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This paper examines the efforts of National Health Service (England) (NHSE) to respond to employee-based racial inequalities via its Workforce Race Equality Standard (WRES). The WRES constitutes a hybridised accountability initiative with characteristics of the moral and imposed regimes of accountability.

The study conceptualises the notion of responsive race accountability with recourse to Favotto et al.’s (2022) moral accountability model and critical race theory (CRT), and through it, examines the enactment of WRES at 40 NHSE trusts using qualitative content analysis.

Despite the progressive nature of the WRES that seeks to nurture corrective actions, results suggest that trusts tend to adopt an instrumental approach to the exercise. Whilst there is some evidence of good practice, the instrumental approach prevails across both the metric reporting that trusts engage in to guide their actions, and the planned actions for progress. These planned actions not only often fail to coalesce with the trust-specific data but also include generic NHSE or equality, diversity and inclusion initiatives and mimetic adoptions of best practice guidance that only superficially address racial concerns.

Whilst the WRES is a laudable voluntary achievement, its moral imperative does not appear to have translated into a moral accountability within individual trusts.

Responding to calls for more research at the accounting-race nexus, this study uniquely draws on CRT to conceptualise and examine race accountability.

Total productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.

In this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.

Our findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.

In terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.

This paper aims to investigate the factors influencing trade artisans’ choice of skills selection as apprentice’s trainee in the Ghanaian construction sector and to identify and address the challenges associated with traditional apprenticeship. Trade artisans with technical know-how in construction and general workplace skills from the traditional apprenticeship training (TAT) in the area of construction were selected from selected sites and training centers.

This paper adopted the purposive sampling technique with the aim of gathering knowledge from individuals with expertise in the research area, particularly trade craftsmen who have been trained through the TAT system and are directly involved in construction-related works. Partial least square structure equation modelling (PLS-SEM) analytical approach and principal component analysis were used to reduce the dimensionality of the data set and preserve as much information as possible.

Three major components, namely, personal and social interest, job assessment and stability and family and faith were identified as the variables that influence an artisan's choice of a skill trade. These influenced the choice of apprenticeship training by young trainees in choosing apprenticeship as a mode of training. Personal interest, living situation of artisans and parents’ educational attainment are the most influencing factors that determine artisans’ choice of selected trades. Moreover, the study also shed light on the challenges inherent in traditional apprenticeship systems, such as the lack of formal technical education, limited access to modern technology and information and poor working conditions.

The study underscores the imperative for stakeholders to enhance apprenticeship programmes within the construction sector. This involves providing more stable job opportunities, improving working conditions and offering access to modern technology and information. Such enhancements not only attract more young individuals to apprenticeship training but also ensure the sustainability and relevance of the workforce in meeting industry demands.

The study finally developed a model that could be used as a foundation for future PLS-SEM evaluation and identified the factors that influence the selection of apprenticeship training by trade artisans.

This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D_Div index, for this purpose.

The D_Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.

The sensitivity analysis demonstrated the D_Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D_Div index reached the highest prediction accuracy of 0.8. Furthermore, the D_Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.

This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

Enterprise resource planning (ERP) systems that are equipped with numerous features and functionalities help to improve the profitability of construction corporations around the world through enhancing the efficiency of the functions related to cost management. Thus, the purpose of this study was to investigate the applicability of ERP systems for cost management of building construction projects in Sri Lanka.

A qualitative technique was used in this study, which comprised two-round Delphi-based semistructured interviews. Purposive sampling was used to determine the interviewees. Content analysis was used to evaluate the collected data.

The findings of this study identified the ERP system as a strategic tool for gaining a competitive advantage for an organization while confirming 14 uses of ERP systems and 16 stages of the cost management process. Eighteen issues were finalized at the end of the interview rounds while categorizing the suitable ERP applications at each stage of the cost management process.

Even though there are numerous distinct studies conducted on cost management and ERP systems, there has been a lack of studies conducted on the synergy between these two areas that can be adapted for the building projects in the Sri Lankan context. Therefore, the findings of this study can bring a new paradigm to the Sri Lankan construction sector by influencing the adaption of correct ERP systems at numerous project stages by providing a competitive edge.

The purpose of this paper is to investigate the impact of demand information sharing on products’ greening levels with downstream competition. Specifically, this study examine two types of green products, “development-intensive” (DI) and “marginal-cost intensive” (MI), in a two-echelon supply chain where the manufacturer produces substitutable products, and competing retailers operate in a market with uncertain demand.

The authors adopt the manufacturer-led Stackelberg game-theoretic framework and consider a multistage game. This study consider how retailers receive private signals about uncertain demand and decide whether to share this information with the manufacturer, who then decides whether to acquire this information at a certain given cost. This paper considers backward induction and Bayesian Nash equilibrium to solve the model.

The authors find that in the absence of competition, information sharing is the only equilibrium and improves the greening level under DI, whereas no-information sharing is the only equilibrium and improves the greening level under MI, an increase in downstream competition drives higher investment in greening efforts by the manufacturer in both DI and MI and the manufacturer needs to offer a payment to the retailers to obtain demand information under both simultaneous and sequential contract schemes.

This paper contributes to the literature by examining how the nature of products (margin intensive green product or development intensive green product) influences green supply chain decisions under information asymmetry and downstream competition.

The accuracy of budgeting is important to fulfilling its various roles. The aim of this study is to examine perceptions of budgeting accuracy in UK universities and to identify and understand the factors that influence them.

A mixed methods research design comprising a questionnaire survey (84 responses, = 51.5%) and 42 semi-structured, qualitative interviews is employed.

The findings reveal that universities tend to be conservative in their budgeting, although previous financial difficulties, the attitude of the governing body and the need to convince lenders that finances are being managed competently might lead to a greater emphasis on a “realistic” rather than cautious budget. Stepwise multiple regression identified four significantly negative influences on perceived budgeting accuracy: the difficulty of forecasting student numbers; difficulties associated with allowing unspent balances to be carried forward; taking a relatively long time to prepare the budget; and the institution’s level of financial surplus. The interviews are drawn upon to both explain and elaborate on the statistical findings. Forecasting student numbers and associated fee income emerges as a particularly challenging and complex issue.

Our regression analysis is cross-sectional and therefore based on correlations. Furthermore, the research could be developed by investigating the views of other parties as well as repeating the study in both the UK and overseas.

Implications for university management follow from the four factors identified as significant influences upon budget accuracy. These include involving the finance department in estimating student numbers, removing or controlling the carry forward of unspent funds, and reducing the length of the budget cycle.

The first study to examine the factors that influence the perceived accuracy of universities’ budgeting, this paper also advances understanding of budgeting accuracy more generally.

The New Zealand (NZ) construction industry significantly impacts the country's economy and is one of the largest sectors in terms of total employment. However, a persistent and pressing need for improvement exists. Meeting the ongoing demand for housing and urban development requires enhancing residential construction productivity. The purpose of this paper is to determine what factors improve construction productivity in the NZ residential construction sector.

Data were obtained from construction industry bodies using a semi-structured online questionnaire survey. From 305 online questionnaires administered, 106 samples were completed by residential industry construction professionals across NZ. The data were analysed using descriptive and inferential statistics to establish the importance of empirical factors for improving construction productivity in the NZ residential construction sector.

The Garrett ranking technique revealed this study's top five factors for enhancing construction productivity: adequate design, communication, quality management (QM), supervision and organizational training. Other factors, such as unskilled workers, skilled workers, reworks and employee motivation, ranked less important.

While providing a valuable exploration of factors that can positively impact residential construction productivity in NZ, this study contains certain limitations. The study's focus on a specific geographic location and a small sample size (n = 106) may restrict the generalizability of its findings to other regions or countries. Furthermore, the reliance on self-reported data from industry professionals introduces the possibility of bias or inaccuracies in the results. In addition, this study did not investigate the potential influence of external factors, such as economic conditions or regulatory changes, on residential construction productivity. Despite these limitations, this study presents a foundation for future research on this topic. Future research could address these limitations by conducting multi-country studies and using objective productivity measures to provide a broader context. In addition, open-ended questions could be used to collect more detailed qualitative data, enhancing this study's dependability. This methodological constraint could have omitted important experiential nuances, which could be explored in future research to provide more comprehensive and rigorous findings.

Research studies indicate that several construction productivity factors have remained unchanged for over three decades (Arditi and Mochtar, 1996; Hasan et al., 2018). The implications of this study are significant for the residential sector in NZ. By identifying the key factors that can improve productivity in the sector, such as complete design and specifications, effective communication, quality management, adequate supervision, training, skilled labour and employee motivation, this study provides valuable insights for industry practitioners and policymakers. It expands the existing productivity literature around factors for improving NZ residential construction productivity. One important implication of this study is the link between QM and improved productivity, highlighting the significance of strategic organizational investments in QM and the added opportunity presented to policymakers concerning industry-wide improvements. Moreover, the findings suggest that investing in worker training is essential. Ensuring workers possess the necessary skills and knowledge to perform their tasks efficiently can enhance productivity and project outcomes. In conclusion, this study's findings emphasize the factors that can improve construction productivity in residential projects in NZ, ultimately leading to improved outcomes for all stakeholders.

This research offers a unique perspective on improving residential construction productivity in NZ by identifying and analysing specific factors that can enhance efficiency across the sector. It provides novel findings and valuable insight into possible organizational improvement strategies yet considered in the NZ residential sector.

This study explores the evolutionary relationship between multimarket contact (MMC) and competitive actions among multinational corporations (MNCs). It aims to enhance the understanding of international market competition by incorporating insights into dynamic competition and parent–subsidiary relationships.

A structured content analysis was used to identify the competitive actions of global shipping liners. The dataset includes 8,204 actions identified across nine global arenas. Data were collected from 6,553 monthly news articles on Alphaliner. The period covered is from January 1, 2015, to June 30, 2023.

The results indicate that a higher degree of MMC leads to greater competitive aggressiveness, supporting the combination of mutual forbearance and the Red Queen effect. Additionally, market importance triggers the mutual forbearance effect, whereas competitive rivalry is weaker for overlapping cross-market contacts. Furthermore, local competitive intensity increases MNCs' contact and echoes the Red Queen effect, especially for subsidiaries facing increasing pressure from local responsiveness.

Limitations include reliance on Alphaliner, potential inaccuracies from proxy variables, and unmeasured headquarters–subsidiary interactions. Future research should explore other industries and extend the study period for broader applicability and generalization.

By interlacing mutual forbearance with the Red Queen effect within a coopetition framework, managers can devise strategies to balance competition and collaboration, thereby ensuring long-term viability and growth in global markets.

This study extends the concept of MMC to the context of global shipping liners, a previously underexplored sector. Unlike earlier research, this study empirically examines MMC dynamics globally and integrates mutual forbearance and the Red Queen effect.