Process-Based Identification of Critical Factors for Residual Value Risk in China's Highway PPP Projects
Author(s): |
Chuanjun Zheng
Jingfeng Yuan Lingzhi Li Mirosław J. Skibniewski |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, 2019, v. 2019 |
Page(s): | 1-21 |
DOI: | 10.1155/2019/5958904 |
Abstract: |
Although the Chinese government at all levels has increasingly embraced Public-Private Partnership (PPP) as their preferred approach to deliver large-scale infrastructure since 2014, residual value risk (RVR) has been ignored in PPP practice. To systematically explore the critical risk factors (CRFs) responsible for measuring RVR in highway PPP projects, this paper proposes and refines a conceptual model composed of two risk dimensions (four risk categories) and 29 indicators through process-based viewpoint. Through literature review and expert interview, a structured questionnaire was developed to collect responses with rich working experience in construction industry or highway PPP projects. The refined measurement model with 21 CRFs was validated through mean value analysis (MVA) and confirmatory factor analysis (CFA) performed by SPSS 23.0 and AMOS 23.0, respectively. The findings indicate that 21 CRFs are significant in influencing RVR of highway PPP projects. Moreover, RVR from system dimension is mainly concentrating on institutional environment, macroeconomy, and relationship aspects, whereas financing in preconstruction, quality in construction, and market demand in operation are the most significant CRFs in nonsystem dimension. Furthermore, there is an accumulative exposure of RVR during the project process, especially in preconstruction and operation. This paper sheds light on the significance of lifecycle management on RVR and provides a practical approach for measuring RVR and implementing sustainable practice in highway or other transportation PPP projects. |
Copyright: | © 2019 Chuanjun Zheng et al. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10313349 - Published on:
13/05/2019 - Last updated on:
02/06/2021