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This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.

After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.

This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.

The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.

The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.

Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.

We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

Apitourism is a form of tourism that deals with the culture and traditions of rural communities and can be considered one of the most sustainable methods of development and tourism. Accordingly, this study aims to identify the key factors and plausible scenarios of Iranian apitourism in the future.

This study is applied research. For this purpose, first, by examining the theoretical foundations and interviewing experts, the key factors affecting the future of Iranian apitourism were identified. Then, using a binomial test, these factors were screened. Both critical uncertainty and DEMATEL techniques were used to select the final drivers.

Two drivers of “apitourism information system and promotional activities” and “organizing ecological infrastructure” were selected for scenario planning using critical uncertainty and DEMATEL techniques. According to these two drivers, four golden beehive, expectancy, anonymous bee and black beehive scenarios were developed. Each scenario represents a situation for apitourism in the future. According to the criteria of trend compliance, fact-based plausibility and compliance with current data, the “Black Beehive” scenario was selected as the most likely scenario. The “Golden Beehive” scenario shows the best case in terms of apitourism information system and implementation of promotional activities and organizing and providing ecological infrastructure. The “Black Beehive” scenario, on the other hand, describes an isolated and vulnerable system.

Developing plausible Iranian apitourism scenarios helps key stakeholders and actors develop flexible plans for various situations.

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.

The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

Since Industry 4.0 (I4.0) is a new idea in Bangladesh, this study supports I4.0 adoption. Companies struggle to implement I4.0 and fully profit from the fourth industrial revolution’s digital transformation due to its novelty. Although barriers to I4.0 adoption are thoroughly studied, the literature has hardly examined the many aspects that are crucial for I4.0 adoption in Bangladesh’s Ready-Made Garment (RMG) industry. So, the purpose of this study is to investigate the barriers of adopting I4.0 in relation to Bangladesh’s RMG industries to enhance the adoption of I4.0 by developing a framework. Ultimately, the goal of this research is to improve the adoption of I4.0 in Bangladesh.

Through a comprehensive analysis of the existing research, this paper aims to reveal the barriers that must be overcome for I4.0 to be adopted. For evaluating those barriers, a decision analysis framework based on the combination of Delphi technique and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method has been developed. The use of DEMATEL has led to a ranking model of those barriers and a map of how the barriers are connected to each other.

The findings reveal that “I4.0 training”, “Lack of Motivation” and “Resistance to Change” are the most significant barriers for adopting Industry 4.0 in RMG sector of Bangladesh based on their prominence scores.

These findings will help the people who make decisions in the RMG industry of Bangladesh, such as company owners, managers and the executive body, come up with a plan for putting I4.0 practices into place successfully. The decision-making framework developed in this research can be utilized by the RMG industry of Bangladesh and other similar industries in developing countries to figure out how important each barrier is for them and how to get rid of them in order of importance.

As far as the authors are aware, there has not been a comprehensive study of the barriers inhibiting the adoption of I4.0 within the scope of Bangladeshi RMG industry. This work is the first to uncover these barriers and analyze them using the combination of Delphi technique and DEMATEL.

The purpose of this study is to analyze the challenges encountered by international nongovernmental organizations (INGOs) operating in armed conflicts within the Democratic Republic of the Congo (DRC) and the Central African Republic (CAR). Through a 20-month fieldwork analysis, this research maps logistical risks and highlights key obstacles on the ground for successful humanitarian deployments in dynamically changing and complex environments. The study brings together academics and practitioners, providing practical and concrete recommendations for nongovernmental organizations (NGOs) to focus on in the conflict zones studied.

Using a mixed-methods approach that combines qualitative and quantitative methods, this research provides valuable insights into the challenges faced by INGOs in conflict zones. After collecting data from the field, including interviews with key stakeholders and on-the-ground observations, the data analysis uses software tools such as Text Analysis Markup System analyzer and Macbeth. By adhering to ethical principles and incorporating a reflexive analysis, the study sheds light on the multidimensional nature of successful humanitarian deployments.

The primary risk in all armed conflict zones, including the DRC and CAR, is insecurity. However, to achieve a successful humanitarian deployment in such contexts, a multidimensional approach is required. This involves first securing the acceptance of local communities and conflict parties, which can be achieved through a deep understanding of both political and customary structures, with a focus on respecting key engagement leaders. Sustainability also plays a crucial role, and NGOs must maintain a secure stock of energy and provide greater initiative for on-the-ground managers to meet the expressed needs of beneficiary populations and involve them from the planning stage onwards. Finally, effective communication, cooperation and collaboration with United Nations Office for the Coordination of Humanitarian Affairs are essential to overcome procurement, technical and security risks, particularly during the initial deployment phases.

This study provides an illustration of the uncommon practice of conducting collaborative research in humanitarian settings amidst two neighboring areas of armed conflict. The authors identified 268 common risk factors across eight categories during five deployment phases. To analyze these risks based on criticality and NGO responsiveness, the authors used a multicriteria method. This approach allowed the authors to validate unanimous judgments, resulting in valuable insights and concrete recommendations.

This article aims to map the expectations of manufacturing companies towards suppliers in terms of implementing improvement activities. The article poses two research questions: RQ1: What kind of improvement of activities do the surveyed producers expect from their suppliers? RQ2: Do factors such as size, capital or implemented systems influence different assessments of the analyzed requirements toward suppliers?

The Computer Assisted Telephone Interview (CATI) technique was used to collect data. The sample consists of 150 producers (employing over 50 people) who were suppliers for enterprises from the automotive, electromechanical and chemical sectors operating in the Polish business-to-business (B2B) market. We analyzed 11 improvement activities, while their correlation structure was examined by exploratory factor analysis.

We have identified three latent factors – risk reduction, product innovation and increasing efficiency – which summarize the main expectations of manufacturing companies towards suppliers. Expectations for these factors are independent of the implemented management system, although the analysis showed higher expectations for product innovation in organizations with the implementation of Kaizen.

The article fills the research gap in the literature. The research results presented in the literature so far have focused on the expectations of enterprises towards suppliers in terms of meeting the criteria for their initial and periodic assessment. The research gap in the article is the result of empirical research presenting the expectations of manufacturers towards suppliers in terms of improving their processes. Based on the findings of the presented study, development trends and implications for managers responsible for purchasing processes and relationships with suppliers can be determined.