A Market and Spatial Perspective of Health Tourism Destinations: The Hungarian Experience

Since health tourism is one of the most popular and most dynamically developing products of modern tourism, this paper aims at studying the characteristic features of health tourism destinations from a regional and spatial perspective. Accordingly, the authors would like to introduce a new approach of spatial and product analysis of tourism where the market and spatial relations and relevance of health tourism were analysed through the example of Hungary. Although the classic medical tourism centres were established on natural medical water basis, by today, due to product diversification, continuous innovation and the involvement of medical services into health tourism, the geographical embeddedness seems to disappear, thus basically restructuring the market. The methodological novelty of the research is that exceeding the classic supply–demand algorithm, we compiled a complex viewpoint system adequate to the specialities of the given product characteristics. In our study, the authors intend to survey the special characteristics of health tourism focusing on medical destinations through Hungarian examples since the country's leading position in the global market is well recognized, including medical services. Copyright © 2014 John Wiley & Sons, Ltd.     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

The impact of ECB and FED announcements on the Euro interest rates

We investigate the impact of news in the ECB and FED monetary policy announcements on daily changes in Euro interest rates. We document significant impacts of ECB announcements throughout the period but only until mid 2004 of FED announcements.     

An empirical investigation into the gravitation and convergence of industry return rates in OECD countries

Tests are offered for the hypotheses that sectoral average profit rates and incremental return rates are gravitating around or converging towards a common value. We study data for various OECD countries relying on an econometric method able to account for residual autocorrelation and cross‐sector correlation. Our null hypotheses receive only a mixed empirical support. This is interpreted as the result of various kinds of limitations to capital mobility. Policy implications are discussed.     

Measurement of organizational investments in social capital: The service employee perspective

This paper describes the development and validation of a measure of organizational investments in social capital (OISC). The scale development process is carried out over three stages (item generation, scale purification, scale validation), with two separate data collection phases involving a total of 735 working adults from multiple and diverse service-related workplace settings. As such, the data provide evidence for the face, content, discriminant, convergent and nomological validity, dimensionality and reliability of the OISC measure. The OISC measure is a concise, unidimensional scale that has the potential for significant usage in the development and testing of theory, as well as practical application in retail and other service provision contexts.     

Schumpeterian patterns of innovation and the sources of breakthrough inventions: evidence from a data-set of R&D awards

This paper examines the relationship between Schumpeterian patterns of innovation and the generation of breakthrough inventions. Our data source for breakthrough inventions is the “R&D 100 awards” competition organized each year by the magazine Research & Development. Since 1963, this magazine has been awarding this prize to 100 most technologically significant new products available for sale or licensing in the year preceding the judgment. We use USPTO patent data to measure the relevant dimensions of the technological regime prevailing in each sector and, on this basis, we provide a characterization of each sector in terms of the Schumpeter Mark I/Schumpeter Mark II archetypes. Our main finding is that breakthrough inventions are more likely to emerge in ‘turbulent’ Schumpeter Mark I type of contexts.     

Employee stock ownership and financial performance in European countries: The moderating effects of uncertainty avoidance and social trust

This study investigates how the effect of employee stock ownership on financial performance may hinge on the diverse cultural and societal contexts of European countries. Based on agency and national culture theories, we hypothesize that the positive relationship between employee stock ownership and return on assets (ROA) is stronger in those nations with lower uncertainty avoidance and higher social trust. Using a multisource, time‐lagged, large‐scale dataset of 1,741 firms from 21 countries in Europe, our multilevel, random coefficient modeling analysis found evidence for these hypotheses, suggesting that uncertainty avoidance and social trust serve as important contextual cues in predicting the linkage between employee stock ownership and financial performance. Our supplemental analysis with distinction between the managerial and nonmanagerial employee stock ownership further indicates managerial employee stock ownership has a direct positive effect on ROA. Although nonmanagerial employee stock ownership had a nonsignificant association with ROA, the relationship was positive and significant when uncertainty avoidance was low and social trust was high. This research contributes to the existing literature by illuminating some of the contextual influences altering the effectiveness of employee stock ownership. Our findings also offer practical suggestions for effectively using employee stock ownership.     

Do the EU countries import at the same price? The case of coffee

The establishment of the Economic and Monetary Union was expected to determine price convergence in the market of the European Union, leading to the equilibrium theorized by the law of one price. This article investigates prices convergence in the coffee market among European importers. Coffee is not only a tradable and traded good, but also one of the most valuable traded commodities. We account for different qualities of coffee in a hedonic regression model, which isolate and remove the effects of factors that might affect price dispersion. Adjusted import prices result to be significantly different between European Member States, and do not support the hypothesis of a deepening European market integration.     

Quantitative and qualitative insights into consumers’ sustainable purchasing behaviour: a segmentation approach based on motives and heuristic cues

The present study draws on the concepts of motives and heuristics to thoroughly understand consumers’ sustainable consumption behaviour in the context of personal care products. The mixed-methods approach combines real purchasing data with in-depth qualitative data to generate insights with a high external validity. In the first section of the study, quantitative analysis is applied to actual purchasing behaviour (n = 10,772,477) to identify market trends. Three main groupings, along with specific heuristic cues, are established. In the second step, a qualitative study (n = 21) provides deeper insights into consumers’ motives and decision-making processes. By synthesising the quantitative and qualitative research findings, a segmentation approach is developed. Relevant motives and values, and corresponding specific heuristic cues are identified for each consumer segment. Analysis suggests that consumers are motivated by self-interest and environmental motives, and that they use simple heuristic cues to make quick and satisfying purchasing decisions. Both retailers and manufacturers can leverage these insights to seize the opportunities of the developing market for sustainable personal care products.