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The purpose of this research study was to explore the relationship between adaptive performance and work-related indicators of psychological well-being among ‘The Episcopal Church bishops.’

Hierarchical regression models were used in this research study to explore the relationship between adaptive performance and work-related psychological health.

There was a positive correlation between adaptive performance and work-related psychological health. Demographic factors did not correlate to adaptive performance. However, a negative correlation was observed between the years ordained as a bishop and the interpersonal adaptability dimension of adaptive performance.

Managing work stress has been revealed as an integral part of adaptive performance and satisfaction in ministry. Interpersonal adaptability and reactivity could be understood, then, as useful vehicles for increasing the capacity of bishops to manage work stress. In this research, the authors applied the Scale for Individual Adaptive Performance and the two scales Scale of Satisfaction in Ministry and Scale of Emotional Exhaustion in Ministry .

The results provided insights into the behaviors necessary for adequate development of bishops in their role. The religious landscape was becoming more challenging from a revenue generation perspective. The resultant complexity and the financial strain would necessitate the need for development of different models of ministry for long-term sustainability. This could further necessitate a different set of knowledge creation related to a set of behavioral capacities like those of adaptive performance. Such insights would assist in the promotion and development of greater work-related psychological health in bishops while deepening their ability to deal with complex and uncertain environments. Furthermore, this would increase satisfaction in ministry through improved workplace management skills.

Presently, very few studies empirically established the developmental needs of bishops as they entered, learned and grew into their leadership roles. Such insights would allow the formation programs for new bishops to be grounded in empirical data. Furthermore, this research study examined a largely unexplored population. This would provide a basis for a larger research agenda related to adaptive performance in judicatory leaders and their work-related psychological health. Consequently, it is posited that improved psychological health would result in better workplace learning.

This study aims to explore how to overcome and address the loss of exploratory innovation, thereby achieving greater success in exploratory innovation. This phenomenon of loss occurs when enterprises decrease their investment in and engagement with exploratory innovation, ultimately leading to an insufficient amount of such innovation efforts. Drawing on dynamic capabilities, this study investigates the relationship between organizational foresight and exploratory innovation and examines the moderating role of breakthrough orientation/financial orientation.

This study used survey data collected from 296 Chinese high-tech companies in multiple industries and sectors.

The evidence produced by this study reveals that three elements of organizational foresight (i.e. environmental scanning capabilities, strategic selection capabilities and integrating capabilities) positively influence exploratory innovation. Furthermore, this positive effect is strengthened in the context of a high-breakthrough orientation. Moreover, the relationships among environmental scanning capabilities, strategic selection capabilities and exploratory innovation become weaker as an enterprise’s financial orientation increases, whereas a strong financial orientation does not affect the relationship between integrating capabilities and exploratory innovation.

Ambidexterity is key to successful enterprise innovation. Compared with exploitative innovation, it is by no means easy to engage in exploratory innovation, which is especially important in high-tech companies. While the loss of exploratory innovation has been observed, few empirical studies have explored ways to promote exploratory innovation more effectively. A key research implication of this study pertains to the role of organizational foresight in the improvement of exploratory innovation in the context of high-tech companies.

This paper contributes to the broader literature on exploratory innovation and organizational foresight and provides practical guidance for high-tech companies regarding ways of avoiding the loss of exploratory innovation and becoming more successful at exploratory innovation.

The literature mainly concentrates on the relationships between externally oriented digital transformation (ExtDT), big data analytics capability (BDAC) and business model innovation (BMI) from an intra-organizational perspective. However, it is acknowledged that the external environment shapes the firm's strategy and affects innovation outcomes. Embracing an external environment perspective, the authors aim to fill this gap. The authors develop and test a moderated mediation model linking ExtDT to BMI. Drawing on the dynamic capabilities view, the authors' model posits that the effect of ExtDT on BMI is mediated by BDAC, while environmental hostility (EH) moderates these relationships.

The authors adopt a quantitative approach based on bootstrapped partial least square-path modeling (PLS-PM) to analyze a sample of 200 Italian data-driven SMEs.

The results highlight that ExtDT and BDAC positively affect BMI. The findings also indicate that ExtDT is an antecedent of BMI that is less disruptive than BDAC. The authors also obtain that ExtDT solely does not lead to BDAC. Interestingly, the effect of BDAC on BMI increases when EH moderates the relationship.

Analyzing the relationships between ExtDT, BDAC and BMI from an external environment perspective is an underexplored area of research. The authors contribute to this topic by evaluating how EH interacts with ExtDT and BDAC toward BMI.

In this study, the impact of access to electricity on poverty reduction for Botswana is examined using the annual data from 1990 to 2021. The study was motivated by the need to establish if access to electricity could be a panacea on poverty reduction in Botswana. Given that the United Nations Sustainable Development Goals deadline is fast approaching, and Botswana being one of the signatories, is expected to end poverty in all its forms – Goal 1. Establishing the role that electrification plays in poverty alleviation, helps in refocusing Botswana’s poverty alleviation strategies on factors that have high impact on poverty. The main objective of this study, therefore, is to investigate the relationship between poverty alleviation and access to electricity in Botswana.

The study uses the autoregressive distributed lag (ARDL) approach to investigate the nature of the relations. Two poverty proxies were used in this study namely, household consumption expenditure and life expectancy.

The study found access to electricity to reduce poverty in the long run and in the short run, regardless of the poverty measure used. Thus, access to electricity plays an important role in poverty alleviation and Botswana is recommended to continue with the rural and urban electrification initiatives.

The study explores the impact of access to electricity on poverty reduction in Botswana, a departure from the current studies that examined the same relationship using energy consumption in general. This is on the back of increasing dependence of economic activities on electricity as a major source of energy.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

In servitization research, there has been a call to move further toward the development of business models based on a service approach. This article aims to answer this call by adopting service logic (SL) and developing strategies and organizational resources and processes to create a service-centric business model called servification, defined as the process of identifying and developing strategies and organizational resources and processes to create a business model based on SL.

This article is conceptual and extends servitization in the direction of service-centric business model innovation by drawing on and extending SL.

The article defines service as a higher-order concept according to SL and develops the concept of a helping strategy as the foundation for a service-based business model. Further, it develops a typology of organizational resources and processes that must be developed for the emergence of such a business model.

Since this article is the first to conceptually develop servification, more both theoretical and empirical research is naturally required. The development of servification takes servitization in the direction of service-based business model innovation and also contributes to the research on SL.

Servification enables the development of service-centric strategies and organizational resources and processes and service-based business models.

This article is the first to adopt SL in studies of business model innovation.

Railways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.

Overall, 26 interviews were conducted with 21 participants from industry and academia.

The results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.

The authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

In this case study, we examine how a citrus peel valorising company based in the Netherlands was able to adopt a circular business model while navigating regulatory, managerial, and supply chain-related barriers.

In-depth, semi-structured interviews with key personnel in the company, notes from field observations, photographs of the production process, and documents from a legal judgement served as data for this single, qualitative case study. Data were coded inductively using the in vivo technique and were further developed into four themes and a case description.

Results from our study indicate that the regulatory and political contexts in the Netherlands were critical to the company’s success. Like in the case of most fruitful industrial symbioses, partnerships founded on mutual trust and economically appealing value propositions played a crucial role in ensuring commercial viability. Collaborating with larger corporations and maintaining transparent communication with stakeholders were also significant contributing factors. Lastly, employees’ outlook towards circularity combined with their willingness to learn new skills were important driving factors as well.

In addition to expanding the scholarship on the adoption of circular business models, this research offers novel insights to policymakers and practitioners. It provides empirical evidence regarding the importance of public awareness, adaptable legislation, and harmonised policy goals for supporting sustainable entrepreneurship in the circular economy.

This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.

In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.

The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.

By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.