Social implications of leagile manufacturing system: TISM approach

Virmani, Naveen; Saha, Rajeev; Sahai, R.

doi:10.1504/ijpqm.2018.090265

Cited by 5 publications

(4 citation statements)

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“…Defining the contextual relationship between the identified CSFs is central to the creation of a hierarchical structure (Kedia, 2013; Virmani, 2018). Contextual links between CSFs are discussed and interpreted here and shown in appendix with expert feedback.Step 3: Structural Self Interaction Matrix (SSIM)…”

Section: Methodsmentioning

confidence: 99%

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Digital supply chain to unlock new agility: a TISM approach

Choudhury

Behl

Sheorey

et al. 2021

BIJ

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PurposeTraditional supply chain arrangements have failed to keep up with escalating customer demands and breakthrough innovations. The way forward is a flexible yet innovative network that leverages ecosystem partners and digital tools to unlock new agility. The paper aims at identifying and analyzing numerous critical success factors (CSFs) that may improve the efficiency of a digital supply chain.Design/methodology/approachTwelve CSFs are identified in this paper through an extensive literature survey. Expert opinion has been considered and the hierarchical structure built using total interpretative structural modeling (TISM) which highlights the interdependencies between these CSFs. Cross-impact matrix multiplication (MICMAC) is used to determine the driving and dependence power of each factor.FindingsThis study identified 12 CSFs through an extensive literature survey. The ISM model resulted in six different levels beginning from redesign organization at the bottom of the structure. The TISM model explained why redesigning the organization is pivotal to bringing about novel agility in the supply chain. MICMAC analysis confirmed that the following enhanced the success of a digital supply chain: Sales and Operation Planning Strategies, Strategic Sourcing Techniques, Smart Manufacturing Processes and Warehouse Management.Research limitations/implicationsVarious other components contributing to the 12 CSFs identified in this paper may be discovered and detailed in future research. Additionally, further research is required to expand the existing technology-based services structural model to a more empirical form.Practical implicationsThis study offers a comprehensive but not exhaustive list of CSFs essential to digital supply chain growth. It will enable market experts and leaders to concentrate on key factors leading to tactical decisions and maximum value for firms.Originality/valueThe paper seeks to add to the body of knowledge on real digitally-led supply chain transformation, which is still in its early stages. This study is one of the first, if not the first, to examine success factors critical to the improvement of the performance of the supply chain. It lays the foundation for further research in this field.

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Section: Methodsmentioning

confidence: 99%

“…Step 1: Variables Identification and Definition For the present study, several factors had to be finalized on the basis of literature review or panel discussion (Kedia, 2013;Virmani, 2018). 12 supply chain CSFs were identified and defined through the literature survey (Table 2).…”

Section: Digital Supply Chain To Unlock New Agilitymentioning

confidence: 99%

Digital supply chain to unlock new agility: a TISM approach

Choudhury

Behl

Sheorey

et al. 2021

BIJ

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“…Mangla et al ( 2014 ) studied the performance variables under the uncertainty and risk of a sustainable supply chain. Further, the application of TISM can also be seen in the area of industry 4.0 (Ajmera & Jain, 2019 ; Jain & Ajmera, 2020 ), lean manufacturing (Chaple et al, 2021 ; Singh et al, 2018 ; Virmani et al, 2018 ), flexibility (Yadav & Sagar, 2021 ; Jain & Raj, 2015 ; Mangla et al, 2014 ), higher education (Sravat & Pathranarakul, 2022 ; Menon et al, 2021 ), implementation (Chaple et al, 2021 ; Singh & Dhir, 2022 ), start-up ecosystem (Sindhwani et al, 2022 ; Singh et al, 2020 ; Singh et al, 2019 ), and information systems (Dwivedi & Madaan, 2020 ; Singh & Singla, 2021 ). With the advancement of technologies and fields, TISM is also applied in the area of blockchain (Shardeo et al, 2020 ; Mathivathanan et al, 2021 ; Dwivedi et al, 2022 ), internet of things (Patil & Suresh, 2019 ; Singh et al, 2020 ), artificial intelligence (Mir et al, 2020 ; Jain et al, 2021 ), and health care research (Logesh & Vinodh, 2022 ; Priyadarsini et al, 2020 ; Patri & Suresh, 2017 ).…”

Section: Overview Of Tism: Review and Applicationmentioning

confidence: 99%

Developing an evidence-based TISM: an application for the success of COVID-19 Vaccination Drive

Singh

Dhir²,

Sushil³

2022

Ann Oper Res

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The study illustrates an application of evidence data for performing Total Interpretive Structural Modeling (TISM). TISM is widely used to analyze the critical success factors or inhibitors and their interlinkages. This study uses learning from evidence data, specifically social media analytics, to identify the relationship between the elements. Thus, it leads to the advancement of the TISM-P methodology with evidence-based TISM (TISM-E). This study uses Twitter as a source of evidence data. Further, 2,60,297 tweets were used to illustrate the process of TISM-E. The paper demonstrates the application of TISM-E for the success of the COVID-19 vaccination drive. The pandemic effects are long-term; therefore, the hierarchical model developed shows a sustainable approach for vaccinating maximum population. Further, the framework developed will ensure the distribution efficacy of vaccines. In addition, it will aid practitioners in developing future vaccination policies. The enhanced model provides evidence for polarity (positive/negative) of relationships and can help to build propositions for theory development. The study contributes to healthcare, modeling research, and graph-theoretic literature.

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“…Therefore, Fuzzy-TISM approach gives a wider flexibility to express the level of influence using fuzzy numbers (Khatwani et al, 2015). Virmani et al (2018) utilized a TISM technique to identify the driving and dependent social implications of leagile manufacturing. Deshmukh and Mohan (2017) established a TISM model to analyze the 12 DCM (demand chain management) variables.…”

Section: Introductionmentioning

confidence: 99%

Modeling and analysis of FMS performance variables by fuzzy TISM

Jain

Soni

2019

JM2

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Purpose The 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/approach Fuzzy 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. Findings In 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/value Fuzzy 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.

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Social implications of leagile manufacturing system: TISM approach

Cited by 5 publications

References 0 publications

Digital supply chain to unlock new agility: a TISM approach

Digital supply chain to unlock new agility: a TISM approach

Developing an evidence-based TISM: an application for the success of COVID-19 Vaccination Drive

Modeling and analysis of FMS performance variables by fuzzy TISM

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