Application of interpretive structural modelling for analyzing the factors of IoT adoption on supply chains in the Chinese agricultural industry

PurposeHumanitarian supply chains (HSCs) by their very nature require urgent reaction to unforeseeable needs, making it difficult to properly plan for the support of actual demands. As such, integrating sustainability into traditional HSC practices continues to present a challenge to governments, nongovernmental organizations (NGOs) and other humanitarian-related agencies. This study focuses on identifying and categorizing the leading enablers to green humanitarian supply chains (GHSCs) and proposes a model for improving the responsiveness based upon a fuzzy total interpretive structural modelling approach.Design/methodology/approachTotal interpretive structural modelling (TISM) uses group decision-making to identify contextual relationships among each pair of enablers and elucidates the nature of each underlying relationship. The fuzzy TISM shows the level of strength (very high influence, high influence, low influence and very low influence) of each enabler in relation to other enablers, which can help to inform management decision-making.FindingsGHSC management requires strategic planning of inventory and logistics management. The importance of collaborative relationship building with HSC partners for developing capability and the effective use of available resources are keys to success. These improved relationships also help to promote postponement and similar speculation-based logistics strategies, as well as advanced purchasing and pre-positioning strategies. Finally, the speed and quality of response is found to be the top enabler in GHSC management.Research limitations/implicationsOne noted shortcoming of the chosen research method is its reliance on subjective expert judgement. However, collecting judgements is at the basis of many research methods, and the research team took utmost care throughout the research process to allay biases. Future empirical research can further examine the relationships suggested herein. Managers can use the model developed in this research to consider impactful ways to design and execute sustainable HSCs.Originality/valueTo the best of the authors' knowledge, this is a novel attempt to identify enablers to GHSC management. Secondly, the research team has used an advanced methodology (fuzzy TISM) to develop the contextual inter-relationships among the enablers which has not been used earlier in this direction before and thus advances the GHSC literature.

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Barriers to the adoption of blockchain technology in business supply chains: a total interpretive structural modelling (TISM) approach

International Journal of Production Research ◽

10.1080/00207543.2020.1868597 ◽

2021 ◽

pp. 1-22

Author(s):

Deepak Mathivathanan ◽

K. Mathiyazhagan ◽

Nripendra P. Rana ◽

Sangeeta Khorana ◽

Yogesh K. Dwivedi

Keyword(s):

Supply Chains ◽

Structural Modelling ◽

Interpretive Structural Modelling ◽

Blockchain Technology ◽

Total Interpretive Structural Modelling

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Analyzing the interaction of factors for flexibility in supply chains

Journal of Modelling in Management ◽

10.1108/jm2-04-2016-0039 ◽

2017 ◽

Vol 12 (4) ◽

pp. 671-689 ◽

Cited By ~ 8

Author(s):

Rajesh Kr. Singh ◽

Saroj Koul ◽

Pravin Kumar

Keyword(s):

Supply Chains ◽

Product Life Cycle ◽

Economic Recession ◽

Interaction Matrix ◽

Strategy Development ◽

Structural Modelling ◽

Content Type ◽

Interpretive Structural Modelling ◽

Major Factors ◽

Suitable Framework

Purpose In the present scenario of global competition and economic recession, most of the organizations are facing tough challenge to survive in the market because of shortening product life cycle and reducing profit margin. Customers are seeking better design, production and delivery, which have made firms to concentrate on flexibility in supply chains. Therefore, the purpose of this study is to identify major factors and develop a suitable framework for flexibility in supply chains. Design/methodology/approach Based on literature review, about 14 factors have been identified. To develop relationship among these factors, a team of five experts from industry and academia was formed. Based on inputs from experts, different relationships are developed among factors to form structural self-interaction matrix (SSIM). Based on this matrix, a flexibility framework is developed by interpretive structural modelling approach. Findings Top management commitment, strategy development for flexible SC, application of advance technology and IT tools, information sharing in SC members, trust development among supply chain members have emerged as major driving factors. Logistics and warehouse management, suppliers flexibility, distribution flexibility and manufacturing flexibility have emerged as dependent factors. Research limitations/implications Framework developed in this study is based on interpretive structural modelling. This framework can be further validated with some case analysis and empirical findings. Originality/value Findings of the study can be useful for industry professionals to develop strategies for flexible supply chains. It will help them in taking new initiatives for making supply chains more responsive and proactive for customers demand.

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