The Port of Rotterdam is a major European hub for trade, logistics, energy, and industry. As the port faces increasing pressure from the energy transition, digitalisation, climate ambitions, and international competition, innovation has become essential for maintaining its competitiveness. Coordinating innovation within the port, however, is challenging because numerous stakeholders with different objectives and interests are involved. Leader firms play a particularly important role, as their investments, technological capabilities, and strategic decisions can shape innovation trajectories across the wider port cluster. For the Port of Rotterdam Authority (PoRA), understanding leader firm priorities is therefore essential for effective innovation coordination.

Although previous research highlights the importance of innovation ecosystems and the role of leader firms in port innovation, relatively little is known about how leader firms prioritise competing innovation proposals or how these priorities can be identified when firms are reluctant to share strategic information. This thesis investigates whether Discrete Choice Modelling (DCM), implemented through a Discrete Choice Experiment (DCE), can reveal leader firm preferences and trade-offs in a way that supports innovation coordination.

The research combines three complementary perspectives. First, Key Enabling Technologies (KETs) are used to map the technological positioning of leader firms. Second, an Innovation Readiness Framework structures the criteria used to evaluate innovation proposals. Third, a DCE quantifies the relative importance of these readiness criteria in innovation decision-making. The empirical analysis is based on a technology-domain mapping of 71 anonymised leader firms using public company information and patent data, complemented by an online survey containing KET-related questions and a DCE completed by 31 respondents with management, innovation, strategy, or business development responsibilities.

The results show that leader firms are unevenly distributed across technological domains, with Digital and Information Technologies, Chemical Technologies, and Engineering and Fabrication Technologies being most prominent. Patent-based technological activity and self-reported technological interests do not always coincide, suggesting that established capabilities and future innovation directions differ. The DCE indicates that commercial readiness has the strongest positive influence on proposal attractiveness, followed by legal readiness, business readiness, and social acceptance readiness, while technological readiness, although important, is not the dominant decision criterion. The study also demonstrates that obtaining reliable insights into leader firm priorities depends strongly on relational access, with personal networks and bridging ties proving substantially more effective than general contact routes.

Overall, this thesis demonstrates that DCM provides a valuable decision-support approach for innovation coordination by making leader firms' underlying prioritisation trade-offs explicit. When combined with insights into firms' technological positioning and the network relationships required to engage relevant decision-makers, the approach can support more informed strategic learning and innovation coordination within the Port of Rotterdam. While the findings are indicative because of the limited sample size and hypothetical choice setting, they provide a practical foundation for improving coordination between the PoRA and leader firms. ... Read more