Skip to main content
SpringerLink
Log in

Ranking of Critical Risk Factors in the Indian Automotive Supply Chain Using TOPSIS with Entropy Weighted Criterions

  • Chapter
  • First Online:
Technology Innovation in Mechanical Engineering

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

To survive and grow in today’s world characterized by fierce competition and surrounded by uncertain environments, manufacturing industries are forced to manage internal and external supply chain (SC) disruptions to achieve operational excellence. Automotive manufacturing industries have multiple collaborations at various operations levels, making a complex network of linked activities. Any unprecedented event of slight to severe magnitude adversely hampers various workday activities in the organization. Multiple researchers have cited the susceptibility of the automotive supply chain to numerous risks. Mitigation of risks is vital as complete elimination is impossible on many occasions. This research aims to find out risk factors through a literature review coupled with input from industry experts. After identifying risks, this article ranks the risk factors critical to the automotive SC based on the severity of adverse impacts by considering five different criterions using Technique for Ordered Preference and Similarity to Ideal Solution (TOPSIS). The weight of the evaluation criteria was calculated based on the entropy method. This study identifies thirteen critical risk factors (CRFs), and ranking tools prioritizes “Delay risks,” “Management risks,”, “Supplier risks,” “Employees risks,” and “Inappropriate tools and techniques risks” as the top five CRFs. These research findings will support managers and policymakers framing risk mitigation plans to achieve operational excellence in the entire SC and use the systematic modeling approach to identify CRFs with adverse impacts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ramey, V.A., Vine, D.J.: Tracking the source of the decline in GDP volatility: an analysis of the automobile industry. SSRN Electron. J. (2011). https://doi.org/10.2139/ssrn.724921

  2. Kumar, G., Singh, R.K., Jain, R., Kain, R., Naveen: Analysis of demand risks for the Indian automotive sector in globally competitive environment. Int. J. Organ. Anal. (2020).https://doi.org/10.1108/IJOA-03-2020-2076

  3. SIAM: Society of Indian Automobile Manufacturers. VOLUNTARY RECALL INFORMATION (2021). https://www.siam.in/siamvoluntaryrecall.aspx?mpgid=31&pgidtrail=84&mpgid=31&pgidtrail=84. Accessed 11 March 2021

  4. Sharma, S., Singh, R., Matai, R.: Force field analysis of Indian automotive strategic sourcing risk management enablers and barriers. Meas. Bus. Excell. 22(3), 258–275 (2018). https://doi.org/10.1108/MBE-09-2017-0062

    Article  Google Scholar 

  5. Babu, H., Bhardwaj, P., Agrawal, A.K.: Modelling the supply chain risk variables using ISM: a case study on Indian manufacturing SMEs. J. Model. Manag. (2020). https://doi.org/10.1108/JM2-06-2019-0126

    Article  Google Scholar 

  6. Tang, C.S.: Perspectives in supply chain risk management. Int. J. Prod. Econ. 103(2), 451–488 (2006). https://doi.org/10.1016/j.ijpe.2005.12.006

    Article  Google Scholar 

  7. Uta Jüttner, M.C., Peck, H.: Supply chain risk management : outlining an agenda for future research. Int. J. Logist. Res. Appl. 6(4), 197–210 (2003). https://doi.org/10.1080/13675560310001627016

  8. Hwang, C.L., Lai, Y.J., Liu, T.Y.: A new approach for multiple objective decision making. Comput. Oper. Res. 20(8), 889–899 (1993). https://doi.org/10.1016/0305-0548(93)90109-V

    Article  MATH  Google Scholar 

  9. Shannon, C.E.: the mathematical theory of communication. ACM Sigmobile Mob. Comput. Commun. Rev. 5(1), 3–55 (2001)

    Article  MathSciNet  Google Scholar 

  10. Kiani, R., Goh, M., Kiani, N.: Supplier selection with Shannon entropy and fuzzy TOPSIS in the context of supply chain risk management. Procedia Soc. Behav. Sci. 235, 216–225 (2016). https://doi.org/10.1016/j.sbspro.2016.11.017

    Article  Google Scholar 

  11. Dehdasht, G., MS, F., Zin, R., NZ, A.: A hybrid approach using entropy and TOPSIS to select key drivers for a successful and sustainable lean construction implementation. PLoS One 15(2) (2020). https://doi.org/10.1371/journal.pone.0228746

  12. Thun, J.H., Hoenig, D.: An empirical analysis of supply chain risk management in the German automotive industry. Int. J. Prod. Econ. 131(1), 242–249 (2011). https://doi.org/10.1016/j.ijpe.2009.10.010

    Article  Google Scholar 

  13. Gautam, A., Prakash, S., Soni, U.: Supply chain risk management and quality: a case study and analysis of Indian automotive industry. Int. J. Intell. Enterp. 5(1–2), 2–17 (2018). https://doi.org/10.1504/IJIE.2018.091189

    Article  Google Scholar 

  14. Silva, E.S., Wu, Y., Ojiako, U.: Developing risk management as a competitive capability. Strateg. Chang. 22(5–6), 281–294 (2013). https://doi.org/10.1002/jsc.1940

    Article  Google Scholar 

  15. Mehrjerdi, Y.Z., Dehghanbaghi, M.: A dynamic risk analysis on new product development process. Int. J. Ind. Eng. Prod. Res. 24(1), 17–35 (2013)

    Google Scholar 

  16. Kidane, T.T., Sharma, R.R.K.: Relating supply chain risks to supply chain strategy. In: Proceedings of the International Conference on Industrial Engineering and Operations Management, 8–10 March, pp. 70–78 (2016)

    Google Scholar 

  17. Simons, R.: How risky is your company? Harv. Bus. Rev. 77(3) (1999)

    Google Scholar 

  18. Prakash, A., Agarwal, A., Kumar, A.: Risk assessment in automobile supply chain. Mater. Today Proc. 5(2), 3571–3580 (2018). https://doi.org/10.1016/j.matpr.2017.11.606

    Article  Google Scholar 

  19. Nunes, B., Bennett, D.: Environmental threats and their impacts on the automobile industry. In: International Conference on Management of Technology, April 2008 (2008). https://doi.org/10.13140/2.1.2227.0248

  20. Deep, S., Gajendran, T., Jefferies, M.: A systematic review of ‘enablers of collaboration’ among the participants in construction projects. Int. J. Constr. Manag. 0(0), 1–13 (2019). https://doi.org/10.1080/15623599.2019.1596624

  21. Alikhani, R., Torabi, S.A., Altay, N.: Strategic supplier selection under sustainability and risk criteria. Int. J. Prod. Econ. 208, 69–82 (2019). https://doi.org/10.1016/j.ijpe.2018.11.018

    Article  Google Scholar 

  22. Islam, A., Tedford, D.: Risk determinants of small and medium-sized manufacturing enterprises (SMEs)— an exploratory study in New Zealand. J. Ind. Eng. Int. 8(1), 1–13 (2012). https://doi.org/10.1186/2251-712X-8-12

    Article  Google Scholar 

  23. Dandage, R.V., Mantha, S.S., Rane, S.B.: Strategy development using TOWS matrix for international project risk management based on prioritization of risk categories. Int. J. Manag. Proj. Bus. 12(4), 1003–1029 (2019). https://doi.org/10.1108/IJMPB-07-2018-0128

    Article  Google Scholar 

  24. Dey, P.K., Ogunlana, S.O.: Selection and application of risk management tools and techniques for build-operate-transfer projects. Ind. Manag. Data Syst. 104(3), 334–346 (2004). https://doi.org/10.1108/02635570410530748

    Article  Google Scholar 

  25. Batkovskiy, A.M., Konovalova, A.V., Semenova, E.G., Trofimets, V.Y., Fomina, A.V.: Risks of development and implementation of innovative projects. Mediterr. J. Soc. Sci. 6(4), 243–253 (2015). https://doi.org/10.5901/mjss.2015.v6n4s4p243

    Article  Google Scholar 

  26. Czuchry, A.J., Yasin, M.M.: Managing the project management process. Ind. Manag. Data Syst. 103(1–2), 39–46 (2003). https://doi.org/10.1108/02635570310456887

    Article  Google Scholar 

  27. Ojiako, U., Johansen, E., Greenwood, D.: A qualitative re-construction of project measurement criteria. Ind. Manag. Data Syst. 108(3), 405–417 (2008). https://doi.org/10.1108/02635570810858796

    Article  Google Scholar 

  28. Cao, Q., Hoffman, J.J.: A case study approach for developing a project performance evaluation system. Int. J. Proj. Manag. 29(2), 155–164 (2011). https://doi.org/10.1016/j.ijproman.2010.02.010

    Article  Google Scholar 

  29. Dandage, R.V., Mantha, S.S., Rane, S.B., Bhoola, V.: Analysis of interactions among barriers in project risk management. J. Ind. Eng. Int. 14(1), 153–169 (2018). https://doi.org/10.1007/s40092-017-0215-9

    Article  Google Scholar 

  30. Maya, R.A.: Performance management for syrian construction projects. Int. J. Constr. Eng. Manag. 5(3), 65–78 (2016). https://doi.org/10.5923/j.ijcem.20160503.01

    Article  Google Scholar 

  31. Keil, M., Cule, P.E., Lyytinen, K., Schmidt, R.C.: A framework for identifying software project risks. Commun. ACM 41(11), 76–83 (1998). https://doi.org/10.1145/287831.287843

    Article  Google Scholar 

  32. Abdolshah, M., Moradi, M.: Fuzzy quality function deployment: an analytical literature review. J. Ind. Eng. 2013, 1–11 (2013). https://doi.org/10.1155/2013/682532

    Article  Google Scholar 

  33. Islam, A., Tedford, D.: Implementation of risk management in manufacturing industry—an empirical investigation. Int. J. Res. Manag. Technol. 2(3), 258–267 (2012). [Online]. Available http://www.iracst.org/ijrmt/papers/vol2no32012/1vol2no3.pdf

  34. Shevtshenko, E., Mahmood, K.: Analysis of machine production processes by risk assessment approach. J. Mach. Eng. 15(1), 112–124 (2015)

    Google Scholar 

  35. Shin, J., Lee, S., Yoon, B.: Identification and prioritisation of risk factors in R&D projects based on an R&D process model. Sustainability. 10(4), 1–18 (2018). https://doi.org/10.3390/su10040972

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Research Scholar at Rajiv Gandhi Institute of Technology, Mumbai and Assistant Professor at St. John College of Engineering, Palghar, Maharashtra, India

    Vinod G. Surange

  2. Principal, Rajiv Gandhi Institute of Technology, Mumbai, Maharashtra, India

    Sanjay U. Bokade

Authors
  1. Vinod G. Surange
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sanjay U. Bokade
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Bansal Institute of Science and Technology, Bhopal, Madhya Pradesh, India

    Prem Kumar Chaurasiya

  2. Department of Mechanical Engineering, National Institute of Technology Patna, Patna, Bihar, India

    Abhishek Singh

  3. Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India

    Tikendra Nath Verma

  4. Department of Mechanical Engineering, Rajeev Gandhi Memorial College of Engineering, Nandyala, Andhra Pradesh, India

    Upendra Rajak

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Surange, V.G., Bokade, S.U. (2022). Ranking of Critical Risk Factors in the Indian Automotive Supply Chain Using TOPSIS with Entropy Weighted Criterions. In: Chaurasiya, P.K., Singh, A., Verma, T.N., Rajak, U. (eds) Technology Innovation in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-7909-4_46

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-7909-4_46

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7908-7

  • Online ISBN: 978-981-16-7909-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation