Firm and project innovation outcome measures in infrastructure megaprojects: An interpretive structural modelling approach

Xiaoyan Chen, Giorgio Locatelli, Xinyue Zhang, Yunhao Gong and Qinghua He

Technovation, 2022, vol. 109, issue C

Abstract: Infrastructure megaprojects are characterised by huge investment, vast complexity in technical and organisational terms, and extensive innovation. Innovation outcomes have been extensively investigated at the owner/operator and project-based firm/supplier levels (both combined shortly named ‘firm-level’), with the project-level being far less studied and the simultaneously study of firm and project innovation being a knowledge gap. Considering the case of infrastructure megaprojects in China, this paper identifies infrastructure megaprojects' innovation outcome measures at both the firm-level and project-level simultaneously and investigates their relationships. This paper employs a mixed-method approach leveraging interpretive structural modelling (ISM) and the matrix of cross-impact multiplications analysis. The model derives 22 innovation outcome measures, divided into five hierarchy levels, describing owner-level, supplier-level, and project-level innovation in infrastructure megaprojects. Five measures have the greatest driving power: 1) Creation or improvement in construction technology, 2) Creation or improvement in the construction process, 3) Creation of new construction standards, 4) Creation or improvement of contract form, and 5) Creation or improvement in financial arrangements. The results can help researchers and practitioners better understand how to evaluate and manage innovations at both the firm-level and project-level in infrastructure megaprojects.

Keywords: Infrastructure megaprojects; Innovation outcomes; Measures; Relationships; Project innovation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:109:y:2022:i:c:s0166497221001309

DOI: 10.1016/j.technovation.2021.102349

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