An integrated fuzzy-ANP and fuzzy-ISM approach using blockchain for sustainable supply chain

Blockchain technology in supply chain management: an organizational theoretic overview and research agenda

Blockchain technology is touted as a game-changer. Many experts consider blockchain technology as one of the disruptive innovations. Following significant success in the banking and finance sector, blockchain technology has found significant success in all fields, including health, manufacturing, transportation, disaster relief operations, and many others. Recently, the academician has contributed significantly towards understanding blockchain technology and its application in the management field. To understand how the literature on blockchain technology in the supply chain has progressed, we undertook an extensive review of the literature published in peer-reviewed journals using databases such as SCOPUS. We have further classified our literature into four stages (pre-adoption, adoption, implementation, and application). Finally, we synthesized the findings of the study and proposed a research framework to explain how an organization can build supply chain resilience and enhance supply chain performance with the help of blockchain technology. Finally, we have noted the limitations of the study and future research directions.

S, M. N. Modelling the drivers of responsiveness of automotive supply chain using an integrated fuzzy DEMATEL-ISM approach

Purpose

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Design/methodology/approach

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

Findings

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

Research limitations/implications

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

Originality/value

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

Blockchain for sustainable supply chain management: trends and ways forward

Blockchain operates on a highly secured framework, and its decentralized consensus has benefits for supply chain sustainability. Scholars have recognized the growing importance of sustainability in supply chains and studied the potential of blockchain for sustainable supply chain management. However, no study has taken stock of high-quality research in this area. To address this gap, this paper aims to provide a state-of-the-art overview of high-quality research on blockchain for sustainable supply chain management. To do so, this paper conducts a systematic literature review using a bibliometric analysis of 146 high-quality articles on blockchain for sustainable supply chain management that have been published in journals ranked “A*”, “A”, and “B” by the Australian Business Deans Council and retrieved from the Scopus database. In doing so, this paper unpacks the most prominent journals, authors, institutions, and countries that have contributed to three major themes in the field, namely blockchain for sustainable business activities, decision support systems using blockchain, and blockchain for intelligent transportation system. This paper also reveals the use of blockchain for sustainable supply chain management across four major sectors, namely food, healthcare, manufacturing, and infrastructure, and concludes with suggestions for future research in each sector.

Modelling the abstract knots in supply chains using interpretive structural modelling (ISM) approaches: a review-based comprehensive toolkit

Purpose

This study endeavours to (a) develop a comprehensive interpretive structural modelling (ISM) toolkit containing sufficient details about the suitability and procedural aspects of each ISM approach and offer points of reference for budding researchers, (b) highlight the compatibility of ISM approaches with other qualitative and quantitative approaches, and (c) chalk-out an agenda for future research.

Design/methodology/approach

This study is based on an extensive review of 74 studies where researchers have used one or more ISM approaches. These studies span across the different industry sectors.

Findings

There exists a huge void in terms of the methodological synthesis of ISM approaches. ISM approaches are frequently used in sync with other qualitative and quantitative approaches. Furthermore, it highlights the need of improving the robustness of the proposed ISM models by sharing the critical details of research process.

Research limitations/implications

Being a review-based work, it could not illustrate the discussed ISM approaches with real data. However, it offers a research agenda for the prospective researchers.

Practical implications

The prerequisites, pitfalls, suitability and the procedural aspects of various ISM approaches contained in this toolkit are equally useful for the academicians as well as practitioners.

Originality/value

In the absence of a synthesized framework, this study contributes a comprehensive ISM toolkit which will help the researchers to choose a suitable ISM approach in a given case.

Antecedents for blockchain technology-enabled sustainable agriculture supply chain

Blockchain can solve the problems that the agriculture supply chain (ASC) is facing to achieve sustainable growth. In a nation like India, blockchain application in the supply chain is still new; therefore, supply chain players need a better understanding and awareness of blockchain through valuable insights. This article aims to study the mediating role of blockchain technology adoption (BLCT) for sustainable supply chain performance (SSCP). This study investigates the influence of numerous factors such as green and lean practices, supply chain integration, supply chain risk, performance expectancy, top management support, cost, internal and external environmental conditions, regulatory support, and innovation capability on BLCT adoption. A sample of 316 respondents from Indian ASC industries was collected, and structural equation modeling (SEM) was used. This study's outcomes show that green and lean practices, supply chain integration, supply chain risks, internal and external conditions, regulatory support, innovation capability, and cost positively influence BLCT adoption. Moreover, BLCT positively influences sustainable agriculture supply chain performance. This article is valuable for policymakers, managers, service providers, researchers, and academicians to understand the role of factors in influencing BLCT and BLCT's role in improving sustainable supply chain performance (SSCP).

Exploring and establishing the barriers to sustainable humanitarian supply chains using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Purpose

The continual onset of natural and manmade disasters propels the humanitarian supply chain (HSC) efforts (by organizations, groups and individuals) to always be on a stand-by mode with more and more sustainable solutions. Despite all the sincere and coordinated efforts from all the humanitarian agents and bodies, the likely sustainable outputs are hampered by certain barriers (impediments) which exist at different levels of the HSCs. A better understanding of such barriers and their mutual relationship is deemed helpful in improving the outcomes of humanitarian efforts. Thus, the purpose of this paper is to explore, refine, establish and classify these barriers which thwart the sustainable efforts of the HSCs individually as well as collectively.

Design/methodology/approach

An extensive literature review is conducted to identify these barriers which were followed by soliciting the experts’ inputs to update, refine and retain the contextually relevant ones. The opinions about the nine identified and refined barriers are taken from eight experts based in the Northern India who are having at least five years of experience in humanitarian operations. Fuzzy interpretive structural modeling (FISM) is used to examine and establish a hierarchical relationship among these barriers, whereas fuzzy Matrice d’impacts croisés multiplication appliquée á un classment analysis is carried out to further classify these barriers into dependent, autonomous, linkage and dependent barriers.

Findings

The analysis led to the formation of a FISM model where the operational challenges affecting the performance occupy the topmost position in the hierarchy. The results reveal that inconsistent motives, coordination and communication and operational challenges affecting the performance are the dependent, poor strategic planning, capacity-related challenges and poor performance measurement system are the autonomous, and financial challenges, locational challenges and lack of proper awareness are the independent barriers.

Research limitations/implications

The focus of the researchers was to study and examine these barriers to sustainable HSCs with special reference to the epidemics and pandemics (especially COVID-19), and it sheds light particularly arising during and post disaster phases.

Practical implications

The structural model contributed by this study is expected to be meaningful for practitioners besides enriching the body of literature. In the context of pandemics, it distinguishes itself from the other available frameworks.

Social implications

As this research has been carried out in the context of the novel COVID-19, the framework is expected to assist policymakers in comprehending the issues impeding the sustainability of noble humanitarian efforts. Thus, ultimately it is expected to contribute to the ultimate cause of society at large.

Originality/value

This research endeavor distinguishes itself from the other accessible published resources in terms of the specific context, the methodological approach and the nature of respondents. This paper concludes with the practical implications and directions for future research.

Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective

Purpose

This article aims to model the challenges of implementing artificial intelligence and machine earning (AI-ML) for moderating the impacts of COVID-19, considering the agricultural supply chain (ASC) in the Indian context.

Design/methodology/approach

20 critical challenges were modeled based on a comprehensive literature review and consultation with experts. The hybrid approach of “Delphi interpretive structural modeling (ISM)-Fuzzy Matrice d' Impacts Croises Multiplication Applique'e à un Classement (MICMAC) − analytical network process (ANP)” was used.

Findings

The study's outcome indicates that “lack of central and state regulations and rules” and “lack of data security and privacy” are the crucial challenges of AI-ML implementation in the ASC. Furthermore, AI-ML in the ASC is a powerful enabler of accurate prediction to minimize uncertainties.

Research limitations/implications

This study will help stakeholders, policymakers, government and service providers understand and formulate appropriate strategies to enhance AI-ML implementation in ASCs. Also, it provides valuable insights into the COVID-19 impacts from an ASC perspective. Besides, as the study was conducted in India, decision-makers and practitioners from other geographies and economies must extrapolate the results with due care.

Originality/value

This study is one of the first that investigates the potential of AI-ML in the ASC during COVID-19 by employing a hybrid approach using Delphi-ISM-Fuzzy-MICMAC-ANP.

Drivers of implementing Big Data Analytics in food supply chains for transition to a circular economy and sustainable operations management

Purpose

The aim of this study is to evaluate Big Data Analytics (BDA) drivers in the context of food supply chains (FSC) for transition to a Circular Economy (CE) and Sustainable Operations Management (SOM).

Design/methodology/approach

Ten different BDA drivers in FSC are examined for transition to CE; these are Supply Chains (SC) Visibility, Operations Efficiency, Information Management and Technology, Collaborations between SC partners, Data-driven innovation, Demand management and Production Planning, Talent Management, Organizational Commitment, Management Team Capability and Governmental Incentive. An interpretive structural modelling (ISM) methodology is used to indicate the relationships between identified drivers to stimulate transition to CE and SOM. Drivers and pair-wise interactions between these drivers are developed by semi-structured interviews with a number of experts from industry and academia.

Findings

The results show that Information Management and Technology, Governmental Incentive and Management Team Capability drivers are classified as independent factors; Organizational Commitment and Operations Efficiency are categorized as dependent factors. SC Visibility, Data-driven innovation, Demand management and Production Planning, Talent Management and Collaborations between SC partners can be classified as linkage factors. It can be concluded that Governmental Incentive is the most fundamental driver to achieve BDA applications in FSC transition from linearity to CE and SOM. In addition, Operations Efficiency, Collaborations between SC partners and Organizational Commitment are key BDA drivers in FSC for transition to CE and SOM.

Research limitations/implications

The interactions between these drivers will provide benefits to both industry and academia in prioritizing and understanding these drivers more thoroughly when implementing BDA based on a range of factors. This study will provide valuable insights. The results from this study will help in drawing up regulations to prevent food fraud, implementing laws concerning government incentives, reducing food loss and waste, increasing tracing and traceability, providing training activities to improve knowledge about BDA and focusing more on data analytics.

Originality/value

The main contribution of the study is to analyze BDA drivers in the context of FSC for transition to CE and SOM. This study is unique in examining these BDA drivers based on FSC. We hope to find sustainable solutions to minimize losses or other negative impacts on these SC.

An ISM Modeling of Barriers for Blockchain/Distributed Ledger Technology Adoption in Supply Chains towards Cybersecurity

Over the last few years, the increasing level of cyber risks derived from the growing connectedness of Industry 4.0 has led to the emergence of blockchain technology as a major innovation in supply chain cybersecurity. The main purpose of this study is to identify and rank the significant barriers affecting the implementation of blockchain technology as a key component of cyber supply chain risk management (CSCRM). This research relied on the “interpretive structural modeling (ISM)” technique in the structure of a hierarchical model to investigate the contextual relationships of identified challenges for blockchain adoption in CSCRM; it also classifies the influential challenges based on their driving and dependence powers. The results highlight that “cryptocurrency volatility” is the challenge at the top level of the hierarchy, implying weak driving power but it is strongly dependent on the other challenges. “Poor regulatory provisions”, “technology immaturity”, “dependent on input information from external oracles”, “scalability and bandwidth issues”, and “smart contract issues” are significant challenges for the adoption of blockchain in cyber supply chain risk management and are located at the bottom level of the hierarchy with higher driving power. The implications for theory and practice of the research are also highlighted.

Proposal of a New Orange Selection Process Using Sensory Panels and AHP

Although the consumption of fruits and vegetables is being promoted by different institutions as a key question of public health, their consumption is decreasing and their waste is increasing. To address this situation, we propose to include the consumer's perception of the quality (from a sensory point of view) of a fruit, in particular Valencian oranges, in the supplier's selection process by retailers. To do so, we use a combination of consumer and trained sensory panels and Analytic Hierarchy Process (AHP). This approach is completely novel in the literature. According to the expert panel, the most important criteria when evaluating the quality of an orange are fruity smell, juiciness, sweetness and acidity. These criteria are related to the freshness and taste of the oranges. Consumers found the methodology proposed useful and easy to develop. The application of the AHP methodology has helped to facilitate a participatory discussion among consumers on the concept of the quality of the oranges. The methodology proposed can help the agrifood sector in different ways up and down the supply chain. Specially, it can contribute to better meet consumer's demands, increasing the consumption of fruits and vegetables and reducing its waste.

Applying Industry 4.0 technologies in the COVID–19 sustainable chains

Purpose

The purpose of this paper is 1) to investigate the effects on the crucial Industry 4.0 technological innovations that interact between the real and virtual worlds and that are applied in the sustainable supply chain process; 2) to contribute to the identification of the opportunities, the challenges and the gaps that will support the new research study developments and 3) to analyze the impact of the Industry 4.0 technologies as facilitators of the sustainable supply chain performance in the midst of the Coronavirus (COVID-19).

Design/methodology/approach

This research is performed through a bibliographic review in the electronic databases of the Emerald Insight, the Scopus and the Web of Science, considering the main scientific publications on the subject.

Findings

The bibliographic search results in 526 articles, followed by two sequential filters for deleting the duplicate articles (resulting in 487 articles) and for selecting the most relevant articles (resulting in 150 articles).

Practical implications

This article identifies the opportunities and the challenges focused on the emerging Industry 4.0 theme. The opportunities can contribute to the sustainable performance of the supply chains and their territories. The Industry 4.0 can also generate challenges like the social inequalities related to the position of the man in the labor market by replacing the human workforce with the machines. Therefore, the man-machine relationship in the Industry 4.0 era is analyzed as a gap in the literature. Therefore, as a way to fill this gap, the authors of this article suggest the exploration of the research focused on the Society 5.0. Also known as “super-smart society,” this recent theme appeared in Japan in April 2016. According to Fukuda (2020), in addition to the focus on the technological development, the Society 5.0 also aims at the quality of life and the social challenge resolutions.

Originality/value

This article contributes to the analysis of the Industry 4.0 technologies as facilitators in the sustainable supply chain performance. It addresses the impacts of the Industry 4.0 technologies applied to the supply chains in the midst of the COVID-19 pandemic, and it analyzes the research gaps and limitations found in the literature. The result of this study can add value and stimulate new research studies related to the application of the Industry 4.0 technologies as facilitators in the supply chain sustainable performance. It can encourage the studies related to the COVID-19 impacts on the sustainable supply chains, and it can promote the research development on the relationship among the man, the machine and the labor in the Fourth Industrial Revolution.