IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v19y2017i1d10.1007_s10796-015-9597-7.html
   My bibliography  Save this article

A hybrid approach for personalized service staff recommendation

Author

Listed:
  • Wei-Lun Chang

    (Tamkang University)

  • Chien-Fang Jung

    (Tamkang University)

Abstract

In this study, we established a novel set of service procedures that epitomize the human-centered spirit of service. By using self-organizing maps and collaborative filtering recommendation, we developed a mechanism that links the two service procedures of selecting service staff members and how customers decide tip amounts based on perceived value. Through the proposed mechanism, the recommender system could effectively predict customer preferences regarding service staff members and assign suitable members for delivering services. In addition, this study integrated the service experiences of previous customers with local tipping cultures for calculating recommended tip amounts for the reference of customers. Under this mechanism, the customer-centered spirit can be completely integrated into service procedures for effectively enhancing customer satisfaction, increasing the job satisfaction of employees, and producing a virtuous cycle of service quality improvement.

Suggested Citation

  • Wei-Lun Chang & Chien-Fang Jung, 2017. "A hybrid approach for personalized service staff recommendation," Information Systems Frontiers, Springer, vol. 19(1), pages 149-163, February.
  • Handle: RePEc:spr:infosf:v:19:y:2017:i:1:d:10.1007_s10796-015-9597-7
    DOI: 10.1007/s10796-015-9597-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-015-9597-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10796-015-9597-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lawrence Bunnell & Kweku-Muata Osei-Bryson & Victoria Y. Yoon, 0. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers," Information Systems Frontiers, Springer, vol. 0, pages 1-42.
    2. Lawrence Bunnell & Kweku-Muata Osei-Bryson & Victoria Y. Yoon, 2020. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers," Information Systems Frontiers, Springer, vol. 22(6), pages 1377-1418, December.
    3. Meihua Zuo & Spyros Angelopoulos & Zhouyang Liang & Carol X. J. Ou, 2023. "Blazing the Trail: Considering Browsing Path Dependence in Online Service Response Strategy," Information Systems Frontiers, Springer, vol. 25(4), pages 1605-1619, August.
    4. Shivam Gupta & Sachin Modgil & Choong-Ki Lee & Uthayasankar Sivarajah, 2023. "The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry," Information Systems Frontiers, Springer, vol. 25(3), pages 1179-1195, June.
    5. Bernd Heinrich & Marcus Hopf & Daniel Lohninger & Alexander Schiller & Michael Szubartowicz, 2022. "Something’s Missing? A Procedure for Extending Item Content Data Sets in the Context of Recommender Systems," Information Systems Frontiers, Springer, vol. 24(1), pages 267-286, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:19:y:2017:i:1:d:10.1007_s10796-015-9597-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.