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Media channels impact in brand indicators in Romania

Abstract

Finding the main influencers in brand indicators is a challenge for every marketing manager and researchers working in the branding investments area. How much to invest, which is the proper media channel mix or what is the influence of brand heritage are the questions of interest and which the paper responds to. Therefore, this paper is aiming to analyze the brand performance indicators in 2018 (awareness, trial and usage) for over 700 brands in Romania based on their investment on each media channel for 2014-2018 period and 2014 brand indicators. As for characterization of media investment 47 variables were retained, principal component analysis was used for reducing factors of influence. Thus, four main components were retrieved: media investment in absolute measures, main and second proportion in terms of media channel mix, and qualitative aspects of the brand. In conclusion, some multivariate regressions were built for identifying impact on each 2018 brand indicator using the four principal components and 2014 levels of the brand indicators.

Open access
Model of analysis of the evolution of international economic exchanges

Abstract

The economic activity of a country is achieved both by domestic activity and by international economic and technical-scientific exchanges. International commercial activity is a necessary one nowadays. This is because there is no state capable of performing an autarchic activity. Regardless of of the technical, scientific, resource, and level of development, any state needs to participate in international economic, technical and scientific exchanges. Through international economic exchanges, the need for resources, means of production, labor resources or goods and services is completed. Also in this economic activity of international exchanges is realized the capitalization of surplus production, goods and services, surplus fixed capital, which is offered for export or as a possibility of cooperation in international projects. Thus, the activity of international exchanges is a necessity for each state. Under the conditions of the European Union, in which Romania is a member, there are a number of facilities and in this respect they are being implemented or are being implemented under the European Directive on trade without borders. In this respect, between the Community countries, in the exchange of goods and services, protection measures such as the import tax are no longer practiced and VAT is no longer charged. The international economic exchanges are a significant role in the final result materialized in the level of gross domestic product achieved in each period of time. The countries that import and do it to supplement domestic needs means that they spend part of the value realized in domestic activity to make imports. The exports are made with surplus goods and services that go to other states. In the European Union there are intra-community economic exchanges, complemented by extra-community international economic relations. The authors have studied this aspect and have found that intra-community economic relations have developed more intensively than non-EU economic relations over the last period. In other respects, states are grouped into two categories, ie states with surplus international economic relations, ie states that export more than imports and the second group, countries with activities in the international deficient relations, which imports more than just exports. Comparison between exports and imports results in net exports that may be a surplus or deficit. Romania has always been a deficit country since 1990 and it has to be analyzed in the sense that, due to the difference in favor of imports, part of the gross domestic product made in Romania diminishes with this deficit. The authors, by analyzing this data, highlight how the activity of international economic exchanges has evolved.

Open access
Modelling monthly Gross Domestic Product on the supply side. A case study for Romania

Abstract

This paper aims to estimate monthly Gross Domestic Product (GDP1), which is an important aggregate indicator; It shows the trend of economic activity in the short term. Thus, the macroeconomic and financial risks in the short term with influences on financial markets and investor confidence (economic sentiment) can be identified and correlated. In addition, the monthly GDP series provides a condensed set of information (monthly data) needed to develop potential GDP estimating models correlated with inflation, unemployment and relevant indicators of labor market. Another applicability is quarterly GDP forecast at least two months ahead of the flash estimate published by National Institute of Statistics (NIS2). This article presents a method of estimating the monthly GDP on the supply side. Gross value added has been broken down into five components: industry, construction, trade and transport, other market services, other activities, the first four of which are well interpolated with unifactorial regressions and some monthly explanatory variables. The results show a high correlation between the 4 components of supply and the additional aggregated quarterly series that are also available on a monthly basis. The highest dynamics of monthly GDP was recorded in August 2017 (+9.3%) and the lowest increase in August 2014 (+1.4%) over the period 2014-2018. Starting in January 2018, economic growth slow down, amid a pronounced base effect of the private consumption and weakening external demand.

Open access
On building early-warning systems for preventing the deterioration of financial institutions’ performance

Abstract

This paper assesses the financial performance of Romania’s non-banking financial institutions (NFIs) using a neural network training algorithm proposed by Kohonen, namely the Self-Organizing Maps algorithm. The algorithm takes the financial dataset and positiones each observation into a self-organizing map (a two-dimensional map) which can be latter used to visualize the trajectories of an individual NFI and explain it based on different performance dimensions, such as capital adequacy, assets’ quality and profitability. Further, we use the map as an early-warning system that would accurately forecast the NFIs future performance (whether they would stay or be eliminated from the NFI’s Special Register three quarters into the future). The results are promising: the model is able to correctly predict NFIs’ performance movements. Finally, we compared the results of our SOM-based model with those obtained by applying a multivariate logit-based model. The SOM model performed worse in discriminating the NFIs’ performance: the performance classes were not clearly defined and the model lacked the interpretability of the results. In the contrary, the multivariate logit coefficients have nice interpretability and an individual default probability estimate is obtained for each new observation. However, we can benefit from the results of both techniques: the visualization capabilities of the SOM model and the interpretability of multivariate logit-based model.

Open access
On the exhaustive generation of generalized ballot sequences in lexicographic and Gray code order

Abstract

A generalized (resp. p-ary) ballot sequence is a sequence over the set of non-negative integers (resp. integers less than p) where in any of its prefixes each positive integer i occurs at most as often as any integer less than i. We show that the Reected Gray Code order induces a cyclic 3-adjacent Gray code on both, the set of fixed length generalized ballot sequences and p-ary ballot sequences when p is even, that is, ordered list where consecutive sequences (regarding the list cyclically) differ in at most 3 adjacent positions. Non-trivial efficient generating algorithms for these ballot sequences, in lexicographic order and for the obtained Gray codes, are also presented.

Open access
On the largest part size and its multiplicity of a random integer partition

Abstract

Let λ be a partition of the positive integer n chosen uniformly at random among all such partitions. Let Ln = L n(λ) and M n = M n(λ) be the largest part size and its multiplicity, respectively. For large n, we focus on a comparison between the partition statistics L n and L n M n. In terms of convergence in distribution, we show that they behave in the same way. However, it turns out that the expectation of L n M nL n grows as fast as 12logn. We obtain a precise asymptotic expansion for this expectation and conclude with an open problem arising from this study.

Open access
Perspectives of the development of world economy in the blockchain conditions and Big Data

Abstract

Blockchain is a concept that tends to revolutionize the world of finance in a technological leap that allows fast, secure and decentralized transactions. The Blockchain technology is used in virtual coins (bitcoin) conditions, with a high innovation potential, applicable in various areas, with the advantage of storing databases, resulting in an unprecedented level of transparency in the private or public area. Interestingly, under the bitcoin conditions, the black chain system uses a decentralized peer-to-peer payment system. Practically, the bitcoin can be considered as the most appropriate triple game accounting system. All of these considerations are developing in the big data era, which is defined as a large, diverse, high-volume information base requiring new forms of processing. Big data is important for businesses because based on these, strategic and marketing decisions can be made to optimize the activity in the market conditions and consumer preferences. European Union directives provide for measures to ensure the development of all states and, in this context, the community. At the same time, some measures provide for a more accelerated development for states with a low accession. For this, funds have been made from which important amounts are allocated to these states. The complex development of the European Union aims, in fact, to improve the quality of life (standard of living) in all Member States. At the European community level there are databases usable in economic analyzes. Also, Eurostat is the institution with the most complex databases. Recently, the Conference of the Directors of the Institute of Statistics in the European States analyzed the perspective of calculating the indicators in the context of the big data to be implemented. The article focuses on the concrete study of the use of large data in the calculation of the indicators that underlie the comparability between the EU Member States.

Open access
Possibilities of statistical analysis of hotel activity performance in a competitive environment

Abstract

The hotel industry is an important driver in tourism development of a region, with positive effects on economic growth, concentrating to a large extent the regional tourism services. The quality of services in this sector is decisive for improving the hotel activity performance, especially in terms of a competitive environment increasingly well defined. The service quality is directly proportional to the hotel comfort category. In 2018 Romania had 34 five-star hotels and 359 four-star hotels, representing less than a quarter of all hotels (24.32%). They owned just over 30% of the total number of hotel bed-places. This paper provides a statistical analysis of activity in the hotel industry in Romania, focusing on main elements of its performance, in terms of a competitive environment. As a result of a case-study on the employees of high comfort category hotels in Bucharest, the key elements of a performing activity are revealed, in order to obtain a competitive advantage.

Open access
Possibilities to quantify the road traffic on the national road network and motorways in Romania

Abstract

As a result of the economic crisis of 2009-2010, the road traffic on the national road network, for the period 2011-2014, decreased considerably. Thus, the evolution coefficients, for the period 2020-2025, registered a trend of decrease in road traffic.

Based on the analysis of the results of the automatic traffic records, it was found that the average daily average traffic increased by about 4.7% in 2016 compared to 2015 (the year of the last general circulation census) and is in continuous growth, one of the reasons being removal of car registration tax. In 2015, for the development of evolution coefficients and the rates of evolution of traffic on the national road network, the linear regression method was used which took into account both the evolution of road traffic reported in 1995, 2000, 2005 and 2010, as well as the evolution of road traffic on the traffic counters network for the period 2010-2015.

The paper analyzes aspects of the efficiency of the method used until the present and the need to develop coefficients and rates of evolution based on more complex methods, based on several economic and social indicators, including the projected evolution of GDP.

Open access
Post-Crisis Household Savings Behavior in Romania

Abstract

The recent linear growth trend recorded by net savings in Romania is very intriguing. We thus study household savings behavior using Vector Autoregression and Vector Error Correction models on a sample of post-2007 monthly data. Contrary to common economic theory, we find that real interest rates do not influence the loan and savings behavior of Romanian households in our sample, despite their significant volatility and, even, negative recorded values. The results indicate a change in attitude and in risk perception of Romanian households in the aftermath of the financial crisis in 2008, in the way that has significantly decreased their preference for present consumption in favor of savings. Despite the significant increase in net savings, we also find that they have not significantly contributed to economic growth.

Open access