• Title/Summary/Keyword: exchange of information

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A Study on the Collaborative Partnership Factors between Freight Forwarders and Consignors (국제물류주선업체와 화주기업의 협력적 파트너쉽 요인에 관한 연구)

  • Jun, Kyung Sook;Jang, Hyun Mi;Kim, Sang Youl
    • Journal of Korea Port Economic Association
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    • v.30 no.4
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    • pp.169-198
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    • 2014
  • Due to the recent worldwide economic downturn, companies are required to put more effort into their innovation and quality improvement. In particular, business relationship is increasingly emphasized to be changed from a vertical relationship to a more horizontal relationship, such as collaborative partnership based on trust. In the logistics industry, through the collaboration, consignors can gain competitive advantages by focusing on their core capabilities, and freight forwarders also take advantages of securing stable cargoes and specialist expertise in distribution. Therefore, this study aims to identify key factors for developing a collaborative partnership between freight forwarders and consignors, and further examine the differences between the two groups empirically by using questionnaire survey. Based on the results, the main factors were found as follows: 1) Trust Building, 2) Competence Improvement, 3) Business Ecosystem and 4) Government Assistance. According to the analysis on sub-factors, first, among the four main factors, it turned out that trust is the most important variable. Specifically, the sub-factor of providing regular and stable service was revealed to be most critical. Second, it was found that forwarders need to improve services on 'Information Exchange System' and 'Electronic Data Interchange'. Finally, it is necessary for both consignors and forwarders to have better understanding of partnership. Key implications for both groups are highlighted based on the results.

eMRA: Extension of MRA Considering the Relationships Between MDR Concepts (eMRA: MDR의 개념간 관계성을 고려한 MRA 확장)

  • Joo, Young-Min;Kim, Jangwon;Jeong, Dongwon;Baik, Doo-Kwon
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.3
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    • pp.161-172
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    • 2013
  • Metadata registry (MDR) is the international standard, developed by ISO/IEC for exchange and sharing data between databases. Many MDR systems are used in diverse domains such as medical service, bibliography, environment for sharing and integrating data. However, those systems have different physical structures individually because the MDR standard defines only the metamodel for registering and storing metadata. It causes heterogeneity between the system structures and requires additional cost to maintain interoperability. ISO/IEC 13249-8 Metadata Registry Access (MRA) is developing as an international standard to provide a consistent access facility to data stored in different metadata registries. However, MRA does not consider the relationships between the concepts (classes) defined in the MDR specification. It causes that incorrect query results returned from MDR systems. It also requires additional cost of modeling and rewriting queries to reflect each physical model. Therefore, this paper suggests eMRA which considers the relationships between the concepts in MDR. The comparative evaluations are described to show the advantages of eMRA. eMRA has superior performance in query modeling and referential integrity than MRA defined by the relationship between the concept of MDR.

The Analysis of the Current Status of Medical Accidents and Disputes Researched in the Korean Web Sites (인터넷 사이트를 통해 살펴본 의료사고 및 의료분쟁의 현황에 관한 분석)

  • Cha, Yu-Rim;Kwon, Jeong-Seung;Choi, Jong-Hoon;Kim, Chong-Youl
    • Journal of Oral Medicine and Pain
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    • v.31 no.4
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    • pp.297-316
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    • 2006
  • The increasing tendency of medical disputes is one of the remarkable social phenomena. Especially we must not overlook the phenomenon that production and circulation of information related to medical accidents is increasing rapidly through the internet. In this research, we evaluated the web sites which provide the information related to medical accidents using the keyword "medical accidents" in March 2006, and classified the 28 web sites according to the kinds of establishers. We also analyzed the contents of the sites, and checked and compared the current status of the web sites and problems that have to be improved. Finally, we suggested the possible solutions to prevent medical accidents. The detailed results were listed below. 1. Medical practitioners, general public, and lawyers were all familiar with and prefer the term "medical accidents" mainly. 2. In the number of sites searched by the keyword "medical accidents", lawyer had the most sites and medical practitioners had the least ones. 3. Many sites by general public and lawyers had their own medical record analysts but there was little professional analysts for dentistry. 4. General public were more interested in the prevention of medical accidents but the lawyers were more interested in the process after medical accidents. The sites by medical practitioners dealt with the least remedies of medical accidents, compared with other sites. 5. General public wanted the third party such as government intervention into the disputes including the medical dispute arbitration law or/and the establishment of independent medical dispute judgment institution. 6. In the comparison among the establishers of web sites, medical practitioners dealt with the least examples of medical accidents. 7. The suggestion of cases in counseling articles related to dental accidents were considered less importantly than the reality. 8. Whereas there were many articles about domestic cases related to the bloody dental treatment, in the open counseling articles the number of dental treatment regarding to non insurance treatment was large. 9. In comparing offered information of medical accidents based on the establishers, general public offered vocabularies, lawyers offered related laws and medical practitioners offered medical knowledge relatively. 10. They all cited the news pressed by the media to offer the current status of domestic medical accidents. Especially among the web sites by general public, NGOs provided the plentiful statistical data related to medical accidents. 11. The web sites that collect the medical accidents were only two. As a result of our research, we found out that, in the flood of information, medical disputes can be occurred by the wrong information from third party, and the medical practitioners have the most passive attitudes on the medical accidents. Thus, it is crucial to have the mutual interchange and exchange of information between lawyer, patients and medical practitioners, so that based on clear mutual comprehension we can solve the accidents and disputes more positively and actively.

VKOSPI Forecasting and Option Trading Application Using SVM (SVM을 이용한 VKOSPI 일 중 변화 예측과 실제 옵션 매매에의 적용)

  • Ra, Yun Seon;Choi, Heung Sik;Kim, Sun Woong
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.177-192
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    • 2016
  • Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

An Analysis of Growth Conditions of old Trees in Yangdong Villages (양동마을의 노거수 생육실태 분석)

  • Kim, Young-Hun;Deng, Bei-Jia;You, Ju-Han
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.38 no.2
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    • pp.95-107
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    • 2020
  • The purpose of this study is to provide the basic data by analyzing and analysing the Growth Conditions of old Trees in Yangdong village. This study investigated about the conducted on tree information, soil information, and tree health. The result are as follows. The trees information in Yangdong Village consists of Juniperus chinensis, Salix chaenomeloides, Salix pseudolasiogyne, Celtis sinensis, Zelkova serrata, Gleditsia japonica, and Gleditsia sinensis trees, The range of height was 4.0~17.0m, and the diameter was 0.51~1.34m, Juniperus chinensis trees of No.17 was most large. In the results of soil analysis, there showed that acidity was pH4.1~6.3, hardness of 5~48mm, organic matter content of 21.2~29.1g/kg, electrical conductivity(EC) of 0.34~1.76dS/m, available P2O5 of 79.8~451.6mg/kg, exchangeable K of 0.22~1.71cmol+/kg, exchangeable Ca of 4.98~7.44cmol+/kg, exchangeable Mg of 0.67~2.19cmol+/kg, exchangeable Na of 0.19~1.04cmol+/kg and cation exchange capacity(C.E.C) of 7.23~13.02cmol+/kg. As a result, the highest number of tree health levels is 8 of 11trees of Celtis sinensis, 2 of 7trees of Zelkova serrata, and 3 of Gleditsia sinensis, and 13 of 30 trees of health levels, The Older trees with high infection, spoil and hollowed part were the remaining trees except for the healthy part. Relatively, more than half of the number of targets is infected, decay, and the hollowed site, and it is necessary to perform surgery on the damaged area. In addition, preservation and protection measures should be implemented by supplying root nutrients for trees, controlling nutrients in the body to prevent secondary and tertiary damages that cause the infection site to metastasize to the health site, In order to continually monitor the trees, measures to improve the location environment and management of the trees should be sought.

The Gains To Bidding Firms' Stock Returns From Merger (기업합병의 성과에 영향을 주는 요인에 대한 실증적 연구)

  • Kim, Yong-Kap
    • Management & Information Systems Review
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    • v.23
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    • pp.41-74
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    • 2007
  • In Korea, corporate merger activities were activated since 1980, and nowadays(particuarly since 1986) the changes in domestic and international economic circumstances have made corporate managers have strong interests in merger. Korea and America have different business environments and it is easily conceivable that there exists many differences in motives, methods, and effects of mergers between the two countries. According to recent studies on takeover bids in America, takeover bids have information effects, tax implications, and co-insurance effects, and the form of payment(cash versus securities), the relative size of target and bidder, the leverage effect, Tobin's q, number of bidders(single versus multiple bidder), the time period (before 1968, 1968-1980, 1981 and later), and the target firm reaction (hostile versus friendly) are important determinants of the magnitude of takeover gains and their distribution between targets and bidders at the announcement of takeover bids. This study examines the theory of takeover bids, the status quo and problems of merger in Korea, and then investigates how the announcement of merger are reflected in common stock returns of bidding firms, finally explores empirically the factors influencing abnormal returns of bidding firms' stock price. The hypotheses of this study are as follows ; Shareholders of bidding firms benefit from mergers. And common stock returns of bidding firms at the announcement of takeover bids, shows significant differences according to the condition of the ratio of target size relative to bidding firm, whether the target being a member of the conglomerate to which bidding firm belongs, whether the target being a listed company, the time period(before 1986, 1986, and later), the number of bidding firm's stock in exchange for a stock of the target, whether the merger being a horizontal and vertical merger or a conglomerate merger, and the ratios of debt to equity capital of target and bidding firm. The data analyzed in this study were drawn from public announcements of proposals to acquire a target firm by means of merger. The sample contains all bidding firms which were listed in the stock market and also engaged in successful mergers in the period 1980 through 1992 for which there are daily stock returns. A merger bid was considered successful if it resulted in a completed merger and the target firm disappeared as a separate entity. The final sample contains 113 acquiring firms. The research hypotheses examined in this study are tested by applying an event-type methodology similar to that described in Dodd and Warner. The ordinary-least-squares coefficients of the market-model regression were estimated over the period t=-135 to t=-16 relative to the date of the proposal's initial announcement, t=0. Daily abnormal common stock returns were calculated for each firm i over the interval t=-15 to t=+15. A daily average abnormal return(AR) for each day t was computed. Average cumulative abnormal returns($CART_{T_1,T_2}$) were also derived by summing the $AR_t's$ over various intervals. The expected values of $AR_t$ and $CART_{T_1,T_2}$ are zero in the absence of abnormal performance. The test statistics of $AR_t$ and $CAR_{T_1,T_2}$ are based on the average standardized abnormal return($ASAR_t$) and the average standardized cumulative abnormal return ($ASCAR_{T_1,T_2}$), respectively. Assuming that the individual abnormal returns are normal and independent across t and across securities, the statistics $Z_t$ and $Z_{T_1,T_2}$ which follow a unit-normal distribution(Dodd and Warner), are used to test the hypotheses that the average standardized abnormal returns and the average cumulative standardized abnormal returns equal zero.

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A Study on Case for Localization of Korean Enterprise in Indonesia (인도네시아 진출 한국기업의 현지화에 관한 사례 연구)

  • Swo, Min-Kyo;Kim, Hee-Jun
    • International Commerce and Information Review
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    • v.15 no.4
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    • pp.481-508
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    • 2013
  • The purpose of this study is to research the specific ways of successful localization by analyzing the success and failures case for localization through the theoretical background and the strategic models of localization. The strategic models of localization are divided by management aspects such as the localization of production and sourcing, the localization of human resources, the localization of marketing, the localization of R&D, harmonious relationship with the local community and authority transfer between headquarters and local subsidiaries. And the specific measures of the successful localization are proposed within the framework of the strategic models by comparing and analyzing the success and failures case for localization of individual companies operating in Indonesia. The results indicate that there are successful companies which develop a suitable products for the local climate and failed automobile company which is weak for assembly of complete vehicle in terms of localization of production and sourcing. In case of localization of human resources, most companies recognize the importance of this part and endeavor to secure superior human resource through a related education. It is found that most of the companies perform R & D in their native country. In part of a harmonious relationship with the local community, Korean companies should contribute to the community and be friendly with local residents and make a good image of the company focusing on the cultural environment. In aspect of authority transfer between headquarters and local subsidiaries, there is a tendency to be determined by the head office rather than the joint participation. In the future, in order for Korean enterprise to be successful one in Indonesia market, a highly interdependent and complex forms between headquarters and local subsidiaries shall be performed and an active exchange of information and the selection of best talent regardless of nationality shall be promoted.

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The Analysis on the Relationship between Firms' Exposures to SNS and Stock Prices in Korea (기업의 SNS 노출과 주식 수익률간의 관계 분석)

  • Kim, Taehwan;Jung, Woo-Jin;Lee, Sang-Yong Tom
    • Asia pacific journal of information systems
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    • v.24 no.2
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    • pp.233-253
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    • 2014
  • Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

Effect of Venture Capitalists on the ChiNext IPO First-Day Return in China (중국 차이넥스트 시장의 벤처캐피탈이 IPO 첫날 수익률에 미치는 영향)

  • Kang, Kai;Ahialey, Joseph Kwaku;Kang, Ho-Jung
    • Management & Information Systems Review
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    • v.36 no.4
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    • pp.117-127
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    • 2017
  • In recent times the size of the world IPO in general has skyrocketed. Specifically, China's financial market development is becoming important as both the size of China's capital market and the number of companies going public are gradually increasing. This has led to a rapid development of venture vapital(VC) institutions in China for the past couple of decades. This study focuses on one of the three markets of China's Shenzhen Stock Exchange-the Growth Enterprise Board((GEB) hereafter, ChiNext). The ChiNext is established in October, 2009 to enable hi-tech or high growth potential technology companies that find it relatively difficult to fulfil the listing requirements of either the Shenzhen Main Board or Small and Medium Size Enterprise Board(SMEB) to go public. This study covers a three-year period(2012/01/-2015/01) and analyze first day initial return of 83 venture capital-backed companies and 53 non-venture capital-backed companies using T-test. Regression analysis is used as to examine the variables affecting IPO's first-day return. The empirical results are four-fold. First, the level of first day return of venture-backed is significantly lower than non venture capital backed support in the Chinese venture capital market. Second, the level of first-day return of listed companies supported by foreign venture capital is significantly higher than that of companies receiving domestic venture capital support. Third, the firms that have a large number of venture capital firms showed a low level of first-day return. Fourth, regression result for the IPO first-day return which is as dependent variable indicates that the venture capital support(VCAP), number of venture capital(VCNum), offering size(Lnsize) and PER all affect have negative effect on the first day initial return. Also, the venture capital type(VCType), turnover ratio and the the firm type(Tech-firms) statistically affect IPO first day return positively. Finally, by shedding more light on the IPO first-day return, this paper provides meaningful information to investors about the Chinese IPO market.

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Searching for the SCM Improvement Directions through the Power Attribute and Partnership (파워 유형과 파트너십 연계를 통한 공급사슬관리 개선방안 모색)

  • Jung, Dae-Hyun;Park, Kwang-O
    • Management & Information Systems Review
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    • v.35 no.3
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    • pp.57-79
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    • 2016
  • It is required to derive various conclusions by identifying the type of power and the relationship between SCMs and presenting practical implications. Thus, we can identify the differential effects of each type of power on SCM performance. We can contribute to develop the practical implications at more sophisticated multi-dimension by comparing results of this study with various SCM theories. Through previous studies, the source of power is largely divided into binding power and non-binding power. Binding power is classified into behavior coercion, binding reward and relationship legitimacy. Non-binding power is classified into work expertise, information superiority and value compliance. Enterprises should fully understand and recognize partners within supply chains including understanding of the source of power, imbalance and results. Thus, we look into types of power and effects on trust and commitment, and identify a causal relationship leading to collaboration and SCM performance. Specific research results are as follows. First, the binding power did not give a significant effect to the trust. However, the binding power gave a positively(+) significant effect to the commitment. Second, non-binding power showed a significant effect on both trust and commitment. As a result of analysis on total effects, it was shown that non-binding power gave indirect effects to collaboration and SCM performance. Third, it was shown that both trust and commitment significantly affected collaboration. From the perspectives of social exchange theory and trading cost theory among inter-organizational relationship theory, it may lead to SCM performance of trust, commitment and collaboration. Moreover, it was found that association of each attribute of power led to the significant result. Fourth, it was shown that trust and collaboration significantly affected SCM performance. However, commitment did not directly affect SCM performance, but it indirectly significantly affected SCM performance through collaboration. Proper use of this power can firmly build partnerships between members of the supply chain and induce the improvement on supply chain performance and satisfaction of members.

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