Exploring the effect of city-level collaboration and knowledge networks on innovation: Evidence from energy conservation field

Abstract

• The study investigates the impact of city-level collaboration and knowledge networks on innovation. • We developed some new indicators of collaboration and knowledge networks that influence innovation. • We calculated cities’ influence force in inter-city collaboration networks by the weighted PageRank algorithm. • Knowledge network embeddedness of a city is measured by embedding depth and embedding breadth. • City-level collaboration and knowledge networks hold distinct structural characteristics and affect innovation in different ways and levels. Collaboration and knowledge networks have been proved to play a crucial role in innovation. From a multilevel network perspective, this study integrates research on the two types of networks and investigates how city-level collaboration and knowledge networks influence innovation in the energy conservation field. To this end, we calculate a city's influence force in its collaboration network based on the weighted PageRank algorithm and propose a novel measurement method of network embedding to gauge the embedding depth and embedding breadth of a city's local knowledge network in the whole knowledge network. Empirical results suggest that a city's aggregation index and influential force in the collaboration network are positively related to its innovation, while geographical distance shows an inverted U-shaped effect. The embedding depth and embedding breadth of a city's local knowledge network have a positive effect, and the structural entropy of its knowledge network generates an inverted U-shaped effect on innovation. Our research contributes to a better understanding of the impact of city-level collaboration and knowledge networks on innovation and points to several general implications for innovation practice and complex network research.