TY  - JOUR
A1  - Skiera, Bernd
A1  - Yan, Shunyao
A1  - Daxenberger, Johannes
A1  - Dombois, Marcus
A1  - Gurevych, Iryna
T1  - Using information-seeking argument mining to improve service
T2  - Journal of service research
N2  - 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.
KW  - service improvement
KW  - textual analysis
KW  - argument mining
KW  - service design
KW  - service innovation
Y1  - 2022
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/86280
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-862801
SN  - 1552-7379
VL  - 25
IS  - 4
SP  - 537
EP  - 548
PB  - Sage Periodicals Press
CY  - London
ER  -