The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Construction automation: Research areas, industry concerns and suggestions for advancement
Abstract
Abstract Construction automation has shown the potential to increase construction productivity after years of technical development and experimenting in its field. Exactly how, and the possible benefits and challenges of construction automation, though is unclear and missing from current research efforts. In order to better understand the comprehensive potential of construction automation for increasing construction productivity and the associated possible ramifications, an objective and data-driven review of the use of automation technologies in construction was done. The review was accomplished by using text mining methods on publically available written documents, covering a wide range of relevant data including scientific publications and social media. The text mining software VOS Viewer and RapidMiner Studio were used to determine the most promising areas of research through the analysis of scientific publications, and the main areas of concern of industry through the analysis of text on social media, respectively. These research areas and concerns are summarized in this paper, and based on them suggestions for industry are made to help advance the uptake of automation in construction.
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Cites
AIMQ: a methodology for information quality assessment
Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002) · Information & Management · doi:10.1016/s0378-7206(02)00043-5 · Cited by 1,611
Cited by
Flexible and transportable robotic timber construction platform – TIM
Wagner, H. J., Alvarez, M., Kyjanek, O., Bhiri, Z., Buck, M., & Menges, A. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103400 · Cited by 127
Metadata
- Authors
- Chen, Q., García de Soto, B., & Adey, B. T.
- Venue
- Automation in Construction
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 94
- Pages
- 22-38
- ISSN
- 0926-5805 (ISSN-L)
- OpenAlex
- W2807113035
- Cited by
- 250
- References
- 1
- FWCI
- 14.08
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, Q., García de Soto, B., & Adey, B. T. (2018). Construction automation: Research areas, industry concerns and suggestions for advancement. Automation in Construction. https://doi.org/10.1016/j.autcon.2018.05.028
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
