Exploring research trends and network characteristics in construction automation and robotics based on keyword network analysis
| Autor: | Taehoon Kim, Dongmin Lee, Hyunsu Lim, Ung-Kyun Lee, Hunhee Cho, Kyuman Cho |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Journal of Asian Architecture and Building Engineering, Vol 20, Iss 4, Pp 442-457 (2021) |
| Druh dokumentu: | article |
| ISSN: | 1347-2852 13467581 |
| DOI: | 10.1080/13467581.2020.1798774 |
| Popis: | Over the past decades, automation and robotics have been widely adopted in the construction industry as a promising solution for troubleshooting issues. This field is highly interdisciplinary and rapidly changing, and new concepts and ideas are being actively introduced in association with the existing ones. To reveal new insights, the evolution of knowledge in this field needs to be characterized by identifying important knowledge elements and research trends from published data. This study investigated research trends and network characteristics in the field of construction automation and robotics by using a keyword network analysis based on published articles. We analyzed the structure of the keyword network and identified major research topics and their relationships. Notable findings of the research characteristics are as follows. 1) Popular research themes with a set of closely connected keywords continue to be selected and contribute to the evolution of the network. 2) As an interdisciplinary research area, popular keywords that actively interact with other keywords also bridge different clusters of related research concepts. This study could provide useful insights and a better understanding of the knowledge structure and research trends as well as information on future directions in the construction automation and robotics field. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|