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An Empirical Analysis of Supply Chain Risk and Uncertainty in Manufacturing Sector to Achieve Robustness

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Data Science and Analytics (REDSET 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1229))

Abstract

The primary purpose of supply chain risk management (SCRM) is to check the vulnerability of the supply chain and link the risks with strategies to manage them to improve the supply chain performance. The risks involved can be from the supplier side, production, transportation or even from the customer experience. The major part of the risk is due to the uncertainty in demand and risks caused by supplier issues. The robust supply chain needs to be conceived to manage the risks. The present study aims to investigate the correlation between uncertainty, risk, and robustness in the complex supply chain network. The research starts with data collection from 53 manufacturing firms about various supply chain risks. Structural equation modeling method for empirical data analysis is deployed to study the correlation among the three proposed SCRM tactics and hypothesis testing is carried out. The result shows that managing risk and uncertainty leads to achieving robustness in the supply chain. There is a positive correlation between risk and uncertainties. The empirical research outcomes can be further used to improve the risk management in supply chain network design.

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Authors and Affiliations

  1. BML Munjal University, Gururgam, Haryana, India

    Surya Prakash, Gianesahwar Aggarwal & Archit Gupta

  2. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Gunjan Soni

Authors
  1. Surya Prakash
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  2. Gianesahwar Aggarwal
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  3. Archit Gupta
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  4. Gunjan Soni
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Corresponding author

Correspondence to Surya Prakash .

Editor information

Editors and Affiliations

  1. GD Goenka University, Gurugram, India

    Usha Batra

  2. GD Goenka University, Sohna, Haryana, India

    Nihar Ranjan Roy

  3. University of Arkansas, Fayetteville, AR, USA

    Brajendra Panda

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Prakash, S., Aggarwal, G., Gupta, A., Soni, G. (2020). An Empirical Analysis of Supply Chain Risk and Uncertainty in Manufacturing Sector to Achieve Robustness. In: Batra, U., Roy, N., Panda, B. (eds) Data Science and Analytics. REDSET 2019. Communications in Computer and Information Science, vol 1229. Springer, Singapore. https://doi.org/10.1007/978-981-15-5827-6_31

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  • DOI: https://doi.org/10.1007/978-981-15-5827-6_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5826-9

  • Online ISBN: 978-981-15-5827-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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