Green innovation in mega transportation infrastructure projects (MTI-GI) requires balancing technological progress and economic growth with environmental protection and sustainable development. Due to the multiple participants, temporary project-based arrangements and significant spillover effects, innovation actors form highly complex and dynamic collaborative networks under the obligation of shared responsibilities. This research aims to analyze the structural characteristics and dynamic evolution of multi-actor collaborative networks of green innovation in mega transportation infrastructure projects, thereby revealing how collaborative relationships operate as a network mechanism within megaproject-based organizations.
The research compiles relevant cases from the Zhan Tianyou Award to build a database and extracts collaboration data to construct the MTI-GI collaborative network. Descriptive statistics present the temporal and spatial characteristics of the case data. Complex network modeling, including social network analysis (SNA) and the Barrat, Barthélemy and Vespignani (BBV) model, is employed to measure the static structural features and dynamic evolutionary pathways.
The results indicated that the past decade (i.e. 2014–2023) was pivotal for MTI-GI development. Rail transit and railway projects are the most active in implementing green innovation, and the innovation actors are distributed mainly across relatively developed regions and relatively less developed yet strategically important areas. SNA metrics revealed that the MTI-GI collaborative network remains weakly connected overall and presents a clear scale-free pattern. This underscores the dominant role of state-owned enterprises in capability-driven and responsibility-supported innovation within the temporary, multi-level and multi-stakeholder context of megaprojects. BBV evolutionary analysis further indicated that a larger evolutionary scale, preferential attachment based on comprehensive strength and fewer cooperative ties of new entrants reinforce the scale-free properties of the collaborative network. Moreover, the MTI-GI collaboration network demonstrates its dynamic feature of enabling an adaptive balance between short-term project collaboration and long-term governance capacity.
The findings of this research enhance the understanding of green innovation network governance in megaproject-based organizations and offer more refined strategies for managing multi-actor collaboration in complex systems.
