Decision Modeling in Service Science

  • Ralph D. BadinelliEmail author
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)


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.


  1. 1.
    Vargo S, Lusch R. Evolving to a new dominant logic for marketing. J Mark. 2004;68:1–17.CrossRefGoogle Scholar
  2. 2.
    Vargo S, Akaka M. Service-dominant logic as a foundation for service science: clarifications. Serv Sci. 2009;1(1):32–41.CrossRefGoogle Scholar
  3. 3.
    Sampson SE, Froehle CM. Foundations and implications of a proposed unified services theory. Prod Oper Manage. 2006;15(2):329–43.CrossRefGoogle Scholar
  4. 4.
    Alter S. Making a science of service systems practical: seeking usefulness and understandability while avoiding unnecessary assumptions and restrictions. In: Demirkan H, Spohrer JC, Krishna V, editors. The Science of service systems. New York: Springer; 2011. P. 61–72.CrossRefGoogle Scholar
  5. 5.
    Ferrario R, Guarino N, Janiesch C, Kiemes T, Oberle D, Probst F. Towards an ontological foundation of service science: the general service model. In: 10th international conference on Wirtschaftsinformatik. Zurich, Switzerland.Google Scholar
  6. 6.
    Maglio PP, Spohrer J. Fundamentals of service science. J Acad Mark Sci. 2008;36(1):18–20.CrossRefGoogle Scholar
  7. 7.
    OMG (Object Management Group). Value delivery modeling language. Accessed 15 June 2018.
  8. 8.
    Qiu R. Service science: the foundations of service engineering and management. New York: Wiley; 2014.Google Scholar
  9. 9.
    Badinelli R. Modeling service systems. Business Expert Press; 2015.Google Scholar
  10. 10.
    Chan W, Hsu C. Service scaling on hyper-networks. Serv Science. 2009;1(1):17–21.CrossRefGoogle Scholar
  11. 11.
    Lessard L. Modeling value cocreation processes and outcomes in knowledge-intensive business service engagements. Serv Sci. 2015;7(3):181–95.CrossRefGoogle Scholar
  12. 12.
    Barile S. Management sistemico vitale. Torino: G. Giappichelli; 2009.Google Scholar
  13. 13.
    Ng I, Badinelli R, Dinauta P, Halliday S, Lobler H, Polese F. S-D logic: research directions and opportunities: the perspective of systems, complexity and engineering. Mark Theor. 2012;12(2):213–7.CrossRefGoogle Scholar
  14. 14.
    Badinelli RD. A stochastic model of resource allocation for service systems. Serv Sci. 2010;2(1):68–83.Google Scholar
  15. 15.
    Badinelli R. Fuzzy modeling of service system engagements. Serv Sci. 2012;4(2):135–46.CrossRefGoogle Scholar
  16. 16.
    Qiu RG. Computational thinking of service systems: dynamics and adaptiveness modeling. Serv Sci. 2009;1(1):42–55.CrossRefGoogle Scholar
  17. 17.
    Qiu R. We must re-think service encounters. Serv Sci. 2013;5(1):1–3.CrossRefGoogle Scholar
  18. 18.
    Paulussen TO, Zöller A, Heinzl A, Braubach L, Pokahr A, Lamersdorf W. Agent-based patient scheduling in hospitals. In: Kirn S, Herzog O, Lockemann PC, Spaniol, O editors. Multiagent Engineering Theory and Applications in Enterprises. Heidelberg, Germany: Springer; 2006. PP. 255–276.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Business Information Technology DepartmentVirginia TechBlacksburgUSA

Personalised recommendations