Abstract: The construction industry is the pillar industry in
China, accounting for about 6% of the gross domestic product. Along
with changes in the external environment of the construction industry
in China, the construction firm faces fierce competition. The paper
aims to investigate the relationship between diversified types of
construction firm and its performance in China. Based on generalist
and specialist strategy in organizational ecology, we think a generalist
organization can be applied to an enterprise with diversified
developments, while specialist groups are extended to professional
enterprises .This study takes advantage of annual financial data of
listed construction firm to empirically verify the relationship between
diversification and corporation performance establishing a regression
equation to econometric analysis. We find that: 1) Specialization can
significantly improve the level of profitability of listed construction
firms, and there is a significant positive relationship with corporate
performance; 2) The level of operating performance of listed
construction enterprises which engage in unrelated diversification is
higher than those with related diversification; 3) The relationship
between state-owned construction firms and corporate performance is
negative. The more the year of foundation is, the higher performance
will be; however, the more the year of being listed, the lower
performance will be.
Abstract: This article analyses the relationship between
sovereign credit risk rating and gross domestic product for Central
and Eastern European Countries for the period 1996 – 2010. In order
to study the metioned relationship, we have used a numerical
transformation of the risk qualification, thus: we marked 0 the lowest
risk; then, we went on ascending, with a pace of 5, up to the score of
355 corresponding to the maximum risk. The used method of analysis
is that of econometric modelling with EViews 7.0. programme. This
software allows the analysis of data into a pannel type system,
involving a mix of periods of time and series of data for different
entities. The main conclusion of the work is the one confirming the
negative relationship between the sovereign credit risk and the gross
domestic product for the Central European and Eastern countries
during the reviewed period.
Abstract: In this paper we present an autoregressive model with
neural networks modeling and standard error backpropagation
algorithm training optimization in order to predict the gross domestic
product (GDP) growth rate of four countries. Specifically we propose
a kind of weighted regression, which can be used for econometric
purposes, where the initial inputs are multiplied by the neural
networks final optimum weights from input-hidden layer after the
training process. The forecasts are compared with those of the
ordinary autoregressive model and we conclude that the proposed
regression-s forecasting results outperform significant those of
autoregressive model in the out-of-sample period. The idea behind
this approach is to propose a parametric regression with weighted
variables in order to test for the statistical significance and the
magnitude of the estimated autoregressive coefficients and
simultaneously to estimate the forecasts.
Abstract: The service sector continues to grow and the percentage
of GDP accounted for by service industries keeps increasing. The
growth and importance of service to an economy is not just a
phenomenon of advanced economies, service is now a majority of the
world gross domestic products. However, the performance evaluation
process of new service development problems generally involves
uncertain and imprecise data. This paper presents a 2-tuple fuzzy
linguistic computing approach to dealing with heterogeneous
information and information loss problems while the processes of
subjective evaluation integration. The proposed method based on group
decision-making scenario to assist business managers in measuring
performance of new service development manipulates the
heterogeneity integration processes and avoids the information loss
effectively.
Abstract: Most people know through experience and intuition what the word „sport“ means. Sport includes a combination of these configurations when it involves team competitions, tournaments, or matches in dual sports or individual sports. Sport management - it is an area of professional endeavor in which a variety of sport-related managerial careers exist and it is also an area of academic professional preparation. Exists three unique aspects of sport management: sport marketing, sport enterprise financial structures and sport industry career paths. The aim of the paper was to highlight the growing importance of sport in contemporary society, especially to emphasize its socio-economic benefits and refer to the development of sport management and marketing. The article has shown that sport contributes 2-3% to gross domestic product in the Czech Republic and that the demand for experts, specialists educated for the sports manager profession is growing.
Abstract: An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.
Abstract: A free-trade agreement is found to increase Thailand-s
agricultural imports from New Zealand, despite the short span of
time for which the agreement has been operational. The finding is
described by autoregressive estimates that correct for possible unit
roots in the data. The agreement-s effect upon imports is also
estimated while considering an error-correction model of imports
against gross domestic product.
Abstract: The aim of this paper is to express the input-output
matrix as a linear ordering problem which is classified as an NP-hard
problem. We then use a Tabu search algorithm to find the best
permutation among sectors in the input-output matrix that will give
an optimal solution. This optimal permutation can be useful in
designing policies and strategies for economists and government in
their goal of maximizing the gross domestic product.