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Stochastic service life cycle analysis using customer reviews

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  • Juram Kim
  • Changyong Lee

Abstract

This study proposes a stochastic service life cycle analysis to gauge where a service is in its life cycle and to give forecasts about its future prospects. We employ customer review data to measure customer-oriented service maturity and use a hidden Markov model to estimate the probability of a service being at a certain stage of its life cycle. Based on this, we also develop three indicators to represent the future prospects of a service’s life cycle progression. The main advantages of the proposed approach lie in its ability to model different shapes of life cycles without any supplementary information and to examine a wide range of services at acceptable levels of time and cost. We believe our method will assist firms in building stage-customised post-launch service strategies. A case study of mobile game services in the Apple App Store is presented.

Suggested Citation

  • Juram Kim & Changyong Lee, 2017. "Stochastic service life cycle analysis using customer reviews," The Service Industries Journal, Taylor & Francis Journals, vol. 37(5-6), pages 296-316, April.
    • Handle: RePEc:taf:servic:v:37:y:2017:i:5-6:p:296-316
    DOI: 10.1080/02642069.2017.1316379
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    References listed on IDEAS

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    Cited by:

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