An Urban Management Approach Based on Socioenomic Geostatistical Modeling

Cities are organic entities and as such; have to be managed with appropriate data, systems and an effective decision making process. To be effective, management processes have to have access to updated data, and be able to convert that data into information, and transform the information into knowledge. Urban management decisions within the domains of physical, environmental, cultural and socioeconomic have profound impact upon the people and their cities. A monitoring process, as well as a measurement mechanism is needed to provide feedback on the level of impact of these decisions, on short term, mid term, and long term policies. In this paper a geo-statistical modeling approach is proposed for the development, and measurement of a socioeconomic indicator. The proposed indicator is to be used within a conceptual framework of an urban management decision support environment, which can utilize the indicator for monitoring the impact of policy decisions and the evaluation of alternate/future scenarios. The analytical framework to design the indicator, uses spatial (i.e. location based), and non spatial/attribute data, this data is processed through a series of statistical and geo-statistical operations, and is transformed into a measurable socioeconomic location based indicator. The research methodology follows a close path with that of the Six Sigma, by way of first starting to investigate the needs, requirements and definitions, as well as the successes and short comings with in the domain of the urban management through the literature review process. The activities performed in this stage are close to the activities described in the Six Sigma Definition Phase. A measurement process of physical, environmental, cultural, and socioeconomic variables/parameters is proposed. The main activities of this stage are the design of data collection instruments (i.e. survey questionnaires) which are used to collect the parameters of interest through a data collection process. The activities performed in this stage are similar to the Measurement Phase of the Six Sigma. Within the analytical framework in this paper, a combination of statistica l and geo-statistical processes define, a model for the computation of a composite socioeconomic location based indicator, as with Six Sigma, the research analytical stage, relies upon the outputs of the literature review (Six Sigma Definition Phase), and the questionnaire design plus data collection activities (Six Sigma Measurement Phase) to investigate the underlying pattern of relationships between the variables, and determining the extent and form of these relationships. The variables relationships are represented as models/formulas, and the extent is identified by the weight of the coefficients of the parameters, the output is the proposed indicator. The indicator is to be used within a conceptual framework of an urban management decision support environment, which can utilize the indicator for monitoring the impact of policy decisions and the evaluation of alternate or future scenarios. This is the same conceptual framework as outlined by The Six Sigma Monitoring & Improvement Phase.

An Urban Management Approach Based on Socioenomic Geostatistical Modeling Keywords:

Six Sigma , urban management , geo-statistical modeling , socioeconomic indicator , decision support environment