Reliability evaluation index for the integrated supply chain utilising BIM and lean approaches. Issue 5 (4th June 2020) - Zhang, Jingxiao; Li, Hui; Golizadeh, Hamed; Zhao, Chuandang; Lyu, Sainan; Jin, Ruoyu
Abstract : Purpose: This research aims to develop an approach to assess the reliability of integrated construction supply chains via an integrated model of building information modelling (BIM) and the lean supply chain (LSC). It reflects the synergistic workflow between BIM and LSC as a novel approach to improve the reliability of construction projects. Design/methodology/approach: This research evaluates the reliability of the BIM-LSC approach through a combination of entropy theory, set pair analysis (SPA), and Markov chains (EESM). An exploratory survey was conducted to collect data from 316 industry professionals experienced in BIM and LSC. Subsequently, multiple cycles of calculations were performed with indirect data inputs. Finally, a reliability evaluation index is established for the BIM-LSC approach and potential applications are identified. Findings: The results show that the EESM model of BIM-LSC developed in this study can handle not only supply chain reliability evaluation at a given state but also the prediction of reliability in supply chain state transitions due to changing project conditions. This is particularly relevant to the current environment of the construction project, which is characterised by an increasing level of complexity in terms of labour, technology, and resource interactions. Research limitations/implications: Future research could consider the accuracy and validity of the proposed model in real-life scenarios with by considering both quantitative and qualitative data across the entire lifecycle of projects. Practical implications: The research offers a model to evaluate the reliability of the BIM-LSC approach. The accuracy of BIM supply chain reliability analysis and prediction in an uncertain environment is improved. Originality/value: The BIM-LSC reliability evaluation and prediction presented in this study provides a theoretical foundation to enhance understanding of the BIM-LSC in the construction project context.