Table of Contents Author Guidelines Submit a Manuscript
Discrete Dynamics in Nature and Society
Volume 2019, Article ID 4695654, 13 pages
https://doi.org/10.1155/2019/4695654
Research Article

Strategic Information Sharing in a Dynamic Supply Chain with a Carrier under Complex Uncertainty

Heng Du1 and Ye Jiang1,2

1School of Management and Engineering, Nanjing University, Nanjing 210093, China
2School of Business, Jiangsu Open University, Nanjing 210011, China

Correspondence should be addressed to Heng Du; moc.361@19789859781

Received 10 January 2019; Accepted 13 May 2019; Published 2 June 2019

Academic Editor: Manuel De la Sen

Copyright © 2019 Heng Du and Ye Jiang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. L. Li, “Information sharing in a supply chain with horizontal competition,” Management Science, vol. 48, no. 9, pp. 1196–1212, 2002. View at Publisher · View at Google Scholar · View at Scopus
  2. M. A. Darwish and O. M. Odah, “Vendor managed inventory model for single-vendor multi-retailer supply chains,” European Journal of Operational Research, vol. 204, no. 3, pp. 473–484, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. Y.-H. Wen, “Impact of collaborative transportation management on logistics capability and competitive advantage for the carrier,” Transportation Journal, vol. 51, no. 4, pp. 452–473, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. J. C. Tyan, F. K. Wang, and T. Du, “Applying collaborative transportation management models in global third-party logistics,” International Journal of Computer Integrated Manufacturing, vol. 16, no. 4-5, pp. 283–291, 2003. View at Publisher · View at Google Scholar · View at Scopus
  5. Q. Qi and Q. Zhang, “Research on information sharing risk in supply chain management,” in Proceedings of the 4th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM '08, pp. 1–6, IEEE, 2008.
  6. H. L. Lee, K. C. So, and C. S. Tang, “Value of information sharing in a two-level supply chain,” Management Science, vol. 46, no. 5, pp. 626–643, 2000. View at Publisher · View at Google Scholar · View at Scopus
  7. Z. Yu, H. Yan, and T. C. E. Cheng, “Benefits of information sharing with supply chain partnerships,” Industrial Management and Data Systems, vol. 101, no. 3, pp. 114–121, 2001. View at Publisher · View at Google Scholar
  8. A. Surana, S. Kumara, M. Greaves, and U. N. Raghavan, “Supply-chain networks: a complex adaptive systems perspective,” International Journal of Production Research, vol. 43, no. 20, pp. 4235–4265, 2005. View at Publisher · View at Google Scholar · View at Scopus
  9. G. P. Cachon and M. Fisher, “Supply chain inventory management and the value of shared information,” Management Science, vol. 46, no. 8, pp. 1032–1048, 2000. View at Publisher · View at Google Scholar · View at Scopus
  10. R. H. Teunter, M. Z. Babai, J. A. Bokhorst, and A. A. Syntetos, “Revisiting the value of information sharing in two-stage supply chains,” European Journal of Operational Research, vol. 270, no. 3, pp. 1044–1052, 2018. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. J. Dejonckheere, S. M. Disney, M. R. Lambrecht, and D. R. Towill, “Measuring and avoiding the bullwhip effect: a control theoretic approach,” European Journal of Operational Research, vol. 147, no. 3, pp. 567–590, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. D. C. Chatfield, J. G. Kim, T. P. Harrison, and J. C. Hayya, “The bullwhip effect—impact of stochastic lead time, information quality, and information sharing: a simulation study,” Production Engineering Research and Development, vol. 13, no. 4, pp. 340–353, 2004. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Ma and X. Ma, “Measure of the bullwhip effect considering the market competition between two retailers,” International Journal of Production Research, vol. 55, no. 2, pp. 313–326, 2017. View at Google Scholar
  14. Y. Zhao, Y. Cao, H. Li et al., “Bullwhip effect mitigation of green supply chain optimization in electronics industry,” Journal of Cleaner Production, vol. 180, pp. 888–912, 2018. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Aviv, “On the benefits of collaborative forecasting partnerships between retailers and manufacturers,” Management Science, vol. 53, no. 5, pp. 777–794, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. R. Fildes and B. Kingsman, “Incorporating demand uncertainty and forecast error in supply chain planning models,” Journal of the Operational Research Society, vol. 62, no. 3, pp. 483–500, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. J. R. Trapero, N. Kourentzes, and R. Fildes, “Impact of information exchange on supplier forecasting performance,” Omega , vol. 40, no. 6, pp. 738–747, 2012. View at Publisher · View at Google Scholar · View at Scopus
  18. N. Sanders and X. Wan, “Mitigating forecast errors from product variety through information sharing,” International Journal of Production Research, vol. 56, no. 12, pp. 1–12, 2018. View at Google Scholar
  19. Y.-H. Wen, “Shipment forecasting for supply chain collaborative transportation management using grey models with grey numbers,” Transportation Planning and Technology, vol. 34, no. 6, pp. 605–624, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. F. T. S. Chan and T. Zhang, “The impact of collaborative transportation management on supply chain performance: a simulation approach,” Expert Systems with Applications, vol. 38, no. 3, pp. 2319–2329, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Li and F. T. S. Chan, “The impact of collaborative transportation management on demand disruption of manufacturing supply chains,” International Journal of Production Research, vol. 50, no. 19, pp. 5635–5650, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. H. A. Simon, “Theories of bounded rationality,” Decision and Organization, vol. 1, no. 1, pp. 161–176, 1972. View at Google Scholar · View at MathSciNet
  23. J. M. Swaminathan, S. F. Smith, and N. M. Sadeh, “Modeling supply chain dynamics: a multiagent approach,” Decision Sciences, vol. 29, no. 3, pp. 607–631, 1998. View at Publisher · View at Google Scholar · View at Scopus
  24. Q. Long, “Three-dimensional-flow model of agent-based computational experiment for complex supply network evolution,” Expert Systems with Applications, vol. 42, no. 5, pp. 2525–2537, 2015. View at Publisher · View at Google Scholar · View at Scopus
  25. C. Yu and T. N. Wong, “A multi-agent architecture for multi-product supplier selection in consideration of the synergy between products,” International Journal of Production Research, vol. 53, no. 20, pp. 6059–6082, 2015. View at Publisher · View at Google Scholar · View at Scopus
  26. I. Dogan and A. R. Güner, “A reinforcement learning approach to competitive ordering and pricing problem,” Expert Systems with Applications, vol. 32, no. 1, pp. 39–48, 2015. View at Publisher · View at Google Scholar · View at Scopus
  27. Z. He, S. Wang, and T. C. E. Cheng, “Competition and evolution in multi-product supply chains: An agent-based retailer model,” International Journal of Production Economics, vol. 146, no. 1, pp. 325–336, 2013. View at Publisher · View at Google Scholar · View at Scopus
  28. B. Ponte, E. Sierra, D. de la Fuente, and J. Lozano, “Exploring the interaction of inventory policies across the supply chain: an agent-based approach,” Computers & Operations Research, vol. 78, pp. 335–348, 2017. View at Publisher · View at Google Scholar · View at Scopus
  29. I. Giannoccaro and A. Nair, “Examining the roles of product complexity and manager behavior on product design decisions: an agent-based study using NK simulation,” IEEE Transactions on Engineering Management, vol. 63, no. 2, pp. 237–247, 2016. View at Publisher · View at Google Scholar · View at Scopus
  30. S. Liu, W. H. Wu, C. C. Kang et al., “A single-machine two-agent scheduling problem by a branch-and-bound and three simulated annealing algorithms,” Discrete Dynamics in Nature and Society, vol. 2015, Article ID 681854, 8 pages, 2015. View at Publisher · View at Google Scholar
  31. L. Wan, “Two-agent scheduling to minimize the maximum cost with position-dependent jobs,” Discrete Dynamics in Nature and Society, vol. 2015, Article ID 932680, 4 pages, 2015. View at Publisher · View at Google Scholar · View at MathSciNet
  32. S. Axsäter, “Using the deterministic EOQ formula in stochastic inventory control,” Management Science, vol. 42, no. 6, pp. 830–834, 1996. View at Publisher · View at Google Scholar · View at Scopus
  33. F. Lu, H. Xu, P. Chen, and S. X. Zhu, “Joint pricing and production decisions with yield uncertainty and downconversion,” International Journal of Production Economics, vol. 197, pp. 52–62, 2018. View at Publisher · View at Google Scholar · View at Scopus
  34. Z. Liu, “Equilibrium analysis of capacity allocation with demand competition,” Naval Research Logistics (NRL), vol. 59, no. 3-4, pp. 254–265, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  35. K. Cattani, W. Gilland, H. S. Heese, and J. Swaminathan, “Boiling frogs: pricing strategies for a manufacturer adding a direct channel that competes with the traditional channel,” Production Engineering Research and Development, vol. 15, no. 1, pp. 40–56, 2006. View at Google Scholar · View at Scopus