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A diffusion model for service products

Research output: Contribution to journalArticlepeer-review

  • Xiaohui Shi
  • Pattarin Chumnumpan
  • Kiran Fernandes
Purpose – This paper aims to develop a diffusion model that can be used to understand and forecast the market growth of service products in a competitive environment. Despite the fast growth of the service sector, the existing literature has dedicated little effort to modeling the market growth of service products.

Design/methodology/approach – The authors propose a choice-type diffusion model that links the issues of service product utility, customers’ choice preference, customer switching behavior and the market growth of service products. The authors use the market data of one online product and assess the performance of the proposed model using this case.

Findings – The results demonstrate the model’s good fitting and forecasting performance. Specifically, the proposed model has better performance than the benchmarks the authors choose from the existing literature.

Originality/value – This study shows that market growth of service products can have different diffusion patterns with that of durable goods, which is evidence of the needs for specific models for service diffusion. Further, this study demonstrates the important role of customer switching in service diffusion. Also for marketing practitioners, this study provides an explanation and forecasting tool for the market growth of service products, which can be used for marketing planning in the service industry.
Original languageEnglish
Pages (from-to)331-341
JournalJournal of Services Marketing
Issue number4
Publication statusPublished - 2014


  • SHI_2014_cright_JSM_A diffusion model for service products

    Rights statement: This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.

    Accepted author manuscript (Post-print), 969 KB, PDF document

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