Assessing sustainable supply chain enablers using total interpretive structural modeling approach and fuzzy-MICMAC analysis

2018 ◽  
Vol 29 (2) ◽  
pp. 216-239 ◽  
Author(s):  
Mahamaya Mohanty
Keyword(s):  
Supply Chain ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Policy Makers ◽  
Consumer Durables ◽  
Content Type ◽  
Micmac Analysis ◽  
Strategic Factors ◽  
Fuzzy Micmac ◽  
Integrated Logistics

Purpose The purpose of this paper is to model the enablers of an integrated logistics. The integration is accounted for incorporating sustainability, thereby aiming in its theory building. Existing models have focused on enablers of sustainable supply chain independently which lacks a holistic view in understanding the integrated logistics for sustainable supply chain. Design/methodology/approach An extensive literature review, expert opinion from both industry and academia based on questionnaire survey, is conducted to find the relevant enablers. The modeling of these enablers is done using total interpretive structural modeling (TISM). Finally, TISM along with its respective fuzzy-matriced impact croises multiplication applique (fuzzy-MICMAC) analysis is depicted. Findings The result of the survey and TISM model with its respective fuzzy-MICMAC has been used to evolve the mutual relationships among the important enablers of integrated logistics of consumer durables. The strategic factors obtained from TISM are integration and collaboration in the supply chain, vehicle type, and capacity; reduction in average length of haul; and real-time information system. Route selection and scheduling, reduction of fuel consumption, customer relationship management, green technology, cost reduction, etc., are some of the operational factors. Sustainable environment performance is obtained as the performance factor. Fuzzy-MICMAC is more responsive than the traditional MICMAC analysis. Research limitations/implications The study has limitation for the development of a conceptual framework for integrated logistics in uncertain environments. So it can be extended by combining soft computing methodologies. There is a lack of mathematical quantification of the proposed model where the enablers of sustainability can be measured. Practical implications The study on integrated logistics for sustainable supply chain is itself a new area to be explored, as very few studies on this relevant topic exist. The research concentrates on TISM for the integrated logistics and the movement of consumer durables through different distribution channels of a supply chain. The study has implications for practitioners, academicians, and policy makers. For practitioners, it provides a list of strategic factors, operational factors, and performance factors. For academicians, this methodology can be opted to conduct an exploratory study by identifying the essential enablers. For policy makers, the regulations can be developed using the above model. Originality/value It is an effort to model the important enablers and establish sustainability in integrated logistics of consumer durables.

Modeling the enablers of green supply chain management

2017 ◽  
Vol 24 (2) ◽  
pp. 536-568 ◽  
Author(s):  
Rakesh Kumar Malviya ◽  
Ravi Kant
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Action Plan ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Interpretive Structural Modeling ◽  
Chain Management ◽  
Content Type ◽  
Micmac Analysis ◽  
Fuzzy Micmac

Purpose The purpose of this paper is to identify and develop the relationships among the green supply chain management enablers (GSCMEs), to understand mutual influences of these GSCMEs on green supply chain management (GSCM) implementation, and to find out the driving and the dependence power of GSCMEs. Design/methodology/approach This paper has identified 35 GSCMEs on the basis of literature review and the opinions of experts from academia and industry. A nationwide questionnaire-based survey has been conducted to rank these identified GSCMEs. The outcomes of the survey and interpretive structural modeling (ISM) methodology have been applied to evolve mutual relationships among GSCMEs, which helps to reveal the direct and indirect effects of each GSCMEs. The results of the ISM are used as an input to the fuzzy Matriced’ Impacts Croisés Multiplication Appliquéeá un Classement (MICMAC) analysis, to identify the driving and the dependence power of GSCMEs. Findings Out of 35 GSCMEs 29 GSCMEs (mean⩾3.00) have been considered for analysis through a nationwide questionnaire-based survey on Indian automobile organizations. The integrated approach is developed, since the ISM model provides only binary relationship among GSCMEs, while fuzzy MICMAC analysis provides precise analysis related to driving and the dependence power of GSCMEs. Research limitations/implications The weightage for ISM model development and fuzzy MICMAC are obtained through the judgment of few industry experts. It is the only subjective judgment and any biasing by the person who is judging might influence the final result. Practical implications The study provides important guidelines for both practitioners, as well as the academicians. The practitioners need to focus on these GSCMEs more carefully during GSCM implementation. GSCM managers may strategically plan its long-term growth to meet GSCM action plan. While the academicians may be encouraged to categorize different issues, which are significant in addressing these GSCMEs. Originality/value Arrangement of GSCMEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of GSCM implementation.

Analyzing enablers of sustainable supply chain: ISM and fuzzy AHP approach

2017 ◽  
Vol 12 (3) ◽  
pp. 498-524 ◽  
Author(s):  
Divesh Kumar ◽  
Zillur Rahman
Keyword(s):  
Supply Chain ◽  
Fuzzy Ahp ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Similar Work ◽  
Sustainable Products ◽  
Focal Firm ◽  
Fuzzy Micmac ◽  
Hierarchy Process

Purpose This paper aims to intend to help focal firms which are keen to develop a sustainable supply chain by identifying enablers, in knowing the interrelationships involved and in ranking the enablers. Design/methodology/approach Interpretive structural modeling and fuzzy MICMAC were used for the modeling and clustering of the enablers and fuzzy analytical hierarchy process has been used for the ranking purpose. Findings Awareness about sustainability incentives, pressure from stakeholders, support from supply chain partners and demand from customer for sustainable products were found very important for developing a sustainable supply chain. Research limitations/implications This research will help practitioners to appreciate the importance of the enablers to focus on the making sustainability adoption feasible across the supply chain. This would also facilitate focal firm management to develop a sustainability culture across the supply chain. Originality/value Similar work has not been carried before in which interaction among enablers and their priorities were analyzed using hybrid methodologies in developing country context.

An ISM approach for the barrier analysis in implementing sustainable supply chain management

2017 ◽  
Vol 55 (8) ◽  
pp. 1824-1850 ◽  
Author(s):  
Mahmood Movahedipour ◽  
Jianqiu Zeng ◽  
Mengke Yang ◽  
Xiankang Wu
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Qualitative Analysis ◽  
Matrix Multiplication ◽  
Future Research ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Chain Management ◽  
Content Type ◽  
Sustainable Supply Chain Management

Purpose Sustainability has been on the executive agenda for years and it is now one of the fastest growing supply chain management trends. The purpose of this paper is to analyze the barriers for the adoption and implementation of the sustainable supply chain management (SSCM) concept. Design/methodology/approach This study has been divided into two phases such as identification of barriers and qualitative analysis. First, to identify the most influential barriers, the authors offer a systematic literature review, taking 188 papers published from 2010 to November 2016 into account. The investigation phase led to the selection of 15 barriers based on the literature in consultation with industrial experts and academicians. Second, the interpretive structural modeling qualitative analysis was used to find out the mutual influences between the 15 barriers by a survey. Findings Further, the authors propose and illustrate the cross-impact matrix multiplication applied to classification analysis to test a framework that extrapolates SSCM barriers and their relationships. “Inadequate information technology implementation” has been identified as the most important barrier that may force organizations to implement SSCM practices to ensure their business sustainability. Research limitations/implications The authors presented some limitations in their research in some fields which could allow new researchers and practitioners to conduct the future research to grow in different dimensions. Practical implications Practitioners or policymakers usually are not familiar with these types of research works; that is why most of these surveys remain theoretical and conceptual. Future investigation needs to be done in practical application domain instead of merely giving opinions. Originality/value Based on the authors’ research, the researchers have more attention to work in conceptual analysis due to other fields, but the authors believe that even with the implementation of SSCM, many remarkable areas still exist for future research which could help in development. The authors also provide more details in this paper.

Using interpretive structure modeling to analyze the interactions between environmental sustainability boundary enablers

2016 ◽  
Vol 23 (3) ◽  
pp. 601-617 ◽  
Author(s):  
Navin K. Dev ◽  
Ravi Shankar
Keyword(s):  
Supply Chain ◽  
Environmental Sustainability ◽  
Business Community ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Modern Business ◽  
The Government ◽  
Power And Dependence

Purpose – The modern business community understands the importance of long-term satisfaction of consumer. Enabling the consumer to return products is a significant part of the equation. The purpose of this paper is to analyze the sustainable boundaries in terms of their relationship toward greening a supply chain. Design/methodology/approach – Using interpretive structural modeling the research presents a hierarchy-based model to realize the driving power and dependence of sustainable boundary enablers. Findings – The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance while another group consists of those variables which have high dependence and are the resultant actions. Practical implications – This classification provides a useful tool to supply chain managers to differentiate between independent and dependent variables and their mutual relationships which would help them to focus while making strategic, tactical or operational decisions as and when required while designing a green supply chain. Originality/value – This research assumes importance in context of greening a supply chain when globally enterprises are getting a lot of pressure from consumers as well as the regulatory measures from the government. Sustainability demands that the resources be used in lean manner through information coordination with all partners in a supply chain. The findings of this study would help delineate those variables that should to be necessarily considered to design a sustainable supply chain.

A stakeholders’ perspective on barriers to adopt sustainable practices in MSME supply chain

2018 ◽  
Vol 22 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Swayam Sampurna Panigrahi ◽  
Nune Srinivasa Rao
Keyword(s):  
Supply Chain ◽  
Small And Medium Enterprises ◽  
Geographical Area ◽  
Environmental Conservation ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
The Government ◽  
Medium Enterprises ◽  
Hierarchy Process

Purpose Enterprises face the wrath of the government for taking part in environmental conservation and adoption of sustainable initiatives along with customer demands. Therefore, enterprises are forced to adopt sustainable supply chain practices (SSCPs), which leads to competitive advantage. Now, sustainable supply chain management (SSCM) is a management process that promotes the adoption of eco-friendly activities in conventional supply chains (SCs). Enterprises in India are under tremendous pressure to include SSCPs into their conventional SCs. The goal of this paper is to evaluate the barriers for the implementation of SSCPs into Indian Micro, Small and Medium Enterprises (MSMEs). Design/methodology/approach This study aims to identify critical barriers for adoption of SSCPs in the textile MSME SCs located in Eastern India, Odisha with the help of interpretive structural modeling (ISM). Findings The paper develops a framework for the evaluation of barriers to the adoption of SSCP in the textile SC. This paper also provides appropriate suggestive measures to deal with the barriers and overcome the same to attain a sustainable textile SC. Research limitations/implications Opportunities exist for extension of this research on wider geographical area. In addition to this, some other quantitative modeling approaches can be applied, like analytical hierarchy process, to prioritize the barriers. Practical implications The framework offers help to SC managers in their decision-making process by enabling them to analyze the barriers and ways to overcome them. Originality/value The paper deals with a particular geographical area where such kinds of studies are rare. The proposed framework provides a foundation for further research.

Modelling the SCM implementation barriers

2015 ◽  
Vol 10 (2) ◽  
pp. 158-178 ◽  
Author(s):  
S. J. Gorane ◽  
Ravi Kant
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Model Development ◽  
Integrated Approach ◽  
Business Managers ◽  
Implementation Barriers ◽  
Chain Management ◽  
Content Type ◽  
Micmac Analysis ◽  
Fuzzy Micmac

Purpose – The purpose of this paper is to develop the relationships among the identified supply chain management barriers (SCMBs) and understand mutual influences of these SCMBs on supply chain implementation. Further, this paper seeks to identify driving and dependent SCMBs using an interpretive structural modelling (ISM) and fuzzy MICMAC (Matrix of Cross-Impact Multiplications Applied to Classification) analysis. Design/methodology/approach – The methodology used in the paper is the ISM with a view to evolving mutual relationships among SCMBs. The identified SCMBs have been classified further, based on their driving and dependence power using fuzzy MICMAC analysis. Findings – This paper has identified 15 key SCMBs which hinder the successful supply chain management (SCM) implementation in an organization and has developed the relationships among the SCMBs using the ISM methodology. Further, this paper analyses the driving and dependent SCMBs using fuzzy MICMAC analysis. The integrated approach is developed here, as the ISM model provides only binary relationship among SCMBs. The fuzzy MICMAC analysis is adopted here, as it is useful in specific analysis related to driving and the dependence power of SCMBs. Research limitations/implications – The weightage for the ISM model development and fuzzy MICMAC is obtained through the judgement of academics and industry experts. Further, validation of the model is necessary through questionnaire survey. Practical implications – The identification of SCMBs, ISM model development and fuzzy MICMAC analysis provide academics and managers a macro picture of the challenges posed by the SCM implementation in an organization. Originality/value – The results will be useful for business managers to understand the SCMBs and overcome these SCMBs during the SCM implementation in an organization.

Modeling reconfigurability in supply chains using total interpretive structural modeling

2017 ◽  
Vol 14 (2) ◽  
pp. 194-221 ◽  
Author(s):  
Pallab Biswas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
New Product Development ◽  
Structural Changes ◽  
Structural Modeling ◽  
Global Market ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis ◽  
Expert Opinions

Purpose The purpose of this paper is to identify, analyze, and categorize the major enablers of reconfigurability that can facilitate structural changes within a supply chain in a global scenario. The paper also addresses five reconfigurability dimensions in the perspective of supply chains and the major enablers to attain them. The paper further aims to understand the mutual interactions among these enablers through the identification of hierarchical relationships among them. Design/methodology/approach A framework that holistically considers all the major enablers of reconfigurability has been developed. The hierarchical interrelationships between major enablers have been presented and interpreted using a novel qualitative modeling technique, i.e., total interpretive structural modeling (TISM), which is an extension of ISM. SPSS 22.0 is employed to carry out a one-tailed one-sample t-test further to test the hypotheses for validating the results of TISM. Impact matrix cross-reference multiplication applied to a classification (MICMAC) analysis has been employed to identify the driving and dependence powers of these reconfigurability enablers. Findings In this paper, 15 enablers for reconfigurability paradigm have been identified through literature review and expert opinions. The authors established interrelationships and interdependencies among these enablers and categorized them as enablers of each dimension. New product development and customer satisfaction come at the highest level of priority. The levels of these enablers were obtained using TISM. The authors compared the results with the clusters derived from MICMAC analysis, and the results are found to be well within the acceptable range. Research limitations/implications The study has implications for both practitioners and academia. The work provides a comprehensive list of enablers that are relevant to reconfigure supply chains in today’s volatile global market. This research will also help decision makers to strategically focus on the top-level enablers and their concerned dimensions. The research is based on an automobile company case study and can be extended to products with volatile and changing demands. Originality/value The proposed model for reconfigurability enablers using TISM is a new effort altogether in the area of supply chain management. The novelty of this research lies in its identification of specific enablers to reconfigure a supply chain through different dimensions.

Development of a framework to improve supply chain performance through e-business and sustainability enablers

2020 ◽  
Vol 31 (5) ◽  
pp. 1045-1070 ◽  
Author(s):  
Sumit Chandak ◽  
Neeraj Kumar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Business Processes ◽  
Customer Relationship ◽  
Supply Chain Performance ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Structural Framework ◽  
Fuzzy Micmac ◽  
Improve Supply Chain

PurposeThe main aim of the study is to develop a structural framework that includes e-business processes and sustainability-oriented enablers to improve supply chain performance.Design/methodology/approachTo improve supply chain performance, the present study conducts a detailed literature review to explore the key enablers based on e-business processes and sustainability aspects of various recognized databases. An automotive case organization is chosen to conduct a case study for developing the structural framework. The structural framework is developed by adopting an interpretive structural modeling approach. Furthermore, the fuzzy-MICMAC approach is applied to compute the driving and the dependence power of each selected enabler.FindingsThis study develops a structural framework that indicates the improved supply chain performance is achieved by “development of supply chain web system,” “strong customer relationship management,” and “enhancement in control over cost quality and sustainability” as the most critical enablers.Research limitations/implicationsThe enablers for the development of framework are obtained through the inputs of an expert panel. However, the researchers may conduct large scale surveys to strengthen the input components of the framework.Originality/valueThis is one of the unique studies that list down a set of 27 most critical e-business processes and sustainability based enablers to improve supply chain performance.

Modeling and analysis of FMS performance variables by fuzzy TISM

2019 ◽  
Vol 14 (1) ◽  
pp. 2-30 ◽  
Author(s):  
Vineet Jain ◽  
Vimlesh Kumar Soni
Keyword(s):  
Fuzzy Sets ◽  
Flexible Manufacturing ◽  
Material Handling ◽  
Extensive Literature ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Performance Variables ◽  
Micmac Analysis ◽  
Fuzzy Micmac ◽  
The Relationship

PurposeThe purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural modeling (ISM) has been reported for this but no study has been done regarding the interaction of its variables. Therefore, fuzzy TISM (total ISM) has been applied to deduce the relationship and interactions between the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.Design/methodology/approachFuzzy TISM and fuzzy MICMAC analysis have been applied to deduce the relationship and interactions among the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.FindingsIn total, 15 variables have been identified from the extensive literature review. The result showed that automation, use of automated material handling, an effect of tool life and rework percentage have high driving power and weak dependence power in the fuzzy TISM model and fuzzy MICMAC analysis. These are also at the lowest level in the hierarchy in the fuzzy TISM model.Originality/valueFuzzy TISM model has been suggested for manufacturing industries with fuzzy MICMAC analysis. This proposed approach is a novel attempt to integrate TISM approach with the fuzzy sets. The integration of TISM with fuzzy sets provides flexibility to decision-makers to further understand the level of influences of one criterion over another, which was earlier present only in the form of binary (0, 1) numbers; 0 represents no influence and 1 represents influence.

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kirti Nayal ◽  
Rakesh D. Raut ◽  
Maciel M. Queiroz ◽  
Vinay Surendra Yadav ◽  
Balkrishna E. Narkhede
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Service Providers ◽  
Hybrid Approach ◽  
Security And Privacy ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
State Regulations ◽  
Network Process ◽  
Fuzzy Micmac

PurposeThis 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/approach20 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.FindingsThe 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/implicationsThis 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/valueThis 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.

Sign in / Sign up

Export Citation Format

Share Document