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The purpose of the research is to recognize and rank the barriers preventing Industry 4.0 (I4.0) adoption in Bangladesh’s food and beverage industries. It aims to highlight the major difficulties the sector is currently facing and offer a hierarchical framework for evaluating these barriers.

An exhaustive literature review was conducted along with expert interviews with academics and industry professionals to identify and assess the barriers. The interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (ISM-MICMAC) approach was used to classify the identified barriers based on driving and dependent power and understand the interrelationships among them.

A total of 20 barriers to I4.0 adoption in the food and beverage sector of Bangladesh were identified. The top tier of significant barriers includes “Financial constraints,” “Lack of management support,” “Lack of research and development team,” “Lack of adequate skills in the workforce,” “Lack of digital strategy alongside resource scarcity” and “Employee resistance to change.”.

The created hierarchical framework offers a useful tool for dealing with the noted barriers and assisting with the successful adoption of I4.0 in the food and beverage sector. Businesses can overcome financial constraints by allocating enough resources and obtaining management support. By creating a focused research and development team and giving the workforce the necessary training, the lack of knowledge and skills can be overcome. By developing a thorough digital strategy and making sure that the necessary resources are available, resource scarcity can be overcome. Furthermore, effective change management methods can support the adoption of I4.0 technologies by overcoming employee resistance to change.

By concentrating specifically on the difficulties encountered by the food and beverage industries in Bangladesh as it attempts to adopt I4.0, this study contributes to the body of existing literature. The study’s originality lies in its thorough analysis of barriers and the use of the ISM-MICMAC approach to comprehend how these barriers interact with one another.

With the rapid low-carbon transformation in China, the industrial approach and labor structure of mining enterprises are undergoing constant changes, leading to an increasing psychological dilemma faced by coal miners. This study aims to reveal the relationship and mechanism of factors influencing the psychological dilemma of miners, and to provide optimal intervention strategies for the safety and sustainable development of employees and enterprises.

To effectively address the complex issue of the psychological dilemma faced by miners, this study identifies and constructs five-dimensional elements, comprising 20 indicators, that influence psychological dilemmas. The relational mechanism of action of factors influencing psychological dilemma was then elucidated using an integration of interpretive structural modeling and cross-impact matrix multiplication.

Industry dilemma perception is a “direct” factor with dependent attributes. The perceptions of management response and relationship dilemmas are “root” factors with driving attributes. Change adaptation dilemma perception is a “susceptibility” factor with linkage attributes. Work dilemma perception is a “blunt” factor with both dependent and autonomous attributes.

The aforementioned findings offer a critical theoretical and practical foundation for developing systematic and cascading intervention strategies to address the psychological dilemma mining enterprises face, which contributes to advancing a high-quality coal industry and efficient energy development.

This study deals with the examination, classification and ranking of the food industry supply chain in Mazandaran Free Economic Zone from a sustainability perspective and its effect on international entrepreneurship. The findings can help international decision-makers and entrepreneurs better understand their decision-making processes. Interpretive structural modelling (ISM) and Matrix-based Multiplication Applied to Classification (MICMAC) methods is an export-oriented method. The indicators are determined based on the definitive opinion of experts. Indicators in this research were selected using fuzzy Delphi with 99% accuracy. A combination of ISM–MICMAC methods were used based on sustainable facts in the food supply chain. The developed classify the factors practical on the sustainable supply chain. The findings showed that minimising the total cost, improvement of health and safety, environmentally friendly packaging, use of environmentally friendly materials and minimising the use of synthetic fertilisers were among the linkage factors. Factors that reduce energy costs, the possibility of immediate customer response and social services were among the dependent factors. Since free economic zones have been established to attract international investment, exploit new technologies, create new job opportunities and increase export capacity, the focus on reducing costs and the ability to respond immediately to customers and providing social services can result in the creation of a suitable business position for international investment and attracting international entrepreneurs.

This paper aims to identify factors that affect the sports tourism destination's competitiveness on a small island. Hence, this study looks at and evaluates these factors. The study then comes up with a model that clarifies the interrelationships between these factors.

The authors broke down the data analysis process into three steps. The first step was to conduct a literature review and use industry and academia experts' help to determine the essential aspects (fuzzy Delphi method). Then, a hierarchical model was developed, and the factors were categorised using the interpretive structural modelling (ISM) approach. Factors' driving and dependency power were also determined using MICMAC analysis.

This work has identified 13 key factors related to the sports tourism destination's competitiveness on a small island. For a small island like Kish Island, the two independent variables (government support and destination political stability) that define the institutional framework for the destination are most important. Building corresponding competitive and support strategies to address these two independent variables is thus beneficial.

The research's results provide decision-makers, practitioners, and researchers with new insights into the hierarchical model of determinants. The study will fill the existing gap between theory and practice.

Sports tourism destination managers on small islands may benefit from the proposed model since the model will enable them to organise the managers' priorities better to enhance the managers' destinations' competitiveness and provide tourists with a more accurate depiction of the destination.

According to the authors' knowledge, the research design presented in this article has provided the first attempt to hierarchical analyse these factors and develop a model for sports tourism destination competitiveness on small islands and destinations with less-developed economies. This study fills the gap in the destination competitiveness and sports tourism literature by not only identifying the key influencing factors but also examining the interactions between these factors and providing empirical evidence supporting their relationships.

Suppliers and marketers have started planning toward postpandemic scenarios where logistics and retail will happen in a new way with the help of technological advances. This shift means new challenges for manufacturers, suppliers and retailers, and there is a need for strategic sourcing decisions for a robust supply chain system, logistics and on-time delivery system, as consumers have shown a positive change in online buying behavior. Furthermore, with digital transformation, customers are expected to not return to traditional buying. Hence, it becomes essential to identify the factors acting as enablers of online purchase behavior for sustainable digital business. This study aims to analyze the positive shifts in online purchasing by consumers, identify and model the enablers of positive transformations in online purchasing by consumers.

The interpretative structural modeling (ISM) technique is used to draw the interrelationships among the variables and their impact on online buying. A context-oriented relationship among the factors has been set up through the expert opinion technique. A total of 40 specialists have been approached for this. ISM with Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis was used to prioritize these drivers, identify the most critical factors and establish a driver-dependence relationship among these drivers.

Several significant categories of enablers like health, trust, convenience, work from home, referral buying, panic purchase and overstocking possess a strong influence on the shift to online due to the pandemic. The results will help the policymakers, suppliers, retailers, managers and practitioners with insights to plan, prepare for challenges and make decisions toward preparation and shifting to the emergent digital world. In addition, the study provides academicians scope for further research in the related area.

Consumer behavior significantly impacts retail and supply chain business, as it is an interface with the customer and links between a manufacturer and a customer. This study provides an insight into the shift in purchase behavior which can help suppliers in this transition phase to be better prepared for tomorrow to achieve sustainable competitive advantage.

This study assists practitioners and researchers in understanding the interrelationships among the factors using ISM-MICMAC analysis in a realistic way rather than daydreaming with overambitious goals.

This paper intends to explore and appraise the humanitarian supply chain management enablers (HSCMEs) for efficient and effective humanitarian operations. This research aims to analyze the interaction of enablers for humanitarian supply chain management (HSCM) using a proposed hybrid framework consists of fuzzy Delphi (FD), interpretive structural modeling (ISM)–matriced impacts croises multiplication appliquee a un classement (MICMAC) and revised Simos approach.

This research is deliberate to identify 28 HSCMEs through a literature review and experts' opinions; out of which 20 HSCMEs are selected using FD. ISM is applied to know contextual relationship among the selected HSCMEs for developing a hierarchical model. The MICMAC analysis classifies the HSCMEs based on driving power and dependence power to validate the developed hierarchical ISM structure. The revised Simos technique is used to prioritize the HSCMEs to access its relative significance in humanitarian operations.

The finding of the analysis suggests that government policy and leadership support obtained the highest priority, having high driving power and low dependence power is significantly strategic and emerged as the leading driver for the HSCM implementation.

ISM model presents an insight into interrelationship among HSCMEs, but this cannot quantify the impact of each HSCMEs.

Disaster relief aid agencies and stakeholders may focus on the enablers having high driving power and higher weight in designing and executing an effective and efficient humanitarian supply chain and to improve their activities and strategies of HSCM.

This research helps humanitarian logisticians and humanitarian organizations to make better decisions to improve their operational performance in pre and postdisaster phases.

This paper explores the application of proposed hybrid framework to analyze the HSCMEs that can be considered as the original contribution.

The purpose of this study is to analyse various risks associated with third-party logistics (3PL) in the coffee supply chain and to present a framework that computes the influence of these risks on the critical success factors of the coffee supply chain.

The risks have been identified through a comprehensive literature review and validation by industry experts. The paper utilises an interpretive structural modelling (ISM) methodology for developing a hierarchical relationship among the CSFs. Furthermore, fuzzy MICMAC analysis is carried out to categorise these CSFs based on their driving power and dependence value. The fuzzy technique for order preferences by the similarity of an ideal solution (fuzzy-TOPSIS) approach has been applied to prioritise the risks associated with 3PL based on their ability to influence the CSFs of the coffee SC. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.

This study illustrates ten risks associated with 3PL and five CSFs in the coffee supply chain. The analysis revealed that coffee enterprises need to develop a balanced pricing strategy to ensure a sustainable competitive advantage, whereas the lack of direct customer communication is the most dominant 3PL risk affecting the CSFs.

This research provides coffee enterprises with a generalised framework with set parameters that can be used to attain a successful coffee supply chain in any developing nation.

The study contributes to the literature by being the first kind of study, which has used fuzzy ISM-MICMAC to analyse the CSFs of the coffee supply chain and fuzzy-TOPSIS for analysing the impact of various risks associated with the 3PL in the coffee supply chain. Thus, this work can be considered a benchmark for future research and advancement in the coffee business field.

The objective of this paper is to investigate, assess and develop a hierarchical model to evaluate the interrelationship of critical success factors (CSFs) that influence the deployment of Sustainable LSS framework in hospitals. Further, developed model has been validated to investigate its applicability in hospitals towards sustainable LSS implementation.

“Interpretive Structural Modeling” (ISM) has been utilized to develop a convenient hierarchy and contextual relationship of key CSFs throughout the implementation pathway in Indian healthcare industry through systematic literature review and expert opinion, which is ensured by a taxonomy of CSFs using MICMAC (“Matrice d' Impacts Croisés-Multiplication Appliquée á un Classement”) and questionnaire-based survey to empirically validate the model through utilizing “Structural Equation Modelling” (SEM).

In this study, 17 keys CSFs to sustainable LSS implementation in healthcare industry have been investigated, and modeled. “Social and environmental responsibility,” “Financial return and project success stories,” “Top management involvement and leadership to implement Sustainable LSS,” “Availability of required resources, and their efficient utilization” are found to be the most essential CSFs for successful sustainable LSS implementation in healthcare industry. Further, classification of CSFs has been done for better interpretation of their nature using MICMAC approach. Moreover, the applicability of the proposed model has been empirically assessed utilizing SEM.

The scrutiny of data reveals that the initial inputs from experts throughout the ISM pathway could trigger biased inputs into the study and generalization of the results into others, it might be viable that this propounded model might trigger distinct outcomes for contrasting types of healthcare organizations.

This model on sustainable LSS would support the decision-makers, practitioners and researchers to predict key CSFs through deployment and support the existing academic research on sustainable LSS. Accordingly, the focus on the CSFs of the sustainable LSS can be prioritized to diminish waste, and enhance patient satisfaction and safety.

This paper is an original contribution of analysis of CSFs in Indian healthcare industry utilizing an integrated ISM-MICMAC and SEM approach.

The purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).

(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.

Results indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.

The findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

This chapter aims to identify, analyse, classify and rank the sustainability indices and internationalisation challenges of the footwear industry in the emerging economy of Iran. This would provide deeper decision-making insights into Iranian footwear businesses. First, a list of sustainability indices and internationalisation challenges was obtained by reviewing the literature. Then, a combination of multi-criteria decision-making (MCDM) approaches was implemented. The initial sustainability indices and internationalisation challenges were screened using the fuzzy Delphi method, keeping a total of 14 criteria. The best–worst method (BWM) was employed to weigh and rank the criteria. The interpretive structural modelling (ISM) technique and cross-impact matrix applied in MICMAC were employed to visualise the conceptual model based on the levels and classification of the important criteria for the internationalisation of the Iranian footwear industry. The 14 criteria were demonstrated to be important in internationalisation. The most critical sustainability indices were reducing hazardous substances in leather tanning and labour education and training. In contrast, exchange rate instability in Iran’s economy and strict chemical regulations for clothing and footwear were found to be the most important internationalisation challenges. Hence, these criteria should be considered in the internationalisation strategies of the Iranian footwear industry. A combined multilayer sustainable decision-making approach was used to analyse the Iranian footwear industry’s essential sustainability indices and internationalisation challenges. Furthermore, implications and insights are offered to footwear businesses for future decision-making.