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Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach

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Supply Chain Management in Manufacturing and Service Systems

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 304))

Abstract

Risks are inevitable in supply chains, and they need to be detected early and appropriately addressed. This chapter primarily attempts to identify early warning signals and implement suitable mitigation decisions to meet exigencies related to the management of supply chain risks. Further, the chapter also presents an approach that addresses the risks in an integrated manner. First, a framework is essential to understand the relationships between the independent and dependent variables. An empirical study is undertaken by develo** a questionnaire that captures the perceptions of the supply chain practitioners on risks perceived in their supply chains, and the framework is subjected to validity tests. Secondly, the data obtained from these surveys is utilized to develop a fuzzy model for identifying and predicting all plausible risks based on the instantaneous risk vector. Fuzzy Cognitive Map (FCM) is used to represent the overall behavior of the dynamical system of the supply chain. The instantaneous risk vector is passed on to the dynamical system to identify all plausible risks that may appear in near future. The resultant vector obtained suggests that ignoring the initially perceived risks eventually lead to possible disruptions in the supply chain. The resultant vector thus obtained is useful for decision making to alleviate the impact of various types of risks. Finally, the relative comparison of the mitigation strategies’ ranking was made for the results obtained from regression, FCM, and Fuzzy TOPSIS.

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Notes

  1. 1.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  2. 2.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  3. 3.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  4. 4.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  5. 5.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  6. 6.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  7. 7.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  8. 8.

    Indicates the factors adapted appropriately and suitably from the work of Dath et al. (2009). The considered items are suitably modified and additional items added to every factor.

  9. 9.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  10. 10.

    Indicates the factors adapted appropriately and suitably from the work of Sodhi and Chopra (2004) and Wagner and Bode (2006).

  11. 11.

    https://tinyurl.com/scrmquestionnaire

  12. 12.

    https://tinyurl.com/scrmquestionnaire

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Acknowledgements

The authors are most grateful to the reviewers of the questionnaire, who have suggested constructive improvements and augmentative comments. The authors also thank the respondents for taking their valuable time in participating in the empirical study. The authors are grateful to the editors and reviewers, who have given us a chance to improve the original version of the book chapter.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Amrita College of Engineering and Technology, Nagercoil, Tamil Nadu, India

    V. Viswanath Shenoi

  2. Department of Mechanical and Manufacturing Engineering, M S Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India

    T.  N. Srikantha Dath

  3. Department of Management Studies, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India

    Chandrasekharan Rajendran

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  1. V. Viswanath Shenoi
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  2. T.  N. Srikantha Dath
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  3. Chandrasekharan Rajendran
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Correspondence to V. Viswanath Shenoi .

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Editors and Affiliations

  1. Department of Industrial and Manufacturing Systems Engineering, College of Engineering, Department of Marketing, Trulaske College of Business, University of Missouri, Columbia, MO, USA

    Sharan Srinivas

  2. Department of Marketing, Trulaske College of Business, Department of Industrial and Manufacturing Systems Engineering, College of Engineering, University of Missouri, Columbia, MO, USA

    Suchithra Rajendran

  3. School of Business, Economics and Information Systems, University of Passau, Passau, Germany

    Hans Ziegler

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Shenoi, V.V., Dath, T. .S., Rajendran, C. (2021). Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach. In: Srinivas, S., Rajendran, S., Ziegler, H. (eds) Supply Chain Management in Manufacturing and Service Systems. International Series in Operations Research & Management Science, vol 304. Springer, Cham. https://doi.org/10.1007/978-3-030-69265-0_4

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