The effectiveness of fiscal spending in Croatia,Slovenia and Serbia: the role of trade openness and public debt level

Various structural characteristics of economies, directly or indirectly, affect the transmission from government stimuli to economic activity and determine the size of fiscal multipliers. In this article, we expand the standard Blanchard–Perotti fiscal SVAR model by incorporating the public debt and trade openness variables to assess the influence of these structural determinants on the effectiveness of fiscal spending in three selected former Yugoslav countries – Slovenia, Croatia and Serbia. The results confirmed the main hypotheses, which state that public debt level and trade openness significantly affect the effectiveness of fiscal spending through the means of reduction in size of fiscal effects in all countries analysed. When comparing internationally, this reduction tends to be more evident in countries with a higher degree of average public debt level and trade openness.     

Managing safety risks in helicopter maritime operations

Nowadays, helicopters have been used in maritime transportation to serve offshore platforms. This paper outlines methodology for assessing safety risks by operating in the vicinity of helidecks. During each flight, decisions must be made regarding the events that involve interactions between the four safety risk elements – the pilot in command, the aircraft, the environment and the operation. This paper evaluates helicopter crash statistics based on region and flight phase. Data collected were used for developing methodology for computing the helicopter impact frequency into facility of interest. The analysis for helicopter impact frequency calculations is based on number of operations, crash rate, frequency, average length of flight and crash area. Furthermore, the conclusion was defined based on future measurements for helicopter accidents mitigation or reduction. The presented paper contributes to safety risk assessment in helicopter maritime operations.     

An Empirical Investigation of Brand Equity: A Cross-Country Validation Analysis

ABSTRACT

The purpose of this article is to propose and test a model in order to better understand brand equity. The goal of this research is to identify the drivers and determine how they influence brand equity performance in the researched industry in order to develop a more effective brand strategy. Quantitative data collected are used to test a model of brand value in the context of the food industry. The findings of this research provided evidence that the customer-based brand equity model can be applied to the food industry context and be used to guide marketing activities internationally. Brand awareness has a positive influence on brand associations and perceived quality. Brand associations have a positive influence on brand loyalty. Finally, brand loyalty, perceived quality, and brand associations all have a positive effect on brand equity. This study contributes to the scarce international brand equity literature by testing the proposed model using data from a sample of consumers in two European countries.     

Conceptual and mathematical model for quality improvement in health care

Numerous studies have shown that implemented models for quality assurance or improvement in healthcare facilities differ, even those models that are based on the same guidelines, i.e. standards, regulations or concepts. The cause of diversity in implemented quality models could be found in the process of translating guidelines into the implemented model for quality assurance or improvements in healthcare facilities, while neglecting processes of healthcare facilities that are not clinical processes, but still responsible for the quality of healthcare services. Therefore, this research recommends a conceptual model that should be a link between guidelines, implemented models and mathematical models derived from the conceptual model, which could provide a means of evaluating quality values of any part of the healthcare organization.     

A new non-linear AR(1) time series model having approximate beta marginals

We consider the mixed AR(1) time series model $$X_t=\left\{\begin{array}{ll}\alpha X_{t-1}+ \xi_t \quad {\rm w.p.} \qquad \frac{\alpha^p}{\alpha^p-\beta ^p},\\ \beta X_{t-1} + \xi_{t} \quad {\rm w.p.} \quad -\frac{\beta^p}{\alpha^p-\beta ^p} \end{array}\right.$$ for ?1 < β ^p ≤ 0 ≤ α ^p  < 1 and α ^p ? β ^p  > 0 when X _t has the two-parameter beta distribution B₂(p, q) with parameters q > 1 and ${p \in \mathcal P(u,v)}$ , where $$\mathcal P(u,v) = \left\{u/v : u < v,\,u,v\,{\rm odd\,positive\,integers} \right\}.$$ Special attention is given to the case p = 1. Using Laplace transform and suitable approximation procedures, we prove that the distribution of innovation sequence for p = 1 can be approximated by the uniform discrete distribution and that for ${p \in \mathcal P(u,v)}$ can be approximated by a continuous distribution. We also consider estimation issues of the model.     

Going beyond the traditional destination competitiveness – reflections on a smart destination in the current research

ABSTRACT

This paper reviews the literature on tourism destination competitiveness from different aspects, focusing on comparative and competitive advantages. Also, the paper highlights the importance of information and communication technologies (ICTs) in tourism destinations and their increasing impact on the achievement of destination competitiveness. Thanks to the wider application of ICTs in tourism, tourists nowadays are well informed and have access to global market which creates a new dynamic environment by creating a smart demand. Since smartness emphasizes on ICT-based tools, including smartness integration for value co-creation, it can increase and enhance destination competitiveness. In this regard, special emphasis is placed on exploring the core components of smartness and smart tourism destination.     

Modelling driver propensity for traffic accidents: a comparison of multiple regression analysis and fuzzy approach

Abstract

This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver’s psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver’s propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.     

Economic growth and carbon emissions: evidence from CIVETS countries

ABSTRACT

This paper examines whether a long-run relationship exists between CO₂ emissions and selected variables: real gross domestic product per capita, inward stock of foreign direct investments, gross fixed capital formation, industry, value added and energy use per capita for Colombia, Indonesia, Viet Nam, Egypt, Turkey and South Africa countries in the period of 1989–2016. We used panel unit root testing, followed by panel cointegration tests and panel causality. The results clearly prove the existence of a bidirectional long-run causal relationship between all the variables except between CO₂ emissions and GDP and CO₂ emissions and GFCF. Major finding of the short-run causality analysis is that CO₂ emission in the short run does not result in changes of other variables. On the other hand, all variables except foreign direct investments (FDI) cause the changes in the CO₂ emissions, and there is a positive bidirectional causal relationship between GDP and FDI, between GFCF and FDI, and between GFCF and IVA. Finally, positive unidirectional causal relationship also exists, running from GDP to IVA, GDP to ENUSE, IVA to FDI and ENUSE to FDI.     

Determination of the most influential factors for number of patents prediction by adaptive neuro-fuzzy technique

Number of patents may be developed on the basis on different natural and science and technological factors. Number of patents prediction based on the different factors in many countries is analyzed in this investigation. These factors represent natural and science resources. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data in order to select the most influential factors for the number of patents prediction. Five inputs are considered: research and development (R&D) resources, natural resources, quality of academic institutions, quality of collaboration with the private sector and quality of education. As the ANFIS output, number of patents is considered. The ANFIS process for variable selection is also implemented in order to detect the predominant factors affecting the prediction of number of patents. Results show that the R&D is the most influential factor for the number of patents prediction.     

A study on the competitive strategy of the universal postal service provider

We analysed how the universal postal service providers could employ their specificities to achieve an advantage over the growing competition. The basic input for the model is expert opinions. We interviewed 18 experts in five stages. As a multiple criteria decision support method, we used an analytic hierarchy process. Further, we proposed a geometric method for determining the business area where a company should focus its biggest attention to achieve the best result. By implementing the proposed model, a company should obtain two types of business directions, the first related to the proposed activities and the second to the business areas. To demonstrate the applicability of the proposed methodology, we tested and verified it in the case of the Serbian universal postal service provider which is a state-owned company called the Post of Serbia.