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DIRECTV: Forecasting Diffusion of a New Technology Prior to Product Launch

Author

Listed:
  • Frank M. Bass

    (School of Management, University of Texas at Dallas, P.O. Box 830688, JO 5.1, Richardson, Texas 75083-0688)

  • Kent Gordon

    (SMART—Strategic Marketing And Research Techniques, 2700 Ygnacio Valley Road, Walnut Creek, California 94598)

  • Teresa L. Ferguson

    (DIRECTV, Inc., 2230 East Imperial Highway, El Segundo, California 90245)

  • Mary Lou Githens

    (DIRECTV, Inc.)

Abstract

We conducted research for planning the launch of a satellite television product, leading to a prelaunch forecast of subscriptions of satellite television over a five-year horizon. The forecast was based on the Bass model. We derived parameters of the model in part from stated-intentions data from potential consumers and in part by guessing by analogy. The 1992 forecast of the adoption and diffusion of satellite television proved to be quite good in comparison with actual subscriptions over the five-year period from 1994 through 1999.

Suggested Citation

  • Frank M. Bass & Kent Gordon & Teresa L. Ferguson & Mary Lou Githens, 2001. "DIRECTV: Forecasting Diffusion of a New Technology Prior to Product Launch," Interfaces, INFORMS, vol. 31(3_supplem), pages 82-93, June.
    • Handle: RePEc:inm:orinte:v:31:y:2001:i:3_supplement:p:s82-s93
    DOI: 10.1287/inte.31.3s.82.9677
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    References listed on IDEAS

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    1. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
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    Cited by:

    1. Gagliardi, Dimitri & Ramlogan, Ronnie & Navarra, Pierluigi & Dello Russo, Cinzia, 2018. "Diffusion of complementary evolving pharmaceutical innovations: The case of Abacavir and its pharmacogenetic companion diagnostic in Italy," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 223-233.
    2. Chul-Yong Lee & Jongsu Lee, 2009. "Demand Forecasting in the Early Stage of the Technology's Life Cycle Using Bayesian update," TEMEP Discussion Papers 200903, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Apr 2009.
    3. 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.
    4. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    7. Jean-Pierre H. Dube & Günter J. Hitsch & Pranav Jindal, 2012. "The Joint Identification of Utility and Discount Functions From Stated Choice Data: An Application to Durable Goods Adoption," NBER Working Papers 18393, National Bureau of Economic Research, Inc.
    8. Herbert Dawid & Reinhold Decker & Thomas Hermann & Hermann Jahnke & Wilhelm Klat & Rolf König & Christian Stummer, 2017. "Management science in the era of smart consumer products: challenges and research perspectives," 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. 25(1), pages 203-230, March.
    9. Jean-Pierre Dubé & Günter Hitsch & Pranav Jindal, 2014. "The Joint identification of utility and discount functions from stated choice data: An application to durable goods adoption," Quantitative Marketing and Economics (QME), Springer, vol. 12(4), pages 331-377, December.
    10. Yonghua Ji & Vijay S. Mookerjee & Suresh P. Sethi, 2005. "Optimal Software Development: A Control Theoretic Approach," Information Systems Research, INFORMS, vol. 16(3), pages 292-306, September.
    11. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    12. Michel Clement, 2004. "Fernsehen im Zeitalter von Networked Personal Video Recordern," Schmalenbach Journal of Business Research, Springer, vol. 56(8), pages 760-779, December.
    13. Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago, 2020. "Forecasting from others’ experience: Bayesian estimation of the generalized Bass model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 442-465.
    14. Edward I. Brody, 2001. "Marketing Engineering at BBDO," Interfaces, INFORMS, vol. 31(3_supplem), pages 74-81, June.
    15. Saarenpää, Jukka & Kolehmainen, Mikko & Niska, Harri, 2013. "Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption," Applied Energy, Elsevier, vol. 107(C), pages 456-464.
    16. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    17. 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.
    18. John D. C. Little, 2004. "Comments on ÜModels and Managers: The Concept of a Decision CalculusÝ," Management Science, INFORMS, vol. 50(12_supple), pages 1854-1860, December.
    19. Jinah Yang & Daiki Min & Jeenyoung Kim, 2020. "The Use of Big Data and Its Effects in a Diffusion Forecasting Model for Korean Reverse Mortgage Subscribers," Sustainability, MDPI, vol. 12(3), pages 1-17, January.
    20. Shin, Jungwoo & Lee, Chul-Yong & Kim, Hongbum, 2016. "Technology and demand forecasting for carbon capture and storage technology in South Korea," Energy Policy, Elsevier, vol. 98(C), pages 1-11.
    21. Lee, Hakyeon & Kim, Sang Gook & Park, Hyun-woo & Kang, Pilsung, 2014. "Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 49-64.
    22. Chul-Yong Lee & Min-Kyu Lee, 2017. "Demand Forecasting in the Early Stage of the Technology’s Life Cycle Using a Bayesian Update," Sustainability, MDPI, vol. 9(8), pages 1-15, August.
    23. 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.

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