Achieving destination competitiveness: an importance–performance analysis of Serbia

As a relatively new and under-researched tourism destination, Serbia provides an interesting context to assess destination competitiveness in conditions of global environmental changes and the additional challenges of transition from a socialist economy to a market-based economy. This article uses importance–performance analysis (IPA) to assess the importance of different activities to underpin tourism development in Serbia, as well as the industry's perceived performance in respect of these activities. There are a number of areas in which Serbian tourism industry considers itself to be underperforming in the implementation of activities to maintain destination competitiveness. This article analyses these results in detail using IPA as a diagnostic tool. Particular attention is paid to investigating the implications of the findings for both destination managers and private tourism operators in Serbia that can assist them to develop a focused action agenda to achieve and maintain destination competitive advantage. The approach can be used in other destinations to assess tourism ability to meet the challenges of global trends.     

Functional Foods and the Young

Factors such as raised consciousness about human health, development of the food industry, and medicine and branches of natural science studying the relation between nutrition and health have led to the popularization of foods with proven health effects. Such foods are called functional foods. Although there is growing interest in functional foods, there are several groups of consumers that are, more than others, interested in functional foods. To examine buying behavior and attitudes toward functional food of young consumers (18–30 years old) and to determine the most interested consumers, we conducted a survey using a self-administered questionnaire on a sample of 570 Croatian students. The majority of the respondents purchase functional foods, usually in supermarkets. Apart from taste, the most important functional food attribute is price/quality ratio. Respondents are buying functional foods because they believe that those foods are healthier and safer than other products. Examined market segments were based on respondents’ attitudes toward functional foods. The results of this research could be used in planning further development of the functional foods market for young consumers.     

TEMPORARY EMIGRATION AND WELFARE: THE CASE OF LOW‐SKILLED LABOR

This article studies the implications of temporary emigration for the welfare of a source country. The framework is one of general equilibrium, where the economy's stocks of both capital and labor are endogenously determined by the saving and migration decisions of optimizing agents. Simulations of the model suggest that for realistic values of the parameters, welfare of nonmigrants of the source country is maximized when the migrants are employed abroad for a period in the range of roughly 8–12 years. The ideal duration is found to be an increasing function of the international wage differential, migration costs, and the degree to which the rights of migrants are protected in the host country.     

Markov decision processes under model uncertainty

We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle, we obtain a local-to-global paradigm, namely solving a local, that is, a one time-step robust optimization problem leads to an optimizer of the global (i.e., infinite time-steps) robust stochastic optimal control problem, as well as to a corresponding worst-case measure. Moreover, we apply this framework to portfolio optimization involving data of the . We present two different types of ambiguity sets; one is fully data-driven given by a Wasserstein-ball around the empirical measure, the second one is described by a parametric set of multivariate normal distributions, where the corresponding uncertainty sets of the parameters are estimated from the data. It turns out that in scenarios where the market is volatile or bearish, the optimal portfolio strategies from the corresponding robust optimization problem outperforms the ones without model uncertainty, showcasing the importance of taking model uncertainty into account.     

Forecasting high-frequency excess stock returns via data analytics and machine learning

Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via various machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long-term analysis (short-term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.     

Intersectional organizing: Building solidarity through radical confrontation

IR scholars reference intersectionality in relation to organizing, but the field lacks a theoretical construct. Based on 2 years of intimate data access, we examine the 2017 U.S. Women's March as a critical case of “intersectional organizing.” We ground this empirical case study in Critical Race and Intersectionality Theory to show how the intersectional organizing model employed by the Women's March handles identity-based fragmentation, with lessons for building a more inclusive labor movement.     

The role of satisfaction in labor diaspora dynamics: An analysis of BREXIT effects

In diaspora research, people's international mobility is often understood as a response to pull-push forces on an economic macro-level or as part of diasporic waves. However, labor diaspora formations are also influenced by micro-level (i.e., individual perceptions) drivers related to work per se, such as satisfaction. This explorative qualitative study takes a novel angle and focuses on the role of Portuguese nurses’ satisfaction with the evaluation of the Brexit scenario and its effects on this labor diaspora's mobility and stability. The findings illustrate that satisfaction, although affected by uncertainty, mainly relates to perceived working conditions and legislation and the possibilities to communicate with locals and other diasporans. This paper provides suggestions for future research and contributes to the development of theory on staying and human stickiness, explaining the dynamics of exit and entry in (re-)migration decision making.     

Entrepreneurial decision-making perspectives in transition economies – tendencies towards risky/rational decision-making

International Entrepreneurship and Management Journal - This paper assesses the ways in which the characteristics of entrepreneurs from transition economies, and the extent to which they...     

How Wealthy are the Rich?

Underreporting and undersampling biases in top tail wealth, although widely acknowledged, have not been statistically quantified so far, essentially because they are not readily observable. Here we exploit the functional form of power law-like regimes in top tail wealth to derive analytical expressions for these biases, and use German microdata from a popular survey and rich list to illustrate that tiny differences in non-response rates lead to tail wealth estimates that differ by an order of magnitude, in our case ranging from 1 to 9 trillion euros. Underreporting seriously compounds the problem, and we find that the estimation of totals in scale-free systems oftentimes tends to be spurious. Our findings also suggest that recent debates on the existence of scale- or type-dependence in returns to wealth are ill-posed because the available data cannot discriminate between scale- or type-dependence, on one hand, and statistical biases, on the other hand. Yet both economic theory and mathematical formalism indicate that sampling and reporting biases are more plausible explanations for the observed data than scale- or type-dependence.