Scientometric Analysis of Climate Change and Construction Cost Research: Trends, Gaps, and Future Directions
Description
The intersection of climate change and construction cost management is one of the most important emerging research areas in the built environment, yet the first mapping of this field's intellectual structure, geography and evolution has not yet been conducted. This is a scientometric study which used a dataset of 177 papers on Scopus between 1997 and 2026. A targeted keyword search - TITLE-ABS-KEY ("Climate Change" AND "Construction Cost") was conducted on Scopus of initial search of 252 documents and limited to engineering, environmental and earth sciences as subject areas (195 documents), with English language peer-reviewed articles, conference papers and book chapters (177 documents). The 177 documents were subject to descriptive bibliometric analysis, trend analysis, keyword burst analysis (Kleinberg algorithm with silhouette scoring), cluster analysis, and geographic mapping using VOSviewer and Bibliometrix R. Output increased by over 400% between before 2010 and 2023-2026 (76 papers in the past four years). 50.2% of publications are from the United States, China and the United Kingdom; less than 3% from Sub-Saharan Africa, despite its extreme vulnerability to climate change and rapid development in the construction sector. Five key research clusters were discovered: cost analysis and adaptation finance; life cycle assessment and embodied carbon; energy transition and carbon costs; climate adaptation infrastructure; and digital optimisation and decision support tools. A keyword burst analysis reveals climate change adaptation (burst strength = 3.250, silhouette = 1.000, 2025-2026), uncertainty quantification (2.203, silhouette = 1.000, 2023-2025) and cost analysis (2.157, silhouette = 0.981, 2024-2025) as the most current and sharply focused research fronts. The study focuses on Scopus-indexed literature, potentially overlooking national journals, grey literature and practitioner reports. The analysis may overlook interdisciplinary work from economics and social sciences as the field is restricted to three Scopus subject areas. The study offers a structured evidence platform for researchers, policymakers and multilateral funding agencies to assess and prioritise funding for climate-resilient construction cost research, especially in developing countries where empirical evidence is lacking and the challenges greatest. This is a scientometric study of the global knowledge structure of climate change and construction cost research as a field of study. Seven key research gaps (geographic, methodological, sectoral, temporal, digital, socioeconomic, and governance) are identified and a structured research agenda for the future.
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The Scopus database was selected as the primary data source, consistent with its established reliability and broader coverage of engineering and environmental science publications (Olawumi and Chan, 2018; Hosseini et al., 2018). The search was executed on 16 April 2026 using the following Boolean query applied across title, abstract, and keyword fields: TITLE-ABS-KEY ("Climate Change" AND "Construction Cost") AND (LIMIT-TO (SUBJAREA, "ENGI") OR LIMIT-TO (SUBJAREA, "ENVI") OR LIMIT-TO (SUBJAREA, "EART")) AND (LIMIT-TO (DOCTYPE, "ar") OR LIMIT-TO (DOCTYPE, "cp") OR LIMIT-TO (DOCTYPE, "ch")) AND (LIMIT-TO (LANGUAGE, "English")) The initial search retrieved 252 documents. Limiting the subject area to engineering, environmental science and earth and planetary science brought this down to 195 documents. Limiting the search to English-only peer-reviewed articles, conference proceedings and book chapters, the final dataset comprised 177 documents published between 1997 and 2026, with a response rate of 100% (all documents returned were included after applying the inclusion criteria). This filtering process is consistent with the protocol used by Olawumi and Chan (2018) and by other similar studies such as Wuni et al. (2019). Four principal analytical techniques were applied to the final dataset. First, descriptive bibliometric analysis characterised the dataset in terms of time, document types and journal distribution, and citation pattern. Second, geographic analysis identified the spatial distribution of research by extracting and coding country data of author affiliations. Third, cluster analysis identified research sub-disciplines based on keyword co-occurrences using VOSviewer's distance-based network visualisation and Bibliometrix R package's co-word analysis. Fourth, keyword burst analysis used Kleinberg's (2002) two-state automaton algorithm (coded in a custom Python environment) to detect time periods of unusually high keyword frequency and to calculate burst strength scores and silhouette scores. Burst strength scores indicate the intensity and concentration of scholarly focus; silhouette scores (on a scale from -1.0 to 1.0) assess the temporal cohesion of each burst cluster. The overall dataset contains 2,726 total citations (15.4 average citations) to 177 documents, with an estimated field-based h-index of 25. These bibliometric indicators confirm the presence of a coherent and substantively significant body of research: twelve publications have received more than 50 citations and five have received more than 100, which is consistent with a field which has produced influential early works and is small enough to form an appropriate analytical unit
Institutions
- Durban University of TechnologyKwaZulu-Natal, Durban