Collective Bargaining on Employment Security: The Influence of the Legal Framework

Employers’ organisations and trade unions (also called the social partners) are given a central role to play in the specification of employment security into concrete regulations through collective bargaining. The question is how employment security can be implemented through collective bargaining. This contribution builds on the assumption that collective bargaining outcomes are influenced by inter alia political, socio-economic, and legal constrains. The chapter seeks to explore the legal framework of collective bargaining in which employment security is (to be) developed and to point out the ways in which this framework can have an effect on employment security and the way it is being shaped

Credit scoring and decision making in Egyptian public sector banks

Purpose – The main aims of this paper are: first, to investigate how decisions are currently made within the Egyptian public sector environment; and, second, to determine whether the decision making can be significantly improved through the use of credit scoring models. A subsidiary aim is to analyze the impact of different proportions of sub-samples of accepted credit applicants on both efficient decision making and the optimal choice of credit scoring techniques. Design/methodology/approach – Following an investigative phase to identify relevant variables in the sector, the research proceeds to an evaluative phase, in which an analysis is undertaken of real data sets (comprising 1,262 applicants), provided by the commercial public sector banks in Egypt. Two types of neural nets are used, and correspondingly two types of conventional techniques are applied. The use of two evaluative measures/criteria: average correct classification (ACC) rate and estimated misclassification cost (EMC) under different misclassification cost (MC) ratios are investigated. Findings – The currently used approach is based on personal judgement. Statistical scoring techniques are shown to provide more efficient classification results than the currently used judgemental techniques. Furthermore, neural net models give better ACC rates, but the optimal choice of techniques depends on the MC ratio. The probabilistic neural net (PNN) is preferred for a lower cost ratio, whilst the multiple discriminant analysis (MDA) is the preferred choice for a higher ratio. Thus, there is a role for MDA as well as neural nets. There is evidence of statistically significant differences between advanced scoring models and conventional models. Research limitations/implications – Future research could investigate the use of further evaluative measures, such as the area under the ROC curve and GINI coefficient techniques and more statistical techniques, such as genetic and fuzzy programming. The plan is to enlarge the data set. Practical implications – There is a huge financial benefit from applying these scoring models to Egyptian public sector banks, for at present only judgemental techniques are being applied in credit evaluation processes. Hence, these techniques can be introduced to support the bank credit decision makers. Originality/value – Thie paper reveals a set of key variables culturally relevant to the Egyptian environment, and provides an evaluation of personal loans in the Egyptian public sector banking environment, in which (to the best of the author's knowledge) no other authors have studied the use of sophisticated statistical credit scoring techniques

Bone phenotyping approaches in human, mice and zebrafish - expert overview of the EU cost action GEMSTONE ("GEnomics of MusculoSkeletal traits TranslatiOnal NEtwork")

A synoptic overview of scientific methods applied in bone and associated research fields across species has yet to be published. Experts from the EU Cost Action GEMSTONE (“GEnomics of MusculoSkeletal Traits translational Network”) Working Group 2 present an overview of the routine techniques as well as clinical and research approaches employed to characterize bone phenotypes in humans and selected animal models (mice and zebrafish) of health and disease. The goal is consolidation of knowledge and a map for future research. This expert paper provides a comprehensive overview of state-of-the-art technologies to investigate bone properties in humans and animals – including their strengths and weaknesses. New research methodologies are outlined and future strategies are discussed to combine phenotypic with rapidly developing –omics data in order to advance musculoskeletal research and move towards “personalised medicine”