Identifying clusters of regions in the European South, based on their economic, social and environmental characteristics

Abstract

Regional development has been in the centre of interest among both academics but also decision makers in the central and local governments of many European countries. Identifying the key problems that regions face and considering how these findings could be effectively used as a basis for planning their development process are essential in order to improve the conditions in the European Union regions. For a long period of time a country’s or a region’s development has been synonymous with its economic growth. Over the last years, however, economies and societies have been undergoing dramatic changes. These changes have led to the concept of sustainable development, which refers to the ability of our societies to meet the needs of the present without sacrificing the ability of future generations to meet their own needs. Measuring sustainable development means going beyond a purely economic description of human activities; requires integration of economic, social and environmental concerns. New techniques are required in order to benchmark performance, highlight leaders and laggards on various aspects of development and facilitate efforts to identify best practices. Furthermore, new tools have to be designed so as to make sustainability decision-making more objective, systematic and rigorous. The growth or decline of a country or region depends on its power to pull and retain both business and the right blend of people to run them. Working in this context, we have so far defined a variable which is called the Image of a region and quantifies this pulling power. The region’s Image is a function of a multitude of factors physical, economic, social and environmental, some common for all potential movers and some specific for particular groups of them and expresses its present state of development and future prospects. The paper examines a number of south European countries and focuses on their NUTS 2 level regions. Its objective is to: • Estimate the Basic Image values of those regions. • Group those regions into different clusters on the basis of the values of the various factors used to define their respective Basic Images. • Present and discuss the results.