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The optimal pace of product updates

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  • Druehl, Cheryl T.
  • Schmidt, Glen M.
  • Souza, Gilvan C.

Abstract

Some firms (e.g. Intel and Medtronics) use a time-pacing strategy for product development (PD), introducing new generations at regular intervals. If the firm adopts a fast pace (introducing frequently), it prematurely cannibalizes its old generation, incurring high development costs, while if it has a slow pace, it fails to capitalize on customer willingness-to-pay for improved technology. We develop a model to gain insight into which factors drive the pace. We consider PD cost, the diffusion rate (coefficients of innovation and imitation), the rate of margin decline, and the degree to which a new generation stimulates market growth. We find that a faster pace is generally associated with faster diffusion, a higher market growth rate and faster margin decay. Not so intuitively, we find that relatively minor differences in the development cost function can significantly impact the pace.

Suggested Citation

  • Druehl, Cheryl T. & Schmidt, Glen M. & Souza, Gilvan C., 2009. "The optimal pace of product updates," European Journal of Operational Research, Elsevier, vol. 192(2), pages 621-633, January.
  • Handle: RePEc:eee:ejores:v:192:y:2009:i:2:p:621-633
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Chen, Yuwen & Carrillo, Janice E., 2011. "Single firm product diffusion model for single-function and fusion products," European Journal of Operational Research, Elsevier, vol. 214(2), pages 232-245, October.
    2. repec:cuf:journl:y:2017:v:18:i:1:duan:shi:sun is not listed on IDEAS
    3. repec:eee:ijrema:v:33:y:2016:i:4:p:780-796 is not listed on IDEAS
    4. Liberali, Guilherme & Gruca, Thomas S. & Nique, Walter M., 2011. "The effects of sensitization and habituation in durable goods markets," European Journal of Operational Research, Elsevier, vol. 212(2), pages 398-410, July.
    5. Ozer, Muammer, 2011. "Understanding the impacts of product knowledge and product type on the accuracy of intentions-based new product predictions," European Journal of Operational Research, Elsevier, vol. 211(2), pages 359-369, June.
    6. 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.
    7. Gyesik Oh & Yoo S. Hong, 0. "The impact of platform update interval on platform diffusion in a cooperative mobile ecosystem," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-10.
    8. Yan, Hong-Sen & Ma, Kai-Ping, 2011. "Competitive diffusion process of repurchased products in knowledgeable manufacturing," European Journal of Operational Research, Elsevier, vol. 208(3), pages 243-252, February.
    9. repec:eee:ejores:v:265:y:2018:i:3:p:1102-1114 is not listed on IDEAS
    10. Goksel Yalcinkaya & Tevfik Aktekin & Sengun Yeniyurt & Setiadi Umar, 2017. "How often should a firm modify its products? A Bayesian analysis of automobile modification cycles," Marketing Letters, Springer, vol. 28(1), pages 85-97, March.
    11. Avagyan, Vardan & Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M., 2016. "Riding successive product diffusion waves. Building a tsunami via upgrade-rebate programs," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 780-796.
    12. 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.
    13. repec:spr:joinma:v:29:y:2018:i:3:d:10.1007_s10845-015-1138-1 is not listed on IDEAS

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