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A DSS Based on a Control Tower for Supply Chain Risks Management

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Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs (ICDSST 2022)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 447))

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Abstract

Propose: This paper presents a supply chain control tower deployed with a decision support system for supply chain risk management in a multi-source data and risk environment. The study provides a digital risk management process and a group decision making approach for companies to improve their supply chain resilience in a supply chain risk environment. We have designed the system from two perspectives. Supply Chain Control Tower and Supply Chain Risk Management. Supply chain risks are mainly all the risks faced in the process from product design to delivery to customers. Supply chain risk management is a very complex activity that requires assessing the vulnerability of all participants in the supply chain. It is a multi-step process. The Supply Chain Control Tower is a dashboard that integrates information from across the supply chain. The supply chain control tower integrates multiple data sources, key performance indicators and activity sources in the supply chain. The control tower should include an intelligent decision support system that uses decision support models and technologies, such as machine learning, to provide decision support and ranking of alternative strategies for supply chain managers.

Results. In this paper, a decision support system-based supply chain control tower is designed to support supply chain decision makers in selecting the most appropriate alternative strategies to reduce the risk impact and enhance the resilience of the supply chain.

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References

  1. Beamon, B.M.: Supply chain design and analysis: models and methods. Int. J. Prod. Econ. 55(3), 281–294 (1998)

    Article  Google Scholar 

  2. Dossou, P.-E.: Impact of sustainability on the supply chain 4.0 performance. Procedia Manuf. 17, 452–459 (2018). https://doi.org/10.1016/j.promfg.2018.10.069

    Article  Google Scholar 

  3. Yazdani, M., Zarate, P., Coulibaly, A., Zavadskas, E.K.: A group decision making support system in logistics and supply chain management. Exp. Syst. Appl. 88, 376–392 (2017)

    Article  Google Scholar 

  4. Erfani, M., Afrougheh, S., Ardakani, T., Sadeghi, A.: Tourism positioning using decision support system (case study: Chahnime—Zabol, Iran). Environ. Earth Sci. 74(4), 3135–3144 (2015). https://doi.org/10.1007/s12665-015-4365-z

    Article  Google Scholar 

  5. Manuj, I., Mentzer, J.T.: Global supply chain risk management strategies. Int. J. Phys. Distrib. Logist. Manag. 38(3), 192–223 (2008). https://doi.org/10.1108/09600030810866986

    Article  Google Scholar 

  6. Zsidisin, G.A., Henke, M. (eds.): Revisiting Supply Chain Risk. SSSCM, vol. 7. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-03813-7

    Book  Google Scholar 

  7. Wieland, A., Wallenburg, C.M.: Dealing with supply chain risks: linking risk management practices and strategies to performance. Int. J. Phys. Distrib. Logist. Manag. 42, 887–905 (2012). https://doi.org/10.1108/09600031211281411

    Article  Google Scholar 

  8. Christopher, M., Peck, H.: Building the resilient supply chain. Int. J. Logist. Manag. 15(2), 1–14 (2004). https://doi.org/10.1108/09574090410700275

    Article  Google Scholar 

  9. 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 

  10. El Baz, J., Ruel, S.: Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era. Int. J. Prod. Econ. 233, 107972 (2021). https://doi.org/10.1016/j.ijpe.2020.107972

    Article  Google Scholar 

  11. Fan, Y., Stevenson, M.: A review of supply chain risk management: definition, theory, and research agenda. Int. J. Phys. Distrib. Logist. Manag. 48(3), 205–230 (2018). https://doi.org/10.1108/IJPDLM-01-2017-0043

    Article  Google Scholar 

  12. Manuj, I., Mentzer, J.T.: Global supply chain risk management. J. Bus. Logist. 29(1), 133–155 (2008)

    Article  Google Scholar 

  13. Ponomarov, S.Y., Holcomb, M.C.: Understanding the concept of supply chain resilience. Int. J. Logist. Manag. 20(1), 124–143 (2009). https://doi.org/10.1108/09574090910954873

    Article  Google Scholar 

  14. Craighead, C.W., Blackhurst, J., Rungtusanatham, M.J., Handfield, R.B.: The severity of supply chain disruptions: design characteristics and mitigation capabilities. Decis. Sci. 38(1), 131–156 (2007). https://doi.org/10.1111/j.1540-5915.2007.00151.x

    Article  Google Scholar 

  15. Falasca, M., Zobel, C., Cook, D.: A decision support framework to assess supply chain resilience. In: Proceedings of ISCRAM 2008 - 5th International Conference on Information Systems Crisis Response Management, January 2008

    Google Scholar 

  16. Gorry, G.A., Scott Morton, M.S.: A framework for management information systems, Cambridge, M.I.T., Working Paper, 1971. Accessed 12 Oct 2021. https://dspace.mit.edu/handle/1721.1/47936

  17. Goswami, R., Barua, P.: Web-based decision support system: concept and issues. In: Handbook of Computational Intelligence in Manufacturing and Production Management 2008. https://www.igi-global.com/chapter/web-based-decision-support-system/www.igi-global.com/chapter/web-based-decision-support-system/19365. Accessed 28 Sep 2021

  18. Marto, M., et al.: Web-based forest resources management decision support system. Forests 10(12), 1079 (2019). https://doi.org/10.3390/f10121079

  19. Mareschal, B., De Smet, Y.: Visual PROMETHEE: developments of the PROMETHEE & GAIA multi criteria decision aid methods. In: 2009 IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1646–1649, December 2009. https://doi.org/10.1109/IEEM.2009.5373124

  20. Carlsson, C., Fullér, R.: Fuzzy multiple criteria decision making: recent developments. Fuzzy Sets Syst. 78(2), 139–153 (1996). https://doi.org/10.1016/0165-0114(95)00165-4

    Article  MathSciNet  MATH  Google Scholar 

  21. Carvalho, J.B., Varela, M.L.R., Putnik, G.D., Hernández, J.E., Ribeiro, R.A.: A web-based decision support system for supply chain operations management towards an integrated framework. In: Dargam, F., et al. (eds.) Decision Support Systems III - Impact of Decision Support Systems for Global Environments. EWG-DSS EWG-DSS 2013 2013. Lecture Notes in Business Information Processing, vol. 184, pp. 104–117. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11364-7_10

  22. Hallikas, J., Karvonen, I., Pulkkinen, U., Virolainen, V.-M., Tuominen, M.: Risk management processes in supplier networks. Int. J. Prod. Econ. 90(1), 47–58 (2004). https://doi.org/10.1016/j.ijpe.2004.02.007

    Article  Google Scholar 

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Authors and Affiliations

  1. IRIT, Toulouse Université, 2 rue du Doyen Gabriel Marty, 31042, Toulouse Cedex 9, France

    Chenhui Ye & Pascale Zaraté

  2. Ecole Des Mines d’Albi, All. des sciences, 81000, Albi, France

    Daouda Kamissoko

Authors
  1. Chenhui Ye
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  2. Pascale Zaraté
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  3. Daouda Kamissoko
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Corresponding author

Correspondence to Chenhui Ye .

Editor information

Editors and Affiliations

  1. Federal University of Pernambuco, Recife, Brazil

    Ana Paula Cabral Seixas Costa

  2. University of Macedonia, Thessaloniki, Greece

    Jason Papathanasiou

  3. Loughborough University, Loughborough, UK

    Uchitha Jayawickrama

  4. Ecole des Mines d'Albi, Albi, France

    Daouda Kamissoko

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Ye, C., Zaraté, P., Kamissoko, D. (2022). A DSS Based on a Control Tower for Supply Chain Risks Management. In: Cabral Seixas Costa, A.P., Papathanasiou, J., Jayawickrama, U., Kamissoko, D. (eds) Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs. ICDSST 2022. Lecture Notes in Business Information Processing, vol 447. Springer, Cham. https://doi.org/10.1007/978-3-031-06530-9_10

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  • DOI: https://doi.org/10.1007/978-3-031-06530-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06529-3

  • Online ISBN: 978-3-031-06530-9

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