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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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    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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