Service interaction flow analysis technique for service personalization

Korhonen, Olli; Syrjänen, Anna-Liisa; Kinnula, Marianne; Isomursu, Minna; Kuutti, Kari (2017-07-23)
 
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https://doi.org/10.1007/978-3-319-64695-4_7

Korhonen, Olli
Syrjänen, Anna-Liisa
Kinnula, Marianne
Isomursu, Minna
Kuutti, Kari
Springer Nature
23.07.2017

Korhonen O., Syrjänen AL., Kinnula M., Isomursu M., Kuutti K. (2017) Service Interaction Flow Analysis Technique for Service Personalization. In: Stigberg S., Karlsen J., Holone H., Linnes C. (eds) Nordic Contributions in IS Research. SCIS 2017. Lecture Notes in Business Information Processing, vol 294. Springer, Cham

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© Springer International Publishing AG 2017. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Business Information Processing. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-64695-4_7.
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doi:https://doi.org/10.1007/978-3-319-64695-4_7
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https://urn.fi/URN:NBN:fi-fe201802093296
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Abstract

Service interaction flows are difficult to capture, analyze, outline, and represent for research and design purposes. We examine how variation of personalized service flows in technology-mediated service interaction can be modeled and analyzed to provide information on how service personalization could support interaction. We have analyzed service interaction cases in a context of technology-mediated car rental service. With the analysis technique we propose, inspired by Interaction Analysis method, we were able to capture and model the situational service interaction. Our contribution regarding technology-mediated service interaction design is twofold: First, with the increased understanding on the role of personalization in managing variation in technology-mediated service interaction, our study contributes to designing service management information systems and human-computer interfaces that support personalized service interaction flows. Second, we provide a new analysis technique for situated interaction analysis, particularly when the aim is to understand personalization in service interaction flows.

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