Client Learning and the Performance of Collaborative Infrastructure Projects
Author(s) -
Karen Manley,
Le Chen
Publication year - 2015
Publication title -
proceedings of the 2013 (4th) international conference on engineering, project, and production management
Language(s) - English
Resource type - Conference proceedings
DOI - 10.32738/ceppm.201509.0049
Subject(s) - procurement , underpinning , knowledge management , collaborative learning , transformative learning , computer science , conceptualization , integrated project delivery , empirical research , process management , project management , business , engineering , systems engineering , marketing , artificial intelligence , psychology , pedagogy , philosophy , civil engineering , epistemology
Australia is a leading user of collaborative procurement methods, which are used to deliver large and complex infrastructure projects. Project alliances, Early Contractor Involvement (ECI), and partnering are typical examples of collaborative procurement models. In order to increase procurement effectiveness and value for money (VfM), clients have adopted various learning strategies for new contract development. However client learning strategies and behaviours have not been systematically analysed before. Therefore, the current paper undertakes a literature review addressing the research question “How can client learning capabilities be effectively understood?”. From the resource-based and dynamic capability perspectives, this paper proposes that the collaborative learning capability (CLC) of clients drives procurement model evolution. Learning routines underpinning CLC carry out exploratory, transformative and exploitative learning phases associated with collaborative project delivery. This learning improves operating routines, and ultimately performance. The conceptualization of CLC and the three sequential learning phases is used to analyse the evidence in the construction management literature. The main contribution of this study is the presentation of a theoretical foundation for future empirical studies to unveil effective learning strategies, which help clients to improve the performance of collaborative projects in the dynamic infrastructure market.
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