L. Papayannakis

Bio: L. Papayannakis is an academic researcher from National Technical University of Athens. The author has contributed to research in topics: Multiple-criteria decision analysis & Higher education. The author has an hindex of 6, co-authored 7 publications receiving 982 citations.

A multicriteria approach for evaluating the performance of industrial firms

Abstract: Multivariate techniques have been widely used for the explanation and prediction of the firm's behaviour. However, in practice, the comparative evaluation and ranking of companies is usually based on the consideration of a single measure of corporate success. But the definition of the most appropriate measure gave rise to a considerable debate. This paper tries to utilise the results of a multicriteria analysis, applied to a large sample of Greek pharmaceutical industries, in order to indicate how suitable some common financial ratios are as indices of the firm's overall performance. The results show that profitability constitutes the most representative measure for the differentiation and ranking of companies. Labour productivity and market share are the best indicators of the business' success, while business' failure is more closely related to ratios indicating long- and short-term solvency. This means that a sound capital structure is a necessary but not a sufficient enough condition to ensure the profitable and effective operation of the firm.

Fostering entrepreneurship education in engineering curricula in Greece. Experience and challenges for a Technical University

Abstract: While entrepreneurship has emerged as an important mechanism for the generation of social returns in terms of economic growth and job creation, entrepreneurship education is still something new in Europe and the debate about the need and the way of introduction of specific entrepreneurship courses in higher education is on going. This paper deals with the introduction of entrepreneurship education in engineering curricula. More specific it presents the experience of the National Technical University in Greece, as a case in point for discussing the need of an interdisciplinary approach in designing engineering curricula. The main argument is that the introduction of entrepreneurship education in University curricula should not result as an application of policy initiatives only related to economic imperatives. It should be part of a more general discussion related to educational priorities and of a strategic design of University curricula in order to provide engineers with entrepreneurial and management sk...

The European commission

Abstract: 2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters

Abstract: Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper applies support vector machines (SVMs) to the bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use a grid-search technique using 5-fold cross-validation to find out the optimal parameter values of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM, we compare its performance with those of multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.