Skip to main content
Log in

Mismatch risk allocation in a coproduct supply chain

  • S.I.: RealCaseOR
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Products such as cattles and pigs can be processed into several types of products (parts) targeting different segments of customers, which belong to the so called coproducts. Mismatch risk is a significant issue in such coproduct supply chains. Under the Stackelberg game setting, we consider a coproduct supply chain consisting of one producer acting as the leader and one retailer being the follower and establish a stylized model to study how the mismatch risk should be allocated. Two supply chain modes are considered, i.e., the P-chain mode under which the producer is responsible for the processing activity and hence holds the mismatch risk, and the R-chain under which the retailer is responsible for the processing activity. We use the unbalanced ratio to reflect the degree of mismatch between supply and demand among different parts of the coproduct and study how the tradeoff between the bargaining power and the mismatch cost, by different mismatch risk allocations, influences the optimal decisions and the performances of the two parties as well as the whole supply chain. Our main findings include: (1) P-chain dominates R-chain from the perspective of the chain performance; and (2) the upstream producer is not always better off in the P-chain under which he bears more mismatch risk. Numerical study shows the robustness of our main results and further studies the effect of demand uncertainty and the processing cost on the performance of P-chain as compared to R-chain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Bansal, S., & Transchel, S. (2014). Managing supply risk for vertically differentiated co-products. Production and Operations Management, 23(9), 1577–1598.

    Google Scholar 

  • Bitran, G., & Gilbert, S. (1994). Co-production processes with random yields in the semiconductor industry. Operations Research, 42(3), 476–491.

    Google Scholar 

  • Boyabatli, O. (2015). Supply management in multiproduct firms with fixed proportions technology. Management Science, 61(12), 3013–3031.

    Google Scholar 

  • Boyabatli, O., Nguyen, D. Q., & Wang, T. (2017). Capacity management in agricultural commodity processing and application in the palm industry. Manufacturing & Service Operations Management, 19(4), 551–567.

    Google Scholar 

  • Cachon, G. P. (2004). The allocation of inventory risk in a supply chain: push, pull, and advance-purchase discount contracts. Management Science, 50(2), 222–238.

    Google Scholar 

  • Chen, Y. J., Tomlin, B., & Wang, Y. (2013). Coproduct technologies: Product line design and process innovation. Management Science, 59(12), 2772–2789.

    Google Scholar 

  • Chong, J. K., Ho, T. H., & Tang, C. S. (2001). A modeling framework for category assortment planning. Manufacturing & Service Operations Management, 3(3), 191–210.

    Google Scholar 

  • Davis, A. M., Katok, E., & Santamarla, N. (2014). Push, pull, or both? A behavioral study of how the allocation of inventory risk affects channel efficiency. Management Science, 60(11), 2666–2683.

    Google Scholar 

  • Dong, L., Kouvelis, P., & Wu, X. (2014). The value of operational flexibility in the presence of input and output price uncertainties with oil refining applications. Management Science, 60(12), 2908–2926.

    Google Scholar 

  • Dong, L., & Zhu, K. (2007). Two-wholesale-price contracts: Push, pull, and advance-purchase discount contracts. Manufacturing & Service Operations Management, 9(3), 291–311.

    Google Scholar 

  • Eric, O., & Sabyasachi, M. (2014). Physical and electronic wholesale markets: An empirical analysis of product sorting and market function. Journal of Management Information Systems, 31(2), 11–46.

    Google Scholar 

  • Ferguson, M., Guide, V. D, Jr., Koca, E., & Souza, G. C. (2010). The value of quality grading in remanufacturing. Production & Operations Management, 18(3), 300–314.

    Google Scholar 

  • Fine, C. H., & Freund, R. M. (1990). Optimal investment in product flexible manufacturing capacity. Management Science, 36(4), 449–466.

    Google Scholar 

  • Galbreth, M. R., & Blackburn, J. D. (2006). Optimal acquisition and sorting policies for remanufacturing. Production & Operations Management, 15(3), 384–392.

    Google Scholar 

  • Gilland, W. G., & Heese, H. S. (2013). Sequence matters: Shelf-space allocation under dynamic customer-driven substitution. Production & Operations Management, 22(4), 875–887.

    Google Scholar 

  • Granot, D., & Yin, S. (2008). Competition and cooperation in decentralized push and pull assembly systems. Management Science, 54(4), 733–747.

    Google Scholar 

  • Graves, S. C., & Tomlin, B. T. (2003). Process flexibility in supply chains. Management Science, 49(7), 907–919.

    Google Scholar 

  • Gupta, D., Gerchak, Y., & Buzacott, J. A. (1992). The optimal mix of flexible and dedicated manufacturing capacities: Hedging against demand uncertainty. International Journal of Production Economics, 28(3), 309–319.

    Google Scholar 

  • Honhon, D., & Pan, X. A. (2017). Improving profits by bundling vertically differentiated products. Production & Operations Management, 26(8), 1481–1497.

    Google Scholar 

  • Jordan, W. C., & Graves, S. C. (1995). Principles on the benefits of man ufacturing process flexibility. Management Science, 41(4), 577–594.

    Google Scholar 

  • Lariviere, M. A., & Porteus, E. (2001). Selling to the newsvendor: An analysis of price-only contracts. Manufacturing & Service Operations Management, 3(4), 293–305.

    Google Scholar 

  • Li, S., & Tirupati, D. (1994). Dynamic capacity expansion problem with multiple products: Technology selection and timing of capacity additions. Operations Research, 42(5), 958–976.

    Google Scholar 

  • Li, S., & Tirupati, D. (1995). Technology choice with stochastic demands and dynamic capacity allocation: A two-product analysis. Journal of Operations Management, 12(3), 239–258.

    Google Scholar 

  • Li, S., & Tirupati, D. (1997). Impact of product mix flexibility and allocation policies on technology. Computers & Operations Research, 24(7), 611C626.

    Google Scholar 

  • Nahmias, S., & Moinzadeh, K. (1997). Lot sizing with randomly graded yields. Operations Research, 47(6), 974–986.

    Google Scholar 

  • Pan, X. A., & Honhon, D. (2012). Assortment planning for vertically differentiated products. Production & Operations Management, 21(2), 253–275.

    Google Scholar 

  • Sunar, N., & Plambeck, E. (2016). Allocating emissions among coproducts: Implications for procurement and climate policy. Manufacturing & Service Operations Management, 18(3), 414–428.

    Google Scholar 

  • Tomlin, B., & Wang, Y. (2005). On the value of mix flexibility and dual sourcing in unreliable newsvendor networks. Manufacturing & Service Operations Management, 7(1), 37–57.

    Google Scholar 

  • Tomlin, B., & Wang, Y. (2008). Pricing and operational recourse in coproduction systems. Management Science, 54(3), 522–537.

    Google Scholar 

  • Transchel, S., Bansal, S., & Deb, M. (2016). Managing production of hightech products with high production quality variability. International Journal of Production Research, 54(6), 1689–1707.

    Google Scholar 

  • Van Mieghem, J. A. (1998). Investment strategies for flexible resources. Management Science, 44(8), 1071–1078.

    Google Scholar 

  • Van Mieghem, J. A. (2004). Note-Commonality strategies: Value drivers and equivalence with flexible capacity and inventory substitution. Management Science, 50(3), 419–424.

    Google Scholar 

  • Wang, Y., Niu, B., & Guo, P. (2014). The comparison of two vertical outsourcing structures under push and pull contracts. Production and Operations Management, 23(4), 610–625.

    Google Scholar 

  • Yayla, H. M., Parlakturk, A. K., & Swaminathan, J. M. (2013). Multi-product quality competition: Impact of resource constraints. Production & Operations Management, 22(3), 603–614.

    Google Scholar 

  • Yin, S. (2010). Alliance formation among perfectly complementary suppliers in a price-sensitive assembly system. Manufacturing & Service Operations Management, 12(3), 527–544.

    Google Scholar 

Download references

Acknowledgements

The authors thanks the editor and the reviewers for their valuable comments on this paper. The paper is supported by NSFC (No. 71471085, 71671040, 71822103, 71871114) and NNSF of Jiangsu Province (BK20140279).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaolin Xu.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (pdf 97 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Peng, Y., Xu, X., Liang, X. et al. Mismatch risk allocation in a coproduct supply chain. Ann Oper Res 291, 707–730 (2020). https://doi.org/10.1007/s10479-018-3049-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-018-3049-y

Keywords

Navigation