Search results for: Georgian wine market

Authors: Suffian H. Ayub, Mohammed R. Hamzah, Nor H. Abdullah, Sharipah N. Syed Azmy, Hishammudin S.

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The liberalisation of the education industry has exposed the institute of higher learning (IHL) in Malaysia to the financial challenges. Without good financial standing, public institution will rely on the government funding. Ostensibly, this contradicts with the government’s aspiration to make universities self-sufficient. With stiff competition from private institutes of higher learning, IHL need to be prepared at the forefront level. The corporate identity itself is the entrance to the world of higher learning and it is in this uniqueness, it will be able to distinguish itself from competitors. This paper examined the perception of the stakeholders at one of the public universities in the east coast region in Malaysia on the perceived reputation and how the university communicate its preparedness for self-sustainability through corporate identity. The findings indicated while the stakeholders embraced the challenges in facing the stiff competition and struggling market conditions, most of them felt the university should put more efforts in mobilising the corporate identity to its constituencies.

Keywords: Communication, corporate identity, market conditions, universities.

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Authors: Kamila Tislerova, Marta Zambochova

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Market segmentation is one of the most fundamental strategic marketing concepts. The better the segment which is chosen for targeting by a particular organisation, the more successful the organisation is assumed to be in the marketplace. Also higher education institutions have to improve their marketing tools for attracting foreign students, particularly when demanding tuition fees. This contribution aims at demonstrating the proper usage of the cluster analysis for segmentation (represented by students' willingness to study abroad) and also, based on large international survey, offers some practical marketing implications.

Keywords: Market Segmentation, Students' Preferences, Study Abroad, Cluster Analysis

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Authors: Van Chung Nguyen

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The purpose of this research is to study the current status of the value chain for fish distribution at Quang Binh Fishing Port with 360 research samples, in which the research subjects are fishermen, traders, retailers, and businesses. The research uses the approach of applying the value chain theoretical framework of Kaplinsky and Morris to quantify and describe market channels and actors participating in the value chain and analyze the value-added process of these companies according to market channels. The analysis results show that fishermen directly catch fish with high economic efficiency, but processing enterprises and, especially retailers, are the agents to obtain higher added value. Processing enterprises play a role that is not really clear due to outdated processing technology; in contrast, retailers have the highest added value. This shows that the added value of the fish supply chain at Quang Binh fishing port is still limited, leading to low output quality. Therefore, the selling price of fish to the market is still high compared to the abundant fish resources, leading to low consumption and limiting exports due to the quality of processing enterprises. This reduces demand and fishing capacity, and productivity is lower than potential. To improve the fish value chain at fishing ports, it is necessary to focus on improving product quality, strengthening linkages between actors, building brands and product consumption markets at the same time, improving the capacity of export processing enterprises.

Keywords: Quang Binh fishing port, value chain, fish market, distributions channel.

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Authors: Ching-I Chen

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The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system.

To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.

Keywords: Multiple-category purchase behavior, inter-purchase time, market basket analysis.

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Authors: Delaram Jarchi, Reza Boostani

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Linear Discrimination Analysis (LDA) is a linear solution for classification of two classes. In this paper, we propose a variant LDA method for multi-class problem which redefines the between class and within class scatter matrices by incorporating a weight function into each of them. The aim is to separate classes as much as possible in a situation that one class is well separated from other classes, incidentally, that class must have a little influence on classification. It has been suggested to alleviate influence of classes that are well separated by adding a weight into between class scatter matrix and within class scatter matrix. To obtain a simple and effective weight function, ordinary LDA between every two classes has been used in order to find Fisher discrimination value and passed it as an input into two weight functions and redefined between class and within class scatter matrices. Experimental results showed that our new LDA method improved classification rate, on glass, iris and wine datasets, in comparison to different versions of LDA.

Keywords: Discriminant vectors, weighted LDA, uncorrelation, principle components, Fisher-face method, Bootstarp method.

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Authors: Zdravka Aljinović, Branka Marasović, Blanka Škrabić

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The paper provides a discussion of the most relevant aspects of yield curve modeling. Two classes of models are considered: stochastic and parsimonious function based, through the approaches developed by Vasicek (1977) and Nelson and Siegel (1987). Yield curve estimates for Croatia are presented and their dynamics analyzed and finally, a comparative analysis of models is conducted.

Keywords: the term structure of interest rates, Vasicek model, Nelson-Siegel model, Croatian Government market.

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Authors: Chih Chin Yang

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The paper proposed a new theory of intellectual capital (so called IC) and a value approach in associated with production and market. After an in-depth review and research analysis of leading firms in this field, a holistic intellectual capital model is discussed, which involves transport, delivery supporting, and interface and systems of on intellectual capital. Through a quantity study, it is found that there is a significant relationship between the product value and infrastructure in a company. The product values are transferred from intellectual capital elements which includes three elements of content and the enterprise includes three elements of infrastructure in its market and product values of enterprise. 

Keywords: Enterprise, product value, intellectual capital.

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Authors: Nino Paresashvili, Nino Abesadze

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The modern world faces huge challenges. Globalization changed the socio-economic conditions of many countries. The current processes in the global environment have a different impact on countries with different cultures. However, an alleviation of poverty and improvement of living conditions is still the basic challenge for the majority of countries, because much of the population still lives under the official threshold of poverty. It is very important to stimulate youth employment. In order to prepare young people for the labour market, it is essential to provide them with the appropriate professional skills and knowledge. It is necessary to plan efficient activities for decreasing an unemployment rate and for developing the perfect mechanisms for regulation of a labour market. Such planning requires thorough study and analysis of existing reality, as well as development of corresponding mechanisms. Statistical analysis of unemployment is one of the main platforms for regulation of the labour market key mechanisms. The corresponding statistical methods should be used in the study process. Such methods are observation, gathering, grouping, and calculation of the generalized indicators. Unemployment is one of the most severe socioeconomic problems in Georgia. According to the past as well as the current statistics, unemployment rates always have been the most problematic issue to resolve for policy makers. Analytical works towards to the above-mentioned problem will be the basis for the next sustainable steps to solve the main problem. The results of the study showed that the choice of young people is not often due to their inclinations, their interests and the labour market demand. That is why the wrong professional orientation of young people in most cases leads to their unemployment. At the same time, it was shown that there are a number of professions in the labour market with a high demand because of the deficit the appropriate specialties. To achieve healthy competitiveness in youth employment, it is necessary to formulate regional employment programs with taking into account the regional infrastructure specifications.

Keywords: Unemployment. analysis, methods, tendencies, regulation mechanisms.

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Authors: Kunyaphat Thanakunwutthirot

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Bangnoi Floating Market located at Bangkhonthi Districts Samut Songkhram Province is a valuable architectural market. The lifestyle of the community's relationship with the living space and the relationship between the architectural style of the area's residential waterfront communities of Bangnoi Floating Bangkhonthi Districts Samut Songkhram Province, which deserves to be preserved. Therefore, this research it helps to know the value of the architectural style of the area's residential waterfront communities of Bangnoi Floating Bangkhonthi Districts SamutSongkhram Province, which deserves to be preserved.

Keywords: Bangnoi Floating Market, floor plan of riverside community architecture, riverside architectural identity, style of riverside community architecture utility space.

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Authors: I. Rodionov, A. Semenov, E. Gosteva, O. Sokolova

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The venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high-risk level. In the developed countries, it plays a key role in transforming innovation projects into successful businesses and creating the prosperity of the modern economy. In Russia, there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates; there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However, the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyse the influence of the previous round, such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. The most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the start-up teams that can attract more money on the start, and the target market growth is not the factor of crucial importance. This supports the point of view that VC in Russia is driven by endogenous factors and not by exogenous ones that are based on global market growth.

Keywords: Venture industry, venture investment, determinants of the venture sector development, IT-sector.

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Authors: Chimaobi V. Okolo, Kenneth A. Okpala, Johnbull S. Ogboi

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A teeming set of doctors that graduated from various universities within and outside Nigeria with the hope of practicing in the country, has their hope shattered because of poor financing, lack of medical equipments and a very weak healthcare systems. Such hydra headed challenges, allows room for quackery which increasingly contributes to the cause of mortality in Nigeria. With a view of reversing the challenges of healthcare delivery and financing in Nigeria, African Health Market for Equity (AHME), a project funded by the Bill and Melinda Gates foundation [With contribution from Department For International Development (DFID)] and currently implemented in three African Countries (Nigeria, Kenya and Ghana) over a Five (5) year period supports the healthcare sector via Medical credit fund (MCF). The study examines the impact of credit policy and medical credit funding on Nigerian health market. Ordinary least square analysis, correlation and granger causality tests were employed to measure the extent to which the Nigerian healthcare market has been influenced. Medical credit fund significantly and positively influenced average monthly turnover of private healthcare providers and Commercial bank’s lending rate had a weak relationship with access to credit/approved loans (13.46%). The programme has so far made 13.91% progress, which is very poor, considering the minimum targeted private health care providers (437.6) and expected number of loan approvals (180.4) for the two years. Medical credit policy in Nigeria should be revised to include private healthcare providers in rural area for more positive impact and increased returns. Good brand advert and sensitization of the programme to stakeholders and health pressure group, and an extension of the programme beyond five years is necessary to better address the issues raised in the study.

Keywords: Credit, health market, medical credit facility, policy.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Luísa P. Cruz-Lopes, Artur Figueirinha, Isabel Brás, Bruno Esteves

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Portugal is an important wine and olive oil producer, activities which generate a high quantity of residues commonly called grape stalks and olive cake, respectively. In this work grape stalks and olive cake were used as lignocellulosic adsorbents for wastewater containing lead treatment. To attain a better knowledge of the factors that could influence the quality of the treated wastewater, a chemical characterization of the materials used in the treatment was done. To access the ecotoxicological safety of the treated wastewater, several tests were performed.

The results of the toxicity test show that the samples leachate has a mild effect on the living models tested. The tests performed in lemna and bacteria were the most sensible to toxicity effects of the samples. The results obtained in this work evidenced the importance of use of simple and fast toxicity tests to predict impacts in the environment.

Keywords: Chemical composition, ecotoxicological, lignocellulosic residues, safety.

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Authors: Aparna Viswanath

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Electricity spot prices are highly volatile under optimal generation capacity scenarios due to factors such as nonstorability of electricity, peak demand at certain periods, generator outages, fuel uncertainty for renewable energy generators, huge investments and time needed for generation capacity expansion etc. As a result market participants are exposed to price and volume risk, which has led to the development of risk management practices. This paper provides an overview of risk management practices by market participants in electricity markets using financial derivatives.

Keywords: Financial Derivatives, Forward, Futures, Options, Risk Management.

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Authors: A. Appe, B. Poluparthi, L. Kasivajjula, U. Mv, S. Bagadi, P. Modi, A. Singh, H. Gunupudi, S. Troiano, J. Paul, J. Stovall, J. Yamamoto

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The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data are considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP (SHapley Additive exPlanations), to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since it is data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for e.g., quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP, a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: Competition, DAGs, hospital, healthcare, machine learning, market share, random forest, SHAP.

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Authors: Jana Chvalkovska, Petr Jansky, Petr Teply

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The impact assessment in its various forms has recently become a very important part of policy-making and legislation in many different countries. Regulatory impact assessment (RIA) is yet another set of analytical methods deployed in the legislation of the European Union, of many developed countries as well as in many developing ones such as Mexico, Malaysia and Philippines. The aim of this paper is to provide a theoretical background for economic models in regulatory impact assessment and an overview of their application especially on the financial market in the Czech Republic. We found out an inadequate application of these models, what makes room for further research in this field.

Keywords: regulatory impact assessment, RIA, impact evaluation, building societies, Czech Republic

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Authors: Markéta Gregušová, Vladimíra Schindlerová, Ivana Šajdlerová, Petr Mohyla, Jan Kedroň

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Company managers are always looking for more and more opportunities to succeed in today's fiercely competitive market. To maintain your place among the successful companies on the market today or to come up with a revolutionary business idea is much more difficult than before. Each new or improved method, tool, or approach that can improve the functioning of business processes or even of the entire system is worth checking and verification. The use of simulation in the design of manufacturing systems and their management in practice is one of the ways without increased risk, which makes it possible to find the optimal parameters of manufacturing processes and systems. The paper presents an example of use of simulation for solution of the bottleneck problem in the concrete company.

Keywords: Practical applications, business processes, systems, simulation.

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Authors: W. Sutopo, M. Hisjam, Yuniaristanto

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In general, small-scale vegetables farmers experience problems in improving the safety and quality of vegetables supplied to high-class consumers in modern retailers. They also lack of information to access market. The farmers group and/or cooperative (FGC) should be able to assist its members by providing training in handling and packing vegetables and enhancing marketing capabilities to sell commodities to the modern retailers. This study proposes an agri-food supply chain (ASC) model that involves the corporate social responsibility (CSR) activities to cultivate the capabilities of farmers to access market. Multi period ASC model is formulated as Weighted Goal Programming (WGP) to analyze the impacts of CSR programs to empower the FGCs in managing the small-scale vegetables farmers. The results show that the proposed model can be used to determine the priority of programs in order to maximize the four goals to be achieved in the CSR programs.

Keywords: agri-food supply chain, corporate social responsibility, small-scale vegetables farmers, weighted goal programming.

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Authors: A. Strateičuks, V. Kaže, R. Škapars

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State tax revenues in most countries started to decrease during the recession. Government of Latvia decided to compensate the decline by increasing rates of several taxes including excise tax on strong alcohol. The total increase in 2009 constituted 42% and the rate increased from 896€ to 1 266€ for 100l of absolute alcohol. Since then this has had a negative impact on consumption volumes and the split between legal and illegal market. The legal alcohol sales decreased by almost 50% (by volume), consequentially having negative effect on the State revenues from VAT and excise tax. Estimated results for 2010 are indicating 54 million € decrease in VAT, excise tax and other taxes versus 2008 (excise tax -19 million €, VAT -30 million €, other taxes -5 million €). The paper aims to analyze impact of the increase in excise tax on consumption patterns, State revenues and competitiveness of the local companies to draw up proposals for the state authorities regarding more effective tax policies. The analysis reveals a relationship between excise tax rate, illegal alcohol market and State revenues. The results can be used to improve excise tax system and effectiveness in Latvia.

Keywords: State revenues, alcohol market, excise tax, competitiveness, consumption.

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Authors: Tinatin Kurdghelashvili

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The paper deals with the usage of speech acts and politeness strategies in an EFL classroom in Georgia (Rep of). It explores the students’ and the teachers’ practice of the politeness strategies and the speech acts of apology, thanking, request, compliment / encouragement, command, agreeing / disagreeing, addressing and code switching. The research method includes observation as well as a questionnaire. The target group involves the students from Georgian public schools and two certified, experienced local English teachers. The analysis is based on Searle’s Speech Act Theory and Brown and Levinson’s politeness strategies. The findings show that the students have certain knowledge regarding politeness yet they fail to apply them in English communication. In addition, most of the speech acts from the classroom interaction are used by the teachers and not the students. Thereby, it is suggested that teachers should cultivate the students’ communicative competence and attempt to give them opportunities to practise more English speech acts than they do today.

Keywords: English as a foreign language, Georgia, politeness principles, speech acts.

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Authors: Larisa N. Pop, Irina M. Ban

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This paper aims to present the main instruments used in the economic literature for measuring the price risk, pointing out on the advantages brought by the conditional variance in this respect. The theoretical approach will be exemplified by elaborating an EGARCH model for the price returns of wheat, both on Romanian and on international market. To our knowledge, no previous empirical research, either on price risk measurement for the Romanian markets or studies that use the ARIMA-EGARCH methodology, have been conducted. After estimating the corresponding models, the paper will compare the estimated conditional variance on the two markets.

Keywords: conditional variance, GARCH models, price risk, volatility

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Authors: Nazira Kakulia, Tsotne Zhghenti

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The institutional development is one of the actual topics in economics science. New trends and directions of institutional development mostly depend on its structure and framework. Transformation of institutions is an important problem for every economy, especially for developing countries. The first research goal is to determine the importance and interactions between different institutions in Georgia. Using World Governance Indicators and Economic Freedom indexes it can be calculated the size for each institutional group. The second aim of this research is to evaluate Georgian institutional backwardness in comparison to other post-communist economies. We use statistical and econometric methods to evaluate the difference between the levels of institutional development in Georgia and in leading post-communist economies. Within the scope of this research, major findings are coefficients which are an assessment of their deviation (i.e. lag) of institutional indicators between Georgia and leading post-communist country which should be compared. The last part of the article includes analysis around the selected coefficients.

Keywords: Post-communist transition, institutions, economic growth, institutional development.

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Authors: Myungsook Klassen

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Training neural networks to capture an intrinsic property of a large volume of high dimensional data is a difficult task, as the training process is computationally expensive. Input attributes should be carefully selected to keep the dimensionality of input vectors relatively small. Technical indexes commonly used for stock market prediction using neural networks are investigated to determine its effectiveness as inputs. The feed forward neural network of Levenberg-Marquardt algorithm is applied to perform one step ahead forecasting of NASDAQ and Dow stock prices.

Keywords: Stock Market Prediction, Neural Networks, Levenberg-Marquadt Algorithm, Technical Indexes

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Authors: Jan Sindelar

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The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of lognormal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.

Keywords: Vector auto-regression, forecasting, financial, Bayesian, efficient markets.

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Authors: Peng Yew Wong

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House prices in the Australian capital cities were at record levels subsequent to Global Financial Crisis (GFC) 2008 and many believed that foreign investors, especially the Chinese investors, were the main reason for the Australian capital cities’ house prices escalation. This research conducted an Australian cross border semi-structured interviews in Shanghai, China to uncover historical evidence and emerging trend supporting the existence of a significant relationship between overseas investors and residential housing markets performance in Australia subsequent to the GFC 2008. Some unique investment strategies of private investors from China which emphasised on non-capitalist factors such as early education were identified, alongside with some insights on the significant China government policies that have incentivised the cross border investments from China. It is believed that this understanding will assist policy makers to effectively manage the overheated Australian residential property market without compromising the steady flow of FREI.

Keywords: Australian housing market, residential property, foreign real estate investment, education, China investor.

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Authors: Davinder Singh, Jaimal Singh Khamba, Tarun Nanda

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MSMEs are regarded as the sunrise sector of the Indian economy in view of its large potential for growth and likely socio economic impact specifically on employment and income generation. In today’s competitive business environment, global competition forces companies to continuously seek ways of improving their products and services. The pressure on organizations to adapt to new technologies and external threats requires resourcefulness, creativity and innovation. Market has become more open, competitive and customers more demanding. Without continuous technology innovation, no organization can ever remain competitive. Innovations reflect a critical way in which organizations respond to either technological or market challenges. The need of the market is to deliver high quality products through continuous changing in features in product, improve existing products, reduce their cost, and improve employee skills, training, technology infrastructure and financial policies. Therefore, the key factor of organization’s ability to change is innovation. The study presents a detailed review of literature on the role of technology innovation in improving manufacturing performance of industries.

Keywords: Competitive, Manufacturing performance, MSMEs, Technological Innovation.

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Authors: Yue-Yang Chen, Hui-Ling Huang, Wan-Yu Yu, Chung-Lun Wei

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In recent years, though, the concept of fit has been now in widespread used in strategic management research, it is in its infancy for applying fit concept to service innovation issue. Therefore, drawing on the concept of fit, this present research proposed an innovation service fit model within service innovation, market orientation, marketing strategy, and IT adoption are coexisted. The perspective of fit as covariation will be employed to test the hypothesis and identify the effects of fit. We contend that the fit among these four factors will contribution to business performance. Finally, according to the empirical data collected from manufacturing, service, and financial industry in Taiwan, meaningful findings and conclusions will be proposed and discussed.

Keywords: Service innovation, market orientation, IT adoption, marketing strategy, fit

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Authors: S. Al Wadi, Mohd Tahir Ismail, Samsul Ariffin Abdul Karim

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It is well known that during the developments in the economic sector and through the financial crises occur everywhere in the whole world, volatility measurement is the most important concept in financial time series. Therefore in this paper we discuss the volatility for Amman stocks market (Jordan) for certain period of time. Since wavelet transform is one of the most famous filtering methods and grows up very quickly in the last decade, we compare this method with the traditional technique, Fast Fourier transform to decide the best method for analyzing the volatility. The comparison will be done on some of the statistical properties by using Matlab program.

Keywords: Fast Fourier transforms, Haar wavelet transform, Matlab (Wavelet tools), stocks market, Volatility.

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Authors: Andrea Paltrinieri, Alberto Dreassi, Stefano Miani, Alex Sclip

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The financial crises caused a collapse in prices of most asset classes, raising the attention on alternative investments such as sukuk, a smaller, fast growing but often misunderstood market. We study diversification benefits of sukuk, their correlation with other asset classes and the effects of their inclusion in investment portfolios of institutional and retail investors, through a comprehensive comparison of their risk/return profiles during and after the financial crisis. We find a beneficial performance adjusted for the specific volatility together with a lower correlation especially during the financial crisis. The distribution of sukuk returns is positively skewed and leptokurtic, with a risk/return profile similarly to high yield bonds. Overall, our results suggest that sukuk present diversification opportunities, a significant volatility-adjusted performance and lower correlations especially during the financial crisis. Our findings are relevant for a number of institutional investors. Long term investors, such as life insurers would benefit from sukuk’s protective features during financial crisis yet keeping return and growth opportunities, whereas banks would gain due to their role of placers, advisors, market makers or underwriters.

Keywords: Asset allocation, asset performance, sukuk, zero beta asset.

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Authors: Aleksandre Ergeshidze

Abstract:

The exchange rate is a pivotal pricing instrument that simultaneously impacts various components of the economy. Depreciation of nominal exchange rate is export promoting, which might be a desired export-led growth policy, and particularly critical to closing-down the widening current account imbalance. However, negative effects resulting from high dollarization and high share of imported intermediate inputs can outweigh positive effect. The aim of this research is to quantify impact of change in nominal exchange rate and test contractionary depreciation hypothesis on Georgian economy using structural and Bayesian vector autoregression. According to the acquired results, appreciation of nominal exchange rate is expected to decrease inflation, monetary policy rate, interest rate on domestic currency loans and economic growth in the medium run; however, impact on economic growth in the short run is statistically not significant.

Keywords: Bayesian vector autoregression, contractionary depreciation, dollarization, nominal exchange rate, structural vector autoregression.

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