Service Research

Part of the Service Science: Research and Innovations in the Service Economy book series (SSRI)


This chapter provides an outlook on two recent research streams from the field of services: service network analysis and service level engineering. Service network research seeks to understand what factors explain the topology and dynamic nature of service networks. Service level engineering proposes to improve service level management by considering customers’ business objectives rather than to focus on the IT infrastructure that provides the service. These streams look beyond the boundaries of services and focus on systems of services represented as networks and bring customers to take part of service systems.


Service Quality Cloud Service Service Level Service Network Service Level Agreement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Spohrer J, Maglio PP (2010) Service science: toward a smarter planet. In: Introduction to service engineering. Wiley, New York, pp 1–30. ISBN: 9780470569627. doi: 10.1002/9780470569627.ch1 Google Scholar
  2. 2.
    Unterharnscheidt P, Kieninger A (2010) Service level management – challenges and their relevance from the customers’ point of view. In: 16th Americas conference on information systems (AMCIS)Google Scholar
  3. 3.
    Taylor R, Tofts C (2005) Death by a thousand SLAs: a short study of commercial suicide pacts. Technical report. Hewlett-Packard LabsGoogle Scholar
  4. 4.
    Vargo S, Lusch R (2004) The four service marketing myths: remnants of a goods-based, manufacturing model. J Serv Res 6(4):324–335CrossRefGoogle Scholar
  5. 5.
    Teeri T, Hirst L (2009) Making service science mainstream white paper. Technical report. Aalto University and IBMGoogle Scholar
  6. 6.
    Spohrer J et al (2007) Steps toward a science of service systems. Computer 40(1):71–77CrossRefGoogle Scholar
  7. 7.
    Börner K, Sanyal S, Vespignani A (2007) Network science. Annu Rev Inf Sci Technol 41(1):537–607CrossRefGoogle Scholar
  8. 8.
    Bizer C, Heath T, Berners-Lee T (2009) Linked data - the story so far. Int J Semantic Web Inf Syst 5(3):1–22CrossRefGoogle Scholar
  9. 9.
    Schweitzer F et al (2009) Economic networks: the new challenges. Science 325(5939):422–425 doi: 10.1126/science.1173644.
  10. 10.
    Easley D, Kleinberg J (2010) Networks, crowds, and markets: reasoning about a highly connected world. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  11. 11.
    Cardoso J (2013) Modeling service relationships for service networks. In: 4th international conference on exploring service science (IESS 1.3). Lecture notes in business information processing. Springer, Heidelberg, pp 114–128Google Scholar
  12. 12.
    Armbrust M et al (2010) A view of cloud computing. Commun ACM 53(4):50–58CrossRefGoogle Scholar
  13. 13.
    Cardoso J et al (2012) Open semantic service networks. In: The international symposium on services science (ISSS 2012), Leipzig, 2012, pp 1–15Google Scholar
  14. 14.
    Cardoso J, Pedrinaci C, De Leenheer P (2013) Open semantic service networks: modeling and analysis. In: 4th international conference on exploring service science (IESS 1.3). Lecture notes in business information processing, vol 143. Springer, Heidelberg, pp 141–154Google Scholar
  15. 15.
    Cardoso J et al (2013) Foundations of open semantic service setworks. Int J Serv Sci Manag Eng Technol 4(2):1–16CrossRefGoogle Scholar
  16. 16.
    De Leenheer P, Cardoso J, Pedrinaci C (2013) Ontological representation and governance of business semantics in compliant service networks. In: 4th international conference on exploring service science (IESS 1.3). Lecture notes in business information processing, vol 143. Springer, Heidelberg, pp 155–169Google Scholar
  17. 17.
    J. Cardoso (2013) Open service networks: research directions. In: 6th international C* conference on computer science & software engineering. ACM, New York, pp 2–3Google Scholar
  18. 18.
    Mislove A et al (2007) Measurement and analysis of online social networks. In: 7th ACM SIGCOMM conference on internet measurement. ACM, New York, pp 29–42CrossRefGoogle Scholar
  19. 19.
    Leskovec J et al (2008) Microscopic evolution of social networks. In: 14th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, New York, pp 462–470CrossRefGoogle Scholar
  20. 20.
    Gordijn J, Yu E, van der Raadt B (2006) e-service design using i* and e3value modeling. IEEE Softw 23:26–33CrossRefGoogle Scholar
  21. 21.
    Akkermans H et al (2004) Value webs: using ontologies to bundle real-world services. IEEE Intell Syst 19(4):57–66CrossRefGoogle Scholar
  22. 22.
    Allee V (2000) Reconfiguring the value network. J Bus Strategy 21(4):36–39CrossRefGoogle Scholar
  23. 23.
    Weill P, Vitale M (2001) Place to space: migrating to eBusiness models. Harvard Business School Press, BostonGoogle Scholar
  24. 24.
    Bitsaki M et al (2008) An architecture for managing the lifecycle of business goals for partners in a service network. In: Mähönen P, Pohl, K, Priol, T (eds) Towards a service-based internet. Lecture notes in computer science, vol 5377. Springer, Berlin/Heidelberg, pp 196–207. ISBN: 978-3-540-89896-2CrossRefGoogle Scholar
  25. 25.
    Applegate L (2001) Emerging e-business models: lessons from de field. Harv Bus Rev 9:801Google Scholar
  26. 26.
    Parolini C (1999) The value net: a tool for competitive strategy. Wiley, HeidelbergGoogle Scholar
  27. 27.
    Osterwalder A, Pigneur Y (2010) Business model generation. Wiley, New York, p 281Google Scholar
  28. 28.
    Linden G, Kraemer KL, Dedrick J (2009) Who captures value in a global innovation network?: the case of Apple’s iPod. Commun ACM 52(3):140–144CrossRefGoogle Scholar
  29. 29.
    Barboza D (2010) Supply chain for iPhone highlights costs in China, New York Times, 5 July, 2010.Google Scholar
  30. 30.
    Guide D, Van Wassenhove L (2009) The evolution of closed-loop supply chain research. Oper Res 57:10–18CrossRefzbMATHGoogle Scholar
  31. 31.
    Kapuscinski R et al (2004) Inventory decisions in Dell’s supply chain. Interfaces 34(3):191–205CrossRefGoogle Scholar
  32. 32.
    Chesbrough H, Spohrer J (2006) A research manifesto for services science. Commun ACM 49:35–40CrossRefGoogle Scholar
  33. 33.
    Wang XF, Chen G (2003) Complex networks: small-world, scale-free and beyond. IEEE Circuits Syst Mag 3(1):6–20CrossRefGoogle Scholar
  34. 34.
    Yule U (1925) A mathematical theory of evolution based on the conclusions of Dr. J. C. Willis. Philos Trans R Soc Lond 213(2):21–87CrossRefGoogle Scholar
  35. 35.
    Cardoso J et al (2010) Towards a unified service description language for the internet of services: requirements and first developments. In: IEEE international conference on services computing (SCC), Florida, 2010, pp 602–609Google Scholar
  36. 36.
    Cardoso J et al (2013) Cloud computing automation: integrating USDL and TOSCA. In: 25th conference on advanced information systems engineering (CAiSE). Lecture notes in computer science, vol 7908. Springer, Heidelberg, pp 1–16Google Scholar
  37. 37.
    Mendes PN et al (2011) Dbpedia spotlight: shedding light on the web of documents. In: 7th international conference on semantic systems (I-Semantics)Google Scholar
  38. 38.
    AlchemyAPI (2013). Accessed 29 July 2013
  39. 39.
    Frei F (2008) The four things a service business must get right. Harv Bus Rev 86(4):70–80, 136Google Scholar
  40. 40.
    Kleinberg J et al (2008) Strategic network formation with structural holes. In: 9th ACM conference on electronic commerce. ACM, New York, pp 284–293Google Scholar
  41. 41.
    Harland C (1996) Supply chain management: relationships, chains and networks. Br J Manag 7(s1):S63–S80CrossRefGoogle Scholar
  42. 42.
    Krötzsch M et al (2011) A better uncle for OWL: nominal schemas for integrating rules and ontologies. In: 20th international conference on world wide web. ACM, New York, pp 645–654CrossRefGoogle Scholar
  43. 43.
    Ilzkovitz F, Dierx A, Sousa N (2008) An analysis of the possible causes of product market malfunctioning in the EU: first results for manufacturing and service sectors. Technical report, Directorate General Economic and Monetary Affairs (DG ECFIN), European CommissionGoogle Scholar
  44. 44.
    Marquis H (2006) In: itSM Solutions DITY Newsletter, vol 2. Dec 2006
  45. 45.
    Skariachan D (2013). Published by Reuters on August 19th, 2013. Accessed 19 Sep 2013
  46. 46.
    O’Sullivan M (2011). Published by TheAge on April 5th, 2013. Accessed 9 Sep 2013
  47. 47.
    Sauvé JP et al (2005) SLA design from a business perspective. In: 16th IFIP/IEEE international workshop on distributed systems: operations and management (DSOM), pp 72–83Google Scholar
  48. 48.
    Kieninger A, Westernhagen J, Satzger G (2011) The economics of service level engineering. In: 44th annual Hawaii international conference on system sciences (HICSS). IEEE Computer Society, KauaiGoogle Scholar
  49. 49.
    Ludwig A, Kowalkiewicz M (2009) Supporting service level agreement creation with past service behavior data. In: Business information systems workshops. Springer, Heidelberg, pp 375–385CrossRefGoogle Scholar
  50. 50.
    Sauvé J et al (2006) Optimal design of e-commerce site infrastructure from a business perspective. In: 39th annual Hawaii international conference on system sciences (HICSS), vol 8. IEEE, Kauia, p 178Google Scholar
  51. 51.
    Marques FT, Sauvé JP, Moura JAB (2007) Service level agreement design and service provisioning for outsourced services. In: Network operations and management symposium, 2007. IEEE, Rio de Janeiro, pp 106–113CrossRefGoogle Scholar
  52. 52.
    Marques F, Sauvé J, Moura A (2009) SLA design and service provisioning for outsourced services. J Netw Syst Manag 17(1):73–90CrossRefGoogle Scholar
  53. 53.
    Kieninger A et al (2013) Leveraging service incident analytics to determine cost-optimal service offers. In: 11th international conference on Wirtschaftsinformatik, vol 2, pp 1015–1029Google Scholar
  54. 54.
    Kieninger A et al (2013) Simulation-based quantification of business impacts caused by service incidents. In: 3rd international conference on exploring service science. Lecture notes in business information processing, vol 143. Springer, Heidelberg, pp 170–185Google Scholar
  55. 55.
    Schmitz B et al (2014) Towards the consideration of performance risks for the design of service offers. In: 4th international conference on exploring services science. Lecture notes in business information processing, vol 169. Springer, Heidelberg, pp 108–123Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Informatics EngineeringUniversidade de CoimbraCoimbraPortugal
  2. 2.Huawei European Research Center (ERC)MunichGermany
  3. 3.Karlsruhe Service Research Institute (KSRI)Karlsruhe Institute of Technology (KIT)KarlsruheGermany

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