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Article

Network-Based Modeling of Lean Implementation Strategies and Planning in Prefabricated Construction

1
School of Economics and Management, Tianjin Chengjian University, No. 26, Jinjing Road, Xiqing District, Tianjin 300384, China
2
School of Engineering, Design & Built Environment, Western Sydney University, Sydney 2150, Australia
3
College of Management and Economics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China
4
School of Economics, Wuhan University of Technology, No. 122, Luoshi Road, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
Buildings 2024, 14(10), 3182; https://doi.org/10.3390/buildings14103182 (registering DOI)
Submission received: 5 September 2024 / Revised: 25 September 2024 / Accepted: 2 October 2024 / Published: 6 October 2024
(This article belongs to the Special Issue Strategic Planning and Control in Complex Project Management)

Abstract

Abstract: Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies.
Keywords: prefabricated construction; Lean implementation; strategy planning; ISM-MICMAC; complex network prefabricated construction; Lean implementation; strategy planning; ISM-MICMAC; complex network

Share and Cite

MDPI and ACS Style

Dang, P.; Geng, L.; Niu, Z.; Jiang, S.; Sun, C. Network-Based Modeling of Lean Implementation Strategies and Planning in Prefabricated Construction. Buildings 2024, 14, 3182. https://doi.org/10.3390/buildings14103182

AMA Style

Dang P, Geng L, Niu Z, Jiang S, Sun C. Network-Based Modeling of Lean Implementation Strategies and Planning in Prefabricated Construction. Buildings. 2024; 14(10):3182. https://doi.org/10.3390/buildings14103182

Chicago/Turabian Style

Dang, Pei, Linna Geng, Zhanwen Niu, Shan Jiang, and Chao Sun. 2024. "Network-Based Modeling of Lean Implementation Strategies and Planning in Prefabricated Construction" Buildings 14, no. 10: 3182. https://doi.org/10.3390/buildings14103182

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