IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2510.05487.html
   My bibliography  Save this paper

Smart Contract Adoption under Discrete Overdispersed Demand: A Negative Binomial Optimization Perspective

Author

Listed:
  • Jinho Cha
  • Sahng-Min Han
  • Long Pham

Abstract

Effective supply chain management under high-variance demand requires models that jointly address demand uncertainty and digital contracting adoption. Existing research often simplifies demand variability or treats adoption as an exogenous decision, limiting relevance in e-commerce and humanitarian logistics. This study develops an optimization framework combining dynamic Negative Binomial (NB) demand modeling with endogenous smart contract adoption. The NB process incorporates autoregressive dynamics in success probability to capture overdispersion and temporal correlation. Simulation experiments using four real-world datasets, including Delhivery Logistics and the SCMS Global Health Delivery system, apply maximum likelihood estimation and grid search to optimize adoption intensity and order quantity. Across all datasets, the NB specification outperforms Poisson and Gaussian benchmarks, with overdispersion indices exceeding 1.5. Forecasting comparisons show that while ARIMA and Exponential Smoothing achieve similar point accuracy, the NB model provides superior stability under high variance. Scenario analysis reveals that when dispersion exceeds a critical threshold (r > 6), increasing smart contract adoption above 70% significantly enhances profitability and service levels. This framework offers actionable guidance for balancing inventory costs, service levels, and implementation expenses, highlighting the importance of aligning digital adoption strategies with empirically observed demand volatility.

Suggested Citation

  • Jinho Cha & Sahng-Min Han & Long Pham, 2025. "Smart Contract Adoption under Discrete Overdispersed Demand: A Negative Binomial Optimization Perspective," Papers 2510.05487, arXiv.org.
    • Handle: RePEc:arx:papers:2510.05487
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2510.05487
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2020. "Reconfigurable supply chain: the X-network," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4138-4163, July.
    2. Dawn Barnes-Schuster & Yehuda Bassok & Ravi Anupindi, 2002. "Coordination and Flexibility in Supply Contracts with Options," Manufacturing & Service Operations Management, INFORMS, vol. 4(3), pages 171-207, May.
    3. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    4. Sara Saberi & Mahtab Kouhizadeh & Joseph Sarkis & Lejia Shen, 2019. "Blockchain technology and its relationships to sustainable supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2117-2135, April.
    5. Hau L. Lee & Kut C. So & Christopher S. Tang, 2000. "The Value of Information Sharing in a Two-Level Supply Chain," Management Science, INFORMS, vol. 46(5), pages 626-643, May.
    6. Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim, 2020. "DeepAR: Probabilistic forecasting with autoregressive recurrent networks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1181-1191.
    7. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    8. Syntetos, Aris A. & Boylan, John E., 2005. "The accuracy of intermittent demand estimates," International Journal of Forecasting, Elsevier, vol. 21(2), pages 303-314.
    9. Min, Hokey, 2019. "Blockchain technology for enhancing supply chain resilience," Business Horizons, Elsevier, vol. 62(1), pages 35-45.
    10. Yossi Aviv, 2003. "A Time-Series Framework for Supply-Chain Inventory Management," Operations Research, INFORMS, vol. 51(2), pages 210-227, April.
    11. Karzan Mahdi Ghafour & Abdulqadir Rahomee Ahmed Aljanabi, 2023. "The role of forecasting in preventing supply chain disruptions during the COVID-19 pandemic: a distributor-retailer perspective," Operations Management Research, Springer, vol. 16(2), pages 780-793, June.
    12. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    13. Dmitry Ivanov, 2021. "Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 59(12), pages 3535-3552, June.
    14. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    15. Mahesh Nagarajan & Yehuda Bassok, 2008. "A Bargaining Framework in Supply Chains: The Assembly Problem," Management Science, INFORMS, vol. 54(8), pages 1482-1496, August.
    16. Horst Treiblmaier, 2019. "Combining Blockchain Technology and the Physical Internet to Achieve Triple Bottom Line Sustainability: A Comprehensive Research Agenda for Modern Logistics and Supply Chain Management," Logistics, MDPI, vol. 3(1), pages 1-13, February.
    17. Kouhizadeh, Mahtab & Saberi, Sara & Sarkis, Joseph, 2021. "Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers," International Journal of Production Economics, Elsevier, vol. 231(C).
    18. Volodymyr Babich & Gilles Hilary, 2020. "OM Forum—Distributed Ledgers and Operations: What Operations Management Researchers Should Know About Blockchain Technology," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 223-245, March.
    19. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    20. Yossi Sheffi, 2005. "The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262693496, December.
    21. Gérard P. Cachon & Martin A. Lariviere, 2005. "Supply Chain Coordination with Revenue-Sharing Contracts: Strengths and Limitations," Management Science, INFORMS, vol. 51(1), pages 30-44, January.
    22. Narendra Agrawal & Stephen A. Smith, 1996. "Estimating negative binomial demand for retail inventory management with unobservable lost sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(6), pages 839-861, September.
    23. Edward A. Silver, 1981. "Operations Research in Inventory Management: A Review and Critique," Operations Research, INFORMS, vol. 29(4), pages 628-645, August.
    Full references (including those not matched with items on IDEAS)

    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. Weili Yin & Wenxue Ran, 2021. "Theoretical Exploration of Supply Chain Viability Utilizing Blockchain Technology," Sustainability, MDPI, vol. 13(15), pages 1-25, July.
    2. Lohmer, Jacob & Bugert, Niels & Lasch, Rainer, 2020. "Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study," International Journal of Production Economics, Elsevier, vol. 228(C).
    3. Gupta, Shivam & Modgil, Sachin & Choi, Tsan-Ming & Kumar, Ajay & Antony, Jiju, 2023. "Influences of artificial intelligence and blockchain technology on financial resilience of supply chains," International Journal of Production Economics, Elsevier, vol. 261(C).
    4. Li, Zhiwen & Xu, Xianhao & Bai, Qingguo & Chen, Cheng & Wang, Hongwei & Xia, Peng, 2023. "Implications of information sharing on blockchain adoption in reducing carbon emissions: A mean–variance analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    5. Long, Xueying & Bui, Quang & Oktavian, Grady & Schmidt, Daniel F. & Bergmeir, Christoph & Godahewa, Rakshitha & Lee, Seong Per & Zhao, Kaifeng & Condylis, Paul, 2025. "Scalable probabilistic forecasting in retail with gradient boosted trees: A practitioner’s approach," International Journal of Production Economics, Elsevier, vol. 279(C).
    6. Chuangneng Cai & Xiancheng Hao & Kui Wang & Xuebing Dong, 2023. "The Impact of Perceived Benefits on Blockchain Adoption in Supply Chain Management," Sustainability, MDPI, vol. 15(8), pages 1-24, April.
    7. Jin Sung Rha, 2020. "Trends of Research on Supply Chain Resilience: A Systematic Review Using Network Analysis," Sustainability, MDPI, vol. 12(11), pages 1-27, May.
    8. repec:tsa:wpaper:0203mss is not listed on IDEAS
    9. Rizwan Manzoor & B. S. Sahay & Sujeet Kumar Singh, 2025. "Blockchain technology in supply chain management: an organizational theoretic overview and research agenda," Annals of Operations Research, Springer, vol. 348(3), pages 1307-1354, May.
    10. Soumyadeb Chowdhury & Oscar Rodriguez-Espindola & Prasanta Dey & Pawan Budhwar, 2023. "Blockchain technology adoption for managing risks in operations and supply chain management: evidence from the UK," Annals of Operations Research, Springer, vol. 327(1), pages 539-574, August.
    11. Jude Jegan Joseph Jerome & Vandana Sonwaney & David Bryde & Gary Graham, 2024. "Achieving competitive advantage through technology-driven proactive supply chain risk management: an empirical study," Annals of Operations Research, Springer, vol. 332(1), pages 149-190, January.
    12. Venkataiah Chittipaka & Satish Kumar & Uthayasankar Sivarajah & Jana Lay-Hwa Bowden & Manish Mohan Baral, 2023. "Blockchain Technology for Supply Chains operating in emerging markets: an empirical examination of technology-organization-environment (TOE) framework," Annals of Operations Research, Springer, vol. 327(1), pages 465-492, August.
    13. 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).
    14. Tang, Liang & Jing, Ke & He, Jie & Stanley, H. Eugene, 2016. "Robustness of assembly supply chain networks by considering risk propagation and cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 129-139.
    15. Ma, Yungao & Wang, Nengmin & He, Zhengwen & Lu, Jizhou & Liang, Huigang, 2015. "Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands," European Journal of Operational Research, Elsevier, vol. 243(3), pages 815-825.
    16. Li Chen & Hau L. Lee, 2012. "Bullwhip Effect Measurement and Its Implications," Operations Research, INFORMS, vol. 60(4), pages 771-784, August.
    17. Davies, Jennifer & Sharifi, Hossein & Lyons, Andrew & Forster, Rick & Elsayed, Omar Khaled Shokry Mohamed, 2024. "Non-fungible tokens: The missing ingredient for sustainable supply chains in the metaverse age?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    18. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    19. Gaalman, Gerard & Disney, Stephen M., 2009. "On bullwhip in a family of order-up-to policies with ARMA(2,2) demand and arbitrary lead-times," International Journal of Production Economics, Elsevier, vol. 121(2), pages 454-463, October.
    20. Aditi S. Saha & Rakesh D. Raut & Vinay Surendra Yadav & Abhijit Majumdar, 2022. "Blockchain Changing the Outlook of the Sustainable Food Supply Chain to Achieve Net Zero?," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    21. Kevin B. Hendricks & Manpreet Hora & Vinod R. Singhal, 2015. "An Empirical Investigation on the Appointments of Supply Chain and Operations Management Executives," Management Science, INFORMS, vol. 61(7), pages 1562-1583, July.

    More about this item

    Statistics

    Access and download statistics

    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:arx:papers:2510.05487. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.