How can innovation district performance be assessed? Insights from South East Queensland, Australia

Abstract

Purpose Many cities across the world are actively investing in ways to excel in the innovation economy through the development of innovation districts as one of the most popular policy options. While innovation districts are among the leading drivers of innovation activities in cities, they are also high-cost and high-risk investments. Besides, holistic approaches for assessing these districts’ multifaceted performances are scarce. Bridging this knowledge gap is critical, hence, this paper aims to explore how innovation district performance can be assessed through a classification framework. Design/methodology/approach The paper introduces a multidimensional innovation district classification framework and applies it into Australian innovation districts with divergent features, functions, spatial and contextual characteristics. The study places 30 innovation districts from South East Queensland under the microscope of the framework to assess the multifaceted nature of innovation district performance. It uses qualitative analysis method to analyse both the primary and secondary data, and descriptive analysis with basic excel spreadsheet calculations to analyse the validity of the data. Findings The data analysis clusters 30 innovation districts from South East Queensland under three performance levels – i.e. desired, acceptable and unsavoury – concerning their form, feature and function characteristics. Originality/value The results disclose that the framework is a practical tool for informing planners, developers and managers on innovation district performances, and it has the capability to provide guidance for policymakers on their policy and investment decisions regarding the most suitable innovation district types and characteristics to consider.

Assessing the Potential for Developing Innovation Districts at the City Scale by Adapting a New Sustainable Entrepreneurial Ecosystems Method

“…Yigitcanlar et al, pointed to a holistic approach for the performance classification of innovation districts through three key factors: (a) function, (b) feature, and (c) space use [19]. Based on this, Adu-McVie et al, proposed a case study matrix in terms of form, function, and features to classify the performance of the sample innovation districts in southeast Queensland [20]. Rapetti et al, presented key performance indicators (KPIs) that can be used to track and monitor the progress of an innovation district in distinct phases of development towards the achievement of its goals [21].…”