• Journal of Digital Convergence
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• v.19 no.11
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• pp.445-456
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• 2021

The purpose of this study is to identify the importance of variables affecting women's golf wear sales with macroeconomic variables and consumer selling prices that affect consumers' purchasing behavior, and to propose a price strategy to increase sales of golf wear. Data of domestic women's golf wear brands were analyzed using decision tree algorithms and ensemble. Consumer selling price is the most significant factors in terms of sales volume for T-shirt, pants and knit, while categories were found to be the most important factors in addition to consumer sales prices for skirt and one piece dress. These findings suggest that items have different economic variables that affect consumers' purchasing behavior, suggesting that sales and profits can be maximized through appropriate price strategies.

• Economic Analysis
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• v.26 no.4
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• pp.98-136
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• 2020

We empirically investigate the determinants of a firm's exit from exporting, using Korean manufacturing firm-level data for the period from 2006 to 2014. Specifically, we estimate the effects of not only firm-level and industry-level characteristics, but also macroeconomic variables on the probability that a firm stops exporting by applying a Complementary Log-Log Model analysis. The results of our estimation suggest that firm-level heterogeneity, such as workforce size, capital intensity, intangible assets and foreign ownership, industry-level variation, such as the labor displacement rate, and macroeconomic variables, such as domestic demand and world demand, significantly affect the possibility of a firm ceasing exports. Also, we show that market interest rates increase the possibility of an export cessation and that the effects of market interest rates are more pronounced on firms with a higher debt ratio. In the primary exporting industries, the probability of a firm ceasing exports decreases as productivity at the firm rises.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.5
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• pp.779-803
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• 2023

The growth of digital news media and the stock price index has resulted in economic fluctuations in the fashion industry. This study examines the impact of fashion industry news and macroeconomic changes on the Textile & Wearing Apparel KOSPI over the past five years. An auto-regressive integrated moving average exogenous time series model was conducted using the fashion industry stock market index, the news topic index, and macro-economic indicators. The results indicated the topics of "Cosmetic business expansion" and "Digital innovation" impacted the Textile & Wearing Apparel KOSPI after one week, and the topics of "Pop-up store," "Entry into the Chinese fashion market," and "Fashion week and trade show" affected it after two weeks. Moreover, the topics of "Cosmetic business expansion" and "Entry into the Chinese fashion market" were statistically significant in the macroeconomic environment. Regarding the effect relation of Textile & Wearing Apparel KOSPI, "Cosmetic business expansion," "Entry into the Chinese fashion market," and consumer price fluctuation showed negative effects, while the private consumption change rate, producer price fluctuation, and unemployment change rate had positive effects. This study analyzes the impact of media framing on fashion industry business cycles and provides practical insights into managing stock market risk for fashion companies.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.162-170
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• 2006

Neural network analysis is expected to enhance the forecasting ability for the real estate market. This paper reviews definition, structure, strengths and weaknesses of neural network analysis, and verifies the applicability of neural network analysis for the real estate market. Neural network analysis is compared with regression analysis using the same sample data. The analyses model the macroeconomic parameters that influence the sales price of apartments. The results show that neural network analysis provides better forecasting accuracy than regression analysis does, what confirms the applicability of neural network analysis for the real estate market.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.3
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• pp.57-65
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• 2016

The purpose of this paper is to investigate the volatility of both Islamic and conventional stock market in Indonesia with the aim of identifying the most appropriate model for risk management practice. The study considers GARCH as a genre of model to measure the volatility of stock market movement. The results support the view that each model shows specific volatility from both Islamic and conventional stock market in Indonesia. In Islamic stock market, volatility is affected by exchange rate and money supply (M1) but not interest rate as interest is prohibited in Islam. However, interest rate is found as a principal factor that affects volatility of conventional stock market. The outcomes of this paper are of particular significance to policy makers, as it provides guidelines to maintain economic health. Furthermore, the findings may assist practitioners to understand the consequences of macroeconomic factors such as exchange rate, money supply and interest rate, which are very crucial for the market stability of Indonesian stock market. The paper enhances the understanding of stock market volatility and proposes guidelines risk management practices.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.15-24
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• 2018

Purpose - The adjustment of one country's monetary policy can cause the macroeconomic change of other countries. Due to this, this paper attempts to analyze the impact of China's monetary policy on South Korea's exchange rate. Research design, data, and methodology - Based on the flexible-price monetary model, sets of annual time series from 1980 to 2017 are employed to perform an empirical estimation. The vector error correction model is also used to exploit the short-run relationship between both of them. Of course, the South Korea's real GDP, the China's real GDP, South Korea's interest rate, the South Korea's interest rate and the South Korea's monetary supply are treated as independent variables in this paper. Result - The long-run findings reveal that the China's money supply has a negative effect on South Korea's exchange rate. Respectively, the short-run findings depicts that the China's money supply has negative a effect on South Korea's exchange rate. Of course, other variables selected in this paper also have an effect on South Korea's exchange rate whatever positive or negative. Conclusions - As the empirical evidence shows, the China's monetary policy has a negative effect on South Korea's exchange rate whenever in the long run or in the short run.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.2
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• pp.5-12
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• 2015

The authors calculate the long-term predictability of GDP, domestic demand, investment, and net exports for Guangdong province, P.R. China from 2000 to 2013. A vector autoregressive (VAR) model with quarterly data for this period is first co-integrated then the Granger causality test is applied to empirically assess the relationships among gross domestic product (GDP), consumption, investment, and net exports. There is a strong causality effect between investment and net exports in Guangdong province. However, the variance decomposition results indicate that exports respond to foreign shocks rather than domestic ones, making their impact on the Guangdong economy to predict. Results show the stimulating effect of domestic demand on GDP is larger than the stimulating effect of net exports and much larger than even the stimulating effect of investment. The analysis suggests that there are dynamic influences with various levels of persistence between GDP, consumption, investment, and net exports. Macroeconomic policy adjustments are urgently required to expand domestic demand and thereby stimulate economic growth in Guangdong province.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.895-904
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• 2021

This study aims to investigate the impact of innovation on firm efficiency. Panel data of fourteen finance companies and nine technology companies from 2011 to 2019 on the Vietnam Stock Exchange Market is derived from audited financial statements, annual reports, and other crucial reports that are provided by Vietstock; macroeconomic variables are collected from the World Bank Database. A two-stage approach is used. First, use of the Data Envelopment Analysis methodology to measure firm efficiency. Second, use of the Pooled ordinary least squares, the Fixed effects model, and the Random effects model to investigate the impact of innovation on firm efficiency. Furthermore, the Generalized Method of Moments and the Tobit model are used to validate the impact of innovation on firm efficiency, and the t-test is used to confirm the difference in efficiency with and without the impact of innovation between two industries. The results show that there is a significant impact of innovation on efficiency, and innovation plays a more important in increasing the efficiency of the finance industry than the technology industry. Moreover, the relation between age and efficiency is like the U-shaped, and between size and efficiency is like the inverted U-shaped, whereas efficiency is not associated with inflation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.480-488
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• 2016

As the subprime mortgage crisis spread globally, it depressed not only the financial market, but also the construction business in Korea. In fact, according to CERIK, the BSI of the construction businesses plunged from 80 points in December 2006 to 14.6 points in November 2008, and the extent of the depression in the housing sector was particularly serious. In this respect, this paper analyzes the influence of the financial market fluctuation on the housing market before and after the Global Financial Crisis using VECM. The periods from January 2000 to December 2007 and January 2008 to October 2015, before and after the financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, when the economy is good, the Gangnam housing market is an attractive one for investment. However, when it is depressed, the Gangnam housing market changes in response to the macroeconomic fluctuations. Second, the Gangbuk and Gangnam housing markets showed different responses to fluctuations in the financial market. Third, when the economy is bad, the effect of low interest rates is limited, due to the housing market risk.

• The Journal of Society for e-Business Studies
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• v.1 no.1
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• pp.27-50
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• 1996

In this paper. we present a definition of the term virtual enterprise (VE) and discuss some related terms and concepts. The definition was given based on Porter's Value Chain Theory. Then we discuss some positioning strategies for entering or joining a virtual enterprise from an executive's viewpoint. which show a framework for making decisions on for what. when and how a (real) enterprise need to participate or form a virtual enterprise and whom the partners should be. The major pert of the paper is on underlying information technologies and architectures for building virtual enterprises. Requirements for modeling virtual enterprises and core technologies needed for implementation are discussed. A virtual enterprise reference architecture based on NIIIP's model is presented. Finally we discuss some points that should. addressed from a macroeconomic and public policies viewpoints. These are the issues of IT standardization and investments in IT infrastructure.