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Blockchain technology enhances information management in healthcare supply chains by securing healthcare information and providing medical resource traceability. However, there is no decision framework to support blockchain implementation for managing information, especially in emerging economies’ healthcare supply chains. This paper develops a hierarchical decision model for implementing blockchain technology for information management in emerging economies’ healthcare supply chains.

This study uses 20 health supply chain experts in Ghana to rank 17 decision criteria for implementing blockchain for healthcare information management using the best-worst method (BWM) multi-criteria decision technique.

The results show that “security” and “privacy,” “infrastructural facility” and “presence of training facilities” are the top three critical factors impacting blockchain adoption in the health supply chain for healthcare information management. Other sub-factors are prioritized.

To implement blockchain effectively to enhance information management in the healthcare supply chain, health institutions, blockchain technology providers and state authorities should concentrate on the highly critical factors extracted from the study.

This is the first study that develops a hierarchical decision model for implementing blockchain technology in emerging economies' health supply chains.

This paper aims to explore the antecedents and consequences of service chain flexibility (SCF) in healthcare service delivery.

A structural model was developed based on a literature review. A 29-indicator questionnaire was circulated among service providers in the healthcare system across India, and 253 valid responses were received, corresponding to a response rate of 46%. The research model was assessed using a cross-sectional research design, and the data were analyzed by structural equation modeling using analysis of moment structures (AMOS) software.

Service orientation (SO), technology integration (TI), knowledge sharing (KS) and supply chain integration (SCI) were identified as antecedents of SCF, the consequence of which is responsiveness in service delivery (RSD). Furthermore, patient-centered care moderates the relationship between SCF and RSD.

This paper highlights the impact of SCF on RSD in healthcare organizations. Consideration of the four constructs of SO, TI, KS and SCI as antecedents of SCF and, in turn, RSD may be one of the limitations. Future work may identify other theoretical constructs with potential impacts on SCF and RSD. Furthermore, eight months for data collection could have resulted in early-late response bias. This study was operationalized in India and may reflect political, economic, social, technological, environmental and legal factors unique to India.

The study provides suggestions to practitioners for building RSD by leveraging SO, TI, KS and SCI in flexibility-driven service chain processes. Recognizing the relationships among these constructs can aid in the timely formulation of corrective actions and patient-centric policies.

This paper highlights how focusing on a SCF can promote RSD. This understanding may aid the design of processes that develop patient-centricity and deliver health as a social good in an effective manner.

The empirical evidence from this study can help hospitals integrate and build flexibility in their functions, thus enabling them to deliver responsiveness in care.

The Covid-19 pandemic generated significant changes in the operating methods of hospital logistics departments. The objective of this research is to understand how these changes took place, what collaboration mechanisms were developed with clinical authorities and, to what extent, logistics and clinical care activities should be decoupled to maximize each area's contribution?

The case study is selected to investigate practices implemented during the COVID-19 pandemic in hospitals in Canada. The pandemic presented an opportunity to contrast practices implemented in response to this crisis with those historically used in this environment.

The strategy of decoupling logistical tasks of an operational nature from clinical activities is well-founded and helps free clinical staff from tasks for which they are not trained. However, the decoupling of operational tasks should be combined with an integration of the clinical information flow to the logistics hub players. With this clinical information, the logistics hub can generate its full potential enabling better inventory management decisions to be made.

The concept of decoupling is studied to identify configurations that offer the best benefits for clinical staff.

The primary objective of this article is to examine current procurement, inventory control and management practices in modern healthcare, with a particular focus on the procurement and management of surgical supplies in a prominent public, highly specialized healthcare sector.

This study was conducted in three phases. In Phase 1, the study team interacted with various hospital management stakeholders, including the surgical hospital store, examined the current procurement process and identified challenges. Phase 2 focused on selecting items for a detailed study and collected the qualitative and quantitative details of the store department of the healthcare sector chosen. A detailed study analyzed revenue, output/demand, inventory levels, etc. In Phase 3, a decision-making framework is proposed, and inventory control systems are redesigned and demonstrated for the selected items.

It was observed that the demand for many surgical items had increased significantly over the years due to an increase in disposable/disposable items, while inventories fluctuated widely. Maximum inventory levels varied between 50 and 75%. Storage and availability were important issues for the hospital. It is assumed the hospital adopts the proposed inventory control system. In this case, the benefits can be a saving of 62% of the maximum inventory, 20% of the average stock in the system and optimal use of storage space, improving the performance and productivity of the hospital.

This study can help the healthcare sector administration to develop better systems for the procurement and delivery of common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels, and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study can help the healthcare sector administration develop better systems for procuring and delivering common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study is an early attempt to develop a decision framework and inventory control system from the perspective of healthcare inventory management. The gaps identified in real hospital scenarios are investigated, and theoretically based-inventory management strategies are applied and proposed.

Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors.

Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain.

In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers.

Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias.

The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area.

Idea of circular economy defies the classical “make-use-dispose” approach of linear economic model. In the context of health-care industry, it relies heavily on the supply chain practices implemented by industry stakeholders. The purpose of this study is to explore such relationships, study their structure and put it across for attaining sustainability at large.

This study is an empirical research conducted on 145 health-care firms. The collected data is analysed to develop structural and measurement model. The five constructed hypotheses are examined and tested through structural equation modelling.

The study illustrates the latent relationships that exist among the stakeholders involvement, sustainable supply chain practices, sustainable performance and circular economy for health-care industry. It is found that the adoption of sustainable supply chain practices improves health-care performance, which, in turn, have positive influence on circular economy.

The structural and measurement model is developed in the context of circular health-care economy. It can be validated or improvised by conducting similar research in other industry using different methods. This research work fulfils the long existing gap in research by offering a linkage between various constructs to achieve health-care circular economy. Based on the research results, future researchers can build theories of circular economy and sustainability for health-care industry.

The study attempts to study the supply chain ways to achieve circular economy for Indian health-care sector. It considered latent relationships among the set of constructs, which are needed for theory building at later stage.

This study aims to document students’ supply chain solutions developed through the internship hackathon program. The study profiled innovative solutions developed by university students in Kenya to solve health supply chain logistics challenges during and beyond COVID-19. This is done by exploring students’ experience in developing sustainable logistics and supply chain management capacity-building programs in a low-middle-income country (LMIC).

This study used a qualitative approach to explore the experiences and perceptions of students and mentors who participated in a hackathon program. The study followed a cross-sectional descriptive survey design, collecting data from the participants through online questionnaires. The data were analyzed and presented using thematic analysis and narrative techniques.

Findings provide preliminary evidence for narrowing the gap between theory and practice through a hackathon internship blended with a mentorship program. Assessment of this program provides evidence for developing solutions toward ensuring the availability of essential medicine in LMICs during a pandemic such as COVID-19 by students. The profiled solutions demonstrate a broader perspective of innovative solutions of university students, mentors and potential opportunities for a triple helix approach to innovation for health supply chain system strengthening.

This original study provides evidence for advancing contribution to developing innovative solutions through partnerships between investors, universities and industry practitioners interested in mentoring students in the health-care supply chain during COVID-19 in LMICs. Specifically, contingency factors that affect the implementation of innovative programs during and beyond global pandemics such as COVID-19 by students’ innovators are identified, and implications for policy action are discussed based on the praxis of sensemaking.

This study examines a novel approach that combines internship, mentorship and hackathon projects for logistics and supply chain students in LMICs. The approach aims to bridge the gap between theory and practice and to create innovative solutions for essential medicines during and after COVID-19. The study urges more resources for supporting such programs, as they benefit both academia and industry. The study also argues that hackathon internship programs can help the logistics and supply chain industry adapt to the post-pandemic era. The study offers insights for investors, universities and practitioners in the health-care industry.

This study shows how to develop innovative solutions for the health-care supply chain during COVID-19 in an LMIC through partnerships between investors, universities and industry practitioners who mentor students. The study identifies the contingency factors that influence the success of such programs during and beyond global pandemics such as COVID-19 and discusses the policy implications based on the sensemaking praxis of the student innovators.

This study aims to assess the effects of green supply chain management (GSCM) strategies on health-care organizations’ environmental performance (EP). It also assesses that green innovation (GI), including green technology innovation (GTI) and green management innovation (GMI), plays mediating roles in the connection between GSCM and EP.

In total, 375 health-care sector employees in the Chattogram division of Bangladesh provided opinions in the questionnaire survey. PLS-SEM was used to verify the data’s validity and reliability and assess the hypotheses.

The findings reveal that GSCM practices significantly positively impact GI and EP. Moreover, GTI and GMI mediate the relationship between GSCM and EP in Bangladesh’s health-care sector.

The current findings could promote environmental sustainability in Bangladesh’s health-care industry by fostering environmental collaboration.

The detection of the mediation effect of GTI and GMI on GSCM and EP is a unique contribution of this study that enriches the present GSCM and GI literature, particularly in the Bangladeshi health-care sector.

Supplier selection along with continuous evaluation of their performance is a crucial activity in healthcare supply chain management for effective utilization of scarce resources while providing quality service at an affordable price, and minimizing chances of stock-out, avoiding serious consequences on the illness or fatality of the patients. Presence of both qualitative and quantitative evaluation criteria, set of potential suppliers and participation of different stakeholders with varying interest make healthcare supplier selection a challenging task which can be effectively solved using any of the multi-criteria decision making (MCDM) methods.

To deal with various qualitative criteria, like cost, quality, delivery performance, reliability, responsiveness and flexibility, this paper proposes integration of grey system theory with a newly developed MCDM tool, i.e. mixed aggregation by comprehensive normalization technique (MACONT) to identify the best performing supplier for pharmaceutical items in a healthcare unit from a pool of six competing alternatives based on the opinions of three healthcare professionals.

While assessing importance of the six evaluation criteria and performance of the alternative healthcare suppliers against those criteria using grey numbers, and exploring use of three normalization procedures and two aggregation operations of MACONT method, this integrated approach singles out S5 as the most compromised healthcare supplier for the considered problem. A sensitivity analysis of its ranking performance against varying values of both balance parameters and preference parameters also validates its solution accuracy and robustness.

This integrated approach can thus efficiently solve healthcare supplier selection problems based on qualitative evaluation criteria in uncertain group decision making environment. It can also be deployed to deal with other decision making problems in the healthcare sector, like supplier selection for healthcare devices, performance evaluation of healthcare units, ranking of physicians etc.

The promulgation of group purchasing organizations (GPOs) into the healthcare (HC) sector is an invaluable procurement strategy to manage the suppliers effectively. This study aims to identify and prioritize the factors of integrating GPOs into the HC sector on the perspectives of the developing countries such as India.

The factors are identified from current literature exploration, experts’ support and experience surveys. The factors are scrutinized and shortlisted using the Delphi technique and analysed further using the best-worst model method.

The findings of the study highlight the cost reduction, fair distribution of savings and healthcare supply chain (HCSC) data standardization among others to be the most prioritized drivers. The consulting services provided by GPOs including training and development as a result of high competitiveness in the HC market has been prioritized the least.

The study bears some important implications for decision and policymakers. The managers should consider factors, namely, cost reduction, fair distribution of savings and HCSC data standardization on a priority basis that acts as motivation for the HC providers to join the GPOs.

The study provides valuable insights for HC providers to participate in the GPOs for cost savings and enhance the performances.