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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.

This paper aims to illuminate the nuanced dynamics of green supply chain management (GSCM), specifically focusing on the intersections of supplier relationships, supplier governance and organizational agility. Recognizing a gap in the understanding of how these elements confluence to promote green purchasing, the paper uses a quantitative study on data collected from the Australian food industry. Advanced analysis techniques provide empirical evidence underscoring the pivotal roles these elements play, expanding on current GSCM literature within a resource-based view.

This study, based on a questionnaire sent to Australian food professionals, used higher-order reflective constructs to assess supplier relationships and governance. Data was analyzed using partial least squares structural equation modeling and Hayes PROCESS, considering factors like firm revenue and manager experience. Both the reliability of measures and mediation hypotheses were stringently validated using established guidelines.

The comprehensive study validated supplier governance's key influence on green purchasing and supplier relationships. Notably, organizational agility emerged as a crucial mediator, underscoring the interplay of these constructs. Concurrently, the reflective measurement model exhibited robust validity and reliability. Interestingly, demographic factors such as company size, revenue and managerial experience showed no discernible impact on green purchasing practices.

In the Australian food sector, supplier governance and relationships are pivotal for advancing green purchasing. This study emphasizes the value of organizational agility in amplifying these practices. Managers, when aligning with supplier relationships enhanced by communication and mutual aid, can foster robust green initiatives. Embracing these insights and the critical importance of supplier governance, managers can drive more sustainable, informed supply chain decisions in the industry.

In pursuit of understanding the relationship between supplier governance, supplier relationships and green purchasing, this research uniquely situates itself within the resource-based view (RBV) to reveal critical theoretical and practical implications. By focusing on the Australian food industry, the study spotlights the often-overlooked mediating role of organizational agility in linking supplier relationships with green purchasing efforts. In doing so, this research not only strengthens the argument for fortified supplier relationships – as a catalyst for enhancing agility and thereby green practices – but also re-contextualizes the RBV in a fresh light. This new perspective provides managers with an enriched model, emphasizing the imperative of solid supplier governance for sustainable, agile and green supply chain operations in the food domain.

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 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.

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.

The present study aims to identify the antecedents and consequences of blockchain adoption in the wine industry from the absorptive capacity perspective through a multiple case study approach.

A multiple case study approach was utilized, wherein data was gathered through semi-structured interviews and secondary sources of information from the five Italian innovative wineries.

The results show that the dynamic capabilities of wineries and the creation of strategic partnerships are common conditions for the adoption of blockchain technology (BCT). In addition, findings reveal that creating value for all supply chain stakeholders and preventing counterfeit products are the most important consequences of BCT adoption.

This study fills a gap in the literature by investigating the drivers of BCT technology adoption under two theoretical lenses, Absorptive capacity and Dynamic capability theories, confirming the usefulness of these two theories in explaining the process of innovation adoption.

The originality of our research study lies in its investigation of the antecedents and consequences of BCT adoption in the wine supply chain, focusing specifically on the role of dynamic capabilities, knowledge acquisition and assimilation, strategic partnerships and open interactions with external actors in driving technological innovation and the successful implementation of BCT in the wine industry. By offering empirical data on the drivers and impacts of BCT adoption, as well as theoretical implications for technological innovation and value creation in the wine sector, our study contributes to filling gaps in the existing literature and provides practical insights for wineries and AgTechs seeking to integrate BCT into their business models.

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.