Navigating the transformation: a systematic analysis of Building Information Modelling, Artificial Intelligence and Internet of Things in smart construction logistics
Open accessAbstract
Purpose: This study aims to explore the transformative impact of emerging technologies such as Building Information Modeling (BIM), Artificial Intelligence (AI) and the Internet of Things (IoT), on construction logistics management systems. Design/methodology/approach: This study employs a systematic literature review (SLR) in three phases: focused database searches to identify research on modern construction logistics technologies, qualitative content analysis to examine key emerging technologies and Scientometric analysis using VOS viewer to highlight trends and advancements in smart construction logistics systems. Findings: The integration of BIM, AI and IoT enhances efficiency and productivity in construction logistics by facilitating real-time data utilization for supply chain optimization, reducing delays and minimizing errors. This transition towards cost-effectiveness and timely project completion signifies a move to streamlined operations and data-driven decision-making. However, challenges such as entrenched conventional practices, resistance to change and concerns regarding privacy and data security present significant challenges. Research limitations/implications: Despite its significance, key limitations include reliance on existing literature, which may introduce bias due to database access restrictions, potentially overlooking relevant or recent developments in construction logistics technologies and the evolving technological landscape. Originality/value: This study provides valuable insights for decision-makers and stakeholders within the construction industry, offering guidance on navigating challenges and harnessing the full potential of BIM, AI and IoT. Recommendations include addressing privacy concerns while leveraging innovative solutions for improved construction logistics management. The research sets the groundwork for further studies aimed at understanding and optimising the dynamic influence of emerging technologies on construction practices.
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Chamola, V., Hassija, V., Gupta, V., & Guizani, M. (2020) · IEEE Access · doi:10.1109/access.2020.2992341 · Cited by 1,099 · see citing works
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- Authors
- Kayembe, M. T., & Obadire, A. M.
- Affiliations
- Botswana Accountancy College (BW)
- Venue
- Modern Supply Chain Research and Applications
- Publisher
- Emerald
- Published
- 2025-06-13
- ISSN
- 2631-3871 (ISSN-L)
- OpenAlex
- W4411243550
- Cited by
- 2
- References
- 1
- Citations by year
- 2025: 2
- FWCI
- 0.84
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Modern Supply Chain Research and Applications (publishedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
- Social Sciences › Decision Sciences › Management Science and Operations Research › Construction Project Management and Performance
- Physical Sciences › Engineering › Building and Construction › Construction Management and Sustainability
- Keywords
- building information modeling, artificial intelligence, Internet of Things, supply chain optimization, data-driven decision making, resistance to change, data privacy and security, construction industry transformation
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