes for the network model development. Second, a Bayesian network was constructed by integrating the expert knowledge with Dempster-Shafer theory. Next, a MKI measurement model was established using 253 training samples. Finally, the factor significance and optimal MKI improvement strategies are identified from the sensitivity analysis and probabilistic reasoning within the BNs.

The results indicate that (1) the BN model exhibits significant reliability and holds promotion and application value in formulating MKI management strategies; (2) knowledge sharing, shared vision and leadership are the key influencing factors of MKI; and (3) simultaneously improving institutional pressure, leadership and knowledge sharing is the most optimal strategy to enhance MKI.

This study innovatively introduced the BN method into the domain of MKI management, providing an appropriate approach for modelling complex relationships among factors and investigate nonlinear influences. The developed model raises megaproject stakeholders’ awareness about factors influencing MKI and presents quantified strategies that increase the likelihood of maximising MKI levels. Its ease of generalisability positions it as a promising decision support tool, facilitating the implementation of sustainable MKI practices.

This study aims to provide an integrated review of the literature on the diffusion, adoption and implementation of multicapital accounting (MCA) innovations.

The paper analyzes a sample of 68 articles collected from 21 peer-reviewed journals. An integrated model of the diffusion, adoption and implementation of MCA innovations is developed and used to frame data collection, content analysis and the critical synthesis of findings.

The involvement of various key actors, including academics, regulatory agencies, non-governmental organizations (NGOs) and businesses, is crucial in the diffusion of MCA innovations as they provide resources, promote legitimacy and drive the adoption process through regulation, advocacy, tool design and capacity building. The adoption of MCA innovations is significantly influenced by their perceived relative advantage, compatibility, complexity, observability and trialability. Organizations may adopt MCA innovations due to rational motives, regulatory requirements or to gain legitimacy by imitating peers. Larger firms with better financial performance and strong corporate sustainability responsibility (CSR) practices are more likely to adopt MCA innovations due to greater resources and exposure to stakeholder pressures. The implementation of MCA innovations often proceeds incrementally, requiring alignment with organizational routines, top management support and consistent use. Successful integration into organizational practices necessitates a culture that values sustainability alongside financial metrics.

This study provides several practical and societal implications. For practitioners, understanding the key drivers of adoption, such as perceived advantages and compatibility with existing organizational processes, can help in designing and implementing more effective MCA strategies. For instance, companies can benefit from training programs and workshops to reduce perceived complexity and enhance trialability. Additionally, regulatory bodies can create supportive policies and incentives to encourage voluntary adoption and improve compliance rates. On a societal level, the broader adoption of MCA innovations can lead to more comprehensive and transparent reporting of both financial and non-financial performance, which in turn enhances stakeholder trust and engagement. This transparency can drive societal benefits by promoting greater accountability and encouraging sustainable business practices.

On a societal level, the broader adoption of MCA innovations can lead to more comprehensive and transparent reporting of both financial and nonfinancial performance, which in turn enhances stakeholder trust and engagement. This transparency can drive societal benefits by promoting greater accountability and encouraging sustainable business practices.

This paper contributes to the emerging research on MCA by offering a systematic review that integrates various perspectives on the diffusion, adoption and implementation of MCA innovations. It provides a nuanced understanding of the dynamics influencing MCA practices and suggests avenues for future research.

To examine objective measures of economic job quality for a broad sample of workers in the US spectator sports industry and compare job quality in spectator sports to other industries.

Logistic and linear regressions are performed on American Community Survey (ACS) data collected from 2015 to 2019. Earnings and employer provision of health insurance are the outcomes.

Earnings and employer-provided health insurance are lower in the spectator sports industry than in other industries after controlling for relevant factors. Differences are partly explained by the occupational composition of the industry and the higher incidence of part-time work. Many but not all occupational groups have lower earnings and less employer-provided health insurance in sports.

ACS data only reports one job, so the results likely underestimate the prevalence of part-time work in the US spectator sports industry. The study finds support for a micro-class occupational composition effect and a pulsating organization effect. Some support is also found for a sports industry compensating wage differential, but the effect is not industry wide, counter to some depictions.

This is the first study to examine objective, economic measures of job quality across all occupational sub-groups in the sports industry. This is the first study to propose theoretical explanations for poor economic job quality in sport.