Impact of risk and risk awareness coupling propagation on the resilience of supply chain in a dual-layer network

A digital twin-based framework for predictive quality assurance and supply chain resilience in the automotive industry

Strategic investment in supply chain resilience: A study of fast-moving consumer goods under demand uncertainty

The impact of ESG rating divergence on supply chain resilience: The threshold effect of corporate information transparency

ESG performance, investment efficiency and supply chain resilience

Artificial intelligence and corporate innovation: A perspective based on supply chain resilience

Economic vulnerability and resilience of aquaculture supply chains in the U.S. Western region

Disruptions and resilience in construction supply chains

Fintech adoption and organizational culture: Pathways to supply chain resilience

Redefining supply chain dynamics: digitization and green innovation as catalysts for energy supply chain resilience under UN-SDGs

How does buffering-bridging alignment influence supply chain resilience? A polynomial regression analysis

AI-Driven Strategies for Supply Chain Resilience: A Review of Challenges and Solutions During Pandemics

Does risk management orientation matter for supply chain resilience? Exploring the role of triple-A supply chain capabilities

Prioritisation of critical operational factors and designing a decision-making model for attaining supply chain resilience through digitalisation

Budget constraints compel managers to prioritize digital investments that demonstrably improve supply chain resilience and mitigate vulnerabilities. This study classifies technologies based on the perceived influence over resilience capabilities reported by Supply Chain Decision Makers (SCDM) in context of an emerging economy, Brazil. Applying a quantitative design, a structured questionnaire was employed using linguistic terms. A combined method, utilizing CRITIC for weighting capabilities and Fuzzy TOPSIS Class for prioritizing technologies, developed a practical framework for digitalization investments. Results indicate that Recovery Efficiency, Redundancy, and Knowledge Management are the most important capabilities. Business Intelligence (BI) and Enterprise Resource Planning (ERP) are the most relevant digital technologies for mitigating risks and enabling faster recovery. The study academically contributes to scholars by presenting a practical framework with a methodology that can be applied to different research topics, thus providing a guide that helps SCDM prioritize investments in digital technologies, thereby enhancing Resilience.

Exposed to unprecedented internal as well as external levels of uncertainties, supply chains have become much more vulnerable than ever before. Although artificial intelligence holds transformative potential to create resilient supply chains, its adoption remains intricate particularly within the industrial zones of developing economies. Previous studies have indicated that there is paucity of research in connection with artificial intelligence and supply chain risk management. Collecting data from twenty-six participants, this qualitative study revolves seeks to explore the impediments which hinder Pakistani textile and clothing firms from adopting artificial intelligence to control supply chain disruptions. Both thematic and content summative analysis techniques were used to attain interpretative depth as well as empirical substantiation. Lack of general understanding and trust in artificial intelligence, digital infrastructure deficits, high cost of investment, scarcity or substandard quality of operational and supply chain data and confidentiality and security issues are the core constraints The outcomes of the investigation are immensely valuable in developing pragmatic strategies to leverage artificial intelligence effectively in order in addressing supply chain risks.

ABSTRACT This study evaluates the effectiveness of policy frameworks that support Maritime Canada’s beef sector, and the regional food service industry by adopting the New Institutional Economics (NIE) theoryA thematic content analysis was conducted using 31 policy documents in MAXQDA. It was found that current policies support sustainable beef production and marketing and, indirectly, impact the food service sector. Opportunities exist to enhance local meat sourcing and supply chain stability for restaurants and institutional buyers. The policy instruments influence sourcing costs and supply chain resilience in the foodservice sector by improving production efficiency and fostering local market integration.

Purpose Although the effectiveness of emergency hospital projects in responding to pandemics and public health crises is well documented, the complexity inherent in these projects—characterized by compressed schedules and stringent infection control protocols—remains insufficiently examined, often resulting in suboptimal project performance. This study aims to advance the understanding and management of such project complexity by systematically investigating its intrinsic attributes and interdependencies. Design/methodology/approach A two-stage hybrid approach combining qualitative and quantitative methods was used. Initially, an emergency hospital project complexity framework was developed through content analysis. Subsequently, the interrelationships and hierarchical structure among the identified complexity attributes were analyzed using the Decision-Making Trial and Evaluation Laboratory Analysis coupled with Interpretive Structural Modeling (DEMATEL-ISM) methodology. Findings The results reveal that the complexity framework comprises eight dimensions and 25 corresponding indicators. Both complexity dimensions and indicators are categorized into root, mediator, and outcome groups based on their hierarchical roles. Environmental complexity and goal complexity are identified as root-group dimensions. Within the indicators, constantly evolving pandemic conditions and the laborious nature of installation tasks are classified as root-group attributes. Practical implications Practitioners are provided with systematic tools to manage complexity during the construction phase, facilitating improved risk and uncertainty mitigation. Emphasis is placed on adopting precautionary measures, enhancement of improvisational capabilities, prioritization of time goals, integration of modular design and digital technologies, and reinforcement of supply chain resilience. These insights hold relevance for a broader range of public emergency response projects. Originality/value This study makes three theoretical contributions. First, by offering novel insights into the attributes of complexity and highlighting the significance of their interrelationships, this study contributes to a systematic comprehension of complexity within pandemic-driven construction projects. Second, as one of the earliest efforts to comprehensively articulate the complexity of emergency hospital projects, it introduces a framework structured around a “root–mediator–outcome” three-tier hierarchy that elucidates the interdependent nature of complexity attributes. Third, by exploring unique characteristics and complex causal relationships, this research expands the theoretical understanding of project complexity in emergency hospital construction and other public emergency response initiatives.

To reveal how digital twin empowers electric vehicle supply chain resilience, this study first proposes a novel “Human–Machine–Material–Environment” system architecture. Then, it employs dynamic fsQCA on data from 27 electric vehicle companies to explore the underlying configurational mechanisms. The results reveal that digital twin empowers electric vehicle supply chain resilience not through singular factors, but through multiple, equally effective configurations of its core dimensions. This study identifies six types of high-resilience pathways, such as “dual-driven by twin and safety” and “comprehensive upgrade digital twin”. This demonstrates that no universal best pathway exists. This finding of equifinality is complemented by causal asymmetry, as the paths leading to non-high resilience are not mere opposites of the successful ones. Across time periods, data security management, human–machine collaboration, and digital twin applications consistently emerge as core prerequisites for improving supply chain resilience. By introducing digital twin, this study expands the theoretical boundaries of electric vehicle supply chain resilience research and provides new analytical perspectives and frameworks.

This research aims to investigate the impact of supply chain resilience and integration on the performance of FMCG firms in Bangladesh. The primary objective is to synthesize existing literature to comprehend how these two interdependent capabilities enhance operational efficiency, delivery reliability, flexibility, innovation, and customer satisfaction in a developing economy. This research used a narrative and integrative review methodology, examining peer-reviewed journal articles, conference proceedings, and industry reports mostly published in the last decade. The technique included the thematic classification of literature into resilience, integration, and performance dimensions, followed by an iterative process of synthesis and interpretation. The study highlights findings that supply chain resilience, which includes adaptation, flexibility, visibility, redundancy, and recovery capacity, allows organizations to successfully absorb and recover from disturbances. The outcomes of the study emphasize the significant role of Supply chain integration to facilitate coordination, information exchange, and cooperation, hence enhancing resilience. Therefore, the research offers actionable insights for managers in cultivating robust and cohesive supply chains, governments in fostering enabling infrastructure and technology integration, and industry stakeholders in advancing collaborative networks.