IDEAS home Printed from https://ideas.repec.org/a/wly/jnddns/v2016y2016i1n2026715.html

Investment Decision‐Making and Coordination of Supply Chain: A New Research in the Big Data Era

Author

Listed:
  • Pan Liu
  • Shu-ping Yi

Abstract

In a Big Data environment, in order to study the decision‐making problem of Big Data information investment and the effects of using Big Data information to improve industry cost on supply chain coordination, firstly the importance of Data Company in supply chain was analyzed, and the original supply chain model was built. Meanwhile, some changes of consumer behavior were analyzed in a Big Data environment. Based on these, the market demand function and the benefit model of stakeholder were built and analyzed. Findings: (1) The first finding is whether an enterprise was suitable for gaining Big Data to improve its costs, which was determined by the cost improvement coefficient; namely, it was related to the ability of excavating and using the value of Big Data. (2) Whether the supply chain was the decentralized decision‐making and the centralized decision‐making, the thresholds of acquisition costs on Big Data information were equal. Moreover, the maximum value that they could undertake was same. (3) Meanwhile the fact that the quantity discount contract could achieve a win‐win outcome for supply chain members was proved. The discount coefficient was related to consumers’ behavior preference in a Big Data environment.

Suggested Citation

  • Pan Liu & Shu-ping Yi, 2016. "Investment Decision‐Making and Coordination of Supply Chain: A New Research in the Big Data Era," Discrete Dynamics in Nature and Society, John Wiley & Sons, vol. 2016(1).
    • Handle: RePEc:wly:jnddns:v:2016:y:2016:i:1:n:2026715
    DOI: 10.1155/2016/2026715
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2016/2026715
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/2026715?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
    ---><---

    References listed on IDEAS

    as
    1. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    2. Z. Kevin Weng, 1995. "Channel Coordination and Quantity Discounts," Management Science, INFORMS, vol. 41(9), pages 1509-1522, September.
    3. 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.
    4. Opresnik, David & Taisch, Marco, 2015. "The value of Big Data in servitization," International Journal of Production Economics, Elsevier, vol. 165(C), pages 174-184.
    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. Pan Liu & Shu-ping Yi, 2018. "A study on supply chain investment decision-making and coordination in the Big Data environment," Annals of Operations Research, Springer, vol. 270(1), pages 235-253, November.
    2. Yanwei Chen & Xiaojun Liu & Kaiqing Huang & Huajun Tang, 2022. "Pricing and Service Effort Decisions of Book Dual-Channel Supply Chains with Showrooming Effect Based on Cost-Sharing Contracts," Sustainability, MDPI, vol. 14(18), pages 1-23, September.
    3. Mutlu, Fatih & Çetinkaya, Sıla, 2020. "Supplier–carrier–buyer channels: Contractual pricing for a carrier serving a supplier–buyer partnership," International Journal of Production Economics, Elsevier, vol. 230(C).
    4. Ray Qing Cao & Dara G. Schniederjans & Vicky Ching Gu, 2021. "Stakeholder sentiment in service supply chains: big data meets agenda-setting theory," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 151-175, March.
    5. Zhan, Yuanzhu & Tan, Kim Hua, 2020. "An analytic infrastructure for harvesting big data to enhance supply chain performance," European Journal of Operational Research, Elsevier, vol. 281(3), pages 559-574.
    6. Zhou, Yong-Wu, 2009. "Two-echelon supply chain coordination through the unified number of annual orders," International Journal of Production Economics, Elsevier, vol. 117(1), pages 162-173, January.
    7. Xiangfeng Chen & Anyu Wang, 2012. "Trade credit contract with limited liability in the supply chain with budget constraints," Annals of Operations Research, Springer, vol. 196(1), pages 153-165, July.
    8. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    9. Subrata Saha, 2016. "Channel characteristics and coordination in three-echelon dual-channel supply chain," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(3), pages 740-754, February.
    10. Hwan Lee, Chang & Rhee, Byong-Duk, 2010. "Coordination contracts in the presence of positive inventory financing costs," International Journal of Production Economics, Elsevier, vol. 124(2), pages 331-339, April.
    11. Ding, Ding & Chen, Jian, 2008. "Coordinating a three level supply chain with flexible return policies," Omega, Elsevier, vol. 36(5), pages 865-876, October.
    12. Giannoccaro, Ilaria & Pontrandolfo, Pierpaolo, 2009. "Negotiation of the revenue sharing contract: An agent-based systems approach," International Journal of Production Economics, Elsevier, vol. 122(2), pages 558-566, December.
    13. Biswas, Indranil & Avittathur, Balram & Chatterjee, Ashis K, 2016. "Impact of structure, market share and information asymmetry on supply contracts for a single supplier multiple buyer network," European Journal of Operational Research, Elsevier, vol. 253(3), pages 593-601.
    14. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Grenoble Ecole de Management (Post-Print) halshs-01923259, HAL.
    15. Yaping Zhao & Zelong Yi, 2021. "Pricing of a Three-Stage Supply Chain with a Big Data Company," SN Operations Research Forum, Springer, vol. 2(4), pages 1-19, December.
    16. Yingxue Zhao & Tsan-Ming Choi & T. C. E. Cheng & Shouyang Wang, 2017. "Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand," Annals of Operations Research, Springer, vol. 257(1), pages 491-518, October.
    17. Subhajyoti Bandyopadhyay & Anand A. Paul, 2010. "Equilibrium Returns Policies in the Presence of Supplier Competition," Marketing Science, INFORMS, vol. 29(5), pages 846-857, 09-10.
    18. Sheu, Jiuh-Biing, 2011. "Marketing-driven channel coordination with revenue-sharing contracts under price promotion to end-customers," European Journal of Operational Research, Elsevier, vol. 214(2), pages 246-255, October.
    19. Lin Jiang & Yong Wang & Xiaoming Yan & Wei Dai, 2014. "Coordinating a three-stage supply chain with competing manufacturers," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 53-72, March.
    20. Geunes, Joseph & Romeijn, H. Edwin & van den Heuvel, Wilco, 2016. "Improving the efficiency of decentralized supply chains with fixed ordering costs," European Journal of Operational Research, Elsevier, vol. 252(3), pages 815-828.

    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:wly:jnddns:v:2016:y:2016:i:1:n:2026715. 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: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/3059 .

    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.