Systemic country differences in the European innovation performance - Does institutional context matter?

The so-called "High Performance Working System" (HPWS) and the lean production are representing the theoretical and methodological foundations of this paper. In this relation it is worth making distinction between various theoretical streams of the HPWS. The first theoretical stream in the literature is focusing on the diffusion of the Japanese-style management and organizational practices both in the US and in the Europe. The second theoretical strand comprises the approach of sociology of work and dealing with the learning/innovation capabilities of the new forms of work organization. Finally, the third theoretical approach is addressing on the types of knowledge and learning process and their relations with the innovation capabilities of the firm. The authors’ analysis is based on the international comparison, both in regional and in cross country comparison. For regional comparison the share of ICT clusters in Europe, USA and the rest of the world was assessed. For the purpose of the cross-country comparison in the EU, the innovation performance measured by the index Innovation Union Scoreboard (IUS) was used in both the before and after the financial crisis.

Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.

Modeling the fiscal impacts caused by climate change

Aim of the paper: The purpose is to gather the practices and to model the impacts of climate change on fiscal spending and revenues, responsibilities and opportunities, balance and debt related to climate change (CC). Methodology of the paper: The methodology will distinguish fiscal cost of mitigation and adaptation, besides direct and indirect costs. It will also introduce cost benefit analyses to evaluate the propensity of policy makers for action or passivity. Several scenarios will be drafted to see the different outcomes. The scenarios shall contain the possible losses in the natural and artificial environment and resources. Impacts on public budget are based on damage of income opportunities and capital/wealth/natural assets. There will be a list of actions when the fiscal correction of market failures will be necessary. Findings: There will be a summary and synthesis of estimation models on CC impacts on public finances, and morals of existing/existed budgeting practices on mitigation. The model will be based on damages (and maybe benefits) from CC, adjusted with probabilities of scenarios and policy making propensity for action. Findings will cover the way of funding of fiscal costs. Practical use, value added: From the synthesis of model, the fiscal cost of mitigation and adaptation can be estimated for any developed, emerging and developing countries. The paper will try to reply, also, for the challenge how to harmonize fiscal and developmental sustainability.