Human-centred and BIM-integrated automated value analysis of buildings

Zhang, Lu; El-Gohary, Nora

doi:10.1080/15623599.2022.2025555

Cited by 3 publications

(1 citation statement)

References 35 publications

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“…These authors then continued their research in the field of value analysis of buildings using BIM technology while including stakeholders' systems of value priorities during the process. They tested their human-centered and BIM-integrated automated value analysis model in a residential building, a commercial office building, and an educational building and found a strong correlation between building values and stakeholder's priorities (Zhang and El-Gohary, 2022). However, their studies did not fully follow a property valuation procedure.…”

Section: Existing Studies and Challengesmentioning

confidence: 99%

BIM and real estate valuation: challenges, potentials and lessons for future directions

Jafary¹,

Shojaei

Rajabifard

et al. 2022

ECAM

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PurposeBuilding information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.Design/methodology/approachThis paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.FindingsFour domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.Originality/valueThis paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

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Section: Existing Studies and Challengesmentioning

confidence: 99%

BIM and real estate valuation: challenges, potentials and lessons for future directions

Jafary¹,

Shojaei

Rajabifard

et al. 2022

ECAM

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A critical review of digital value engineering in building design towards automated construction

Khan,

Alaloul,

Musarat

2024

Environ Dev Sustain

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A multi-label text classifier: application on an Italian public tender procedure, project ISCOL@

Locatelli,

Tagliabue,

Di Giuda

2024

ITcon

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The main means of communication during the pre-design phase is natural language. Effective communication during the pre-design phase through text documents and reports is essential to the success of a design and construction project. The study develops and evaluates a Natural Language Processing (NLP) tool called ArchiBERTo to process textual data related to design tender documents in the Italian public procurement process. Documenti di Indirizzo alla Progettazione (DIPs) are key documents, as they outline the demands, needs, and objectives of the public appointing party. ArchiBERTo is developed to process and convert DIP quality objective sentences into a hierarchy of objectives and criteria. The performances are evaluated by comparing the tool’s rankings with those provided by a group of domain experts. The results demonstrate ArchiBERTo's capability to reflect the collective ability of a panel of experts and to properly reflect the different contents of the DIP in the objectives hierarchy. The proposed system aims to address the issue of information asymmetry and potential misunderstandings, or varying interpretations, among the key actors of the Italian tendering procedure, namely the public appointing party, the design teams, and the external committee, regarding the relative importance of quality objectives and evaluation criteria. The utilization of the NLP systems ArchiBERTo to establish a shared hierarchy of objectives is expected to enhance communication and promote consensus during the pre-design phase. The minimization of the consensus issue among the actors can have a positive impact on the overall quality of the design proposals and facilitate the evaluation process conducted by the external committee, bridging the gap between expected and actual quality, ensuring that design proposals align with the quality objectives and demands of the public actor.

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Human-centred and BIM-integrated automated value analysis of buildings

Cited by 3 publications

References 35 publications

BIM and real estate valuation: challenges, potentials and lessons for future directions

BIM and real estate valuation: challenges, potentials and lessons for future directions

A critical review of digital value engineering in building design towards automated construction

A multi-label text classifier: application on an Italian public tender procedure, project ISCOL@

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