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Enterprise Resilience Assessment—A Quantitative Approach

Author

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  • Raquel Sanchis

    (Research Centre on Production Management and Engineering (CIGIP), Universitat Politècnica de València, Escuela Politécnica Superior de Alcoy, Calle Alarcón, nº1, 03801 Alcoy (Alicante), Spain)

  • Raúl Poler

    (Research Centre on Production Management and Engineering (CIGIP), Universitat Politècnica de València, Escuela Politécnica Superior de Alcoy, Calle Alarcón, nº1, 03801 Alcoy (Alicante), Spain)

Abstract

Enterprise resilience is a key capacity to guarantee enterprises’ long-term continuity. This paper proposes a quantitative approach to enhance enterprise resilience by selecting optimal preventive actions to be activated to cushion the impact of disruptive events and to improve preparedness capability, one of the pillars of the enterprise resilience capacity. The proposed algorithms combine the dynamic programming approach with attenuation formulas to model real improvements when a combined set of preventive actions is activated for the same disruptive event. A numerical example is presented that shows remarkable reductions in the expected annual cost due to potential disruptive events.

Suggested Citation

  • Raquel Sanchis & Raúl Poler, 2019. "Enterprise Resilience Assessment—A Quantitative Approach," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4327-:d:256486
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    References listed on IDEAS

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    1. Timothy Prior & Jonas Hagmann, 2014. "Measuring resilience: methodological and political challenges of a trend security concept," Journal of Risk Research, Taylor & Francis Journals, vol. 17(3), pages 281-298, March.
    2. H. Martin Weingartner & David N. Ness, 1967. "Methods for the Solution of the Multidimensional 0/1 Knapsack Problem," Operations Research, INFORMS, vol. 15(1), pages 83-103, February.
    3. Reyes Levalle, Rodrigo & Nof, Shimon Y., 2015. "Resilience by teaming in supply network formation and re-configuration," International Journal of Production Economics, Elsevier, vol. 160(C), pages 80-93.
    4. Vincent Boyer & Didier El Baz & Moussa Elkihel, 2010. "Solution of multidimensional knapsack problems via cooperation of dynamic programming and branch and bound," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 4(4), pages 434-449.
    5. Oliva, Fábio Lotti, 2016. "A maturity model for enterprise risk management," International Journal of Production Economics, Elsevier, vol. 173(C), pages 66-79.
    6. Baghersad, Milad & Zobel, Christopher W., 2015. "Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors," International Journal of Production Economics, Elsevier, vol. 168(C), pages 71-80.
    7. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2016. "A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 116-133.
    8. Richard Bellman, 1954. "Some Applications of the Theory of Dynamic Programming---A Review," Operations Research, INFORMS, vol. 2(3), pages 275-288, August.
    9. Joel Cord, 1964. "A Method for Allocating Funds to Investment Projects when Returns are Subject to Uncertainty," Management Science, INFORMS, vol. 10(2), pages 335-341, January.
    10. H. Martin Weingartner, 1966. "Capital Budgeting of Interrelated Projects: Survey and Synthesis," Management Science, INFORMS, vol. 12(7), pages 485-516, March.
    11. Dormady, Noah & Roa-Henriquez, Alfredo & Rose, Adam, 2019. "Economic resilience of the firm: A production theory approach," International Journal of Production Economics, Elsevier, vol. 208(C), pages 446-460.
    12. Anna Corinna Cagliano & Alberto De Marco & Sabrina Grimaldi & Carlo Rafele, 2012. "An integrated approach to supply chain risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 15(7), pages 817-840, August.
    13. Ana Paula Barroso & Virginia Helena Machado & Virgilio Cruz Machado, 2011. "Supply Chain Resilience Using the Mapping Approach," Chapters, in: Pengzhong Li (ed.), Supply Chain Management, IntechOpen.
    14. Bilal M. Ayyub, 2014. "Systems Resilience for Multihazard Environments: Definition, Metrics, and Valuation for Decision Making," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 340-355, February.
    15. Richard Bellman, 1954. "On some applications of the theory of dynamic programming to logistics," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(2), pages 141-153, June.
    16. Vanpoucke, E. & Boyer, K. & Vereecke, A., 2009. "Supply chain information flow strategies: an empirical taxonomy," Vlerick Leuven Gent Management School Working Paper Series 2009-03, Vlerick Leuven Gent Management School.
    17. Roland W. Scholz & Yann B. Blumer & Fridolin S. Brand, 2012. "Risk, vulnerability, robustness, and resilience from a decision-theoretic perspective," Journal of Risk Research, Taylor & Francis Journals, vol. 15(3), pages 313-330, March.
    18. G. L. Nemhauser & Z. Ullmann, 1969. "Discrete Dynamic Programming and Capital Allocation," Management Science, INFORMS, vol. 15(9), pages 494-505, May.
    19. Neelke Doorn, 2017. "Resilience indicators: opportunities for including distributive justice concerns in disaster management," Journal of Risk Research, Taylor & Francis Journals, vol. 20(6), pages 711-731, June.
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    Cited by:

    1. Beatriz Andres & Giulio Marcucci, 2020. "A Strategies Alignment Approach to Manage Disruptive Events in Collaborative Networks," Sustainability, MDPI, vol. 12(7), pages 1-23, March.
    2. Dong Wang & Shengli Chen, 2022. "Digital Transformation and Enterprise Resilience: Evidence from China," Sustainability, MDPI, vol. 14(21), pages 1, October.
    3. Raquel Sanchis & Alfonso Duran-Heras & Raul Poler, 2020. "Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming," Mathematics, MDPI, vol. 8(9), pages 1-29, September.
    4. Raquel Sanchis & Maria Rosa Sanchis-Gisbert & Raul Poler, 2020. "Conceptualisation of the Three-Dimensional Matrix of Collaborative Knowledge Barriers," Sustainability, MDPI, vol. 12(3), pages 1-24, February.
    5. Bhavya Sharma & Murari Lal Mittal & Gunjan Soni & Bharti Ramtiyal, 2023. "An Implementation Framework for Resiliency Assessment in a Supply Chain," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 591-614, December.
    6. Raquel Sanchis & Luca Canetta & Raúl Poler, 2020. "A Conceptual Reference Framework for Enterprise Resilience Enhancement," Sustainability, MDPI, vol. 12(4), pages 1-27, February.

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