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International Journal of Construction Management

For a Special Issue on

Towards Efficient and Sustainable Construction Project Management: Leveraging AI and Disruptive Technologies

Abstract deadline
15 September 2024

Manuscript deadline
01 February 2025

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Special Issue Editor(s)

Khalil Rahi, Abu Dhabi University, UAE
[email protected]

Issam Krimi, Abu Dhabi University, UAE
[email protected]

Yongjian Ke, University of Technology Sydney, Australia
[email protected]

Srinath Perera, Western Sydney University, Australia
[email protected]

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Towards Efficient and Sustainable Construction Project Management: Leveraging AI and Disruptive Technologies

Aim and Scope

Project management, particularly in the construction sector, is undergoing significant transformations to address sustainability and emerging technology challenges (Bento et al., 2022; Nikmehr et al., 2021; Zubizarreta et al., 2020). The integration of disruptive technologies, such as Artificial Intelligence (AI), is reshaping construction project management to ensure sustainability, enhance stakeholder engagement, and enable organizations to thrive in a Volatile, Uncertain, Complex and Ambiguous (VUCA) world (Afzal et al., 2021; Borg et al., 2020). This evolution aims to provide construction project managers with frameworks, tools, and best practices for managing efficient and sustainable projects.

Integrating sustainability into construction project decision-making is becoming important (Dobrovolskienė & Tamošiūnienė, 2015). Therefore, it is imperative to explore how construction project managers perceive and incorporate sustainability principles by identifying the factors that drive their adoption (Borg et al., 2020). Moreover, exploring the soft competencies required for sustainable construction project management can aid in developing training programs to enhance project managers' abilities to address sustainability challenges effectively (Xue et al., 2020).

Sustainability principles can be integrated into project initiation, planning, monitoring and control, and closing processes to address environmental, economic, and social aspects (Larsson & Larsson, 2020; Yu et al., 2018). This integration necessitates a comprehensive approach to embedding sustainability processes, tools, policies, and procedures within construction project management standards (Xue et al., 2020). Academic research can bridge the gap between theoretical concepts and practical applications, and offer valuable guidance on effectively integrating sustainability into construction project management.

On the other hand, AI is increasingly being recognized as a transformative technology in construction project management (Bento et al., 2022). The integration of AI offers new opportunities and challenges. Clarifying the boundaries between human decision-making and AI algorithms in construction project management is essential (Fernández et al., 2022). This balance between human expertise and AI-driven insights can optimize project outcomes. Exploring AI applications, such as project success prediction through recurrent neural networks, can provide valuable insights into improving construction project outcomes (Hsu et al., 2021).

Investigating the adoption of AI in construction can offer valuable insights into the challenges and opportunities of integrating AI into construction project management practices (Gao et al., 2023). For instance, AI can optimize scheduling, resource allocation, and risk management by analyzing vast amounts of data and providing predictive analytics (Perera & Eadie, 2023). AI-driven tools can also improve site safety through real-time monitoring and predictive maintenance, thus reducing accidents and operational disruptions. Studying the impact of AI on talent management can also provide valuable insights into leveraging AI for effective organizational management (Liu et al., 2021). These academic developments, among others, can pave the way for integrating AI technologies in construction project management, ultimately leading to improved project outcomes and organizational success (Abioye, 2021; Bento et al., 2022).

Therefore, the purpose of this special issue is to investigate challenges related to construction project management, sustainability, and AI capabilities, and explore methods, processes, tools, and techniques to ensure project success. This special issue hence aims to examine the distinct difficulties encountered by construction project managers while overseeing sustainable projects and how these challenges can be addressed with the use of disruptive technologies (machine learning, GenAI, IoT, blockchain, etc.), particularly during periods of uncertainty and skill deficiencies.

Topics for Papers

Submissions for this special issue may focus on any concepts that contribute to our understanding of leveraging AI and disruptive technologies to enable sustainable construction project management. We welcome submissions with a broad range of research methodologies and encourage interdisciplinary contributions that bridge the gap between construction project management, artificial intelligence, organizational behavior, and sustainability studies. Potential topics include, but are not limited to:

  • The impact of AI and other disruptive technologies on various knowledge areas of construction project management, such as risk management, scheduling, resource optimization, and stakeholder engagement.
  • Strategies for integrating AI-powered predictive analytics, early warning systems, and resource optimization tools in sustainable project management in the construction industry.
  • The role of disruptive technologies (e.g., GenAI, IoT, Blockchain) in enhancing construction project resource management and sustainability.
  • Sustainable project management practices in the digital era, including the use of AI-enabled platforms for stakeholder collaboration and engagement for the construction industry.
  • Frameworks and metrics for measuring the sustainability performance of construction projects leveraging AI and disruptive innovations.
  • Ethical and social considerations related to the use of AI in construction project management, such as bias, transparency, and accountability.
  • Case studies and empirical evidence showcasing the successful implementation of AI and disruptive technologies in construction project management initiatives.


Abioye, S. O. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44, 103299.

Afzal, F., Yunfei, S., Nazir, M., & Bhatti, S. M. (2021). A review of artificial intelligence based risk assessment methods for capturing complexity-risk interdependencies: Cost overrun in construction projects. International Journal of Managing Projects in Business, 14(2), 300–328.

Bento, S., Pereira, L., Gonçalves, R., Dias, Á., D, R. L., & Costa, A. (2022). Artificial intelligence in project management: Systematic literature review. International Journal of Technology Intelligence and Planning, 13(2), 143.

Borg, R., Dalli Gonzi, R., & Borg, S. (2020). Building Sustainably: A Pilot Study on the Project Manager’s Contribution in Delivering Sustainable Construction Projects—A Maltese and International Perspective. Sustainability, 12(23), 10162.

Dobrovolskienė, N., & Tamošiūnienė, R. (2015). An Index to Measure Sustainability of a Business Project in the Construction Industry: Lithuanian Case. Sustainability, 8(1), 14.

Fernández, J. M. M., Moreno, J. J. G., Vergara-González, E. P., & Iglesias, G. A. (2022). Bibliometric analysis of the application of artificial intelligence techniques to the management of innovation projects. Applied Sciences, 12(22), 11743.

Gao, S., Low, S. P., & Lim, X. (2023). Prospects, drivers of and barriers to artificial intelligence adoption in project management. Built Environment Project and Asset Management, 13(5), 629–645.

Hsu, M.-W., Dacre, N., & Senyo, P. (2021). Applied Algorithmic Machine Learning for Intelligent Project Prediction: Towards an AI Framework of Project Success. SSRN Electronic Journal.

Larsson, J., & Larsson, L. (2020). Integration, Application and Importance of Collaboration in Sustainable Project Management. Sustainability, 12(2), 585.

Liu, S., Li, G., & Xia, H. (2021). Analysis of talent management in the artificial intelligence era. Proceedings of the 5th Asia-Pacific Conference on Economic Research and Management Innovation (ERMI 2021).

Nikmehr, B., Hosseini, M. R., Martek, I., Zavadskas, E. K., & Antucheviciene, J. (2021). Digitalization as a strategic means of achieving sustainable efficiencies in construction management: A critical review. Sustainability, 13(9), 5040

Perera, S and Eadie, R. (2023). Managing Information Technology Projects, Building A Body of Knowledge in IT Project Management, World Scientific, ISBN: 9789811240577

Xue, J., Rasool, Z., Gillani, A., & Khan, A. I. (2020). The Impact of Project Manager Soft Competences on Project Sustainability. Sustainability, 12(16), 6537.

Yu, M., Zhu, F., Yang, X., Wang, L., & Sun, X. (2018). Integrating Sustainability into Construction Engineering Projects: Perspective of Sustainable Project Planning. Sustainability, 10(3), 784.

Zubizarreta, M., Ganzarain, J., Cuadrado, J., & Lizarralde, R. (2020). Evaluating Disruptive Innovation Project Management Capabilities. Sustainability, 13(1), 1.

Submission Instructions

Information to Contributors

This call for papers involves a two-stage submission process:

Stage 1: Paper Development

  • This call for papers invites authors to attend the 2nd International Conference on Advancing Sustainable Futures (ICASF 2024) at Abu Dhabi University, United Arab Emirates (11-12 December 2024). Authors wishing to take this opportunity should submit their short paper to the track with the theme "Sustainable Project Management: Leveraging AI and Disruptive Technologies" by 25 July 2024 directly through the ICASF submission system ( The guest editors of this special issue are either leading this track and/or will be present during the conference to provide initial feedback on the papers. A submission to ICASF is not a prerequisite for submission to this special issue but is highly encouraged.
  • Authors who do not plan to attend the ICASF should submit a one-page abstract to the editors (via [email protected]). The editors will provide comments to guide the authors in writing their full papers.

Stage 2: Full Paper Submission

Authors should submit the full paper to IJCM. Submitted papers will be subject to the routine IJCM anonymized peer review process.

The manuscript should cover the following four research components to be considered:

  • Relevance of the problem (description of the real-world phenomena and need for research);
  • Theoretical underpinning of the research;
  • Methodology (clear steps of the research design and descriptions of the data); and
  • Contributions to the discipline of construction project management studies.

Authors should carefully review and follow the IJCM author guidelines and indicate the publication category Special Issue: “Towards Efficient and Sustainable Construction Project Management: Leveraging AI and Disruptive Technologies”. We expect authors and reviewers to work in a timely manner to comply with the anticipated time lines of submission and publication outlined as follows. If you have any additional questions, please consult any of the guest editors.

Key dates

For authors who plan to attend the ICASF 2024:

  • ICASF 2024 short Paper Submission: 25 June 2024.
  • ICASF 2024 decision about abstracts acceptance: 15 July 2024.
  • ICASF 2024 full paper submission: 15 September 2024.
  • ICASF 2024 decisions about papers acceptance: 1 October 2024.
  • Feedback from guest editors at ICASF 2024: 11-12 December 2024.

For authors who do not plan to attend the ICASF 2024:

  • Abstract submission deadline: 15 September 2024.
  • Feedback from guest editors: two weeks after the abstract submission.
  • Paper submission deadline: 1 February 2025.
  • Notifications to authors: From March 2025 to September 2025.
  • Expected publication: Early 2026.

Instructions for AuthorsSubmit an Article