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A Business Application of the Business Intelligence and the Big Data Analytics
이기광,김태환 한국산업경영시스템학회 2019 한국산업경영시스템학회지 Vol.42 No.4
Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It’s also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business’ changing requirements, if they prove to be highly valuable to business environment.
Twitter를 활용한 기상예보서비스에 대한 사용자들의 만족도 분석
이기광 한국산업경영시스템학회 2018 한국산업경영시스템학회지 Vol.41 No.2
This study is intended to investigate that it is possible to analyze the public awareness and satisfaction of the weather forecast service provided by the Korea Meteorological Administration (KMA) through social media data as a way to overcome limitations of the questionnaire-based survey in the previous research. Sentiment analysis and association rule mining were used for Twitter data containing opinions about the weather forecast service. As a result of sentiment analysis, the frequency of negative opinions was very high, about 75%, relative to positive opinions because of the nature of public services. The detailed analysis shows that a large portion of users are dissatisfied with precipitation forecast and that it is needed to analyze the two kinds of error types of the precipitation forecast, namely, ‘False alarm’ and ‘Miss’ in more detail. Therefore, association rule mining was performed on negative tweets for each of these error types. As a result, it was found that a considerable number of complaints occurred when preventive actions were useless because the forecast predicting rain had a ‘False alarm’ error. In addition, this study found that people’s dissatisfaction increased when they experienced inconveniences due to either unpredictable high winds and heavy rains in summer or severe cold in winter, which were missed by weather forecast. This study suggests that the analysis of social media data can provide detailed information about forecast users’ opinion in almost real time, which is impossible through survey or interview.
맥주배송게임에서 다구찌 방법에 의한 불확실 정보 기반 의사결정 연구
이기광 한국산업경영시스템학회 2010 한국산업경영시스템학회 학술대회 Vol.2010 No.하계
Information is known to be a key element for the successful operation of a supply chain, which is required of the efficient ordering strategies and accurate predictions of demands. This study proposes a method to effectively utilize the meteorological forecast information in order to make decisions about ordering and prediction of demands by using the Taguchi experimental design. It is supposed that each echelon in a supply chain determines the order quantity with the prediction of precipitation in the next day based on probability forecast information. The precipitation event is predicted when the probability of the precipitation exceeds a chosen threshold. Accordingly, the choice of the threshold affect the performances of a supply chain. The Taguchi method is adopted to deduce a set of thresholds for echelons which is least sensitive to changes in environmental conditions, such as variability of demand distributions and production periods. A simulation of the beer distribution game was conducted to show that the set of thresholds found by the Taguchi method can reduce the cumulative chain cost, which consists of inventory and backlog costs.
Decision Strategies Based on Meteorological Forecast Information in a Beer Distribution Game
이기광,김인겸,한창희 한국데이터전략학회 2008 Journal of information technology applications & m Vol.15 No.3
With the corporate environment nowadays being surrounded by plenty of information, the sharing of information among businesses through mutual cooperation tops the list of hot issues. Predictions of demands from the customer, business, or consumer by sharing information can affect the inventory and order production system. However, notwithstanding the importance of sharing information, empirical studies on quantitative use of information still remain insufficient in spite of many a discussion now being made on the sharing of information. This paper proposes to examine the ways meteorological information may affect the rises in the achievements of supply chains in distributive businesses, the kind of information that noticeably affects the consumer behavioral patterns in the distributive businesses but rarely perceived as a form of information shared by businesses. This study is based on a model in which meteorological information has been added as the one used to predict demands, after the beer distribution game has been modified to fit the current status, and simulations under an assumptive situation, where decisions are made on a daily basis, were conducted 50 times for a period of 1000 days for the generalization of the results, while at the same time a Duncan Test was conducted to determine the threshold to use the meteorological information that will be most profitable to the retailer, wholesaler, supplier and the supply chain as a whole. Our findings indicate that corporations have thresholds that vary from business to business depending upon the ratio of backlog costs to inventory costs. At the same time, our findings also show that there existed effective thresholds depending upon the ratio of backlog costs to inventory costs for the performance of the overall supply chain.