Decision tree of indicator benchmark: A hybrid method for assessing cities’ performance through urban indicators and benchmark

Abstract

The rapid process of urbanization has brought out a series of challenges in urban governance, which prompts an increasing number of studies focusing on monitoring and evaluating the status of the cities. However, the detailed illustration of the establishment of a scientific-made basis for setting cities’ indicators benchmarks is often overlooked or inadequately explained in previous studies. Therefore, this study proposes a hybrid method to determine the benchmark for assessing cities’ performance. Firstly, this study establishes a mechanism called the Decision Tree of Indicator Benchmark (DTIB) which incorporates decision tree theory and benchmark management theory for urban indicator benchmark determination. Then, a deviation-degree-based model is proposed for assessing the performance of each indicator and the AHP method is applied for attaining the comprehensive performance of the city. To verify the effectiveness of the proposed hybrid method, an empirical study is conducted, and a comparison between the proposed method with other traditional evaluation methods is made to demonstrate the advantages of the proposed method. This hybrid method can facilitate decision-makers to understand the status of a city and explore the underlying problems of urban development to design more tailored policies and plans for cities.