Scrutinizing governments’ collaborative learning: Partner selection strategies and knowledge dimensions’ development

Abstract

Collaborative public innovation literature suggests that collaboration with multiple partners may provide the necessary learning to respond to the complex problems facing city governments. However, scarce research has been developed to (1) scrutinize the nature of the new knowledge needed by city governments, and (2) understand how the different types of partners contribute to government’s learning. This study shows that a government’s election of different types of partners influences the scope of the knowledge developed (knowledge breadth), the level of refinement of that knowledge (knowledge depth), and the extent to which knowledge is difficult to document in writing (knowledge tacitness).