Small towns as 'sub-poles' in English rural development: Investigating rural-urban linkages using sub-regional social accounting matrices

This paper uses spatial economic data from four small English towns to measure the strength of economic integration between town and hinterland and to estimate the magnitude of town-hinterland spill-over effects. Following estimation of local integration indicators and inter-locale flows, sub-regional social accounting matrices (SAMs) are developed to estimate the strength of local employment and output multipliers for various economic sectors. The potential value of a town as a 'sub-pole' in local economic development is shown to be dependent on structural differences in the local economy, such as the particular mix of firms within towns. Although the multipliers are generally small, indicating a low level of local linkages, some sectors, particularly financial services and banking, show consistently higher multipliers for both output and employment. (c) 2007 Elsevier Ltd. All rights reserved.

Factors affecting regional SMEs progression to Digital Business Ecosystems

SMEs are widely recognized as an important driving force of economic growth, yet, their uptake of ICT is still very low. Tosupport SMEs ICT adoption and to foster regional development, in 2000, the Lisbon Strategy on the Information Society andKnowledge-based economy created a vision for 2010 towards the creation of the European Digital Business Ecosystems(DBE). This paper is positioned within that context and reports upon a project involving 6000 SMEs whose aim was tosupport ICT adoption and to encourage SME networks through the creation of a Regional Business Portal. The papere xplores factors affecting the regional SMEs participating in the DBE. An in-depth longitudinal case study approach was adopted and multiple sources of evidence were used. Many factors affecting SMEs progression to DBE were identified:including people and organization, environmental, diffusion networks, technological, regional and time factors

Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

Decadal predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy and society. The present study examines the decadal predictability of regional wind speed and wind energy potentials in three generations of the MiKlip (‘Mittelfristige Klimaprognosen’) decadal prediction system. The system is based on the global Max-Planck-Institute Earth System Model (MPI-ESM), and the three generations differ primarily in the ocean initialisation. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess the forecast skill for 10 m wind speeds and wind energy output (Eout) over Central Europe with lead times from one year to one decade. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD-simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. This forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skills of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer and persist longest in autumn. A large-scale westerly weather type with strong pressure gradients over Central Europe is identified as potential source of the skill for wind energy potentials, showing a similar forecast skill and a high correlation with Eout anomalies. These results are promising towards the establishment of a decadal prediction system for wind energy applications over Central Europe.