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Configuring strategies to ensure a health service provider’s resilience when extreme disruptions occur is not simple. Optimal configuration in such circumstances is rare. Therefore, this research has relied on the dynamic capability view (DCV) to develop a decision-support framework for configuring resilience strategies that will mitigate the worst challenges and improve the performance of health service providers during “extreme” disruptive events.

The research adopted a multi-study, multi-method approach comprising interviews, quality function deployment (QFD), and fuzzy set qualitative comparative analysis (fsQCA).

The findings reveal that, during a crisis, standalone resilience strategies are not enough. To guarantee performance, healthcare services require a combination of resilience strategies and a negation of challenges.

This research extends our current knowledge of healthcare operational management by offering optimal configurations of resilience strategies to manage performance during extreme disruptions. Thus, it offers strategic insights into how health-service managers can be more resilient during a crisis.

Blockchain technology, renowned for its decentralization, security, reliability, and data integrity, has the potential to revolutionize businesses globally. However, its full potential remains unrealized due to adoption barriers, necessitating further studies to address these challenges. Identifying these barriers is crucial for businesses and practitioners to effectively tackle them. This systematic review analyzed 70 eligible studies out of 1944 gathered from various databases to understand and identify common blockchain adoption barriers. The Technology–Organization–Environment (TOE) framework was the most popular theory used in these studies. Despite differences in variable definitions, financial constraints, lack of stakeholder collaboration and coordination, and social influences like resistance to change and negative perceptions emerged as the top three barriers. The supply chain domain had the highest number of studies on blockchain adoption. Notably, there was a significant increase in studies addressing blockchain adoption in 2023, comprising 34.2% of the total reviewed studies. This review provides a comprehensive overview of identified barriers, serving as a valuable foundation for future research. Understanding these challenges allows researchers to design targeted studies aimed at developing solutions, strategies, and innovations to overcome obstacles hindering blockchain adoption.

This study aims to investigate the mediating role of green employee empowerment (GEE) in the relationship between green discipline management and green involvement with green employee creativity and innovation (GECI) within public universities in Yemen. The research explores how the components of green human resource management (GHRM) influence green creativity and innovation through employee empowerment.

The study utilizes both primary and secondary data. The primary data were gathered through structured questionnaires distributed to 363 employees in public universities in Yemen. The data were analyzed using structural equation modeling (SEM) with AMOS to assess the relationships among the variables.

The findings reveal that green discipline management and green involvement have a significantly positive impact on GEE and GECI. Furthermore, GEE partially mediates this relationship, which demonstrates that empowered employees are more likely to contribute to environmentally sustainable creativity and innovation.

This research helps better understand how GHRM practices, such as discipline management and involvement, can promote green creativity and innovation through employee empowerment. By examining the mediating role of GEE, the study provides valuable insights for academic institutions and organizational leaders seeking to integrate sustainability into human resource (HR) practices and policies.

The research on entrepreneurial leadership (EL) and supply chain resilience (SCR) relationship is still in its exploration stage. Previous research indicates that EL is important for enhancing supply chain performance, including its resilience. However, the conditions through which EL affects SCR remain unclear. The purpose of this study is to examine the effect of EL on SCR in the context of SMEs, in addition to explore the combined moderating effects of big data analytics capability (BDAC) and environmental dynamism (ED) in the EL–SCR relationship.

Hierarchical regression analysis via PROCESS Macro was used to analyze the data collected from manufacturing SMEs in India.

The findings reveal that EL positively and significantly affects SCR. Importantly, BDAC actually positively moderates the EL–SCR relationship regardless of the level of dynamism of the business environment.

This research expands the existing body of knowledge on EL and SCR within the context of developing countries. The findings offer useful insights for SME managers and decision-makers, who are anticipated to consider the adoption of BDAC in their firms. This has implications that with BDAC adoption, it is anticipated that SMEs will be able to take advantage of the full potential of EL to enhance their SCR regardless of the level of dynamism of the business environment.

Despite the growing interest in enhancing mass customization capability (MCC), firms still have little knowledge of dealing with the superimposed challenges of increased market uncertainty and supply chain disruptions. Based on the dynamic capability view, this study focuses on the impacts of frequent sensing and reconfiguring processes on MCC and the mediating roles of proactive and reactive supply chain resilience (SCR).

We collected survey data from 277 manufacturing firms and conducted a structural equation model to test hypotheses.

The results reveal that although its direct effect on MCC is insignificant, sensing process improves MCC indirectly via reactive SCR. Our findings also show that reconfiguring process enhances MCC both directly and indirectly via reactive SCR.

This study provides theoretical and practical insights into how to combine dynamic capability and SCR to strengthen MCC.

This study aims to examine Musina municipality’s tourism development status and plans with existing documents and respondents’ responses on their envisaged implications on tourism development and sustainability initiatives in Vhembe District, Limpopo Province, South Africa.

Surveys, interviews and focus group discussions, supplemented by field observation and document reviews, gray literature alongside published literature, were applied. Subsequently, Microsoft Excel and cross-tabulation analysis orchestrated the analysis of the data.

The policy and strategy aspects contributing to the previous and actual tourism statuses in Musina municipality are defined. The study concludes that Musina Municipality has rich tourism possibilities but lacks a better tourism strategy to empower local communities. Nonetheless, it dwells in the most tourism-based landscape within the Vhembe District of Limpopo.

Musina Municipality is one of the driest areas in the north of Limpopo Province in South Africa. It is also marked by impoverished rural communities. Studies on sustainable tourism and development have increased in recent years. However, rare studies specialize in synergies within various forms of tourism. Also, significant resources to advance local communities in rural areas are not sufficiently appreciated.

This study aims to investigate the dynamic capabilities of wineries, focusing on sensing and its role in enabling digital innovation. Furthermore, it explores the role of blockchain technology (BCT) in validating credence attributes of wine, emphasising blockchain as a strategic asset that enhances the ability of wineries to innovate and respond to changing market conditions.

The study adopts an exploratory approach based on a longitudinal, single-case study of the Argentinian Costaflores Organic Winery.

Findings reveal that integrating digital disruptive innovations such as blockchain can strategically position wineries to better meet emerging consumer preferences and market trends. Blockchain simultaneously acts as both a mediator and a moderator. As a mediator, it facilitates the validation of credence attributes of wine such as authenticity and sustainability, enhancing customer trust and loyalty. As a moderator, it influences the strength and effectiveness of the relationship between sensing and innovation capabilities. This enables wineries to more effectively respond to changing consumer requirements and market trends and improve operational performance.

The study was limited by its focus on a single case study of the Argentinian Costaflores Organic Winery, which may affect the generalisability of the findings. However, the study provides valuable insights into the strategic adaptation and competitive positioning of wineries in response to the continuing market challenges. It significantly contributes to the understanding of integrating digital disruptive innovations as strategic assets in the agri-food sector, particularly in the wine sector.

This study addresses a significant research gap by exploring how BCT facilitates the organisation of sensing capabilities. It contributes to the understanding of how the wineries’ sensing capabilities both influence and are influenced by the adoption of BCT, particularly in the context of innovation enabling and improved operational performance.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

Blockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships.

A three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score.

The findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group.

The outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains.

The research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.