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Blood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.

This study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.

The results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.

This study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.

This study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

Maintaining a safe and available supply of blood requires a mindfully coordinated supply chain (SC) and is fundamental to the effective operation of health systems across the world. This study investigates how blood supply chain (BSC) actors demonstrate collective mindfulness (CM) principles in their operations and how these demonstrations lead to improvements in blood safety and availability (BSA) in different operational contexts.

Six case studies drawn from two contrasting BSCs, the UK and Indonesia, which differ in structure and regulation are investigated in this research. Qualitative data are collected and analysed using template analysis.

The cases reveal how the CM principles are demonstrated in the supply chain context in a range of operational conditions and their impact on BSA. The BSC actors in the more centralised and tightly regulated cases display more behaviours consistent with more of the CM principles over a greater range of operational conditions compared to those in the more decentralised and loosely regulated cases. As such, more improvements in BSA are found in the former compared to the latter cases.

This paper is considered the first to investigate the demonstration of CM principles at the SC as opposed to the single organisational level. It proposes an alternative approach to understanding and evaluating reliability performance using behavioural rather than statistical principles.

Are lateral transshipments an effective instrument to ensure the safe and efficient supply of blood? This paper will use the lens of institutional theory to determine how the blood supply chain can benefit from lateral transshipments and what requirements are necessary for their implementation. The paper aims to discuss these issues.

The research design comprises two stages. First, 16 case studies clustered into two case groups were conducted with transfusion laboratories in UK hospitals resulting in the derivation of eight key themes which were tested using a follow-up survey.

The blood supply chain acts under the influence of significant institutional pressures. Coercive pressures result from regulations enforced to ensure the safe supply of blood, normative pressures are imposed by society, demanding wastage is minimized and mimetic pressure from other hospitals fosters efficient supply chain operation. Lateral transshipments offer a powerful organizational tool to allow the blood supply chain to conform to these pressures.

This paper offers a novel institutional perspective on a complex supply chain issue where additional external pressures are seen to complicate the context. Due to the special characteristics of the blood supply chain, generalization of the findings to other industries must be done with care.

The paper confirms the benefits of lateral transshipments in a perishable product context. Special requirements for the blood supply chain/health care services are identified.

The key contributions of this paper are five propositions which offer an institutional theory perspective on the application of lateral transshipment relationships in the blood supply chain.

This research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.

Since the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.

A novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.

By building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.

The purpose of this study was to advance the knowledge of pharmaceutical supply chain (PSC) resilience using complex adaptive system theory (CAS).

An exploratory research design, which adopted a qualitative approach was used to achieve the study’s research objective. Qualitative data were gathered through 23 semi-structured interviews with key supply chain actors across the PSC in the UK.

The findings demonstrate that CAS, as a theory, provides a systemic approach to understanding PSC resilience by taking into consideration the various elements (environment, PSC characteristics, vulnerabilities and resilience strategies) that make up the entire system. It also provides explanations for key findings, such as the impact of power, conflict and complexity in the PSC, which are influenced by the interactions between supply chain actors and as such increase its susceptibility to the negative impact of disruption. Furthermore, the antecedents for building resilience strategies were the outcome of the decision-making process referred to as co-evolution from a CAS perspective.

Based on the data collected, the study was able to reflect on the relationships, interactions and interfaces between actors in the PSC using the CAS theory, which supports the proposition that resilience strategies can be adopted by supply chain actors to enhance this service supply chain. This is a novel empirical study of resilience across multiple levels of the PSC and as such adds valuable new knowledge about the phenomenon and the use of CAS theory as a vehicle for exploration and knowledge construction in other supply chains.

Ineffective management inventory of medical products such as blood and vaccines can create severe repercussions for hospitals, clinics or medical enterprises, such as surgery delays and postponements. Inventory sharing is a form of horizontal collaboration that can provide solutions to key actors of the healthcare supply chain (HSC), yet no prior study reviewed this topic.

This study conducts a systematic literature review of thirty-nine inventory-sharing studies in the context of HSCs published from 2012 until early 2022. The descriptive and thematic analyses include chronological distribution, geographical location, comparison between developed/developing regions, stakeholder and incident analysis.

Thematic analysis classified inventory sharing among five product supply chains (blood, medical supplies, medicines, vaccines and generic medical products). Benefits include shortage reduction, cost minimisation, and wastage mitigation. Barriers include (1) IT infrastructure, (2) social systems, (3) cost and (4) supply chain operations. Perishable inventory policies include Fresher-First (FF), Last-Expire-First-Out (LEFO), First-In-First-Out (FIFO) and First-Expire-First-Out (FEFO). The analysis also showed differences between developed and developing countries. The study identifies several future research opportunities that include (1) product utilisation rate, (2) cost reductions, (3) shortage mitigation and (4) waste reduction.

No prior study has systematically reviewed inventory sharing in HSCs to reveal benefits, barriers, patterns and gaps in the current literature. It makes five propositions and develops a research model to guide future research. The study concludes with theoretical and managerial implications.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Supply chain risk management can effectively reduce the loss of retailers. In this regard, retailers need to consider the competition risks of competitors in addition to the disruption risks. This paper designs a resilient retail supply chain network for perishable foods under the dynamic competition to maximize retailer's profits.

A two-stage mixed-integer non-linear model is presented for designing the supply chain network. In the first stage, an equilibrium model that considers the characteristics of perishable foods is developed. In the second stage, a mixed integer non-linear programming model is presented to deal with the strategic decisions. Finally, an efficient memetic algorithm is designed to deal with large-scale problems.

The optimal the selection of suppliers, distribution centers and the order allocation are found among the supply chain entities. Considering the perishability of agri-food products, the equilibrium retail price and selling quantity are determined. Through a numerical example, the optimal inventory period under different maximum shelf life and the impact of three resilient strategies on retailer's profit, selling price and selling quantity are analyzed.

As for future research, the research can be extended in a number of directions. First, this paper studies the retail supply chain network design problem under competition among retailers. It can be an interesting direction to consider retailers competing with suppliers. Second, the authors can try to linearize the non-linear model and solve the large-scale integer programming problem by exact algorithm. Finally, the freshness of perishable foods gradually declines linearly to zero as the maximum shelf life approaches, and it would be a meaningful attempt to consider the freshness of perishable foods declines exponentially.

This paper innovatively designs the resilient supply chain network for perishable foods under dynamic competition. The retailer's dynamic competition and resilient strategies are considered simultaneously when designing supply chain network for perishable foods. In addition, this paper gives insights into how to obtain the optimal inventory period and compare the retailer's resilient strategies.

This paper aims to conduct a systematic literature review of the research in the field of Artificial Intelligence (AI) and Big Data Analytics (BDA) in Supply Chain Risk Management (SCRM). Finally, future research directions in this field have been suggested.

The papers were searched using a set of keywords in the SCOPUS database. These papers were filtered using the Title abstract keywords principle. Further, more papers were found using the forward-backward referencing method. The finalized papers were then classified into eight categories.

The previous papers in AI and BDA in SCRM were studied. These papers emphasized various modelling and application techniques for AI and BDA in making the supply chain (SC) more resilient. It was found that more research has been done into conceptual modelling rather than real-life applications. It was seen that the use of AI-based techniques and structural equation modelling was prominent.

AI and BDA help build the risk profile, which will guide the decision-makers and risk managers make their decisions quickly and more effectively, reducing the risks on the SC and making it resilient. Other than this, they can predict the risks in disasters, epidemics and any further disruption. They also help select the suppliers and location of the various elements of the SC to reduce the lead times.

The paper suggests various future research directions that fellow researchers can explore. None of the previous research examined the role of BDA and AI in SCRM.

The purpose of this explorative research is to analyse the resilience of the United Kingdom's (UK) healthcare supply chains from a customer’s perspective in the light of the coronavirus pandemic.

Using the capabilities of preparedness, robustness, recovery and adaptability as the foundational percept for supply chain resilience, 22 healthcare professionals in 17 of the UK's National Health Scheme (NHS) Trusts were interviewed to explore their personal and organisational approaches adopted relative to the provision of eye protection, gloves, gowns, aprons, masks and respirators. The Dynamic Capabilities View is mapped to the resilience capabilities and used to analyse the data from a transformational supply chain research perspective.

The supply chains were largely unprepared, which was not particularly surprising even though the availability of gloves was significantly better compared to the other personal protective equipment (PPE). Techniques adopted to ensure robustness and recovery revealed the use of unsanctioned methods such as extended use of PPE beyond recommended use, redefinition of guidelines, protocols and procedures by infection control and the use of expired PPE – all of which compromised customer well-being.

As the paper views resilience through the lens of customers, it does not provide the perspectives of the supply chain practitioners as to the reasons for the findings and the challenges within these supply chains.

The compromise of the well-being of healthcare workers due to the vulnerabilities of healthcare supply chains is highlighted to managers and prescriptions for post-disruption adaptability are made.

This paper introduces transformative research to supply chain resilience research by uniquely looking at resilience from the customers' well-being perspective.