Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Applications of intelligent & fuzzy theory in engineering technologies and applied science
Guest editors: Stanley Lima and Álvaro Rocha
Article type: Research Article
Authors: Zhang, Zhena | Yu, Jintiana | Hu, Chunhuab; *
Affiliations: [a] School of Management, Wuhan University of Technology, Wuhan, China | [b] School of Management, Wuhan Donghu University, Wuhan, China
Correspondence: [*] Corresponding author. Chunhua Hu, School of Management, Wuhan Donghu University, Wuhan, China. E-mail: [email protected].
Abstract: Studies on path dependence (PD) and lock-in have indicated several limitations, such as chaotic literature information, interdisciplinarity complexity, and evolution vagueness. In this study, literature on path dependence and lock-in are obtained from the database of Web of Science Core Collection from 2001 to 2017. The knowledge mining model of the evolution of path dependence and lock-in is constructed based on knowledge mining process and content. The evolution of this area is also explored. Results show that the evolution of path dependence and lock-in can be categorized as follows: (1) English, American, and German scholars have led the research on path dependence and lock-in. (2) The research topics have undergone four stages. (3) The research levels have been classified as policy system (macro-level), regional economy (meso-level), and organizational path dependence (micro-level). (4) The research design can be represented as theory basis, case discussion, lock-in or reformation, and path creation. (5) The research method can be transformed from case study into lock-in mathematical modeling. A panoramic knowledge mapping of path dependence and lock-in is displayed by the research system to enhance understanding on research trajectories and future research directions.
Keywords: Path dependence, lock-in, knowledge mining, evolution, knowledge mapping
DOI: 10.3233/JIFS-169651
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2951-2963, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]