IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v39y2011i3p313-322.html
   My bibliography  Save this article

Supply chain configuration for diffusion of new products: An integrated optimization approach

Author

Listed:
  • Amini, Mehdi
  • Li, Haitao

Abstract

We develop an integrated/hybrid optimization model for configuring new products' supply chains while explicitly considering the impact of demand dynamics during new products' diffusion. The hybrid model simultaneously determines optimal production/sales plan and supply chain configuration. The production and sales plan provides decisions on the optimal timing to launch a new product, as well as the production and sales quantity in each planning period. The supply chain configuration provides optimal selection of options and safety stock level kept at each supply chain function. Extensive computational experiments on randomly generated testbed problems indicate that the hybrid modeling and solution approach significantly outperforms non-hybrid alternative modeling and solution approaches under various diffusion and supply chain topologies. We provide insights on optimal production/sales plan and supply chain configuration for new products during their diffusion process. Also, managerial implications relevant to effectiveness of the hybrid approach are discussed.

Suggested Citation

  • Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
  • Handle: RePEc:eee:jomega:v:39:y:2011:i:3:p:313-322
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305-0483(10)00098-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stephen C. Graves & Sean P. Willems, 2000. "Optimizing Strategic Safety Stock Placement in Supply Chains," Manufacturing & Service Operations Management, INFORMS, vol. 2(1), pages 68-83, June.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Sunil Kumar & Jayashankar M. Swaminathan, 2003. "Diffusion of Innovations Under Supply Constraints," Operations Research, INFORMS, vol. 51(6), pages 866-879, December.
    4. A. M. Geoffrion & G. W. Graves, 1974. "Multicommodity Distribution System Design by Benders Decomposition," Management Science, INFORMS, vol. 20(5), pages 822-844, January.
    5. Stephen C. Graves & Sean P. Willems, 2005. "Optimizing the Supply Chain Configuration for New Products," Management Science, INFORMS, vol. 51(8), pages 1165-1180, August.
    6. Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
    7. Inderfurth, Karl & Minner, Stefan, 1998. "Safety stocks in multi-stage inventory systems under different service measures," European Journal of Operational Research, Elsevier, vol. 106(1), pages 57-73, April.
    8. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2002. "Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint," Management Science, INFORMS, vol. 48(2), pages 187-206, February.
    9. Yu, Haisheng & Zeng, Amy Z. & Zhao, Lindu, 2009. "Single or dual sourcing: decision-making in the presence of supply chain disruption risks," Omega, Elsevier, vol. 37(4), pages 788-800, August.
    10. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    11. Francas, David & Minner, Stefan, 2009. "Manufacturing network configuration in supply chains with product recovery," Omega, Elsevier, vol. 37(4), pages 757-769, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Negahban, Ashkan & Dehghanimohammadabadi, Mohammad, 2018. "Optimizing the supply chain configuration and production-sales policies for new products over multiple planning horizons," International Journal of Production Economics, Elsevier, vol. 196(C), pages 150-162.
    2. Liu, Songsong & Papageorgiou, Lazaros G., 2013. "Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry," Omega, Elsevier, vol. 41(2), pages 369-382.
    3. Formaneck, Steven D. & Cozzarin, Brian P., 2013. "Technology adoption and training practices as a constrained shortest path problem," Omega, Elsevier, vol. 41(2), pages 459-472.
    4. György Kovács & Béla Illés, 2019. "Development of an Optimization Method and Software for Optimizing Global Supply Chains for Increased Efficiency, Competitiveness, and Sustainability," Sustainability, MDPI, vol. 11(6), pages 1-28, March.
    5. Tsai-Chi Kuo & Ming-Lang Tseng & Hsiao-Min Chen & Ping-Shun Chen & Po-Chen Chang, 2018. "Design and Analysis of Supply Chain Networks with Low Carbon Emissions," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1353-1374, December.
    6. Lukas, Elmar & Welling, Andreas, 2017. "Efficient non-cooperative bargaining despite keeping strategic information private," Journal of Corporate Finance, Elsevier, vol. 42(C), pages 287-294.
    7. Li, Haitao & Womer, Keith, 2012. "Optimizing the supply chain configuration for make-to-order manufacturing," European Journal of Operational Research, Elsevier, vol. 221(1), pages 118-128.
    8. Brandenburg, Marcus, 2017. "A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects," Omega, Elsevier, vol. 70(C), pages 58-76.
    9. Sabri, Yasmine & Nuur, Cali & Micheli, Guido J.L., 2015. "Exploring the configuration of innovation-based supply chains," INDEK Working Paper Series 2015/12, Royal Institute of Technology, Department of Industrial Economics and Management.
    10. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    11. Li, Xiaohong & Yang, Dong & Hu, Mengqi, 2018. "A scenario-based stochastic programming approach for the product configuration problem under uncertainties and carbon emission regulations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 126-146.
    12. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    13. Ashkan Negahban & Jeffrey S. Smith, 2018. "A joint analysis of production and seeding strategies for new products: an agent-based simulation approach," Annals of Operations Research, Springer, vol. 268(1), pages 41-62, September.
    14. Gaur, Jighyasu & Amini, Mehdi & Rao, A.K., 2017. "Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model," Omega, Elsevier, vol. 66(PB), pages 212-223.
    15. Zhang, Juan & Gou, Qinglong & Liang, Liang & Huang, Zhimin, 2013. "Supply chain coordination through cooperative advertising with reference price effect," Omega, Elsevier, vol. 41(2), pages 345-353.
    16. Garcia, C.A. & Ibeas, A. & Herrera, J. & Vilanova, R., 2012. "Inventory control for the supply chain: An adaptive control approach based on the identification of the lead-time," Omega, Elsevier, vol. 40(3), pages 314-327.
    17. Moncayo-Martínez, Luis A. & Zhang, David Z., 2013. "Optimising safety stock placement and lead time in an assembly supply chain using bi-objective MAX–MIN ant system," International Journal of Production Economics, Elsevier, vol. 145(1), pages 18-28.
    18. Garcia Salcedo, Carlos Andres & Ibeas Hernandez, Asier & Vilanova, Ramón & Herrera Cuartas, Jorge, 2013. "Inventory control of supply chains: Mitigating the bullwhip effect by centralized and decentralized Internal Model Control approaches," European Journal of Operational Research, Elsevier, vol. 224(2), pages 261-272.
    19. Nihan Kabadayi & Mohammad Dehghanimohammadabadi, 2022. "Multi-objective supplier selection process: a simulation–optimization framework integrated with MCDM," Annals of Operations Research, Springer, vol. 319(2), pages 1607-1629, December.

    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. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    2. Wenjing Shen & Izak Duenyas & Roman Kapuscinski, 2014. "Optimal Pricing, Production, and Inventory for New Product Diffusion Under Supply Constraints," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 28-45, February.
    3. Hong, Zhaofu & Dai, Wei & Luh, Hsing & Yang, Chenchen, 2018. "Optimal configuration of a green product supply chain with guaranteed service time and emission constraints," European Journal of Operational Research, Elsevier, vol. 266(2), pages 663-677.
    4. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    5. Negahban, Ashkan & Dehghanimohammadabadi, Mohammad, 2018. "Optimizing the supply chain configuration and production-sales policies for new products over multiple planning horizons," International Journal of Production Economics, Elsevier, vol. 196(C), pages 150-162.
    6. Gaur, Jighyasu & Amini, Mehdi & Rao, A.K., 2017. "Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model," Omega, Elsevier, vol. 66(PB), pages 212-223.
    7. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    8. Bernd Frick & Franziska Prockl, 2018. "Information Precision In Online Communities: Player Valuations On Www.Transfermarkt.De," Working Papers Dissertations 37, Paderborn University, Faculty of Business Administration and Economics.
    9. Stefan N. Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    10. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    11. Ashkan Negahban & Jeffrey S. Smith, 2018. "A joint analysis of production and seeding strategies for new products: an agent-based simulation approach," Annals of Operations Research, Springer, vol. 268(1), pages 41-62, September.
    12. Massiani, Jérôme, 2015. "Cost-Benefit Analysis of policies for the development of electric vehicles in Germany: Methods and results," Transport Policy, Elsevier, vol. 38(C), pages 19-26.
    13. Yang Liu and Taoyuan Wei, 2016. "Market and Non-market Policies for Renewable Energy Diffusion: A Unifying Framework and Empirical Evidence from Chinas Wind Power Sector," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    14. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
    15. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    16. Bin Hu & Zhankun Sun, 2022. "Managing Self-Replicating Innovative Goods," Management Science, INFORMS, vol. 68(1), pages 399-419, January.
    17. Gary Biglaiser & Jacques Crémer & André Veiga, 2020. "Migration between Platforms," CESifo Working Paper Series 8185, CESifo.
    18. Sharad Goel & Ashton Anderson & Jake Hofman & Duncan J. Watts, 2016. "The Structural Virality of Online Diffusion," Management Science, INFORMS, vol. 62(1), pages 180-196, January.
    19. Bi-Huei Tsai & Yiming Li, 2011. "Modelling competition in global LCD TV industry," Applied Economics, Taylor & Francis Journals, vol. 43(22), pages 2969-2981.
    20. Eryn Juan He & Joel Goh, 2022. "Profit or Growth? Dynamic Order Allocation in a Hybrid Workforce," Management Science, INFORMS, vol. 68(8), pages 5891-5906, August.

    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:eee:jomega:v:39:y:2011:i:3:p:313-322. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.