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The authors contribute to the literature on leadership by investigating how characteristics of principal investigators (PIs) affect innovation performance, and how collaborative and non-collaborative projects moderate this relationship within the context of inter-organisational research projects.

The authors analysed panel data from the National Science and Technology Information Service on 171 research projects within a biomedical and regenerative medicines programme overseen by the Korea Health Industry Development Institute. The authors used a hierarchical regression model, based on the ordinary least squares method, to examine the relationship between PI characteristics and performance, considering both quantity and quality.

The results show that the characteristics of PIs have diverse effects on the quantity and quality of innovation performance. Gender diversity within PIs negatively affects the quality of innovation performance, while the capacity of PIs positively influences it. Moreover, the degree of PI’s engagement is positively associated with the quantity of innovation performance but does not have a significant relationship with the quality of performance. In terms of moderating effects, collaborative projects with multiple leaders seem less reliant on PI capacity than non-collaborative projects led by a single leader, in terms of innovation performance.

The results contribute significantly to the literature on innovation management by examining the role of leadership in collaborative environments to enhance innovation performance, addressing the need for empirical evidence in this area. Analyses of PI characteristics in government R&D management can lead to improved team performance, more efficient processes and effective resource allocation, ultimately fostering innovation.

The purpose of this study was to investigate and propose the appropriate K‐mapping models as an approach to integrating key project components and technologies for the effective improvement of project performance within and across construction projects.

In this holistic, single‐case study, one of the largest construction consulting firms in South Korea has been studied by conducting 15 semi‐structured interviews and the different loci for each of the K‐mapping components are identified and analyzed. Based on the different loci, four types of the K‐mapping model are provided and elucidated.

Research findings indicate that these four types of the K‐mapping model provide the criteria to identify the appropriate types of K‐map for construction project organizations, according to the characteristics and conditions of their own construction personnel, construction processes, and K‐transfer technologies. With the K‐mapping models, an appropriate knowledge management system (KMS) can be developed more effectively.

First, as interpretivism was adopted as the research philosophy, the case study findings were subjective and qualitative to both the interviewees in the case study company and the researchers, though this study provided an important underpinning for future research on K‐mapping within construction project organizations. Second, the theory developed in this study was based on an investigation of the appropriate K‐mapping models with only a single case study. Nevertheless, this case study provided sufficient data and information to develop and propose a theory for successful K‐mapping model development within construction project organizations.

In the KM area, the definition, benefits, purposes, principles and types of K‐map have been already provided by many KM researchers and practitioners. However, no industry (practical)‐based K‐mapping model has been developed and proposed, especially in the construction industry. Accordingly, the originality of this study to be presented in one of the paper's conclusions: construction processes must be considered and adopted as a key component in the K‐mapping process, and the discussion of the four types of K‐map this research have generated, which significantly expands the existing literature on K‐mapping.