Madalina Constantinescu

Many mathematical models have been developed in the last years in order to analyze economic phenomena and processes. Some of these models are optimization models, static or dynamic, while others are developed specially to study the evolution of economic phenomena. The topic of this paper is forecasting with nonlinear models. A few well-known nonlinear models are introduced, and their properties are discussed. The variety of nonlinear relationships is important both from the perspective of estimation and from the precision of forecasts in the medium and especially long term. Most nonlinear forecasting methods and all methods based on neural networks lead to predictions that have a better quality than the forecasts obtained by linear methods. The last section of this paper contains a detailed study of the relationship between inflation and unemployment and a numerical application with numerical data from Romania.

Creativity has recently joined innovation and becomes a key term in knowledge-based economy debates. In the last decades, organisations are more and more confronted with complex innovation challenges. The main objective of this research is to provide a comprehensive view of the current state of research and practices regarding the development of knowledge-based economy: innovation as a key driver in wealth creation; how to maximise creativity and innovation in any individual, organisation, region or economy. Another objective of the paper addresses this within the context of how information technology (IT) can aid the transformation process of knowledge. In our study we also analyse the impacts and dimensions of knowledge management (KM) upon the innovation and labour productivity within the organisation and how KM affects the firm's innovative performance.