• Journal of Distribution Science
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• v.11 no.12
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• pp.25-37
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• 2013

Purpose - The structure of retailing has changed as retailers develop markets in response to business environment changes. This study aims to analyze the general situation of retailers in order to predict future global strategy using case studies of overseas expansion strategy and the Metro Group's global strategy. Research design, data, and methodology - The backgrounds to the new retail business model and retailer classification are analyzed as theoretical data. In addition, the key success point of the Metro Group's "cash and carry" strategy is analyzed as is the Metro Group's global CFAR (collaborative planning, forecasting, and replenishment) strategy. Finally, the plan for cooperation and precise forecasting under the Metro Group's supply chain management are analyzed from the promotion environment viewpoint. Related materials analyzed included the 2012 annual report, the Metro Group's web page, and a video interview with the executive in charge of global strategy and the new market development department. Some data were revised to avoid disrupting essential aspects of the case studies. Results - The important finding was that the Metro Group could be a world-class retail company with its successful global expansion strategy. The Metro Group's global strategy's primary goal is to have a leading business position in Eastern and Western Europe. The "cash and carry" strategy is highest priority in its overseas expansion strategy. Moreover, the Metro Group has standardized product planning capacity, which could be applied in various countries with different structural and cultural backgrounds. This is the main reason that the Metro Group could rapidly become successful in the Eastern Europe and Asian markets through its structural overseas expansion strategies. In addition, the Metro Group emphasizes the importance of supply chain management. Conclusions - First, retailers should create additional value through utilizing the domestic market, market power, and economies of scale to launch a global strategy to maximize benefits from diversification. Second, the political, economic, and cultural background of the target country needs to be understood to successfully implement the overseas expansion strategy. Third, the main factor of successful cooperation with a local partner is how quickly the company gains total understanding of the business resources and core competence of its partner. All organizations should focus on the achievement of goals in order to successfully operate the partnership. Fourth, retailers should improve their business, financial and organizational structure. Moreover, the work processes and company culture should also be improved to respond strongly in the competitive global market. Fifth, the essential point of a successful retail business is the control capacity of its branding and format. The retailer could avoid forecasting errors through supply chain management by perfectly distributing the actual amount of its inventory. In addition, the risks along the supply chain are effectively shared between the supply chain partners. Finally, the central tendency of the market is to gain in strength with this taking place across all parts of the business.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.