Data-Driven Understanding of Smart Service Systems Through Text Mining

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Title
Data-Driven Understanding of Smart Service Systems Through Text Mining
Author
Lim, ChiehyeonMaglio, Paul P.
Issue Date
2018-06
Publisher
INFORMS
Citation
SERVICE SCIENCE, v.10, no.2, pp.154 - 180
Abstract
Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define “smart service system” based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems.
URI
https://scholarworks.unist.ac.kr/handle/201301/24238
URL
https://pubsonline.informs.org/doi/abs/10.1287/serv.2018.0208
DOI
10.1287/serv.2018.0208
ISSN
2164-3962
Appears in Collections:
SME_Journal Papers
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