Modelling and analysis of energy efficiency drivers by fuzzy ISM and fuzzy MICMAC approach

Sindhwani, Rahul; Mittal, Varinder Kumar; Singh, Punj Lata; Kalsariya, Vivek; Salroo, Faizan

doi:10.1504/ijpqm.2018.094768

Cited by 15 publications

(7 citation statements)

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“… Portrays an intricate system in a simplified way Fails to handle imprecise and vague information usually exists in real cases Identifies the structure of the influential aspects in a system typically in a hierarchical way, i.e. digraph Cannot answer “why” aspects which typically helps in a theory building Evaluate the driving and dependence power of aspects Used a Consensus vote method to aggregate the experts’ judgments, which itself comprises drawbacks (Huang et al, 2021 ; Jena et al, 2017 ; Sindhwani & Malhotra, 2017 ; Sushil, 2012 ) Explain “what” and “how” characteristics of a system (Kamble et al, 2018 ; Li et al, 2019 ; Majumdar & Sinha, 2019 ; Sivaprakasam et al, 2015 ) Total ISM (TISM) Includes all the benefits of ISM Uses binary scale to measure the influence Attempts to answer the “why” phenomenon (Huang et al, 2021 ; Jena et al, 2017 ; Sindhwani & Malhotra, 2017 ; Sushil, 2018 ) Fails to compute the level of influence Fails to handle imprecise and vague information usually exists in real cases Uses consensus vote method to aggregate the experts’ judgments (Huang et al, 2021 ; Jena et al, 2017 ) Fuzzy ISM Includes all the benefits of classical ISM We have identified the following drawbacks in Fuzzy ISM Effectively Handles the imprecise or vague nature through one-grade membership degree Aggregates the experts’ opinions using the consensus vote method Describe the preference judgment values of the decision-maker efficiently Unable to incorporate the membership degrees, namely—‘truth, indeterminacy, and falsity’ degrees Computes the level of influence (Lamba & Singh, 2018 ; Sindhwani et al, 2018 ; Srivastava & Dashora, 2021 ...…”

Section: Methodsmentioning

confidence: 99%

Examining the barriers to operationalization of humanitarian supply chains: lessons learned from COVID-19 crisis

et al. 2022

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Humanitarian supply chains (HSC) have vital significance in mitigating different disruptive supply chain risks caused due to natural or man-made activities such as tsunami, earthquakes, flooding, warfare, or the recent COVID-19 pandemic. Each kind of disaster poses a unique set of challenges to the operationalization of HSC. This study attempts to determine the critical barriers to the operationalization of HSC in India during the COVID-19 pandemic. Initially, we determined and validated 10 critical barriers to HSC operationalization through a Delphi method. Further, we analyzed the barriers by computing the driving and dependence power of each barrier to determine the most critical ones. To do so, we coined a distinct form of interpretive structural modeling (ISM) by amalgamating it with the neutrosophic approach, i.e. Neutrosophic ISM. The findings indicate, “lack of Government subsidies and support, lack of skilled and experienced rescuers, and lack of technology usage” are the most critical barriers that influence the streamline operations of HSC during the COVID-19 outbreak, unlike other disruptions. This is the first-of-its-kind research work that has identified and analyzed the critical barriers to HSC operationalization during COVID-19 in the Indian context. The results and recommendations of the study can aid policymakers and HSC professionals in formulating suitable strategies for successful HSC operations. Supplementary Information The online version contains supplementary material available at 10.1007/s10479-022-04752-x.

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Section: Methodsmentioning

confidence: 99%

Examining the barriers to operationalization of humanitarian supply chains: lessons learned from COVID-19 crisis

et al. 2022

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“…By application of approach such as analytic hierarchy process (AHP) the interdependencies between the factors cannot be observed (Mittal et al , 2019). Singh et al (2019) observed that DEMATEL is the preferred technique over AHP, total interpretive structural modeling, interpretive structural modeling or any multiple-criteria decision making techniques as it dissevers challenges into cause and effect group and indicates the severity of their effects too (Sindhwani et al , 2018; Shanker et al , 2019; Sindhwani et al , 2019a; Sindhwani et al , 2021). Bai and Satir (2020) stated that DEMATEL has a range to respond (0, 1, 2, 3 and 4) to explore the relationship between factors and further help in formulating futuristic strategies.…”

Section: Methodsmentioning

confidence: 99%

IIoT implementation challenges: analysis and mitigation by blockchain

Kumar

Sindhwani

Singh

2021

JGOSS

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Purpose The purpose of this methodology is to categorise the challenges into cause and effect group. The modern scenario of customization, personalization and multi-restrictive working because of pandemics has affected the operations of manufacturing small and medium enterprises (SMEs). In the new normal, the digitalization of manufacturing SMEs can be the path breaker. Modern digitalization includes a mix of technologies such as the industrial internet of things (IIoT), the internet of things, cyber-physical system and big data analytics. This digitalization can help in achieving new design changes, efficient production scheduling, smart manufacturing and unrestricted on-time delivery of quality products. This research paper aims to recognize and analyze the challenges faced while implementing IIoT technologies in manufacturing SMEs and tries to find the possibility of mitigating challenges by blockchain technology. Design/methodology/approach There were ten challenges of IIoT implementation identified from the literature review and experts’ opinions. To collect information from Indian manufacturing SMEs, a survey tool was formed in the form of a questionnaire. On the fundament of responses received from industrial experts, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique has been used for categorizing these challenges into cause and effect groups. Further, the authors tried to mitigate observed challenges with the help of blockchain technology. Findings With the implementation of IIoT technologies, the manufacturing processes become conciliatory, effective and traceable in real time. Observation of the current study states that the top effect group challenges such as the security of data and reliability of technologies can be mitigated by enabling blockchain technologies. The authors conclude that blockchain-enabled IIoT technologies will be highly beneficial for the Indian SMEs strategically and practically in the current scenario. Research limitations/implications Methodology of DEMATEL focuses on responses received from experts. The broader approach of survey from manufacturing organizations is compromised due to small sample size in this methodology. Experts approached for survey were from manufacturing SMEs of Delhi National Capital Region only. Broader survey-based techniques may be applied covering different sectors of SMEs in future work. Practical implications Technologies such as blockchain can facilitate advanced security in the application of IIoT and other such practices. While dealing with significant issues and challenges of new technologies, blockchain gives an edge of balance in the current scenario. Its properties of fixity, temper evident and circumvent fraud make this technology ideal for the digitalization of the manufacturing systems in SMEs. Originality/value Digitalization of manufacturing facilities is the need of the hour. Pandemic challenges have highlighted the urgency of it. This research will motivate and guide the manufacturing SMEs in planning strategies and long-term policies in implementing modern technologies and coping up with the pandemic challenges.

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“…); (2) Unable to handle vague and ambiguous information; (3) The multiple experts' opinions are aggregated using the consensus, which itself comprises subjectivity; (4) Does not include membership degrees viz. "truth, indeterminacy and falsity" (Dohale et al, 2022a;Jena et al, 2017;Sindhwani et al, 2018). To overcome these shortcomings in the existing forms of ISM, Enablers of circular supply chain Dohale et al (2022a, b, c) developed N-ISM approach by integrating ISM with Neutrosophic theory to cope with uncertainties and inconsistencies in experts' judgments (Nabeeh et al, 2019).…”

Section: Neutrosophic Interpretive Structural Modeling (N-ism)mentioning

confidence: 99%

Analyzing the enablers of circular supply chain using Neutrosophic-ISM method: lessons from the Indian apparel industry

Dohale

Ambilkar

Kumar

et al. 2023

IJLM

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PurposeThis research identifies the enablers for implementing circular supply chains (CSCEs) and analyzes interrelationships between them to quantify their driving and dependence power to understand the critical CSCEs.Design/methodology/approachInitially, 10 CSCEs are identified for the Indian apparel industries through an extant literature review and validated using the Delphi method by seeking experts' opinions. The identified CSCEs are subjected to a novel neutrosophic interpretive structural modeling (N-ISM) method to capture the interrelationships between CSCEs and compute the driving and dependence power of CSCEs.FindingsThe findings of the present research work revealed that “supportive legislative framework, awareness of circular economy's potential for revenue gain and availability of trained research and development (R&D) team” are the critical CSCEs that need to be considered while implementing a circular supply chain in apparel industries.Research limitations/implicationsThis study offers insightful implications to guide practitioners in implementing the circular economy in apparel supply chains.Originality/valueThis research work is one of the earlier studies to analyze the enablers for implementing circular supply chains. This study has explored CSCEs in the context of apparel industries. From a methodological perspective, the novel N-ISM method is worth highlighting as the originality of the work.

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Modelling and analysis of energy efficiency drivers by fuzzy ISM and fuzzy MICMAC approach

Cited by 15 publications

References 0 publications

Examining the barriers to operationalization of humanitarian supply chains: lessons learned from COVID-19 crisis

Examining the barriers to operationalization of humanitarian supply chains: lessons learned from COVID-19 crisis

IIoT implementation challenges: analysis and mitigation by blockchain

Analyzing the enablers of circular supply chain using Neutrosophic-ISM method: lessons from the Indian apparel industry

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