Presentation strategy of data analysis and knowledge for web-based decision support in sustainable urban development

Abstract

The need to measure and evaluate urban development has led to the development of numerous social-economic indicators. However, depending upon the large set of indicators, we find difficulties in interpreting the progress and often reach different conclusions regarding economic and social development of towns and evaluating the sustainability. The aim of the research reported in this paper was to develop the research methods and analysis tools for assessing and implementing the goals of sustainable urban development, including the presentation of information needed for decision making in the Internet. The research presented in this paper uses factor and cluster analysis methods to generate a set of underlying attributes (factors) that capture the sustainable urban development. Based upon the factor scores of systems’, the study finds the towns with similar characteristics (clusters). We demonstrate an application of the model using a database of economic and social development of towns in Lithuania.