Mapping Technological Frontiers in Construction Planning and Scheduling: A Bibliometric Review (2015-2025)

Authors

Mohd Haykal Adli Abdul Rahman

Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (Malaysia)

Nurshikin Mohamad Shukery

Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (Malaysia)

Abdul Rashid Zailan

Department of Student Affairs, UTMSPACE (Malaysia)

Muhamad Norfiqiri Hamid

Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.100300088

Subject Category: Operations Management

Volume/Issue: 10/3 | Page No: 1277-1286

Publication Timeline

Submitted: 2026-03-07

Accepted: 2026-03-12

Published: 2026-03-26

Abstract

Construction planning and scheduling remain critical processes in project management, yet projects frequently experiences delay due to complex coordination, resource constraints, and dynamic project nature. While research into digital technologies to improve scheduling practices has increased steadily, systematic studies on the evolution of these solutions within the broader academic discourse of planning and scheduling remain limited. This study aims to map the development of technological solutions to construction planning and scheduling challenges through a bibliometric analysis of academic literature published between 2015 and 2025. Scopus databases were selected resulting in 359 peer-reviewed journal articles. Keyword co-occurrence analysis was conducted using VOS viewer to identify thematic relationships and research trends. The analysis revealed five major research themes: (1) optimization-based scheduling, (2) BIM and information integration, (3) operational construction management, (4) decision support and economic evaluation, and (5) artificial intelligence (AI) technologies. Results indicate that optimization algorithms remain backbone for methodological approach in addressing scheduling challenges, while BIM is the hub for digital platform in data integration and coordination. Emerging AI and machine learning themes currently augment predictive capabilities rather than replacing established scheduling methods. Overall, the finding demonstrates gradual shift in construction scheduling research from managerial-centric approaches towards computational aided optimization and digital planning environments. This study provides a structured overview of technological evolution in construction planning and scheduling domain.

Keywords

Construction planning and scheduling; BIM; Optimization

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References

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