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.

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.

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.

A fuzzy AHP and TOPSIS methodology to evaluate 3PL in a supply chain

2012 ◽  
Vol 7 (3) ◽  
pp. 287-303 ◽  
Author(s):  
Pravin Kumar ◽  
Rajesh K. Singh
Keyword(s):  
Supply Chain ◽  
Service Providers ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Third Party ◽  
Preference Ranking ◽  
Relative Importance ◽  
Content Type ◽  
Logistics Service Providers ◽  
Hierarchy Process

PurposeThe purpose of this paper is to provide an insight into the use of an integrated approach of fuzzy analytical hierarchy process (fuzzy AHP) and TOPSIS in evaluating the performance of global third party logistics service providers for effective supply chain management.Design/methodology/approachIn this study, the integration of fuzzy AHP with TOPSIS is proposed in determining the relative importance (weight) of criteria and then ranking of 3PLs.FindingsFindings show that the logistics cost and service quality are two most important criteria for performance rating of 3PLs. Deciding the relative importance of various criteria for 3PLs evaluation is a complex task. The superiority of one criterion over the other varies from person to person and firm to firm. Therefore, to capture the variability in decision fuzzy extended AHP is very useful tool. Finally, the preference raking of alternatives are found using TOPSIS.Research limitations/implicationsFuzzy AHP is a complex methodology and requires more numerical calculations than the traditional AHP and hence it increases the effort. But in this paper single stage fuzzy AHP is used to simplify the process. Fuzzy AHP is integrated with TOPSIS for preference ranking of 3PL, which provides a good methodology to rank 3PLs.Originality/valueThere is a lack of research in the literature to deal directly with the uncertainty of human decisions in evaluating the relative importance of multiple criteria. Therefore, fuzzy AHP is an appropriate methodology to find the relative importance of the criteria to rank the 3PLs using TOPSIS.

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.

Evaluating sustainable supply chain indicators using fuzzy AHP

2017 ◽  
Vol 24 (6) ◽  
pp. 1742-1766 ◽  
Author(s):  
Divesh Kumar ◽  
Chandra Prakash Garg
Keyword(s):  
Supply Chain ◽  
Automotive Industry ◽  
Environmental Concern ◽  
Fuzzy Ahp ◽  
Relevant Literature ◽  
Three Dimensions ◽  
Successful Implementation ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Sustain Ability

Purpose Sustainability in supply chain is gaining attention in recent years due to environmental concern, enforced legislation, green issues, social responsibility, etc. Sustainable supply chain (SSC) has revolved around the various dimensions including economy, environment and societal factors since its inception. The purpose of this paper is to identify, prioritize and evaluate the indicators of SSC so that organizations can cultivate strategies to implement them on priority. Design/methodology/approach This paper proposes a methodology based on fuzzy analytic hierarchy process to prioritize the indicators of SSC. A numerical analysis of Indian automotive industry is presented to demonstrate the use of the proposed method. This proposed method considered fuzzy framework that can handle impreciseness and uncertainty. Sensitivity analysis is also performed to test the robustness of the proposed model. Findings Potential indicators are identified from relevant literature and validated by industry experts. This research finalizes the SSC indicators under three dimensions so that prioritization of identified indicators can be developed and the insights relationship of factors would be explored. The results of the study found that environmental and social dimensions of sustainability contribute more toward the sustainability. Research limitations/implications This study is limited to identify evaluation factors and other factors have not been identified and categorized. Evaluation is done by experts in this area so it is natural that views of decision makers may be subjective and vary with regard to industry type, priorities, resources, etc. Practical implications This study will help industry to identify, evaluate and prioritize factors for successful implementation of sustainability in their supply chain. Automotive companies could device these factors by applying the outcome of the study in their operations with higher priority to integrate sustainability in their supply chain. Originality/value These factors are identified to implement sustain ability into supply chain practices for automotive industry.

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.

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.

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.

Modeling the key barriers of knowledge management adoption in sustainable supply chain

2020 ◽  
Vol 33 (5) ◽  
pp. 1077-1109 ◽  
Author(s):  
Muhammad Nazam ◽  
Muhammad Hashim ◽  
Sajjad Ahmad Baig ◽  
Muhammad Abrar ◽  
Rizwan Shabbir
Keyword(s):  
Knowledge Management ◽  
Supply Chain ◽  
Analytical Hierarchy Process ◽  
Bullwhip Effect ◽  
Sustainable Supply Chain ◽  
Fuzzy Analytical Hierarchy Process ◽  
Food Sector ◽  
Content Type ◽  
Fuzzy Vikor ◽  
Hierarchy Process

PurposeThe food industry is crucial in delivering healthy products for life saving of the society. The identification of key barriers of knowledge management (KM) is desired to enhance the sustainability of the industry. KM has been seen as a part of sustainable development by reducing the bullwhip effect in the entire supply chain. The core objective of the existing research is to prioritize the essential factors of KM adoption in sustainable supply chain (SSC) based on fuzzy analytical hierarchy process (FAHP) method.Design/methodology/approachIn order to fulfill objectives of this study, an extensive review of literature and a questionnaire-based field visits were conducted. A total of five major barriers categories and 22 sub-barriers categories were identified in food sector of Pakistan using experts' inputs. This study employed fuzzy analytical hierarchy process (FAHP).FindingsManagerial barriers, innovation and technological barriers categories are found to be highly prioritized among others. Further, the sensitivity analysis is applied to check the incremental changes of ranked barriers. This prioritization of barriers and incremental changes in them is expected to serve food sector for long-term sustainability and competitive advantage for importers and exporters. Finally, the findings of this research are very helpful for industrial experts, practitioners, consultants and government officials in effectively developing policies regarding KM adoption in line with sustainable goals.Research limitations/implicationsThe present work is conducted in the Pakistani context; however, the benchmark model may be tested and applied to other developing countries to compare the outcomes. For further research, the identified barriers may also be evaluated to establish their inter-relationships, using ISM, DEMATEL, ANP, etc. Similarly, the results of this study can also be compared with that of other fuzzy multi-criteria techniques like fuzzy TOPSIS, fuzzy VIKOR, fuzzy ELECTRE, fuzzy PROMETHEE, or fuzzy VIKOR.Practical implicationsThis research study can facilitate policymakers, government bodies, stakeholders and supply chain professionals to recognize the key barriers they may encounter in adopting KM practices in their SSC. Additionally, this work helps managers to evaluate the identified barriers by computing their relative importance in adopting KM practices at managerial levels like strategically, tactically and operationally activities in business. This study also facilitates industrial management in formulating policies and action plans in case of implementation, eliminating the barriers in adoption of KM, and SSC successfully.Originality/valueFew research studies were conducted on KM adoption in industries of China, India, Turkey, Saudi Arabia and Malaysia, but due to workforce diversity these industries have dissimilar views of experts about KM adoption. This study significantly contributed to fill the existing literature gap for prioritization of key barriers against KM implementation in Pakistani context.

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