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Building Viable Digital Business Ecosystems with Collaborative Supply Chain Platform SupplyOn

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Supply Network Dynamics and Control

Part of the book series: Springer Series in Supply Chain Management ((SSSCM,volume 20))

Abstract

Digital supply chains evolve toward business ecosystems that are becoming ever more complex and in which companies and supply chains collaborate in an increasingly networked manner. The viability consideration at the level of ecosystems can be supported by associated digital collaborative supply chain platforms. The COVID-19 pandemic times have clearly shown that the viability and ecosystem views are crucial when coping with and recovering from large-scale, massive crises. This chapter focuses on the current challenges of digital supply chains in the manufacturing industry and how they can be addressed. To this end, a concrete use case is highlighted at the Chinese premium car manufacturer Seres, where the Supplier Collaboration Portal SupplyOn with its integrated solutions has made a significant contribution to building ecosystem viability.

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References

  • Aldrighetti, R., Battini, D., Ivanov, D., & Zennaro, I. (2021). Costs of resilience and disruptions in supply chain network design models: A review and future research directions. International Journal of Production Economics, 108103. https://doi.org/10.1016/j.ijpe.2021.108103

  • Altay, N., Gunasekaran, A., Dubey, R., & Childe, S. J. (2018). Agility and resilience as antecedents of supply chain performance under moderating effects of organizational culture within humanitarian setting: A dynamic capability view. Production Planning and Control, 29(14), 1158–1174.

    Article  Google Scholar 

  • Ardolino, M., Bacchetti, A., & Ivanov, D. (2022). Analysis of the COVID-19 pandemic’s impacts on manufacturing: A systematic literature review and future research agenda. Operations Management Research. https://doi.org/10.1007/s12063-021-00225-9

  • Azadegan, A., & Dooley, K. (2021). A typology of supply network resilience strategies: Complex collaborations in a complex world. Journal of Supply Chain Management, 57(1), 17–26.

    Google Scholar 

  • Basole, R. C., & Nowak, M. (2018). Assimilation of tracking technology in the supply chain. Transportation Research Part E: Logistics and Transportation Review, 114, 350–370.

    Article  Google Scholar 

  • Blackhurst, J., Dunn, J., & Craighead, C. (2011). An empirically derived framework of global supply resiliency. Journal of Business Logistics, 32(4), 347–391.

    Article  Google Scholar 

  • Brintrup, A., Pak, J., Ratiney, D., Pearce, T., Wichmann, P., Woodall, P., & McFarlane, D. (2020). Supply chain data analytics for predicting supplier disruptions: A case study in complex asset manufacturing. International Journal of Production Research, 58(11), 3330–3341.

    Article  Google Scholar 

  • Cai, Y., Choi, T. M., & Zhang, J. (2021). Platform supported supply chain operations in the blockchain era: Supply contracting and moral hazards. Decision Sciences, 52(4), 866–892.

    Google Scholar 

  • Cavalcante, I. M., Frazzon, E. M., Forcellinia, F. A., & Ivanov, D. (2019). A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing. International Journal of Information Management, 49, 86–97.

    Article  Google Scholar 

  • Choi, T. M., Wallace, S. W., & Wang, Y. (2018). Big data analytics in operations management. Production and Operations Management, 27(10), 1868–1883.

    Article  Google Scholar 

  • Choi, T.-M. (2020). Risk analysis in logistics systems: A research agenda during and after the COVID-19 pandemic. Transportation Research Part E: Logistics and Transportation, 140, 101961.

    Article  Google Scholar 

  • Christopher, M., & Lee, H. (2004). Mitigating supply chain risk through improved confidence. International Journal of Physical Distribution & Logistics Management, 34(5), 388–396.

    Article  Google Scholar 

  • Currie, C. S. M., Fowler, J. W., Kotiadis, K., Monks, T., Onggo, B. S., Robertson, D. A., & Tako, A. A. (2020). How simulation modelling can help reduce the impact of COVID-19. Journal of Simulation, 14(2), 83–97.

    Article  Google Scholar 

  • Das, A., Gottlieb, S., & Ivanov, D. (2019). Managing disruptions and the ripple effect in digital supply chains: Empirical case studies. In D. Ivanov et al. (Eds.), Handbook of Ripple Effects in the Supply Chain (pp. 261–285). Springer.

    Google Scholar 

  • Demirel, G., MacCarthy, B. L., Ritterskamp, D., Champneys, A., & Gross, T. (2019). Identifying dynamical instabilities in supply networks using generalized modeling. Journal of Operations Management, 65(2), 133–159.

    Article  Google Scholar 

  • Demirel, S., Kapuscinski, R., & Yu, M. (2018). Strategic behavior of suppliers in the face of production disruptions. Management Science, 64(2), 533–551.

    Article  Google Scholar 

  • Dolgui, A., Ivanov, D., Potryasaev, S., Sokolov, B., Ivanova, M., & Werner, F. (2020c). Blockchain-oriented dynamic modelling of smart contract design and execution control in the supply chain. International Journal of Production Research, 58(7), 2184–2199.

    Article  Google Scholar 

  • Dolgui, A., & Ivanov, D. (2020). Exploring supply chain structural dynamics: New disruptive technologies and disruption risks. International Journal of Production Economics, 229, 107886.

    Article  Google Scholar 

  • Dolgui, A., Ivanov, D., & Rozhkov, M. (2020a). Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain. International Journal of Production Research, 58(5), 1285–1301.

    Article  Google Scholar 

  • Dolgui, A., Ivanov, D., & Sokolov, B. (2018). Ripple effect in the supply chain: An analysis and recent literature. International Journal of Production Research, 56(1–2), 414–430.

    Article  Google Scholar 

  • Dolgui, A., Ivanov, D., & Sokolov, B. (2020b). Reconfigurable supply chain: The X-Network. International Journal of Production Research, 58(13), 4138–4163.

    Article  Google Scholar 

  • Dolgui, A., & Ivanov, D. (2022). 5G in digital supply chain and operations management: Fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. International Journal of Production Research, 60(2), 442–451.

    Article  Google Scholar 

  • Dubey, R., Gunasekaran, A., Childe, S. J., Wamba, S. F., Roubaud, D., & Foropon, C. (2021). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research, 59(1), 110–128.

    Article  Google Scholar 

  • Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2019). Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view and big data culture. British Journal of Management, 30(2), 341–361.

    Article  Google Scholar 

  • El Baz, J., & Ruel, S. (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, 233, 107972.

    Article  Google Scholar 

  • Frazzon, E. M., Freitag, M., & Ivanov, D. (2021). Intelligent methods and systems for decision-making support: Toward digital supply chain twins. International Journal of Information Management, 57, 102281.

    Article  Google Scholar 

  • Ghadge, A., Er Kara, M., Ivanov, D., & Chaudhuri, A. (2021). Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: A System Dynamics approach. International Journal of Production Research. https://doi.org/10.1080/00207543.2021.1987547

  • Giannoccaro, I., & Iftikhar, A. (2021). Mitigating ripple effect in supply networks: The effect of trust and topology on resilience. International Journal of Production Research. https://doi.org/10.1080/00207543.2020.1853844

  • Gupta, S., Starr, M. K., Zanjirani Farahani, R., & Asgari, N. (2022). Pandemics/epidemics: Challenges and opportunities for operations management research. Manufacturing and Service Operations Management, 24(1), 1–23.

    Google Scholar 

  • Gupta, V., Ivanov, D., & Choi, T.-M. (2021). Competitive pricing of substitute products under supply disruption. Omega, 101, 102279.

    Article  Google Scholar 

  • Hosseini, S., Ivanov, D., & Blackhurst, J. (2020). Conceptualization and measurement of supply chain resilience in an open-system context. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2020.3026465

  • Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E: Logistics and Transportation Review, 125, 285–307.

    Article  Google Scholar 

  • Ivanov, D. (2022). Blackout and supply chains: Performance, resilience and viability impact analysis. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04754-9

  • Ivanov, D., Dolgui, A., & Sokolov, B. (2022). Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “supply chain-as-a-service”. Transportation Research – Part E: Logistics and Transportation Review, 160, 102676.

    Article  Google Scholar 

  • Ivanov, D. (2020). Viable Supply Chain Model: Integrating agility, resilience and sustainability perspectives – lessons from and thinking beyond the COVID-19 pandemic. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03640-6

  • Ivanov D. & Das A. (2020). Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: A research note. International Journal of Integrated Supply Management, 13(1), 90–102.

    Google Scholar 

  • Ivanov, D. (2021a). Introduction to supply chain resilience. Springer Nature, ISBN 978-3-030-70490-2.

    Book  Google Scholar 

  • Ivanov, D. (2021b). Exiting the COVID-19 pandemic: After-shock risks and avoidance of disruption tails in supply chains. Annals of Operations Research. forthcoming.

    Google Scholar 

  • Ivanov, D. (2021c). Supply chain viability and the COVID-19 pandemic: A conceptual and formal generalisation of four major adaptation strategies. International Journal of Production Research, 59(12), 3535–3552

    Google Scholar 

  • Ivanov, D., Tang, C. S., Dolgui, A., Battini, D., & Das, A. (2021). Researchers’ perspectives on Industry 4.0: Multi-disciplinary analysis and opportunities for operations management. International Journal of Production Research, 59(7), 2055–2078.

    Article  Google Scholar 

  • Ivanov, D., & Dolgui, A. (2021a). A digital supply chain twin for managing the disruptions risks and resilience in the era of Industry 4.0. Production Planning and Control, 32(9), 775–788.

    Article  Google Scholar 

  • Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: Extending the sup-ply chain resilience angles towards survivability: A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904–2915.

    Article  Google Scholar 

  • Ivanov, D., & Dolgui, A. (2021b). OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications. International Journal of Production Economics, 232, 107921.

    Article  Google Scholar 

  • Ivanov, D., & Rozhkov, M. (2020). Coordination of production and ordering policies under capacity disruption and product write-off risk: An analytical study with real-data based simulations of a fast moving consumer goods company. Annals of Operations Research, 291(1–2), 387–407.

    Article  Google Scholar 

  • Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829–846.

    Article  Google Scholar 

  • Kumar, S., Mookerjee, V., & Shubham, A. (2018). Research in operations management and information systems interface. Production and Operations Management, 27(11), 1893–1900.

    Article  Google Scholar 

  • Li, Y., Chen, K., Collignon, S., & Ivanov, D. (2021). Ripple effect in the supply chain network: Forward and backward disruption propagation, network health and firm vulnerability. European Journal of Operational Research, 291(3), 1117–1131.

    Article  Google Scholar 

  • Lohmer, J., Bugert, N., & Lasch, R. (2020). Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study. International Journal of Production Economics, 228, 107882.

    Article  Google Scholar 

  • Lücker, F., Chopra, S., & Seifert, R. W. (2021). Mitigating product shortage due to disruptions in multi-stage supply chains. Production and Operations Management, 30(4), 941–964.

    Google Scholar 

  • MacCarthy, B. L., Blome, C., Olhager, J., Srai, J. S., & Zhao, X. (2016). Supply chain evolution – theory, concepts and science. International Journal of Operations & Production Management, 36(12), 1696–1718.

    Article  Google Scholar 

  • MacCarthy, B., & Ivanov, D. (2022). Digital supply chain. Elsevier.

    Google Scholar 

  • Nguyen, S., Chen, P. S.-L., & Du, Y. (2021). Risk identification and modeling for blockchain-enabled container shipping. International Journal of Physical Distribution and Logistics Management, 51(2), 126–148.

    Article  Google Scholar 

  • Panetto, H., Iung, B., Ivanov, D., Weichhart, G., & Wang, X. (2019). Challenges for the cyber-physical manufacturing enterprises of the future. Annual Reviews in Control, 47, 200–213.

    Article  Google Scholar 

  • Papadopoulos, T., Gunasekaran, A., Dubey, R., Altay, N., Childe, S. J., & Wamba, S. F. (2017). The role of Big Data in explaining disaster resilience in supply chains for sustainability. Journal of Cleaner Production, 142(2), 1108–1118.

    Article  Google Scholar 

  • Pavlov, A., Ivanov, D., Werner, F., Dolgui, A., & Sokolov, B. (2020). Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains. Annals of Operations Research. https://doi.org/10.1007/s10479-019-03454-1

  • Pettit, T. J., Croxton, K. L., & Fiksel, J. (2019). The evolution of resilience in supply chain management: A retrospective on ensuring supply chain resilience. Journal of Business Logistics, 40(1), 56–65.

    Article  Google Scholar 

  • Queiroz, M. M., Ivanov, D., Dolgui, A., & Fosso Wamba, S. (2020). Impacts of epidemic outbreaks on supply chains: Mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03685-7

  • Queiroz, M. M., Telles, R., & Bonilla, S. H. (2019). Blockchain and supply chain management integration: A systematic review of the literature. Supply Chain Management, 25(2), 241–254.

    Article  Google Scholar 

  • Ralston, P., & Blackhurst, J. (2020). Industry 4.0 and resilience in the supply chain: A driver of capability enhancement or capability loss? International Journal of Production Research, 58(16), 5006–5019.

    Article  Google Scholar 

  • Roeck, D., Sternberg, H., & Hofmann, E. (2020). Distributed ledger technology in supply chains: A transaction cost perspective. International Journal of Production Research, 58(7), 2124–2141.

    Article  Google Scholar 

  • Rozhkov, M., Ivanov, D., Blackhurst, J., & Nair, A. (2022). Adapting supply chain operations in anticipation of and during the COVID-19 pandemic. Omega, 110, 102635.

    Article  Google Scholar 

  • Ruel, S., El Baz, J., Ivanov, D., & Das, A. (2021). Supply chain viability: Conceptualization, measurement, and nomological validation. Annals of Operations Research. https://doi.org/10.1007/s10479-021-03974-9

  • Sheffi, Y. (2015). Preparing for disruptions through early detection. MIT Sloan Management Review, 57, 31.

    Google Scholar 

  • Sodhi, M., Tang, C., & Willenson, E. (2021). Research opportunities in preparing supply chains of essential goods for future pandemics. International Journal of Production Research. https://doi.org/10.1080/00207543.2021.1884310

  • Sokolov, B., Ivanov, D., & Dolgui, A. (Eds.). (2020). Scheduling in Industry 4.0 and cloud manufacturing. Springer, ISBN 978-3-030-43176-1.

    Google Scholar 

  • Tang, C. S., & Veelenturf, L. P. (2019). The strategic role of logistics in the Industry 4.0 era. Transportation Research Part E: Logistics and Transportation Review, 129, 1–11.

    Article  Google Scholar 

  • Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77–84.

    Article  Google Scholar 

  • Wamba, S. F., & Queiroz, M. M. (2020). Industry 4.0 and the supply chain digitalisation: A blockchain diffusion perspective. Production Planning & Control, 1–18.

    Google Scholar 

  • Winkelhaus, S., & Grosse, E. H. (2020). Logistics 4.0: A systematic review towards a new logistics system. International Journal of Production Research, 58(1), 18–43.

    Article  Google Scholar 

  • Yang, H., Kumara, S., Bukkapatnam, S. T. S., & Tsung, F. (2019). The internet of things for smart manufacturing: A review. IISE Transactions, 51(11), 1190–1216.

    Article  Google Scholar 

  • Yoon, J., Talluri, S., & Rosales, C. (2020). Procurement decisions and information sharing under multi-tier disruption risk in a supply chain. International Journal of Production Research, 58(5), 1362–1383.

    Article  Google Scholar 

  • Zouari, D., Ruel, S., & Viale, L. (2021). Does digitalising the supply chain contribute to its resilience? International Journal of Physical Distribution and Logistics Management, 51(2), 149–180.

    Article  Google Scholar 

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Authors and Affiliations

  1. SupplyOn AG, Hallbergmoos, Germany

    Arvid Holzwarth & Cornelia Staib

  2. Department of Business and Economics, Supply Chain and Operations Management Group, Berlin School of Economics and Law, Berlin, Germany

    Dmitry Ivanov

Authors
  1. Arvid Holzwarth
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  2. Cornelia Staib
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  3. Dmitry Ivanov
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Correspondence to Dmitry Ivanov .

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Editors and Affiliations

  1. Department of Automation, Production and Computer Sciences, IMT Atlantique, LS2N-CNRS, Nantes, France

    Alexandre Dolgui

  2. Department of Business and Economics, Supply Chain and Operations Management, Berlin School of Economics and Law, Berlin, Germany

    Dmitry Ivanov

  3. Laboratory for Information Technologies in Systems Analysis and Modeling, St. Petersburg Institute of Informatics and Automation of the RAS (SPIIRAS), St. Petersburg, Russia

    Boris Sokolov

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Holzwarth, A., Staib, C., Ivanov, D. (2022). Building Viable Digital Business Ecosystems with Collaborative Supply Chain Platform SupplyOn. In: Dolgui, A., Ivanov, D., Sokolov, B. (eds) Supply Network Dynamics and Control. Springer Series in Supply Chain Management, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-031-09179-7_9

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