Sources of local knowledge spillover within the Algarve tourism region: evidence to identify a regional innovation system

Tourism sector in Algarve region is the main engine of regional economy. Although frequently, tourism is considered as a low – moderate innovative sector, tourism competitiveness is still highly dependent on specific features of a Regional Innovation Platform, highlighting the crucial importance of knowledge creation and diffusion, learning, cooperative and collaborative interaction that may evolve to a Regional Innovation System (RIS). Studies of Local Knowledge Spillovers have been frequently focused on empirical evidence provided by regions highly related with manufacturing sectors. Considering a case study in Tourism Algarve Region, emphasizing a theoretical character on the analysis of these areas and using a qualitative methodology, the goal of this study was to provide preliminary evidence of the main sources and vehicles of regional knowledge spillovers used by tourism enterprises. Main information has been obtained using primary information collected from 20 interviews over main stakeholders regarding regional private and public sector. Primary information was complemented with secondary information, a deeply and extensive bibliography revision and also statistical information. Results show that, on the one hand, main sources of knowledge used by micro and small tourism enterprises are human resources and formal and informal networks. On the other hand, large tourism companies are weakly related with regional sources using mainly internal company and economic group resources to generate innovation activities. Regional innovation platform shows clear weaknesses on linkages and coordinated initiatives to promote and support innovation performance of firms hampering to increase tourism competitiveness and regional development.

Generate disaggregated soil allocation data using a Minimum Cross Entropy Model

Montado ecosystem in the Alentejo Region, south of Portugal, has enormous agro-ecological and economics heterogeneities. A definition of homogeneous sub-units among this heterogeneous ecosystem was made, but for them is disposal only partial statistical information about soil allocation agro-forestry activities. The paper proposal is to recover the unknown soil allocation at each homogeneous sub-unit, disaggregating a complete data set for the Montado ecosystem area using incomplete information at sub-units level. The methodological framework is based on a Generalized Maximum Entropy approach, which is developed in thee steps concerning the specification of a r order Markov process, the estimates of aggregate transition probabilities and the disaggregation data to recover the unknown soil allocation at each homogeneous sub-units. The results quality is evaluated using the predicted absolute deviation (PAD) and the "Disagegation Information Gain" (DIG) and shows very acceptable estimation errors.