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Using information-seeking argument mining to improve service

  • If service providers can identify reasons users are in favor of or against a service, they have insightful information that can help them understand user behavior and what they need to do to change such behavior. This article argues that the novel text-mining technique referred to as information-seeking argument mining (IS-AM) can identify these reasons. The empirical study applies IS-AM to news articles and reviews about electric scooter-sharing systems (i.e., a service enabling the short-term rentals of electric motorized scooters). Its results point to IS-AM as a promising technique to improve service; the data enable the authors to identify 40 reasons to use or not use electric scooter-sharing systems, as well as their importance to users. Furthermore, the results show that news articles are better data sources than reviews because they are longer and contain more arguments and, thus, reasons.

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Metadaten
Author:Bernd SkieraORCiDGND, Shunyao YanORCiDGND, Johannes DaxenbergerORCiDGND, Marcus DomboisORCiDGND, Iryna GurevychORCiDGND
URN:urn:nbn:de:hebis:30:3-862801
DOI:https://doi.org/10.1177/10946705221110845
ISSN:1552-7379
Parent Title (English):Journal of service research
Publisher:Sage Periodicals Press
Place of publication:London
Document Type:Article
Language:English
Date of Publication (online):2022/06/29
Date of first Publication:2022/06/29
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2024/07/21
Tag:argument mining; service design; service improvement; service innovation; textual analysis
Volume:25.2022
Issue:4
Page Number:12
First Page:537
Last Page:548
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Angeschlossene und kooperierende Institutionen / E-Finance Lab e.V.
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International