IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v40y2010i5p353-367.html
   My bibliography  Save this article

General Electric Uses an Integrated Framework for Product Costing, Demand Forecasting, and Capacity Planning of New Photovoltaic Technology Products

Author

Listed:
  • Bex George Thomas

    (General Electric Global Research, Computing and Decision Science, Niskayuna, New York 12309)

  • Srinivas Bollapragada

    (General Electric Global Research, Computing and Decision Science, Niskayuna, New York 12309)

Abstract

General Electric (GE) Energy's nascent solar business has revenues of over $100 million, expects those revenues to grow to over $1 billion in the next three years, and has plans to rapidly grow the business beyond this period. GE Global Research (GEGR), in partnership with GE Energy's solar platform team, is pursuing a number of technological alternatives to bring new low-cost solar products to the market. However, the GE solar business is facing a challenge---making optimal investment decisions to realize its growth objectives in the presence of major uncertainties in technology, costs, demands, and energy policy. We have developed analytical decision support tools with embedded mathematical models to estimate product costs and demands, and to support capacity planning decisions under cost and demand uncertainties. In this paper, we outline our algorithmic approach and system implementation, which help to support strategic decisions at GE.

Suggested Citation

  • Bex George Thomas & Srinivas Bollapragada, 2010. "General Electric Uses an Integrated Framework for Product Costing, Demand Forecasting, and Capacity Planning of New Photovoltaic Technology Products," Interfaces, INFORMS, vol. 40(5), pages 353-367, October.
    • Handle: RePEc:inm:orinte:v:40:y:2010:i:5:p:353-367
    DOI: 10.1287/inte.1100.0518
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.1100.0518
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.1100.0518?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. Wander Jager & Marco A. Janssen, 2002. "Stimulating diffusion of green products," Journal of Evolutionary Economics, Springer, vol. 12(3), pages 283-306.
    2. Gruber, Harald, 1996. "Trade policy and learning by doing: the case of semiconductors," Research Policy, Elsevier, vol. 25(5), pages 723-739, August.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Gary D. Eppen & R. Kipp Martin & Linus Schrage, 1989. "OR Practice—A Scenario Approach to Capacity Planning," Operations Research, INFORMS, vol. 37(4), pages 517-527, 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. Martínez-Costa, Carme & Mas-Machuca, Marta & Benedito, Ernest & Corominas, Albert, 2014. "A review of mathematical programming models for strategic capacity planning in manufacturing," International Journal of Production Economics, Elsevier, vol. 153(C), pages 66-85.
    2. Ghadimi, Foad & Aouam, Tarik, 2021. "Planning capacity and safety stocks in a serial production–distribution system with multiple products," European Journal of Operational Research, Elsevier, vol. 289(2), pages 533-552.
    3. Diana Sánchez-Partida & Rodolfo Rodríguez-Méndez & José Luis Martínez-Flores & Santiago-Omar Caballero-Morales, 2018. "Implementation of Continuous Flow in the Cabinet Process at the Schneider Electric Plant in Tlaxcala, Mexico," Interfaces, INFORMS, vol. 48(6), pages 566-577, November.
    4. Smirnov, Dina & van Jaarsveld, Willem & Atan, Zümbül & de Kok, Ton, 2021. "Long-term resource planning in the high-tech industry: Capacity or inventory?," European Journal of Operational Research, Elsevier, vol. 293(3), pages 926-940.
    5. Bian, Yuan & Lemoine, David & Yeung, Thomas G. & Bostel, Nathalie & Hovelaque, Vincent & Viviani, Jean-laurent & Gayraud, Fabrice, 2018. "A dynamic lot-sizing-based profit maximization discounted cash flow model considering working capital requirement financing cost with infinite production capacity," International Journal of Production Economics, Elsevier, vol. 196(C), pages 319-332.

    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. Cantono, Simona, 2012. "Unveiling diffusion dynamics: an autocatalytic percolation model of environmental innovation diffusion and the optimal dynamic path of adoption subsidies," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201222, University of Turin.
    2. M Günther & C Stummer & L M Wakolbinger & M Wildpaner, 2011. "An agent-based simulation approach for the new product diffusion of a novel biomass fuel," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 12-20, January.
    3. 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).
    4. Yu Chang & Tao Zhang, 2019. "The Effects of Product Consistency and Consumer Resistance to Innovation on Green Product Diffusion in China," Sustainability, MDPI, vol. 11(9), pages 1-14, May.
    5. Welsch, Heinz & Kühling, Jan, 2009. "Determinants of pro-environmental consumption: The role of reference groups and routine behavior," Ecological Economics, Elsevier, vol. 69(1), pages 166-176, November.
    6. Rode, Johannes & Weber, Alexander, 2016. "Does localized imitation drive technology adoption? A case study on rooftop photovoltaic systems in Germany," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 38-48.
    7. Meihan He & Jongsu Lee, 2020. "Social culture and innovation diffusion: a theoretically founded agent-based model," Journal of Evolutionary Economics, Springer, vol. 30(4), pages 1109-1149, September.
    8. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," 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. 20(2), pages 183-230, June.
    9. Oscar Gutiérrez & Francisco Ruiz-Aliseda, 2011. "Real options with unknown-date events," Annals of Finance, Springer, vol. 7(2), pages 171-198, May.
    10. Shari, Babajide Epe & Dioha, Michael O. & Abraham-Dukuma, Magnus C. & Sobanke, Victor O. & Emodi, Nnaemeka V., 2022. "Clean cooking energy transition in Nigeria: Policy implications for Developing countries," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 319-343.
    11. 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.
    12. Tiruwork B. Tibebu & Eric Hittinger & Qing Miao & Eric Williams, 2024. "Adoption Model Choice Affects the Optimal Subsidy for Residential Solar," Energies, MDPI, vol. 17(3), pages 1-19, February.
    13. Simon P. Anderson & André de Palma, 2012. "Competition for attention in the Information (overload) Age," RAND Journal of Economics, RAND Corporation, vol. 43(1), pages 1-25, March.
    14. Van, Tien Linh Cao & Barthelmes, Lukas & Gnann, Till & Speth, Daniel & Kagerbauer, Martin, 2021. "Addressing the gaps in market diffusion modeling of electrical vehicles: A case study from Germany for the integration of environmental policy measures," Working Papers "Sustainability and Innovation" S05/2021, Fraunhofer Institute for Systems and Innovation Research (ISI).
    15. Francisco Barahona & Stuart Bermon & Oktay Günlük & Sarah Hood, 2005. "Robust capacity planning in semiconductor manufacturing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 459-468, August.
    16. Ma, Peng, 2021. "Optimal generic and brand advertising efforts in a decentralized supply chain considering customer surplus," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    17. Sergio Currarini & Carmen Marchiori & Alessandro Tavoni, 2016. "Network Economics and the Environment: Insights and Perspectives," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(1), pages 159-189, September.
    18. Klingler, Anna-Lena & Luthander, Rasmus, 2018. "Market diffusion of residential PV and battery systems driven by self-consumption: A comparison of Sweden and Germany," Working Papers "Sustainability and Innovation" S18/2018, Fraunhofer Institute for Systems and Innovation Research (ISI).
    19. Robertson, Alastair & Soopramanien, Didier & Fildes, Robert, 2007. "A segment-based analysis of Internet service adoption among UK households," Technology in Society, Elsevier, vol. 29(3), pages 339-350.
    20. Edgardo Arturo Ayala Gaytán, 2009. "Social network externalities and price dispersion in online markets," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-28, November.

    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:orinte:v:40:y:2010:i:5:p:353-367. 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.