 Stochastic service life cycle analysis using customer reviewsJuram Kim and Changyong Lee The Service Industries Journal, 2017, vol. 37, issue 5-6, 296-316 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. Date: 2017 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:servic:v:37:y:2017:i:5-6:p:296-316 Ordering information: This journal article can be ordered from DOI: 10.1080/02642069.2017.1316379 Access Statistics for this article The Service Industries Journal is currently edited by Eileen Bridges, Professor Domingo Ribeiro, Ronald Goldsmith, Barry Howcroft and Youjae Yi More articles in The Service Industries Journal from Taylor & Francis Journals |
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