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Biswas, P K, Khan, S M, Piratla, K and Chowdhury, M (2023) Development and evaluation of statistical and machine-learning models for queue-length estimation for lane closures in freeway work zones. Journal of Construction Engineering and Management, 149(05).
Chong, H Y and Cheng, M (2023) Smart contract implementation in building information modeling-enabled projects: Approach to contract administration. Journal of Construction Engineering and Management, 149(05).
Ding, S, Hu, H, Dai, L and Wang, W (2023) Blockchain adoption among multi-stakeholders under government subsidy: From the technology diffusion perspective. Journal of Construction Engineering and Management, 149(05).
Feng, Z, Chao, Q, Tan, C and Yang, Y (2023) Using bargaining model with loss aversion and a risk of breakdown to determine compensation for buyback of early terminating BOT highway projects. Journal of Construction Engineering and Management, 149(05).
Garg, S and Misra, S (2023) Framework for estimating quality-related incentive and disincentive in construction projects. Journal of Construction Engineering and Management, 149(05).
Gonsalves, N, Akanmu, A, Gao, X, Agee, P and Shojaei, A (2023) Industry perception of the suitability of wearable robot for construction work. Journal of Construction Engineering and Management, 149(05).
Han, S, Jiang, Y, Huang, Y, Wang, M, Bai, Y and Spool-White, A (2023) Scan2drawing: Use of deep learning for as-built model landscape architecture. Journal of Construction Engineering and Management, 149(05).
Jung, H, Seo, W and Kang, Y (2023) Differences in workers' safety behavior by project size and risk level of work in South Korea. Journal of Construction Engineering and Management, 149(05).
Labik, O, Nahmens, I, Ikuma, L and Harvey, C (2023) On-site versus in-factory installation of solar-plus-storage in modular construction. Journal of Construction Engineering and Management, 149(05).
Saqib, G, Hassan, M U, Zubair, M U and Choudhry, R M (2023) Investigating the acceptance of an electronic incident reporting system in the construction industry: An application of the technology acceptance model. Journal of Construction Engineering and Management, 149(05).
Shen, K, Zhu, Y, Pan, J and Li, X (2023) An intelligent decision-making model for the design of precast slab joints based on case-based reasoning. Journal of Construction Engineering and Management, 149(05).
Ullal, A (2023) Construction conditions and practices during war in Afghanistan. Journal of Construction Engineering and Management, 149(05).
Wang, C, Zhang, S, Gao, Y, Guo, Q and Zhang, L (2023) Effect of contractual complexity on conflict in construction subcontracting: Moderating roles of contractual enforcement and organizational culture distance. Journal of Construction Engineering and Management, 149(05).
Wang, J, Han, C and Li, X (2023) Modified streamlined optimization algorithm for time-cost tradeoff problems of complex large-scale construction projects. Journal of Construction Engineering and Management, 149(05).
Xue, G, Liu, S, Ren, L and Gong, D (2023) Adaptive cross-scenario few-shot learning framework for structural damage detection in civil infrastructure. Journal of Construction Engineering and Management, 149(05).
Zhang, Y, Minchin, R E, Flood, I and Ries, R J (2023) Preliminary cost estimation of highway projects using statistical learning methods. Journal of Construction Engineering and Management, 149(05).
Zhou, Y, Wang, X, Gosling, J and Naim, M M (2023) The system dynamics of engineer-to-order construction projects: Past, present, and future. Journal of Construction Engineering and Management, 149(05).
- Type: Journal Article
- Keywords: literature review; modeling; project management
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-12926
- Abstract:
System dynamics (SD) applications in high-volume production operations are widely used, helping to define decision rules to reduce costs associated with the variance in planning orders and inventory. The exploitation of SD in engineer-to-order (ETO) project-oriented supply chains - e.g., in construction, shipbuilding, and capital goods - is less well established. Hence, this research reviews the literature that takes a systematic ETO perspective in modeling construction projects, exploiting SD approaches. To comprehensively identify and filter previously published works, we used a keyword searching method using Web of Science and Scopus databases. After applying relevant exclusion criteria, 143 papers were selected. Although previous reviews of ETO literature, more generally, have been done, this work contributes to the body of knowledge by specifically reviewing SD applications in ETO industries and providing insights by creating a categorization system by which to determine existing gaps. Articles are categorized into the classic four phases of a project: aggregated planning, preproject planning, project execution, and postdelivery. Analyses of the methods, attributes, and applications of SD were undertaken for each phase. Findings indicate that SD research covers the range of ETO industries, of which construction is the most dominant, demonstrating SD's high applicability. The wealth of case-orientated research in the construction field provides a solid foundation for further SD studies in the ETO field. Further research should focus on (1) developing a general ETO archetype for performance benchmarking and strategy development in construction projects; (2) introducing analytical tools, such as control theoretic approaches as found in manufacturing production planning and control design, to improve understanding of the ETO systems' dynamic behaviors; (3) developing cross-phase, cross-project, design-production integrated, aggregated planning models via hybrid techniques modeling, which can improve understanding of an ETO system's performance; and (4) improving model fidelity. We also provide a research agenda for each phase of the ETO production.