City intelligence for enhancing urban performance value: a conceptual study on data decomposition in smart cities

Abstract

The contemporary ‘digital age’ prompts the need for a re-assessment of urban planning principles and practices. Against the background of current data-rich urban planning, this study seeks to address the question whether an appropriate methodological underpinning can be provided for smart city governance based on a data-driven planning perspective. It posits that the current digital technology age has a drastic impact on city strategies and calls for a multi-faceted perspective on future urban development, termed here the ‘XXQ-principle’ (which seeks to attain the highest possible level of quality for urban life). Heterogeneity in urban objectives and data embodied in the XXQ-principle can be systematically addressed by a process of data decomposition (based on a ‘cascade principle’), so that first, higher-level urban policy domains are equipped with the necessary (‘big’) data provisions, followed by lower-ranking urban governance levels. The conceptual decomposition principle can then be translated into a comprehensive hierarchical model architecture for urban intelligence based on the ‘flying disc’ model, including key performance indicators (KPIs). This new model maps out the socio-economic arena of a complex urban system according to the above cascade system. The design of this urban system architecture and the complex mutual connections between its subsystems is based on the ‘blowing-up’ principle that originates from a methodological deconstruction-reconstruction paradigm in the social sciences. The paper advocates the systematic application of this principle to enhance the performance of smart cities, called the XXQ performance value. This study is not empirical, although it is inspired by a wealth of previous empirical research. It aims to advance conceptual and methodological thinking on principles of smart urban planning.