The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Cost prediction model for building deconstruction in urban areas
Abstract
Abstract Many U.S. cities have suffered economic decline and contain widespread residential, commercial, and industrial property abandonment. Such abandonment results in negative economic, social, and environmental consequences in urban areas. Demolition and landfilling are prevalent methods to remove these abandonments while generating large amounts of construction and demolition (CD however, this concern is problematic because current cost prediction methods for deconstruction are insufficiently accurate. To address this problem, the authors have developed a novel cost prediction model using case-based reasoning, an artificial intelligence based technique. The paper elaborates on the model development and demonstrates the model application through a real world deconstruction case in the state of Michigan. Results indicate the accuracy of the new prediction model is greater than 95% and show a lower net cost of deconstruction than demolition. Findings suggest an additional option of design for deconstruction for green buildings in the construction industry. Findings implicate a broader construct of sustainable urban transformation where a full supply chain of deconstructed materials emerges.
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In the citing paper
“This factor, which is partially the outcome of the tight project schedules (Tatiya et al., 2017), results in the lack of sufficient supply of reused components with the desired characteristics (dimension, quality, etc.) (Brütting et al., 2019; da Rocha and Sattler, 2009; Dunant et al., 2017; Gorgolewski, 2008; Rose and Stegemann, 2018; Tingley et al., 2017).”
From Components reuse in the building sector – A systematic review (2020) · cites this paper as Tatiya et al., 2017
In the citing paper
“Sometimes the deconstruction time extends beyond anticipations because of issues such as a lack of space for equipment, complexity of the building design and the geographic location of the building (Tatiya et al., 2017).”
From Components reuse in the building sector – A systematic review (2020) · cites this paper as Tatiya et al., 2017
In the citing paper
“It is because, during the deconstruction of a building, or while treating a component for reuse, there is a risk of encountering hazardous, banned or contaminating coatings on the reused components (Rameezdeen et al., 2016; Tatiya et al., 2017; Tingley et al., 2017).”
From Components reuse in the building sector – A systematic review (2020) · cites this paper as Tatiya et al., 2017
Citations
Cites
Decision making with the analytic hierarchy process
Saaty, T. L. (2008) · International Journal of Services Sciences · doi:10.1504/ijssci.2008.017590 · Cited by 10,301
Galit Shmueli, A. (2010) · Statistical Science · doi:10.1214/10-sts330 · Cited by 3,456
Riesbeck, C. K., & Schank, R. C. (2013) · Psychology Press eBooks · doi:10.4324/9780203781821 · Cited by 1,443
Kim, G.-H., An, S.-H., & Kang, K.-I. (2004) · Building and Environment · doi:10.1016/j.buildenv.2004.02.013 · Cited by 462
Marzouk, M., & Azab, S. (2014) · Resources, Conservation and Recycling · doi:10.1016/j.resconrec.2013.10.015 · Cited by 383
A neural network approach for early cost estimation of structural systems of buildings
Murat Günaydın, H., & Zeynep Doğan, S. (2004) · International Journal of Project Management · doi:10.1016/j.ijproman.2004.04.002 · Cited by 285
Akbarnezhad, A., Ong, K. C. G., & Chandra, L. R. (2013) · Automation in Construction · doi:10.1016/j.autcon.2013.10.017 · Cited by 242
COST ESTIMATION PREDICTIVE MODELING: REGRESSION VERSUS NEURAL NETWORK
Smith, A. E., & Mason, A. K. (1997) · The Engineering Economist · doi:10.1080/00137919708903174 · Cited by 222
Neural Networks as Tools in Construction
Moselhi, O., Hegazy, T., & Fazio, P. (1991) · Journal of Construction Engineering and Management · doi:10.1061/(asce)0733-9364(1991)117:4(606 · Cited by 200
A case-based reasoning cost estimating model using experience by analytic hierarchy process
An, S.-H., Kim, G.-H., & Kang, K.-I. (2006) · Building and Environment · doi:10.1016/j.buildenv.2006.06.007 · Cited by 174
Research works printed but not linked: 2
- Behnan, 2014, Lansing gets $6M to fight blight, Lansing State J.
- Guy, 2001, Building deconstruction assessment tool. Deconstruction and Materials Reuse, Technol. Econ. Policy, 125
Cited by
Components reuse in the building sector – A systematic review
Rakhshan, K., Morel, J.-C., Alaka, H., & Charef, R. (2020) · Waste Management & Research: The Journal for a Sustainable Circular Economy · doi:10.1177/0734242x20910463 · Cited by 167
Rakhshan, K., Morel, J.-C., & Daneshkhah, A. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.102791 · Cited by 53
Metadata
- Authors
- Tatiya, A., Zhao, D., Syal, M., Berghorn, G. H., & LaMore, R.
- Affiliations
- Michigan State University (US)
- Corresponding author
- Zhao, Dong
- Venue
- Journal of Cleaner Production
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 195
- Pages
- 1572-1580
- ISSN
- 0959-6526 (ISSN-L)
- OpenAlex
- W2744742808
- Cited by
- 90
- References
- 36
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 18 · 2023: 17 · 2022: 9 · 2021: 10 · 2020: 8 · 2019: 5 · 2018: 1
- FWCI
- 3.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Locations
- Journal of Cleaner Production (publishedVersion)
- Funders
- National Housing Endowment of the National Association of Home Builders
- Topics
- Physical Sciences › Engineering › Building and Construction › Recycled Aggregate Concrete Performance
- Physical Sciences › Engineering › Building and Construction › Sustainable Building Design and Assessment
- Physical Sciences › Engineering › Building and Construction › Construction Management and Sustainability
- Keywords
- building deconstruction, cost prediction model, case-based reasoning, construction and demolition waste, property abandonment, material reuse and recycling, design for deconstruction, sustainable construction, sustainable urban transformation, urban economic decline
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- CoChat. (2026). Citation check: Cost prediction model for building deconstruction in urban areas. https://app.cochat.ai/papers/10.1016/j.jclepro.2017.08.084
- The paper
- Tatiya, A., Zhao, D., Syal, M., Berghorn, G. H., & LaMore, R. (2018). Cost prediction model for building deconstruction in urban areas. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2017.08.084
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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.
