IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v68y2022i1p399-419.html
   My bibliography  Save this article

Managing Self-Replicating Innovative Goods

Author

Listed:
  • Bin Hu

    (Naveen Jindal School of Management, University of Texas at Dallas, Richardson, Texas 75080)

  • Zhankun Sun

    (Department of Management Sciences, College of Business, City University of Hong Kong, Kowloon, Hong Kong)

Abstract

Inspired by self-replicating three-dimensional printers and innovative agricultural and husbandry goods, we study optimal production and sales policies for a manufacturer of self-replicating innovative goods with a focus on the unique “keep-or-sell” trade-off—namely, whether a newly produced unit should be sold to satisfy demand and stimulate future demand or added to inventory to increase production capacity. We adopt the continuous-time optimal control framework and marry a self-replication model on the production side to the canonical innovation-diffusion model on the demand side. By analyzing the model, we identify a condition that differentiates Strong and Weak Replicability regimes, wherein production and sales, respectively, take priority over the other and fully characterize their distinct optimal policies. These insights prove robust and helpful in several extensions, including backlogged demand, liquidity constraints, stochastic innovation diffusion, launch inventory decision, and exogenous demand. We also find that social marketing strategies are particularly well suited for self-replicating innovative goods under Strong Replication.

Suggested Citation

  • Bin Hu & Zhankun Sun, 2022. "Managing Self-Replicating Innovative Goods," Management Science, INFORMS, vol. 68(1), pages 399-419, January.
    • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:1:p:399-419
    DOI: 10.1287/mnsc.2020.3936
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2020.3936
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2020.3936?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. Jing-Sheng Song & Yue Zhang, 2020. "Stock or Print? Impact of 3-D Printing on Spare Parts Logistics," Management Science, INFORMS, vol. 66(9), pages 3860-3878, September.
    2. Arbabian, Mohammad E. & Wagner, Michael R., 2020. "The impact of 3D printing on manufacturer–retailer supply chains," European Journal of Operational Research, Elsevier, vol. 285(2), pages 538-552.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Sunil Kumar & Jayashankar M. Swaminathan, 2003. "Diffusion of Innovations Under Supply Constraints," Operations Research, INFORMS, vol. 51(6), pages 866-879, December.
    5. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    6. Dipak Jain & Vijay Mahajan & Eitan Muller, 1991. "Innovation Diffusion in the Presence of Supply Restrictions," Marketing Science, INFORMS, vol. 10(1), pages 83-90.
    7. 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.
    8. Qi Feng & Sirong Luo & J. George Shanthikumar, 2020. "Integrating Dynamic Pricing with Inventory Decisions Under Lost Sales," Management Science, INFORMS, vol. 66(5), pages 2232-2247, May.
    9. Mayorga, Maria E. & Ahn, Hyun-Soo, 2011. "Joint management of capacity and inventory in make-to-stock production systems with multi-class demand," European Journal of Operational Research, Elsevier, vol. 212(2), pages 312-324, July.
    10. Özlem Bilginer & Feryal Erhun, 2015. "Production and Sales Planning in Capacitated New Product Introductions," Production and Operations Management, Production and Operations Management Society, vol. 24(1), pages 42-53, January.
    11. Wenjing Shen & Izak Duenyas & Roman Kapuscinski, 2011. "New Product Diffusion Decisions Under Supply Constraints," Management Science, INFORMS, vol. 57(10), pages 1802-1810, October.
    12. 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.
    13. Chen, Li & Cui, Yao & Lee, Hau L., 2017. "Retailing with 3D Printing," Research Papers repec:ecl:stabus:3591, Stanford University, Graduate School of Business.
    14. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2011. "Note: A Reply to "New Product Diffusion Decisions Under Supply Constraints"," Management Science, INFORMS, vol. 57(10), pages 1811-1812, October.
    15. H. Scott Gordon, 1954. "The Economic Theory of a Common-Property Resource: The Fishery," Journal of Political Economy, University of Chicago Press, vol. 62, pages 124-124.
    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. Yunke Mai & Bin Hu, 2023. "Optimizing Free-to-Play Multiplayer Games with Premium Subscription," Management Science, INFORMS, vol. 69(6), pages 3437-3456, June.

    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. Schwarz, Justus Arne & Tan, Barış, 2021. "Optimal sales and production rollover strategies under capacity constraints," European Journal of Operational Research, Elsevier, vol. 294(2), pages 507-524.
    2. Yunke Mai & Bin Hu, 2023. "Optimizing Free-to-Play Multiplayer Games with Premium Subscription," Management Science, INFORMS, vol. 69(6), pages 3437-3456, June.
    3. 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.
    4. 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.
    5. 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.
    6. Negahban, Ashkan & Smith, Jeffrey S., 2018. "Optimal production-sales policies and entry time for successive generations of new products," International Journal of Production Economics, Elsevier, vol. 199(C), pages 220-232.
    7. Rachel Lacroix & Anna Timonina-Farkas & Ralf W. Seifert, 2023. "Utilizing additive manufacturing and mass customization under capacity constraints," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 281-301, January.
    8. Hong, Zhaofu & Li, Mengfan & Han, Xiaoya & He, Xuhuai, 2020. "Innovative green product diffusion through word of mouth," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    9. 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.
    10. 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.
    11. Nie, Jiajia & Xu, Xiaoxuan & Yue, Xiaohang & Guo, Qiang & Zhou, Yu, 2023. "Less is more: A strategic analysis of 3D printing with limited capacity," International Journal of Production Economics, Elsevier, vol. 258(C).
    12. Vahideh Manshadi & Sidhant Misra & Scott Rodilitz, 2020. "Diffusion in Random Networks: Impact of Degree Distribution," Operations Research, INFORMS, vol. 68(6), pages 1722-1741, November.
    13. Il-Horn Hann & JooHee Oh, 2017. "Combating Prerelease Piracy: Modeling the Effects of Antipiracy Measures in P2P Networks," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 92-107, February.
    14. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    15. Kartik Hosanagar & Peng Han & Yong Tan, 2010. "Diffusion Models for Peer-to-Peer (P2P) Media Distribution: On the Impact of Decentralized, Constrained Supply," Information Systems Research, INFORMS, vol. 21(2), pages 271-287, June.
    16. 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.
    17. Ivan Diaz-Rainey & Dionisia Tzavara, 2011. "Financing Renewable Energy through Household Adoption of Green Electricity Tariffs: A Diffusion Model of an Induced Environmental Market," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2011-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    18. Apurva Jain & Swapnil Rayal, 2023. "Managing medical equipment capacity with early spread of infection in a region," Production and Operations Management, Production and Operations Management Society, vol. 32(5), pages 1415-1432, May.
    19. Yan, Xiaoming & Liu, Ke, 2009. "Optimal control problems for a new product with word-of-mouth," International Journal of Production Economics, Elsevier, vol. 119(2), pages 402-414, June.
    20. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.

    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:inm:ormnsc:v:68:y:2022:i:1:p:399-419. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.