50th Congress of the European Regional Science Association: "Sustainable Regional Growth and Development in the Creative Knowledge Economy", 19-23 August 2010, Jönköping, Sweden
Greece is a country with noticeable regional disparities. Those disparities are due to a number of reasons, historic, socioeconomic, structural and geographic and create a series of adverse consequences, such as over congestion and environmental degradation in big urban areas on one hand, depopulation, unutilized resources, low income and unemployment in rural areas on the other. The need to bridge inequalities between Greek regions has been the focus of all regional policies implemented in Greece over the last 40-50 years. The main objectives of those policies were to limit further concentration of economic activities and population in large urban areas and ensure a well-balanced growth of all regions. Toward this end, regions were classified in various groups, on the basis of their state of development. Within this framework, large amounts of money have been spent to improve the infrastructure of less developed regions and to provide financial incentives to industries and employees so as to move into those regions. However, the results of those measures have been rather poor and the main reason for this were that the policies employed were ill-designed and addressed to regions unprepared to take full advantage of them. Hence, a first step towards improving this situation would be to define a measure giving the true picture of the region and the prospects of its sustainable development. This measure, the Image of a region, has already been defined (Angelis, 1980, 1990) and successfully applied (Mavri et al, 2009, Gaki et al, 2009, Angelis et al, 2010). In this paper we substantially improve the way of measuring a region's image and we show that it can be used as a basis for assessing the alternative paths for its future development and selecting the optimum. The method is applied to selected regions of Greece and the values of their Images have been calculated. Furthermore, starting from the Image value of each region at a given point in time, we draw the optimum path for its future development.