期刊
SERVICE SCIENCE
卷 10, 期 2, 页码 154-180出版社
INFORMS
DOI: 10.1287/serv.2018.0208
关键词
smart service; smart system; smart service system; text mining; data-driven understanding
资金
- National Research Foundation of Korea [NRF-2017R1C1B1006614]
- Human Resources Program in Energy Technology of the Korea Institute of Energy Technology Evaluation and Planning from the Ministry of Trade, Industry and Energy, Republic of Korea [20164010201030]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据