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Decision Modeling in Service Science

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Advances in Service Science (INFORMS-CSS 2018)

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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.

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Author information

Authors and Affiliations

  1. Business Information Technology Department, Virginia Tech, Blacksburg, VA, 24061, USA

    Ralph D. Badinelli

Authors
  1. Ralph D. Badinelli
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Correspondence to Ralph D. Badinelli .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Pennsylvania State University, University Park, PA, USA

    Hui Yang

  2. Division of Engineering and Information Science, Pennsylvania State University, Malvern, PA, USA

    Robin Qiu

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Badinelli, R.D. (2019). Decision Modeling in Service Science. In: Yang, H., Qiu, R. (eds) Advances in Service Science. INFORMS-CSS 2018. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-04726-9_18

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