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International Conference on Exploring Services Science

IESS 2016: Exploring Services Science pp 45–59Cite as

New Service’s Expectation Positioning by Applying Cumulative Prospect Theory

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 247))

Abstract

In the context of service innovation, the question of when to assess a new service by customer and how to achieve personalized assessment are yet to be explored. This is especially true under the situations of uncertainty when it comes to bringing the effectiveness of new service’s promotion and decision making, i.e., for service provider to attain service competitiveness and for potential service customer to decide whether to try the new service. Accordingly, an appropriate expectation positioning method proposed in this study aims to collect and analyze psychological information from potential service customer in order to make service promotion decisions capable of achieving service provider’s purpose as well as satisfying service customer, utilizing Cumulative Prospect Theory.

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Author information

Authors and Affiliations

  1. Service Science Research Center, National Chengchi University, Taipei, Taiwan

    Soe-Tsyr Daphne Yuan & Hsi-Yun Wang

Authors
  1. Soe-Tsyr Daphne Yuan
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  2. Hsi-Yun Wang
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Corresponding author

Correspondence to Soe-Tsyr Daphne Yuan .

Editor information

Editors and Affiliations

  1. Faculty of Automatic Control & Computers, University Politehnica of Bucharest, Bucharest, Romania

    Theodor Borangiu

  2. Faculty of Automatic Control & Computers, University Politehnica of Bucharest, Bucharest, Romania

    Monica Dragoicea

  3. Faculty of Engineering - FEUP, University of Porto, Porto, Portugal

    Henriqueta Nóvoa

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© 2016 Springer International Publishing Switzerland

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Yuan, ST.D., Wang, HY. (2016). New Service’s Expectation Positioning by Applying Cumulative Prospect Theory. In: Borangiu, T., Dragoicea, M., Nóvoa, H. (eds) Exploring Services Science. IESS 2016. Lecture Notes in Business Information Processing, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-32689-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-32689-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32688-7

  • Online ISBN: 978-3-319-32689-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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