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Technology Adoption with Uncertain Future Costs and Quality

Author

Listed:
  • James E. Smith

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Canan Ulu

    (McCombs School of Business, The University of Texas at Austin, Austin, Texas 78712)

Abstract

In this paper we study the impact of uncertainty about future innovations in quality and costs on consumers' technology adoption decisions. We model the uncertainty in the technology's quality and costs as a Markov process and consider three models of the adoption decision. The first model assumes that consumers do a simple net present value (NPV) analysis that compares the NPV of adopting to that of not adopting, without considering the possibility of waiting. The second model is a stochastic dynamic program that considers the possibility of waiting and views the adoption decision as a one-time event, i.e., the consumer will only make a single purchase, the only question is when. The third model allows repeat purchases so the consumer may “upgrade” by purchasing new versions of the technology whenever it suits her.We study structural properties of these models, e.g., the following: What changes in qualities and costs will make the consumer better off? What changes will encourage adoption? We will see that the simple NPV and single-purchase model have many intuitive properties: with the right notion of improvements and reasonable assumptions about the technology changes, we find that improvements in the technology make the consumer better off and encourage adoption. Here improvements are defined using a partial order on quality and cost pairs. The results are more complicated in the repeat-purchase model. Under the same conditions on technology changes, technology improvements will make the consumer better off. However, except for special cases of transitions, these improvements may make the consumer better off and discourage adoption.

Suggested Citation

  • James E. Smith & Canan Ulu, 2012. "Technology Adoption with Uncertain Future Costs and Quality," Operations Research, INFORMS, vol. 60(2), pages 262-274, April.
  • Handle: RePEc:inm:oropre:v:60:y:2012:i:2:p:262-274
    DOI: 10.1287/opre.1110.1035
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    References listed on IDEAS

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    2. Brozynski, Max T. & Leibowicz, Benjamin D., 2022. "A multi-level optimization model of infrastructure-dependent technology adoption: Overcoming the chicken-and-egg problem," European Journal of Operational Research, Elsevier, vol. 300(2), pages 755-770.
    3. N. Bora Keskin & John R. Birge, 2019. "Dynamic Selling Mechanisms for Product Differentiation and Learning," Operations Research, INFORMS, vol. 67(4), pages 1069-1089, July.
    4. Hagspiel, V. & Huisman, Kuno & Kort, Peter M. & Nunes, Claudia & Pimentel, Rita, 2018. "Product Innovation of an Incumbent Firm : A Dynamic Analysis," Discussion Paper 2018-048, Tilburg University, Center for Economic Research.
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