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Managing a product family under stochastic technological changes

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  • Liu, Heng
  • Özer, Özalp

Abstract

This paper characterize a decision framework by which a firm can manage generational product replacements under stochastic technological changes. First, we characterize an optimal threshold-based product replacement policy that maximizes the firm's expected total profit for a finite planning horizon. With this policy, the firm should optimally replace its current product when the performance gap of the product is above a threshold. Upon each product replacement, we also show that the firm should adopt the latest technology for the new product. Second, using stochastic ordering concepts, we quantify the negative impact from the accelerated technological changes on the expected total profit. Finally, we provide an analytical example based on a consumer choice model and characterize a technology follower's joint product replacement and pricing decisions upon the arrival of each innovation from a technology leader.

Suggested Citation

  • Liu, Heng & Özer, Özalp, 2009. "Managing a product family under stochastic technological changes," International Journal of Production Economics, Elsevier, vol. 122(2), pages 567-580, December.
  • Handle: RePEc:eee:proeco:v:122:y:2009:i:2:p:567-580
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    References listed on IDEAS

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    Cited by:

    1. Nur Sunar & John R. Birge & Sinit Vitavasiri, 2019. "Optimal Dynamic Product Development and Launch for a Network of Customers," Operations Research, INFORMS, vol. 67(3), pages 770-790, May.
    2. Biswas, Sumana & Ali, Ismail & Chakrabortty, Ripon K. & Turan, Hasan Hüseyin & Elsawah, Sondoss & Ryan, Michael J., 2022. "Dynamic modeling for product family evolution combined with artificial neural network based forecasting model: A study of iPhone evolution," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    3. Liao, Shuangqing & Seifert, Ralf W., 2015. "On the optimal frequency of multiple generation product introductions," European Journal of Operational Research, Elsevier, vol. 245(3), pages 805-814.

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