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Prefabricated products are continually entering the building construction market; yet, the decision to use prefabricated products in a construction project is based mostly on personal preferences and the evaluation of direct costs. Researchers and practitioners have debated appropriate measurement systems for evaluating the impacts of prefabricated products and for comparing them with conventional on-site construction practices. The more advanced, cost–benefit approach to evaluating prefabricated products often inspires controversy because it may generate inaccurate results when converting non-monetary effects into costs. As prefabrication may affect multiple organisations and product subsystems, the method used to decide on production methods should consider multiple direct and indirect impacts, including nonmonetary ones. Thus, this study aims to develop a multi-criteria method to evaluate both the monetary and non-monetary impacts of prefabrication solutions to facilitate decision-making on whether to use prefabricated products.

Drawing upon a literature review, this research suggests a multi-criteria method that combines the choosing-by-advantage approach with a cost–benefit analysis. The method was presented for validation in focus group discussions and tested in a case involving a prefabricated bathroom.

The analysis indicates that the method helps a project’s stakeholders communicate about the relative merits of prefabrication and conventional construction while facilitating the final decision of whether to use prefabrication.

This research contributes a method of evaluating the monetary and non-monetary impacts of prefabricated products. The research underlines the need to evaluate the diverse benefits and sacrifices that stakeholder face when considering production methods in construction.

This paper investigates the constraints an organisation faces when using recruitment agencies and having to trade-off between the speed of hiring a candidate, the cost of a candidate and the match of the candidate against the job requirements across different job seniorities. We analyse how technology can shift the cost and hiring speed in spite of these constraints.

The research design is exploratory, quantitative and cross-sectional. The study employed a two-factor, unbalanced class Analysis of Variance (ANOVA) including interaction effects to test the difference between the means of the class of interest and a control class.

Our empirical findings confirm that (1) the technological innovation of a recruitment agency marketplace can liberate organisations from their time, cost and quality hiring constraints, accelerating the time to hire by four times and reducing costs by over 12%, and (2) these results hold across varying role seniority levels.

This study contributes to the existing literature in three ways: (1) it introduces the recruitment triangle from project management into the recruitment literature; (2) it demonstrates how technological innovations such as recruitment agency marketplaces are able to provide a shift in the constraints posed by the recruitment triangle.

This study aims to examine the role of supplier selection and supplier monitoring in public procurement efficiency in terms of cost reduction in Tanzania.

A structured questionnaire was used to collect cross-sectional survey data from 179 public procuring entities in Tanzania. Structural equation modelling (SEM) was used to analyse the collected data.

The findings revealed that supplier selection and supplier monitoring are positive and significant predictors of public procurement efficiency in terms of cost reduction.

This study was conducted in Tanzanian public procurement contexts, so generalisations should be made with caution. Also, this study collected cross-sectional data; other studies may consider longitudinal data.

This study provides procurement practitioners with insights into selecting the proper suppliers and embracing supplier monitoring to achieve procurement efficiency in terms of cost reduction.

This study examines the effects of supplier selection and supplier monitoring on procurement cost reduction as a measure of public procurement efficiency in the Tanzanian context. Consequently, it provides empirical evidence of supplier management practices in the public procurement context.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The ability of companies to develop organizational resilience before, during and after crises is crucial for their development and growth. The future forecasts increasingly more crises, thus this paper aims at identifying key topics around organizational resilience in COVID-19 times, differentiating them of pre-crisis literature and synthesizing them into a research framework.

Based on Web of Science and Scopus, the authors analysed the content of the only twenty-seven VHB-ranked primary studies discussing organizational resilience during COVID-19, providing a complete survey of this research area.

Following a content analysis, the authors identified main topics of interest for researchers at the moment of COVID-19, how it differed from before this adversity and provide an outlook on future research. The results presented include in the COVID-19 context: an adapted definition of organizational resilience, key theoretical framework, insights for future research. Some topics have been found to be increasingly more important during COVID-19 (i.e. digitalization, partnerships and learning) while others have been less explored although present in pre-COVID-19 research on organizational resilience (i.e. dynamic capabilities, anticipation and preparedness).

Understanding key issues in global disruptions could help practitioners in fostering resilience as much as researchers in identifying new ways to advance and maintain resilience. This paper differs from other reviews by providing a full text analysis, based on qualitative content analysis, of all ranked published papers in the considered period.

Drawing on the conservation of resources (COR) theory, this study aims to examine the effects of servant leadership and despotic leadership on employees’ happiness at work (HAW) through job crafting.

To test the hypothesized relationships, the data were collected from 309 Pakistani employees. Structural equation modeling was used to analyze the data.

The findings showed that servant leadership is an optimal leadership style for creating employees’ HAW. In addition, job crafting was found to mediate the effects of servant leadership on employees’ broad-based positive attitudinal outcome (HAW). Moreover, results showed that despotic leadership negatively influences employees’ HAW through job crafting.

This study is novel as it investigates how newer forms of positive (servant) and negative (despotic) leadership styles influence employees’ multidimensional attitudinal outcome (HAW) via job crafting. By doing so, this research extends the nomological network of servant leadership, despotic leadership, job crafting and HAW.

The role of procurement managers is crucial for diffusing sustainability throughout the supply chain. Whether or not they are willing to pay for sustainability is an important and not yet fully understood question. The authors examine antecedents and consequences of their willingness to pay (WTP) for sustainability.

The authors develop a multi-level framework to examine the WTP for sustainability in a B2B context. The authors test this multi-level framework with 372 procurement managers from multiple sectors and countries using partial least squares structural equation modeling.

The authors find that individual values of procurement managers and institutional pressures directly, while ethical organizational culture indirectly influence WTP for sustainability. Functional and cognitive competencies of procurement managers improve the sustainability of procurement, but not WTP for sustainability. Importantly, WTP for sustainability directly influences the performance of the procurement function which in turn is positively associated with increased organizational performance.

The study, examining the interplay between individual, organizational and contextual factors, provides empirical evidence on the pivotal role of procurement managers in diffusing sustainability throughout the supply chain. The findings of the study, on the one hand, contribute to the literature on operations management and sustainability, and on the other hand, guide policy and managerial actions.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.