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Decision Modeling in Service Science

In: Advances in Service Science

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  • Ralph D. Badinelli

    (Virginia Tech)

Abstract

The purpose of this paper is to highlight the need for innovative decision modeling in the field of service science. Each step of the service journey through a service ecosystem is initiated by a decision to integrate resources among actors and engage in a service activity. Consequently, engagement decisions are the driving force of any service journey and decision models are the foundation of service-system models. Each engagement decision must be modeled and executed as joint, adaptive, stochastic and perhaps fuzzy decisions among all actors who are involved in the associated service activity. However, such models are sparse in the research literature, and the current emphasis on predictive analytics and data science seems to distract attention from their development. Three examples of service systems are provided in this paper to illustrate this conclusion.

Suggested Citation

  • Ralph D. Badinelli, 2019. "Decision Modeling in Service Science," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu (ed.), Advances in Service Science, pages 181-191, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-04726-9_18
    DOI: 10.1007/978-3-030-04726-9_18
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