IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v151y2021ics1366554521001186.html
   My bibliography  Save this article

Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds

Author

Listed:
  • Chen, Li-Ming
  • Chang, Wei-Lun

Abstract

This study investigated the speeds (i.e., radical, incremental, relaxed benchmarking, rigorous benchmarking, matching, and market-driven) of firms’ recovery from supply- and cyber-related disruptions in cloud supply chains (SCs). Supply-related disruptions downgrade the firm’s operational capabilities (e.g., production capacity and labor supply), and cyber-related disruptions reduce its intangible capabilities (e.g., reputation, brand image, and public trust). This study introduced a cellular automata (CA) simulation model to determine the best recovery speeds following the loss of operational and intangible capabilities. Furthermore, to investigate the impact of cloud adoption on an SC firm’s best speeds of recovery from supply-related disruptions, we compared firms that had adopted the cloud with those using the on-site data centers.

Suggested Citation

  • Chen, Li-Ming & Chang, Wei-Lun, 2021. "Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:transe:v:151:y:2021:i:c:s1366554521001186
    DOI: 10.1016/j.tre.2021.102347
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554521001186
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2021.102347?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wen Jun Tan & Wentong Cai & Allan N. Zhang, 2020. "Structural-aware simulation analysis of supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5175-5195, September.
    2. Niu, Baozhuang & Mu, Zihao & Cao, Bin & Gao, Jie, 2021. "Should multinational firms implement blockchain to provide quality verification?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    3. Seyed Mohammad Khalili & Fariborz Jolai & Seyed Ali Torabi, 2017. "Integrated production–distribution planning in two-echelon systems: a resilience view," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1040-1064, February.
    4. Li, Xiang, 2020. "Reducing channel costs by investing in smart supply chain technologies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    5. Tobias Bier & Anne Lange & Christoph H. Glock, 2020. "Methods for mitigating disruptions in complex supply chain structures: a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 58(6), pages 1835-1856, March.
    6. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2018. "Co-residence based data vulnerability vs. security in cloud computing system with random server assignment," European Journal of Operational Research, Elsevier, vol. 267(2), pages 676-686.
    7. Hou, Yunzhang & Wang, Xiaoling & Wu, Yenchun Jim & He, Peixu, 2018. "How does the trust affect the topology of supply chain network and its resilience? An agent-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 229-241.
    8. Wang, Haijun & Tan, Jie & Guo, Shuojia & Wang, Shenhao, 2018. "High-value transportation disruption risk management: Shipment insurance with declared value," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 293-310.
    9. Van Nguyen, Truong & Zhang, Jie & Zhou, Li & Meng, Meng & He, Yong, 2020. "A data-driven optimization of large-scale dry port location using the hybrid approach of data mining and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    10. Goldbeck, Nils & Angeloudis, Panagiotis & Ochieng, Washington, 2020. "Optimal supply chain resilience with consideration of failure propagation and repair logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    11. Tadeusz Sawik, 2017. "A portfolio approach to supply chain disruption management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1970-1991, April.
    12. Liu, Weihua & George Shanthikumar, J. & Tae-Woo Lee, Paul & Li, Xiang & Zhou, Li, 2021. "Special issue editorial: Smart supply chains and intelligent logistics services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    13. Wilson, Martha C., 2007. "The impact of transportation disruptions on supply chain performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 295-320, July.
    14. Loree, Nick & Aros-Vera, Felipe, 2018. "Points of distribution location and inventory management model for Post-Disaster Humanitarian Logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 1-24.
    15. Li, Jianbin & Zheng, Yuting & Dai, Bin & Yu, Jiang, 2020. "Implications of matching and pricing strategies for multiple-delivery-points service in a freight O2O platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    16. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    17. Yu, Wantao & Chavez, Roberto & Jacobs, Mark A. & Feng, Mengying, 2018. "Data-driven supply chain capabilities and performance: A resource-based view," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 371-385.
    18. Dobrila Petrovic & Magdalena Kalata, 2019. "Multi-objective optimisation of risk and business strategy in real-world supply networks in the presence of uncertainty," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(11), pages 1869-1884, November.
    19. Q Mu & Z Fu & J Lysgaard & R Eglese, 2011. "Disruption management of the vehicle routing problem with vehicle breakdown," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 742-749, April.
    20. 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.
    21. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    22. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    23. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    24. Chen, Li-Ming & Liu, Yan Emma & Yang, Shu-Jung Sunny, 2015. "Robust supply chain strategies for recovering from unanticipated disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 198-214.
    25. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov, 2019. "The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics," International Journal of Production Research, Taylor & Francis Journals, vol. 57(3), pages 829-846, February.
    26. B Ritchie & C Brindley, 2007. "An emergent framework for supply chain risk management and performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(11), pages 1398-1411, November.
    27. M S Sodhi & S Lee, 2007. "An analysis of sources of risk in the consumer electronics industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(11), pages 1430-1439, November.
    28. Liang, Zhe & Xiao, Fan & Qian, Xiongwen & Zhou, Lei & Jin, Xianfei & Lu, Xuehua & Karichery, Sureshan, 2018. "A column generation-based heuristic for aircraft recovery problem with airport capacity constraints and maintenance flexibility," Transportation Research Part B: Methodological, Elsevier, vol. 113(C), pages 70-90.
    29. Wang, Jianxin & Lim, Ming K. & Zhan, Yuanzhu & Wang, XiaoFeng, 2020. "An intelligent logistics service system for enhancing dispatching operations in an IoT environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    30. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    31. Jonkman, S.N. & Bockarjova, M. & Kok, M. & Bernardini, P., 2008. "Integrated hydrodynamic and economic modelling of flood damage in the Netherlands," Ecological Economics, Elsevier, vol. 66(1), pages 77-90, May.
    32. Song Xu & Xiaotong Zhang & Lipan Feng & Wenting Yang, 2020. "Disruption risks in supply chain management: a literature review based on bibliometric analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3508-3526, June.
    33. Adam Rose, 2004. "Economic Principles, Issues, and Research Priorities in Hazard Loss Estimation," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 2, pages 13-36, Springer.
    34. Dutta, Pankaj & Choi, Tsan-Ming & Somani, Surabhi & Butala, Richa, 2020. "Blockchain technology in supply chain operations: Applications, challenges and research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    35. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    36. Paul, Sanjoy Kumar & Sarker, Ruhul & Essam, Daryl, 2014. "Real time disruption management for a two-stage batch production–inventory system with reliability considerations," European Journal of Operational Research, Elsevier, vol. 237(1), pages 113-128.
    37. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2021. "The impact of congestion on protection decisions in supply networks under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    38. Yossi Sheffi, 2005. "The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262693496, December.
    39. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    40. Hishamuddin, H. & Sarker, R.A. & Essam, D., 2012. "A disruption recovery model for a single stage production-inventory system," European Journal of Operational Research, Elsevier, vol. 222(3), pages 464-473.
    41. Linh Nguyen Khanh Duong & Josephine Chong, 2020. "Supply chain collaboration in the presence of disruptions: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3488-3507, June.
    42. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    43. Jafar Namdar & Xueping Li & Rupy Sawhney & Ninad Pradhan, 2018. "Supply chain resilience for single and multiple sourcing in the presence of disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2339-2360, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lai, Xinfeng & Chen, Zhixiang & Wang, Xin & Chiu, Chun-Hung, 2023. "Risk propagation and mitigation mechanisms of disruption and trade risks for a global production network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    2. Wang, Jiepeng & Zhou, Hong & Zhao, Yujie, 2022. "Behavior evolution of supply chain networks under disruption risk — From aspects of time dynamic and spatial feature," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    2. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    3. Zhu, Xiaoyan & Cao, Yunzhi, 2021. "The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    5. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    6. Liu, Weihua & George Shanthikumar, J. & Tae-Woo Lee, Paul & Li, Xiang & Zhou, Li, 2021. "Special issue editorial: Smart supply chains and intelligent logistics services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    7. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    8. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    9. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    10. El Baz, Jamal & Ruel, Salomée, 2021. "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," International Journal of Production Economics, Elsevier, vol. 233(C).
    11. Shashi & Piera Centobelli & Roberto Cerchione & Myriam Ertz, 2020. "Managing supply chain resilience to pursue business and environmental strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1215-1246, March.
    12. Sawik, Tadeusz, 2021. "On the risk-averse selection of resilient multi-tier supply portfolio," Omega, Elsevier, vol. 101(C).
    13. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    14. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    15. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    16. Zhao, Nanyang & Hong, Jiangtao & Lau, Kwok Hung, 2023. "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International Journal of Production Economics, Elsevier, vol. 259(C).
    17. Aarti Singh & Ratri Parida, 2022. "Decision-Making Models for Healthcare Supply Chain Disruptions: Review and Insights for Post-pandemic Era," International Journal of Global Business and Competitiveness, Springer, vol. 17(2), pages 130-141, December.
    18. Cheramin, Meysam & Saha, Apurba Kumar & Cheng, Jianqiang & Paul, Sanjoy Kumar & Jin, Hongyue, 2021. "Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    19. Papanagnou, Christos & Seiler, Andreas & Spanaki, Konstantina & Papadopoulos, Thanos & Bourlakis, Michael, 2022. "Data-driven digital transformation for emergency situations: The case of the UK retail sector," International Journal of Production Economics, Elsevier, vol. 250(C).
    20. Ghanei, Shima & Contreras, Ivan & Cordeau, Jean-François, 2023. "A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:151:y:2021:i:c:s1366554521001186. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.