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Universities globally have faced the introduction of research performance assessment systems that provide monetary and ranking rewards based on publication outputs. This study aims to seek an understanding of the implementation of performance-based research funding (PBRF) and its impact on the heads of departments (HoDs) and accounting academics in New Zealand (NZ) tertiary institutions. The study explores NZ accounting academics’ experiences and their workload; the relationship between teaching and research in the accounting discipline and any issues and concerns affecting new and emerging accounting researchers because of PBRF.

Applying an institutional theoretical lens, this paper explores accounting HoDs’ perceptions concerning the PBRF system’s impact on their academic staff. The research used semi-structured interviews to collect data from NZ’s eight universities.

The key findings posit that many institutional processes, some more coercive in nature, whereas others were normative and mimetic, have been put in place to ensure that academics are able to meet the PBRF requirements. HoDs suggest that their staff understand the importance of research, but that PBRF is a challenge to new and emerging researchers and pose threats to their recruitment. New academics must “hit the ground running” as they must demonstrate not only teaching abilities but also already have a track record of research publications; all in all, a daunting experience for new academics to overcome. There is also a teaching and research disconnect. Furthermore, many areas where improvements can be made in the design of this measurement tool remain.

The PBRF system has significantly impacted on accounting academics. Central university research systems were established that subsequently applied coercive institutional pressures onto line managers to ensure that their staff performed. This finding offers scope for future research to explore a better PBRF that measures and rewards research productivity but without the current system’s unintended negative consequences.

This study aims to assess the essential elements of internal organisational capability that influence the cybersecurity effectiveness of a construction firm. An extended McKinsey 7S model is used to analyse the relationship between a construction firm's cybersecurity effectiveness and nine internal capability elements: shared values, strategy, structure, systems, staff, style, skills, relationships with third parties and regulatory compliance.

Based on a quantitative research strategy, this study collected data through a cross-sectional survey of professionals working in the construction sector in the United Kingdom (UK). The collected data was analysed using descriptive and inferential statistical methods.

The findings underlined systems, regulatory compliance, staff and third-party relationships as the most significant elements of internal organisational capability influencing a construction firm's cybersecurity effectiveness, organised in order of importance.

Future research possibilities are proposed including the extension of the proposed diagnostic model to consider additional external factors, examining it under varying industrial relationship conditions and developing a dynamic framework that helps improve cybersecurity capability levels while overseeing execution outcomes to ensure success.

The extended McKinsey 7S model can be used as a diagnostic tool to assess the organisation's internal capabilities and evaluate the effectiveness of implemented changes. This can provide specific ways for construction firms to enhance their cybersecurity effectiveness.

This study contributes to the field of cybersecurity in the construction industry by empirically assessing the effectiveness of cybersecurity in UK construction firms using an extended McKinsey 7S model. The study highlights the importance of two additional elements, third-party relationships and construction firm regulatory compliance, which were overlooked in the original McKinsey 7S model. By utilising this model, the study develops a concise research model of essential elements of internal organisational capability that influence cybersecurity effectiveness in construction firms.

Environmental risks (ERs) are critical to any highway construction project (HCP). One of the main contracting parties responsible for ERs is the contractor. Hence, it has been crucial to look into ways to control ERs in HCPs from the contractor’s perspective. This study aims to investigate how ERs can be managed in HCP in Sri Lanka.

A quantitative research approach with three rounds of Delphi was used. Statistical techniques were used to analyse and validate the ERs, the parties to whom the risks were to be allocated, and risk management measures identified from the empirical data collection.

The study reveals the 11 most significant ERs for HCP. Further, the most significant ERs in HCP were mainly found to be the responsibility of contractors in Sri Lanka. Twenty-four most appropriate risk response measures were determined; 13 were found to be common measures that could be used to manage two or more risks, while the remaining 11 were unique to specific risks.

Overall, this research determines the most significant ERs in HCP, the best risk allocation among the parties and appropriate risk-handling strategies and measures for each significant ERs. Additionally, the study addresses the demand for ERs management in HCP.

Total risk score (TRS) is considered one of the main indicators for risk evaluation. Several studies attempted to employ different types of risk indices for the evaluation of cost overrun causes. Hence, this study aims at performing a comparative analysis to evaluate the efficiency of three different approaches for TRS calculation.

Thirty-eight unique causes of cost overrun in urban-related construction projects were identified and a survey was conducted among construction professionals in Iran. The TRS for each cost overrun cause is calculated using single-attribute (SA), double-attribute (DA), and multiple-attribute (MA) approaches, and eventually, causes were ranked. Furthermore, principal component analysis (PCA), logistic regression analysis (LRA), and K-means clustering are utilized to compare the differences in the generated TRS using different approaches.

The results revealed that the TRS generated through the MA approach demonstrated the highest efficiency in terms of generating correlation between causes and their identified latent constructs, prediction capability, and classification of the influential causes in the same group.

The originality of this study primarily stems from the adoption of statistical approaches in the evaluation of the recently introduced TRS calculation approach in comparison to traditional ones. Additionally, this study proposed a modified application of the relative importance index (RII) for risk prioritization. The results from this study are expected to fulfill the gap in previous literature toward exploring the most efficient TRS calculation approach for those researchers and practitioners who seek to utilize them as a measure to identify the influential cost overrun causes.

Time-cost trade-off is normal conduct in construction projects when projects are expectedly late for delivery. Existing research on time-cost trade-off strategic management mostly focused on the technical calculation towards the optimal combination of activities to be accelerated, while the managerial aspects are mostly neglected. This paper aims to understand the managerial efforts necessary to prepare construction projects ready for an upcoming trade-off implementation.

A preliminary list of critical factors was first identified from the literature and verified by a Delphi survey. Quantitative data was then collected by a questionnaire survey to first shortlist the preliminary factors and quantify the predictive model with different machine learning algorithms, i.e. k-nearest neighbours (kNN), radial basis function (RBF), multiplayer perceptron (MLP), multinomial logistic regression (MLR), naïve Bayes classifier (NBC) and Bayesian belief networks (BBNs).

The model's independent variable importance ranking revealed that the top challenges faced were the realism of contractual obligation, contractor planning and control and client management and monitoring. Among the tested machine learning algorithms, multilayer perceptron was demonstrated to be the most suitable in this case. This model accuracy reached 96.5% with the training dataset and 95.6% with an independent test dataset and could be used as the contingency approach for time-cost trade-offs.

The identified factor list contributed to the theoretical explanation of the failed implementation in general and practical managerial improvement to better avoid such failure. In addition, the established predictive model provided an ad-hoc early warning and diagnostic tool to better ensure time-cost implementation success.

Construction projects, and particularly highway infrastructures, are known to be major contributors to the socio-economic growth of developing countries. However, these types of projects are infamous for being highly risky due to the interplay of numerous risk factors. This study aims to explore the key risk factors impacting on the performance of highway infrastructure projects in Nigeria from the contextual viewpoint of key industry stakeholders.

Qualitative data was collected using semi-structured interviews. Specifically, 17 in-depth expert interviews were conducted with experienced stakeholders in the highway sector of the Nigerian construction industry. The collected data was transcribed and analysed using an established coding framework (grounded on case study approach, principles of thematic analysis and saliency analysis).

Overall, 17 key risks were identified from the data analysis process, and 6 risks were recognised as the most significant, based on the combination of prevalence of occurrence and significance of the coded information. The six top risks were: change in government, corruption, cost of construction materials, inflation, project funding issues and construction project delay. However, the first two of these risks (change in government and corruption) are politically related, which is specific and unique to the setting of Nigeria and thus might be seen as discouraging indicators that could have an impact on attracting foreign investors/contractors to Nigeria.

The study addressed the gap related with identifying context-specific risk factors impeding the performance of highway projects in Nigeria from the viewpoints of industry experts. It is expected that the findings will provide a better insight into the various risk factors and thus aid relevant policymakers to provide context-specific mitigating strategies.

It is widely accepted that one criterion for determining if a construction project is successful is whether it is completed within the expected budget. There have been advancements in the management of building projects throughout time but cost overruns remain a key concern in the construction sector internationally, particularly in emerging economies such as Ghana. This study aims to answer the question, “What are the critical success factors (CSFs) that can assist reduce cost overruns in public sector infrastructure projects in the Ghanaian construction industry?”

This study used a quantitative survey method. The questionnaire was pre-tested by interviewing 15 contractors to ascertain the validity of the content. Factor analysis and multiple regression were adopted to analyze the data.

This study discovered that the critical factors that can reduce cost overruns in construction projects in Ghana are directly linked to five themes: early contractor involvement in the project planning stage, adequate funding, good project team relations, competent managers/supervisors and project participant incentives/bonuses. This study identifies indestructible, empirically measurable important success criteria for reducing cost overruns in public building projects in Ghana.

When well thought through from the project initiation stage to completion, these critical successes can also be used to deal with damaging economic effects such as allocative inefficiency of scarce resources, further delays, contractual disputes, claims and litigation, project failure and total abandonment.

The uniqueness of this research resides in the fact that it is, to the best of the authors’ knowledge, a first-of-its-kind investigation of the CSFs for reducing cost overruns in public building projects in developing countries.

This study aims to explore the factors that influence job satisfaction among women in Jordan and contribute to the growing interest in women’s workplace happiness in the context of the Middle East.

The authors used an explanatory sequential mixed-method approach. During the first phase, 250 female respondents were surveyed from the private sector in Jordan. The authors analyzed the impact of various employment-related attributes and other variables, including educational level, position, work experience, daily work hours, income level, relationships with colleagues and supervisors and internal career opportunities on job satisfaction. During the second stage, the authors interviewed 23 supervisor female respondents and conducted a thematic analysis to explore in more depth the determinants of job satisfaction of females working in the private sector in Jordan.

The quantitative findings of this study indicate that job satisfaction is positively influenced by education level and income, while notably, it was negatively impacted by work experience and daily work hours. Relationships with colleagues and supervisors, as well as internal career opportunities, positively affect job satisfaction. The qualitative findings of the study indicate that positive corporate culture, developing subordinates, financial independence, self-worthiness, work-life balance, internal career opportunities and factors that spillover from the personal life domain contributed highly to job satisfaction.

The findings of this study can help employers in gaining a deeper understanding of the needs and behaviors of female workers in the Middle East, potentially resulting in decreased job turnover and heightened productivity.

This study offers valuable insights into the cultural dynamics at play and sheds light on the psychology of the Arab female workforce. Given the limited research on job satisfaction among women in the Middle East and the Arab world, this study holds significant importance for practitioners.

Managing farm waste is a fundamental problem for farmers with economic, environmental and social impacts throughout the supply chain. Little research has explored innovative product solutions. This paper examines gleaning to reduce farm waste and proposes a resource-based Gleaning Innovation Framework which can lead to differentiated consumer products.

A multi-method approach, including descriptive company reviews, practitioner interviews and consumer surveys, evaluated how different participants in the food supply chain view the farm waste problem and the innovation of products through gleaning.

This research found that practitioners and consumers are cognizant and invested in reducing farm waste, with gleaning as a plausible solution. Future research includes gathering perspectives from retailers and other supply chain members, which may further develop the conceptualization of the gleaning innovation process.

Uniquely, the authors propose the Gleaning Innovation Framework that provides a platform for innovation across the supply chain to reduce farm waste. The research contributes to the farm waste debate with evidence that gleaning can assist the reduction of farm waste through product innovation. Developing innovations to reduce farm waste in sustainable and environmentally friendly ways would not only benefit the supply chain platform but also society.

This study aims to investigate the feasibility of health cadres in Indonesia to take perinatal depression screening in the community using Edinburgh Postnatal Depression Scale (EPDS) and Whooley.

The field study involved 11 health cadres (community volunteers who assist in maternal and child health) who were trained to administrate EPDS and Whooley towards 36 pregnant and postpartum mothers in a low resource urban setting for a month. A comparison of scores from both tools, the number and type of mistakes made by the cadres, and cadres perception about the tools were combined to determine the most feasible tool for cadres in identifying depression symptoms.

The results show both tools are comparable for screening depression symptoms in mothers; however, EPDS was better at differentiating the level of symptoms. Whooley, with two case-finding questions, is simpler for cadres, whereas the EPDS is more difficult to be computed by cadres. Cadres support the implementation of such a screening, as it provides a channel for mothers to express their negative feelings.

The findings indicate Whooley is sufficient for first-level screening in the community by cadres, whereas the EPDS should be used by qualified health-care workers for further evaluation at primary health clinics.

Health cadres could potentially be trained to use standardized yet simple psychological tools. Involving trained health cadres in integrated maternal mental health services in primary health care in Surabaya, Indonesia is promising.

The use of the EPDS and the Whooley questions has not been applied in Indonesia particularly among health cadres despite their long-lasting role in primary health-care system.