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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.

Natural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. Resilient functions in the supply chain are required to absorb the impact of resultant disruptions in perishable food supply chains (FSC). The present study identifies specific resilient functions to overcome the problems created by natural disasters in the FSC context.

The quality function deployment (QFD) method is utilized for identifying these relations. Further, fuzzy term sets and the analytical hierarchy process (AHP) are used to prioritize the identified problems. The results obtained are employed to construct a QFD matrix with the solutions, followed by the technique for order of preference by similarity to the ideal solution (TOPSIS) on the house of quality (HOQ) matrix between the identified problems and functions.

The results from the study reflect that the shortage of employees in affected areas is the major problem caused by a natural disaster, followed by the food movement problem. The results from the analysis matrix conclude that information sharing should be kept at the highest priority by policymakers to build and increase resilient functions and sustainable crisis management in a perishable FSC network.

The study suggests practical implications for managing a FSC crisis during a natural disaster. The unique contribution of this research lies in finding the correlation and importance ranking among different resilience functions, which is crucial for managing a FSC crisis during a natural disaster.

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.

The study's goal is to assess the influence of multichannel integration quality on perceived value, service convenience and service experience in a multichannel banking context. Furthermore, the study investigated the impact of perceived value, service convenience and service experience on positive electronic word of mouth (e-WoM).

Data were collected from 527 respondents using online surveys distributed on various social media platforms in Ghana. The data were analysed using the partial least squares approach to structural equation modelling.

The results showed that multichannel integration quality influences consumers' perceptions of value and service experience favourably. It also showed that the two factors influencing service convenience were service experience and perceived value. Further, the research revealed a significant relationship between positive electronic word of mouth and perceived value, service convenience and service experience.

The study adds to the existing body of knowledge on multichannel integration by empirically testing the relationship between multichannel integration quality and consumer response in the context of multichannel banking.

The study is one of a few that provide important insights into the growing body of literature on multichannel integration quality from the consumers' perspective. The study further develops a model that explicates the relationship between multichannel integration quality, perceived value, service convenience and e-WoM.

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.

This viewpoint article provides insights into the potential role of blockchain technology in addressing crucial issues facing society and global supply chains. We seek to bring more attention to blockchain capabilities for social good in global supply chain settings.

This viewpoint paper provides a perspective on some major current social good and global supply chain issues. The method is based on the current state-of-the-art debate and discourse on blockchain technology as an enabler for social good. Literature, practice and author knowledge concerning the topic are used to support the concepts and actions presented in this study.

Social good, sustainable supply chains and blockchain technology have great promise and potential. Joint research and practice evaluation are essential to reveal the full potential and applications of blockchain technology and address the trade-offs and challenges. Theory and modeling are needed for understanding and advancing these topical areas.

Blockchain application for social good is a new area. We call for transdisciplinary research and development to advance this emerging area. We propose many open questions, and many more are arising in this blockchain and benchmarking community. The impact of this research can be substantive as we can actually seek to make our world a better place as we focus on social good.