dc.contributor.author |
Patel, Tirth |
|
dc.contributor.author |
Guo, Brian HW |
|
dc.contributor.author |
Zou, Yang |
|
dc.date.accessioned |
2022-06-14T04:54:28Z |
|
dc.date.available |
2022-06-14T04:54:28Z |
|
dc.date.issued |
2021-07-23 |
|
dc.identifier.citation |
(2021). Engineering, Construction and Architectural Management, ahead-of-print(ahead-of-print). |
|
dc.identifier.issn |
0969-9988 |
|
dc.identifier.uri |
https://hdl.handle.net/2292/59856 |
|
dc.description.abstract |
<jats:sec>
<jats:title content-type="abstract-subheading">Purpose</jats:title>
<jats:p>This article aims to explore valuable insights into the construction progress monitoring (CPM) research domain, which include main research topics, knowledge gaps and future research themes. For a long time, CPM has been significantly researched with increasing enthusiasm. Although a few review studies have been carried out, there is non-existence of a quantitative review study that can deliver a holistic picture of CPM.</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title>
<jats:p>The science mapping-based scientometric analysis was systematically processed with 1,835 CPM-related journal articles retrieved from Scopus. The co-authorship analysis and direct citation analysis were carried out to identify the most influential researchers, countries and publishers of the knowledge domain. The co-occurrence analysis of keyword was assessed to reveal the most dominating research topics and research trend with the visual representation of the considered research domain.</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Findings</jats:title>
<jats:p>This study reveals seven clusters of main research topics from the keyword co-occurrence analysis. The evolution of research confirms that CPM-related research studies were mainly focused on fundamental and traditional CPM research topics before 2007. The period between 2007 and 2020 has seen a shift of research efforts towards digitalization and automation. The result suggests Building Information Modelling (BIM) as the most common, growing and influential research topic in the CPM research domain. It has been used in combination with different data acquisition technologies (e.g. photogrammetry, videogrammetry, laser scanning, Internet of Things (IoT) sensors) and data analytics approaches (e.g. machine learning and computer vision).</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Practical implications</jats:title>
<jats:p>This study provides the horizon of potential research in the research domain of CPM to researchers, policymakers and practitioners by availing of main research themes, current knowledge gaps and future research directions.</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Originality/value</jats:title>
<jats:p>This paper represents the first scientometric study depicting the state-of-the-art of the research by assessing the current knowledge domain of CPM.</jats:p>
</jats:sec> |
|
dc.language |
en |
|
dc.publisher |
Emerald |
|
dc.relation.ispartofseries |
Engineering Construction & Architectural Management |
|
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
|
dc.subject |
Science & Technology |
|
dc.subject |
Social Sciences |
|
dc.subject |
Technology |
|
dc.subject |
Engineering, Industrial |
|
dc.subject |
Engineering, Civil |
|
dc.subject |
Management |
|
dc.subject |
Engineering |
|
dc.subject |
Business & Economics |
|
dc.subject |
Scheduling |
|
dc.subject |
Construction |
|
dc.subject |
Project management |
|
dc.subject |
Building information modelling |
|
dc.subject |
INFORMATION MODELING BIM |
|
dc.subject |
LABOR PRODUCTIVITY |
|
dc.subject |
SIMULATION |
|
dc.subject |
INFRASTRUCTURE |
|
dc.subject |
SYSTEM |
|
dc.subject |
VISION |
|
dc.subject |
VISUALIZATION |
|
dc.subject |
INDUSTRY |
|
dc.subject |
PROJECTS |
|
dc.subject |
0905 Civil Engineering |
|
dc.subject |
1202 Building |
|
dc.subject |
1503 Business and Management |
|
dc.title |
A scientometric review of construction progress monitoring studies |
|
dc.type |
Journal Article |
|
dc.identifier.doi |
10.1108/ecam-10-2020-0799 |
|
pubs.issue |
ahead-of-print |
|
pubs.volume |
ahead-of-print |
|
dc.date.updated |
2022-05-04T10:18:27Z |
|
dc.rights.holder |
Copyright: The author |
en |
pubs.author-url |
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000677688400001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e41486220adb198d0efde5a3b153e7d |
|
pubs.publication-status |
Published online |
|
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Review |
|
pubs.subtype |
Early Access |
|
pubs.subtype |
Journal |
|
pubs.elements-id |
861441 |
|
pubs.org-id |
Engineering |
|
pubs.org-id |
Civil and Environmental Eng |
|
dc.identifier.eissn |
1365-232X |
|
pubs.record-created-at-source-date |
2022-05-04 |
|
pubs.online-publication-date |
2021-07-23 |
|