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How often should a firm modify its products? A Bayesian analysis of automobile modification cycles

Author

Listed:
  • Goksel Yalcinkaya

    (University of New Hampshire)

  • Tevfik Aktekin

    (University of New Hampshire)

  • Sengun Yeniyurt

    (Rutgers University)

  • Setiadi Umar

    (Rutgers University)

Abstract

In this paper, we develop and estimate a series of Bayesian generalized gamma family and mixture family models of product modification timing that take into account both firm- and industry-specific effects that are time varying. Our models are capable of capturing non-standard modification behavior such as multi-modality and non-monotonicity in the hazard rates motivated by real data. Additionally, we explore the existence of latent groups with respect to product modification timing strategies. The models are estimated using Markov chain Monte Carlo (MCMC) methods using a panel data from the automotive industry that covers 50 years and contains 6598 car model-year observations for 683 car models. The results reveal the non-monotonic modification behavior over time and the existence of three latent groups. Larger product portfolios and higher industry product proliferation lengthen the modification time. Brand and competitive modification dynamism increases the frequency of major modifications.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:mktlet:v:28:y:2017:i:1:d:10.1007_s11002-015-9384-8
    DOI: 10.1007/s11002-015-9384-8
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    References listed on IDEAS

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    1. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    2. John Liechty & Duncan Fong & Eelko Huizingh & Arnaud Bruyn, 2008. "Hierarchical Bayesian conjoint models incorporating measurement uncertainty," Marketing Letters, Springer, vol. 19(2), pages 141-155, June.
    3. Dadpay, Ali & Soofi, Ehsan S. & Soyer, Refik, 2007. "Information measures for generalized gamma family," Journal of Econometrics, Elsevier, vol. 138(2), pages 568-585, June.
    4. Barry L. Bayus & William P. Putsis, Jr., 1999. "Product Proliferation: An Empirical Analysis of Product Line Determinants and Market Outcomes," Marketing Science, INFORMS, vol. 18(2), pages 137-153.
    5. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    6. Yair Orbach & Gila Fruchter, 2014. "Predicting product life cycle patterns," Marketing Letters, Springer, vol. 25(1), pages 37-52, March.
    7. Lawrence Brown & Noah Gans & Avishai Mandelbaum & Anat Sakov & Haipeng Shen & Sergey Zeltyn & Linda Zhao, 2005. "Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 36-50, March.
    8. 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.
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    Cited by:

    1. Heinz Ahn & Marcel Clermont & Stephan Schwetschke, 2018. "Research on target costing: past, present and future," Management Review Quarterly, Springer, vol. 68(3), pages 321-354, August.
    2. Dadpay, Ali, 2018. "Using a generalized model for air traffic delay: An application of information based duration analysis," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 153-156.
    3. Yalcinkaya, Goksel & Aktekin, Tevfik & Yeniyurt, Sengun, 2020. "Out with the old: A Bayesian approach to estimating product modification rates," Journal of Business Research, Elsevier, vol. 118(C), pages 141-149.

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