Comparison of Localisation Motives for R&;D Investment of Multinational Enterprises in the New and Old EU Member Regions

The issue of localisation motives is one of the key topics in attracting and motivating MNEs to establish or enhance their R&D activities abroad. The paper aims to compare localisation motives for R&D investment of multinational enterprises in the new and old EU member regions and to find out main localization motives differences among them. We have found out the key motives were technology/supply side factors, which strongly influence decision-making at MNEs in locating and maintaining R&D in all regions. In the more developed regions, the localisation is positively influenced also by the presence of other important/large (high-tech) companies and important universities in the region, which provide relevant services to MNEs. Localisation decisions in the new EU member regions were positively influenced particularly by presence of a quality and cheap labour force and a suitable R&D infrastructure and experience in R&D in these regions. Considerable differences between the old and new EU member states reflects their distinctive economic history, recent re-opening of their economies and consequences of the process of post-communist transition.     

The main features of population development in the Czech Republic during the transformation of society

"The behaviour of the population of the Czech Republic has been changing since 1991. The changes have resulted in a considerable decrease in marriages and births, and a slight fall in mortality rates. The decline in the number of newly-weds and new-born children can be attributed to significant structural changes in society connected with the transformation of the reproductive model established in the post war era. The changes have been initiated most notably by the younger generation...."     

Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case

Abstract. In general, the risk of joint extreme outcomes in financial markets can be expressed as a function of the tail dependence function of a high‐dimensional vector after standardizing marginals. Hence, it is of importance to model and estimate tail dependence functions. Even for moderate dimension, non‐parametrically estimating a tail dependence function is very inefficient and fitting a parametric model to tail dependence functions is not robust. In this paper, we propose a semi‐parametric model for (asymptotically dependent) tail dependence functions via an elliptical copula. Under this model assumption, we propose a novel estimator for the tail dependence function, which proves favourable compared to the empirical tail dependence function estimator, both theoretically and empirically.     

Scheduling professionals in the retail pharmacy chain

To control operating costs, a zero-one integer programming model is developed to assist pharmacy staff scheduling decisions. Variable scheduling needs are met by the assignment of relief (mobile) pharmacists to help or temporarily replace full-time pharmacists. Assignments of relief pharmacists over a two-week planning horizon are determined with consideration given to variations in wage rates and travel costs together with the underlying corporate, contractual and operating constraints. The developed model has been applied with considerable success using data collected from a business district in the US located in northern Louisiana related to a national retail chain pharmacy. Forecasting the number of chain retail outlets in the near future has been also performed and the results obtained argue in favor of adopting the model by the entire chain.