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Technical Note—A Note on Optimal Strategic Pricing of Technological Innovations

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  • Frank M. Bass

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

  • Alain V. Bultez

    (Faculté Universitaire Catholique de Mons (FUCAM, Belgium) and European Institute for Advanced Studies in Management, Brussels, Belgium)

Abstract

The experience curve phenomenon of falling marginal costs associated with accumulated output or production experience has given rise to dynamic pricing models. Optimal pricing policies will depend upon the nature of the dynamic demand and cost functions. In this note we shall show that the demand function employed by Bass (Bass, F. M. 1980. The relationship between diffusion rates, experience curves, and demand elasticities for consumer durable technological innovations. (July) S51–S67.) when taken in conjunction with the experience curve cost function leads to a multiperiod pricing strategy which is always less than the myopically optimal price. Further, we present a dynamic programming algorithm for the multiperiod strategy in which we have explored the effects on discounted profits of myopic pricing versus multiperiod pricing. The results of this comparison may, to some, be somewhat surprising and may have managerial significance.

Suggested Citation

  • Frank M. Bass & Alain V. Bultez, 1982. "Technical Note—A Note on Optimal Strategic Pricing of Technological Innovations," Marketing Science, INFORMS, vol. 1(4), pages 371-378.
    • Handle: RePEc:inm:ormksc:v:1:y:1982:i:4:p:371-378
    DOI: 10.1287/mksc.1.4.371
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    Cited by:

    1. Jorgensen, Steffen & Zaccour, Georges, 1999. "Price subsidies and guaranteed buys of a new technology," European Journal of Operational Research, Elsevier, vol. 114(2), pages 338-345, April.
    2. Xiaoyu Li & Jiahong Yuan & Yan Shi & Tianteng Wang & Xiangpei Hu & Felix Tung Sun Chan & Junhu Ruan, 2020. "An extended Bass Model on consumer quantity of B2C commerce platforms," Electronic Commerce Research, Springer, vol. 20(3), pages 609-628, September.
    3. Yao, Fanjun & Parilina, Elena & Zaccour, Georges & Gao, Hongwei, 2022. "Accounting for consumers’ environmental concern in supply chain contracts," European Journal of Operational Research, Elsevier, vol. 301(3), pages 987-1006.
    4. Parker, Philip M. & Sarvary, Miklos, 1997. "Formulating dynamic strategies using decision calculus," European Journal of Operational Research, Elsevier, vol. 98(3), pages 542-554, May.
    5. Fuxiao Lu & Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2016. "Benefits of partial myopia in a durable product supply chain considering pricing and advertising," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(10), pages 1309-1324, October.
    6. Luo, Qi & Saigal, Romesh & Chen, Zhibin & Yin, Yafeng, 2019. "Accelerating the adoption of automated vehicles by subsidies: A dynamic games approach," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 226-243.
    7. Mohan V. Tatikonda & Mitzi M. Montoya-Weiss, 2001. "Integrating Operations and Marketing Perspectives of Product Innovation: The Influence of Organizational Process Factors and Capabilities on Development Performance," Management Science, INFORMS, vol. 47(1), pages 151-172, January.
    8. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2020. "Modeling technology diffusion: a study based on market coverage and advertising efforts," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 154-162, July.
    9. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    10. Benchekroun, Hassan & Martín-Herrán, Guiomar & Taboubi, Sihem, 2009. "Could myopic pricing be a strategic choice in marketing channels? A game theoretic analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1699-1718, September.
    11. Zhang, Jie & Chiang, Wei-yu Kevin, 2020. "Durable goods pricing with reference price effects," Omega, Elsevier, vol. 91(C).
    12. Peng Du & Qiushuang Chen, 2017. "Skimming or penetration: optimal pricing of new fashion products in the presence of strategic consumers," Annals of Operations Research, Springer, vol. 257(1), pages 275-295, October.
    13. Samuel Sale, R. & Mesak, Hani I. & Inman, R. Anthony, 2017. "A dynamic marketing-operations interface model of new product updates," European Journal of Operational Research, Elsevier, vol. 257(1), pages 233-242.
    14. Jiwen Ge & Dorothee Honhon & Jan C. Fransoo & Lei Zhao, 2021. "Supplying to Mom and Pop: Traditional Retail Channel Selection in Megacities," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 19-35, 1-2.
    15. Trichy V. Krishnan & Frank M. Bass & Dipak C. Jain, 1999. "Optimal Pricing Strategy for New Products," Management Science, INFORMS, vol. 45(12), pages 1650-1663, December.
    16. Adil Baykasoğlu & İlker Gölcük & Derya Eren Akyol, 2017. "A fuzzy multiple-attribute decision making model to evaluate new product pricing strategies," Annals of Operations Research, Springer, vol. 251(1), pages 205-242, April.
    17. Wei-yu Kevin Chiang, 2012. "Supply Chain Dynamics and Channel Efficiency in Durable Product Pricing and Distribution," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 327-343, April.
    18. Martín-Herrán, Guiomar & Taboubi, Sihem & Zaccour, Georges, 2012. "Dual role of price and myopia in a marketing channel," European Journal of Operational Research, Elsevier, vol. 219(2), pages 284-295.
    19. Koray Cosguner & P. B. (Seethu) Seetharaman, 2022. "Dynamic Pricing for New Products Using a Utility-Based Generalization of the Bass Diffusion Model," Management Science, INFORMS, vol. 68(3), pages 1904-1922, March.
    20. Collantes, Gustavo O, 2005. "Foreseeing the Market for Hydrogen Fuel-Cell Vehicles: Stakeholders' Perspectives and Models of New Technology Diffusion," Institute of Transportation Studies, Working Paper Series qt8918f70m, Institute of Transportation Studies, UC Davis.
    21. Shepherd, Simon & Bonsall, Peter & Harrison, Gillian, 2012. "Factors affecting future demand for electric vehicles: A model based study," Transport Policy, Elsevier, vol. 20(C), pages 62-74.
    22. Hernández-Mireles, C. & Fok, D. & Franses, Ph.H.B.F., 2008. "The Triggers, Timing and Speed of New Product Price Landings," ERIM Report Series Research in Management ERS-2008-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    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.
    24. Collantes, Gustavo, 2005. "Foreseeing The Market For Hydrogen Fuel-Cell Vehicles: Stakeholders’ Perspectives And Models Of New Technology Diffusion," Institute of Transportation Studies, Working Paper Series qt1dt4555z, Institute of Transportation Studies, UC Davis.

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