Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025)

Zakaria Ghedjati; Imane Fantazi; Choubeila Koreichi

doi:10.31127/tuje.2027622

Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025)

Abstract

The construction industry faces growing challenges that require better decision-making frameworks. Combining Multi-Criteria Decision-Making (MCDM) with digital tools like Building Information Modeling (BIM) and Artificial Intelligence (AI) offers a promising way forward. Yet their integration remains fragmented across research efforts, revealing a significant gap in theory and practice. As a result, their potential remains underutilized, limiting the development of flexible, data-driven decision-making tools for complex construction projects. This study conducts a systematic bibliometric analysis to map the development and structure of the MCDM-BIM-AI connection in construction management from 2015 to 2025. Using a PRISMA-compliant protocol, we analyzed 253 peer-reviewed articles from the Scopus database. Our approach combines performance analysis with science mapping through keyword co-occurrence networks and thematic evolution analysis across three time periods: 2015-2018, 2019-2021, 2022-2025, along with a country-level co-authorship network analysis. Our findings identify five main thematic clusters and show a significant increase in publications since 2019, mainly driven by the Asia-Pacific region. The analysis highlights a notable knowledge gap in the deep connection between BIM and AI within MCDM frameworks. The temporal mapping reveals three phases of evolution: pre-integration (2015-2018), Integration (2019-2021), and Innovation (2022-present), with AI and Machine Learning becoming key focus areas in the latest phase. The study suggests promising future directions for combining MCDM, BIM, and AI to promote more sustainable, data-driven, and resilient construction practices. It proposes a conceptual outline for the Intelligent Cognitive Decision Framework (ICDF), where BIM serves as a semantic data backbone, MCDM acts as the evaluation engine, and AI provides cognitive support for flexible, data-driven decision-making in construction 4.0 applications. This intellectual mapping offers researchers data-driven guidance for prioritizing impactful investigations, practitioners with technology investment plans that match research developments, and policymakers with informed priorities for research and development investment in underrepresented regions.

Keywords

Supporting Institution

No external funding or institutional financial support was received for this research.

Ethical Statement

This study is based exclusively on bibliographic data obtained from the Scopus database and does not involve human participants, personal data, or animal experiments. Therefore, ethical approval was not required.

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Details

Primary Language

English

Subjects

Architectural Engineering

Journal Section

Research Article

Authors

Zakaria Ghedjati ^*
0009-0009-0743-274X
Algeria

Imane Fantazi
0009-0006-6349-2024
Algeria

Choubeila Koreichi
0000-0002-8407-0115
Algeria

Publication Date

October 16, 2026

Submission Date

August 28, 2026

Acceptance Date

October 10, 2026

Published in Issue

Year 2026 Volume: 10 Number: 4

DOI

https://doi.org/10.31127/tuje.2027622

IZ

https://izlik.org/JA66FS22MK

Cite

RIS / Bibtex

APA

Ghedjati, Z., Fantazi, I., & Koreichi, C. (2026). Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025). Turkish Journal of Engineering, 10(4), 1732-1748. https://doi.org/10.31127/tuje.2027622

AMA

1.Ghedjati Z, Fantazi I, Koreichi C. Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025). TUJE. 2026;10(4):1732-1748. doi:10.31127/tuje.2027622

Chicago

Ghedjati, Zakaria, Imane Fantazi, and Choubeila Koreichi. 2026. “Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025)”. Turkish Journal of Engineering 10 (4): 1732-48. https://doi.org/10.31127/tuje.2027622.

EndNote

Ghedjati Z, Fantazi I, Koreichi C (October 1, 2026) Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025). Turkish Journal of Engineering 10 4 1732–1748.

IEEE

[1]Z. Ghedjati, I. Fantazi, and C. Koreichi, “Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025)”, TUJE, vol. 10, no. 4, pp. 1732–1748, Oct. 2026, doi: 10.31127/tuje.2027622.

ISNAD

Ghedjati, Zakaria - Fantazi, Imane - Koreichi, Choubeila. “Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025)”. Turkish Journal of Engineering 10/4 (October 1, 2026): 1732-1748. https://doi.org/10.31127/tuje.2027622.

JAMA

1.Ghedjati Z, Fantazi I, Koreichi C. Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025). TUJE. 2026;10:1732–1748.

MLA

Ghedjati, Zakaria, et al. “Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025)”. Turkish Journal of Engineering, vol. 10, no. 4, Oct. 2026, pp. 1732-48, doi:10.31127/tuje.2027622.

Vancouver

1.Zakaria Ghedjati, Imane Fantazi, Choubeila Koreichi. Multi-Criteria Decision-Making in Construction Management: A Bibliometric Analysis of the Integration of MCDM, BIM, and Artificial Intelligence (2015–2025). TUJE. 2026 Oct. 1;10(4):1732-48. doi:10.31127/tuje.2027622