• Journal of Distribution Science
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• v.11 no.2
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• pp.45-55
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• 2013

Purpose - The development and implementation of OSS (Open Source Software) led to a dramatic change in corporate IT infrastructure, from system server to smart phone, because the performance, reliability, and security functions of OSS are comparable to those of commercial software. Today, OSS has become an indispensable tool to cope with the competitive business environment and the constantly-evolving IT environment. However, the use of OSS is insufficient in small and medium-sized companies and software houses. This study examines the need for OSS Intermediaries in the Software Distribution Channel. It is expected that the role of the OSS Intermediary will be reduced with the improvement of the distribution process. The purpose of this research is to prove that OSS Intermediaries increase the efficiency of the software distribution market. Research design, Data, and Methodology - This study presents the analysis of data gathered online to determine the extent of the impact of the intermediaries on the OSS market. Data was collected using an online survey, conducted by building a personal search robot (web crawler). The survey period lasted 9 days during which a total of 233,021 data points were gathered from sourceforge.net and Apple's App store, the two most popular software intermediaries in the world. The data collected was analyzed using Google's Motion Chart. Results - The study found that, beginning 2006, the production of OSS in the Sourceforge.net increased rapidly across the board, but in the second half of 2009, it dropped sharply. There are many events that can explain this causality; however, we found an appropriate event to explain the effect. It was seen that during the same period of time, the monthly production of OSS in the App store was increasing quickly. The App store showed a contrasting trend to software production. Our follow-up analysis suggests that appropriate intermediaries like App store can enlarge the OSS market. The increase was caused by the appearance of B2C software intermediaries like App store. The results imply that OSS intermediaries can accelerate OSS software distribution, while development of a better online market is critical for corporate users. Conclusion - In this study, we analyzed 233,021 data points on the online software marketplace at Sourceforge.net. It indicates that OSS Intermediaries are needed in the software distribution market for its vitality. It is also critical that OSS intermediaries should satisfy certain qualifications to play a key role as market makers. This study has several interesting implications. One implication of this research is that the OSS intermediary should make an effort to create a complementary relationship between OSS and Proprietary Software. The second implication is that the OSS intermediary must possess a business model that shares the benefits with all the participants (developer, intermediary, and users).The third implication is that the intermediary provides an OSS of high quality like proprietary software with a high level of complexity. Thus, it is worthwhile to examine this study, which proves that the open source software intermediaries are essential in the software distribution channel.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.443-456
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• 2010

This study is an empirical research of the stock markets to prove the synchronization phenomenon of the world economy. For this research I analyzed Korea's KOSPI, USA's DOW & NASDAQ reflecting stock markets in North America, Japan's NIKKEI in Asia, and Germany's DAX in Europe. Because the raw series are not stationary, they are to be transformed to returns series. The results of the study are follows: First of all, there are significant causalities between KOSPI's returns and those of other indices. Second, feedback effects are found between the market returns with several time lags. Third, there are 4 cointegrating equations which embody the relation of the five returns series. And forth, KOSPI reacts more sensitively to impacts from the foreign indices compared to the other indices do when they got impacts from each other except KOSPI. On conclusion, there exists a clear evidence for the synchronization phenomenon in returns of the stock indices, and we can expect Korea market may get similar changes depending on the economic changes of North America, Europe, or Asia. Therefore more closing researches should be conducted about the world economy synchronization in various fields as soon as possible.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.109-124
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• 2020

Using panel data on freight rates and ship prices in the dry freighter market from January 2015 to December 2019, this study investigates the characteristics of shipping industry fluctuations. The analysis aims at two aspects of academic contribution. First, this study analyzes the relationship between shipping indicators and ship price based on separate dry-bulk ships, while the previous research considered the overall shipping index and weighted average ship prices. Second, the VAR model for the causality test is extended to a heterogeneous mixed panel model capable of limiting coefficients. There is a peak estimated by removing the cross-correlation problem, which is mainly raised in panel data analysis, using bootstrap estimation and solving the problem of information loss due to differences in non-stationary data. An empirical investigation of the causal relationship between economic fluctuations and ship price shows that the effect on the ship price from the freight is significant at the 1% level. This implies that there is a one-way relationship with demand in the shipping industry rather than a bilateral relationship.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.502-512
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• 2019

To examine the problem structure of balanced regional development policy and identify the causes of the gap between the capital and non-capital areas, this study examined the causal structure in terms of the concentration and distribution of functions in the metropolitan area and non-capital area and explored the policy leverage. As a research method, the causal map was drawn using System Dynamics techniques and policy leverage was derived through an exploration of the feedback structure. In particular, the causes of the problems in balanced regional development policies were approached by system accidents rather than by single-circuit accidents, and causality analysis was performed among the variables constituting balanced regional development policies based on system accidents. In particular, it singled out 31 variables, developed 13 feedback loops, and confirmed four major policy leverages, including relocation of the capital function, local decentralization policies, consistent development, and investment practices centered on the Non­Capital Area. Subsequently, a follow-up study by computer simulation is needed by modeling the structure of the system to identify the ripple effect of the policies of the Capital Area on the Non­Capital Area.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• Cartoon and Animation Studies
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• s.32
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• pp.263-288
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• 2013

This research is about effects which frontal-flat cameras have on narrative films. This kind of confined camera angles make the audience have a sense of tension which is barely defined logically. I think the tension comes from aleatorism. The paper is a research on how aleatorism is working on what kind of value, and what kind of effects it has on narrative films. Russian Formalism had argued they had to meet aesthetic values by totally excluding narratives. It can be said that this was a practice for Brecht's estrangement that a sensitive arousal prohibits the audience immersing into excessive empathy and then make them have a reflective thought. But occasionally, optical arousals in narrative films induce deeper immersion into contemplation rather than reflective thought. I intend to find cases regarding this textualising Front-flat camera angles in narrative films and analysing their contents. To do this, I suggest a more specified definition of 'aleatorism'. Because the concept of the aleatorism is different between an aspect of static image like paintings or photographs and narrative contents like cinema. It is divided into approach through form and approach through content. And I also suggest an operative definition about 'Frontal-flat camera angle' with a several confinements because its formal definition is very flexible depending on audience. The case analysis will be done with a form of discourse discerning two aspects of form and content. Conclusively, Frontal-flat camera angle in narrative film is basically have an effect of attention by optical stimuli. But it cannot be said that this always means deterioration of narrative value. Depending on causality of episodes in the whole story, aleatorism which Frontal-flat camera angle has can support immersed contemplation regarding following narrative rather than reflective thought regarding amusing aesthetics.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.155-164
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• 2016

Algal blooms not only destroy fish habitats but also diminish biological diversity of ecosystem which results into water quality deterioration of 4 major rivers in South Korea. The relationship between algal bloom and environmental factors had been analyzed through the cross-correlation function between concentration of chlorophyll a and other environmental factors. However, time series of cross-correlations can be affected by the stochastic structure such auto-correlated feature of other controllers. In order to remove external effect in the correlation analysis, the pre-whitening procedure was implemented into the cross correlation analysis. The modeling process is consisted of a series of procedure (e.g., model identification, parameter estimation, and diagnostic checking of selected models). This study provides the exclusive correlation relationship between algae concentration and other environmental factors. The difference between the conventional correlation using raw data and that of pre-whitened series was discussed. The process implemented in this paper is useful not only to identify exclusive environmental variables to model Chl-a concentration but also in further extensive application to configure causality in the environment.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.304-316
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• 2020

Laos is rich in natural resources but lacks the capital to develop them. Partly alleviating the shortage is FDI from neighboring countries, especially Thailand. Not only does this contribute to directly increasing GDP by increasing effective demand, it also has an additional GDP increase effect by expanding Laos' production capacity. Laos' exports mostly consist of mineral resources and electricity. This, too, contributes to an increase in GDP by increasing the effective demand. Thailand accounts for more than 40 percent of Laos' exports. This paper tries to confirm the economic impact on Laos in Thailand through a econometric analysis of Laos' GDP, Laos' exports to Thailand and Thailand's FDI to Laos. It turns out that economic ties with Thailand, including exports to Thailand and Thailand's FDI, play a very important role in Laos' economic growth. Laos recently recorded relatively robust economic growth, but its driving force is weak. That's because Laos' growth engines are very limited and have no resilience to external shocks. Moreover, economic growth has not been linked to an increase in employment because the economy is not diversified and growth in the hydroelectric power sector does not lead to growth in other sectors. Given this, Laos needs to actively take advantage of its geographical proximity to Thailand. It is necessary to create a more active environment for the inflow of FDI in Thailand, to foster resource-based and labor-based manufacturing to take advantage of the Thai market.

• Korean Security Journal
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• no.45
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• pp.221-242
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• 2015

Verification for the causality of factors affecting fear of criminal victim which has a bad influence on the senior's quality of life and directions to prevent the crimes against the elderly have been suggested. This study proves the applicability for fear of crime to old people especially based on risk interpretation model consisting of perceived risk of crime, behavioral response and fear of crime. Analysis results are as follows. First, disorder factors as social characteristics showed statistically significant influences on perceived risk of crime, behavioral response and fear of crime. Second, direct experienced crime victimization only affected perceived risk of crime while indirect experienced crime victimization had an effect on perceived risk of crime and fear of crime as well. Third, perceived risk of crime influenced fear of crime. Fourth, perceived risk of crime was concerned with fear of crime. Fifth, behavioral response was affiliated with fear of crime. These results reveal that risk interpretation model can be applied to senior's fear of crime. Moreover, disorder factor as social characteristic and experienced crime victimization as individual characteristic help the elderly perceive the risk of crime, bring behavioral response. Consequently, they play a role of factors affecting fear of crime. It is emphasized that support policy is required for the elderly who had experienced crime and stabilization of community environment if necessary to improve the quality of life.