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Academics and practitioners have long acknowledged the potential of multiagent systems (MAS) to automate and autonomize decision-making in logistics and supply chain networks. Despite the manifold promises of MAS, industry adoption is lagging behind, and the exact benefits of these systems remain unclear. This study aims to fill this knowledge gap by analyzing 11 specific MAS use cases, highlighting their benefits, clarifying how they can help enhance logistics network resilience and identifying existing barriers.

A three-stage Delphi study was conducted with 18 industry experts. In the first round, these experts identified 11 use cases of MAS and their potential benefits, as well as any barriers that could hinder their adoption. In the second round, they assessed the identified use cases with regard to their potential to enhance logistics network resilience and improve organizational productivity. Furthermore, they estimated the complexity of MAS implementation. In the third round, the experts reassessed their evaluations in light of the evaluations of the other study participants.

This study proposes 11 specific MAS use cases and illustrates their potential for increasing logistics network resilience and enhancing organizational performance due to autonomous decision-making in informational processes. Furthermore, this study discusses important barriers for MAS, such as lack of standardization, insufficient technological maturity, soaring costs, complex change management and a lack of existing use cases. From a theoretical perspective, it is shown how MAS can contribute to resilience research in supply chain management.

The identification and assessment of diverse MAS use cases informs managers about the potential of this technology and the barriers that need to be overcome.

This study fills a gap in the literature by providing a thorough and up-to-date assessment of the potential of MAS for logistics and supply chain management. To the best of the authors’ knowledge, this is the first study to investigate the relevance of MAS for logistics network resilience using the Delphi method.

In business-to-business interactions, conflicts are inevitable, and conflict-handling strategies that consider different variables improve the decision-making process of actors. This study aims to reveal the role of power and criticality in conflict-handling research in logistics service networks.

A 2 × 2 between-subject experimental design with four different scenarios was used. One hundred sixty logistics service actors completed an online questionnaire. Data were analyzed with ANOVA and paired sample t-tests using the SPSS 28.0 program.

In comparative scenarios involving high and low power dynamics, individuals with high power and high criticality situations are more inclined to favor the dominating strategy compared to low-power and low-criticality contexts. However, when faced with specific circumstances characterized by both high power and high criticality, actors tend to prioritize the integrating strategy initially, followed by the dominating and obliging strategies in that order. Notably, the statistical analysis revealed no significant interaction effect between criticality and power concerning the integrating, obliging and dominating conflict-handling strategies.

This study used an experimental approach to investigate criticality and power as contextual elements in determining conflict-handling strategies in an inter-firm environment within logistics service networks. This study is particularly groundbreaking in its knowledge of the relationship among power dynamics, conflict criticality and conflict-handling strategies.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

As the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.

A causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.

The result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.

In this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.

The purpose of this paper is to explore how companies approach the management of cyber and information risks in their supply chain, what initiatives they adopt to this aim, and to what extent along the supply chain. In fact, the increasing level of connectivity is transforming supply chains, and it creates new opportunities but also new risks in the cyber space. Hence, cyber supply chain risk management (CSCRM) is emerging as a new management construct. The ultimate aim is to help organizations in understanding and improving the CSCRM process and cyber resilience in their supply chains.

This research relied on a qualitative approach based on a comparative case study analysis involving five large multinational companies with headquarters, or branches, in the UK.

Results highlight the importance for CSCRM to shift the viewpoint from the traditional focus on companies’ internal information technology (IT) infrastructure, able to “firewall themselves” only, to the whole supply chain with a cross-functional approach; initiatives for CSCRM are mainly adopted to “respond” and “recover” without a well-rounded approach to supply chain resilience for a long-term capacity to adapt to changes according to an evolutionary approach. Initiatives are adopted at a firm/dyadic level, and a network perspective is missing.

This paper extends the current theory on cyber and information risks in supply chains, as a combination of supply chain risk management and resilience, and information risk management. It provides an analysis and classification of cyber and information risks, sources of risks and initiatives to managing them according to a supply chain perspective, along with an investigation of their adoption across the supply chain. It also studies how the concept of resilience has been deployed in the CSCRM process by companies. By laying the first empirical foundations of the subject, this study stimulates further research on the challenges and drivers of initiatives and coordination mechanisms for CSCRM at a supply chain network level.

Results invite companies to break the “silos” of their activities in CSCRM, embracing the whole supply chain network for better resilience. The adoption of IT security initiatives should be combined with organisational ones and extended beyond the dyad. Where applicable, initiatives should be bi-directional to involve supply chain partners, remove the typical isolation in the CSCRM process and leverage the value of information. Decisions on investments in CSCRM should involve also supply chain managers according to a holistic approach.

A supply chain perspective in the existing scientific contributions is missing in the management of cyber and information risk. This is one of the first empirical studies dealing with this interdisciplinary subject, focusing on risks that are now very high in the companies’ agenda, but still overlooked. It contributes to theory on information risk because it addresses cyber and information risks in massively connected supply chains through a holistic approach that includes technology, people and processes at an extended level that goes beyond the dyad.

To be able to continuously provide affordable services to consumers, managers of critical infrastructure (CI) maintenance supply networks have to balance investments in resilience with costs. At the same time, CI providers need to consider factors that influence resilience such as the geographical spread or the location of the network. This study aims to contextualize supply chain resilience knowledge by exploring how maintenance resource configurations impact resilience and costs in CI supply networks.

An in-depth longitudinal single case study of a representative CI provider that has centralized its maintenance supply network is used. Data were collected before and after the change to evaluate the effect of the changes on the maintenance supply network.

This study shows that in this specific CI maintenance context, structural resource choices such as the quantity or location of spare parts and tools, the creation and exploitation of tacit knowledge and staff motivation impact both resilience and costs due to geographical spread, network location and other network properties.

This study extends general supply chain resilience knowledge to a new setting (i.e. CI) and shows how existing insights apply in this context. More specifically, it is shown that even in engineered supply networks there is a need to consider the effect of human agency on resilience as the creation and exploitation of tacit knowledge are of immense importance in managing the network. In addition, the relationship between normal accidents theory and high reliability theory (HRT) is revisited as findings indicate that HRT is also important after a disruption has taken place.

The increasing risk of natural disasters is challenging humanitarian actors to create resilient disaster management systems. However, the role of the private sector in disaster management operations (DMOs) is not as prominent as the role played by (inter)governmental agencies. This article aims to investigate the relationship of collaboration and resilience in disaster management supply networks (DMSNs).

Supply network resilience criteria were defined as robustness, flexibility, velocity and visibility based on the literature review. DMSN capabilities were identified characterising each resilience criterion through the development of the Collaboration–Resilience (COLRES) Analysis Framework for DMSNs. This theoretical model was then applied to an empirical case study in the Philippines using semi-structured interviews for data gathering.

A total of 46 cross-sector collaboration activities were identified across four disaster management phases and linked to the resilience criteria. A causal analysis of each collaboration activity and its outcome was conducted to identify relationships between collaboration types and resilience constructs. Based on these results, patterns were identified, and dependencies between collaboration and resilience were defined. Collective DMSN resilience (DMSNRES) enabled by existing cross-sector collaboration activities was evaluated against a future disaster scenario to identify resilience gaps. These gaps were used to recognise new cross-sector collaboration opportunities, thereby illustrating the continuous process of resilience building.

This research provides new insights on how private sector is involved within a DMOs through collaboration with the government and other NGOs. It augments existing literature on private sector involvement in DMOs where common perception is that the sector is only involved in short-term response and recovery activities. This study finds that the private sector can be operationally involved not just in post-disaster activities, but also in mitigation and preparation phases as well. This then sets a new baseline for further research on private sector involvement within DMOs. As this study provided a novel framework to analyse collaboration activities and its impact to DMSN resilience, future work could be done by applying the model to further cases such as other countries'. DMSNs, or to more specific contexts such as inter-organisational collaborations rather than big sectors. A more detailed assessment method against a future disaster will prove relevance for the model in providing practical insights on how resilience can be built in DMSNs.

This research proposed a novel DMSN collaboration-resilience (COLRES) model (Figure 11) to analyse existing processes in preparation for specific disasters. Practitioners may be able to use this model with the goal of identifying resilience gaps to fill and continuously improve their processes. The model also provides practitioners the lens to improve processes with the perspective on collaboration to complement government and NGO efforts and expertise with those of the private sector. For the private sector perspective, this research provides new insights on how they can be more involved with the community to provide more sustainable and long-term contributions to the society.

With disasters becoming more complex and frequent by the day and as humanitarian actors focus on improving their expertise, the need for every piece of the society to contribute to disaster risk reduction is continuously intensified. This research shows that each sector of the society can take part in disaster management operations to reduce unpredictability, lives impacted and increase speed of response and recovery. Each sector of the society can be of great contribution not only during post-disaster response and recovery but also during pre-disaster mitigation and preparedness phase. As such, this research echoes the call for everyone to be involved in disaster risk reduction and mitigation as a way of life.

This research ultimately finds that cross-sector collaboration builds resilience in DMSNs through capacity building, redundancy sourcing, information reliability and logistics responsiveness. This study shows that the private sector is able to go beyond existing short-term partnerships by participating in the 46 collaboration activities identified across four disaster management phases in order to build resilience in DMSNs.

Using the logistics service supply chain (LSSC) as a research object, this study focuses on the relationship between integration quality (IQ), value co-creation (VCC), and LSSC resilience. Moreover, it discusses the moderating role of digital technology (DT).

Based on data about China, this study used the structural equation model to test the research hypothesis. To verify the validity of each construct, this study used various established scales in the literature to conduct exploratory and confirmatory analysis.

The results show that IQ is an essential antecedent variable that promotes VCC and LSSC resilience. Moreover, this study confirms that DT has a positive moderating effect on the relationship between IQ, VCC, and resilience.

This study constructs a research framework to examine LSSC resilience and expands the theoretical research on the VCC theory in the supply chain literature. Moreover, this paper studies supply chain integration from a new perspective, that is, IQ, which is more in line with the reality of LSSC.

This paper explores the potential opportunities and challenges that Belt and Road Initiative (BRI) may bring for resilient supply chains.

This study employs multiple case study methodology by considering five south Asian countries. Overall, 36 semi-structured interviews with supply chain managers from three supplying firms, two transportation centers and four buying firms are undertaken. Three supplying firms were based in Pakistan, providing cement and steel products. Simultaneously, two transportation centers were located in Sri Lanka and Bangladesh, mainly engaged in cargo and freight handling. Finally, the buying firms were located in Mainland China and India, mainly constructing road and rail networks.

Our findings reveal both challenges and opportunities for supply chain resilience within the context of BRI. In particular, findings suggest that BRI can improve quality infrastructure, greater connectivity for logistics firms and enhance consumer markets. Conversely, BRI also poses challenges to supply chain resilience in managing large-scale logistics infrastructure and the potential conflicts between countries participating in BRI.

As this study attempts to build a theory, its result should not be generalized to a broader population. Second, this study only explores BRI's implications for resilient supply chains within five South Asian countries.

Firms can use our study results to understand BRI’s implications for resilient supply chains. Particularly, it presents firms with the potential opportunities and challenges that BRI brings for resilient supply chains.

BRI has been the subject of much research in domains like political science, economics and law but its application to the supply chain resilience is rather scant. Our study, therefore, contributes to the emergent literature on supply chain resilience within the context of BRI by exploring its potential opportunities and challenges.

This paper aims to assess the impact of different drivers of country risk, including business environment, corruption, economic, environmental, financial, health and safety and political risks, on the country-level logistics performance.

This study utilizes three datasets published by reputed international organizations, including the World Bank Group, AM Best and Global Risk Profile, to explore interactions among country risk drivers and the Logistics Performance Index (LPI) in a network setting. The LPI, published by the World Bank Group, is a composite measure of the country-level logistics performance. Using the three datasets, a Bayesian Belief Network (BBN) model is developed to investigate the relative importance of country risk drivers that influence logistics performance.

The results indicate a moderate to a strong correlation among individual risks and between individual risks and the LPI score. The financial risk significantly varies relative to the extreme states of the LPI score, whereas corruption risk and political risk are the most critical factors influencing the LPI score relative to their resilience and vulnerability potential, respectively.

This study has made two unique contributions to the literature on logistics performance assessment. First, to the best of the authors’ knowledge, this is the first study to establish associations between country risk drivers and country-level logistics performance in a probabilistic network setting. Second, a new BBN-based process has been proposed for logistics performance assessment and operationalized to help researchers and practitioners establish the relative importance of risk drivers influencing logistics performance. The key feature of the proposed process is adapting the BBN methodology to logistics performance assessment through the lens of risk analysis.