• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.161-164
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• 2006

The sales of consumer durables are composed of first time purchases and replacement purchases. Since the sales for most mature durable products are dominated by replacement sales, it is necessary to develop a model incorporating replacement component of sales in order to forecast total sales accurately. Several single product diffusion models incorporating replacement demand have been developed, but research addressing the multi-product diffusion models has not considered replacement sales. In this paper, we propose a model based on consumer choice behavior that simultaneously captures the diffusion and the replacement process for multi-product relationships. The proposed model enables the division of replacement sales into repurchase by previous users and transition purchase by users of different products. As a result, the model allows the partitioning of the total sales according to the customer groups (first-time buyers, repurchase buyers, and transition buyers), which allows companies to develop their production and marketing plans based on their customer mix. We apply the proposed model to the Korean automobile market, and compare the fitting and forecasting performance with other Bass-type multi-product models.

• The International Journal of Costume Culture
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• v.13 no.2
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• pp.130-140
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• 2010

This research was carried out by setting hypotheses on recognition of the global image of the research subject, a domestic cosmetic brand and consequent quality of the brand, reputation of the brand, purchasing decision, influence of images of expanded countries and their correlations to investigate what effect the global images of local brands practically have on domestic consumers' purchasing decision. The analysis results show that overseas expansion of the research subject brand has positive influence on the brand possessing global images. However, it can be seen that the quality of the brand has much larger influence on the reputation of the brand than the images of global brand. In addition, the images of the expanded countries have influence on purchasing decisions but the global images based on the expanded countries did not have much influence on purchasing decisions. Therefore, it can be seen that global images based on high levels of brand reputation and quality are requirements of a most competitive brand than images of the expanded countries in forecasting likelihood of purchase.

• Proceedings of the Technology Innovation Conference
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• 1999.12a
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• pp.328-347
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• 1999

The substitution of Electronic Commerce(EC) for the traditional transactions triggers the changes of the industry structures and promotes the cost reductions of the firms in the areas of distributions and other administrative operations associated with purchase via EC. Our study clarifies the changes of the environments attributable to EC which are faced inter-and-externally by firms and try to exhibit the trend of EC market growth through such descriptions. Regardless of the rapid spread of EC, recent studies do not show appropriately its impact on the relevant industries and our domestic economy. Therefore, our study focuses on the forecasting of the impacts of EC on the domestic productions and imports. To this end, we develop an analytic framework using the existing data in Input/Output Analysis and the estimations of the EC market growth in the future. We, finally, identify the industrial sectors whose productions and imports are estimated to be accelerated by the extension of EC and forecast the whole effects of EC on domestic productions and imports.

• IE interfaces
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• v.21 no.3
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.97-121
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• 2001

Until now, we have believed that one of advantages of cyber market is that it can virtually display and sell goods because it does not necessary maintain expensive physical shops and inventories. But, in a highly competitive environment, business model that does away with goods in stock must be modified. As we know in the case of AMAZON, leading companies already consider merchandise management as a critical success factor in their business model. That is, a solution to compete against one's competitors in a highly competitive environment is merchandise management as in the traditional retail market. Cyber market has not only past sales data but also web log data before sales data that contains information of path that customer search and purchase on cyber market as compared with traditional retail market. So if we can correctly analyze the characteristics of before sales patterns using web log data, we can better prepare for the potential customers and effectively manage inventories and merchandises. We introduce a systematic analysis method to extract useful data for merchandise management - demand forecasting, evaluating & selecting - using web mining that is the application of data mining techniques to the World Wide Web. We use various techniques of web mining such as clustering, mining association rules, mining sequential patterns.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.1-10
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• 2011

This study investigates the dynamic structure of interdependence on the domestic and related major stock markets by employing a statistical framework. Finance theory predicts potential gains by international portfolio diversification if returns from investment in different national stock markets are not perfectly correlated or not cointegrated. The benefit of international diversification is limited when national stock markets are cointegrated because of the limited amount of independent variation by the presence of common factors. The statistical tests suggest that international diversification appears to be favorable after the period of the comovement of the stock prices caused by 1997 Asian financial crisis. The result reflects the increase in overseas investment and purchase of overseas funds after the early 2000's.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.361-369
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• 1998

Recently, the improvement of on-board satellite sensors covering hyperspectral image sensors, high spatial resolution sensors provide data on earth in diverse aspect. The application field relating remotely sensed data also varies depending on what type of job one wants. The various resolution of sensors from low to extremely high is also available on the market with a user defined specific location. The expense to purchase remote sensed data is going down compare to the cost it need past few years ago in terms of research or private use. Now, the satellite remote sensed data is used on the field of forecasting, forestry, agriculture, urban reconstruction, geology, or other research field in order to extract meaningful information by applying special techniques of image processing. There are many image processing packages available worldwide and one common aspect is that they are expensive. There need to be a advanced satellite data processing package for people who can not afford commercial packages to apply special remote sensing techniques on their data and produce valued-added product. The study was carried out with the purpose of developing a special satellite data processing package which covers almost every satellite produced data with normal image processing functions and also special functions needed on specific research field with friendly graphical user interface (GUI). And for the people with any background of remote sensing with windows platform.

• Journal of Fashion Business
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• v.4 no.1
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• pp.87-96
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• 2000

Merchandiser continue to play an important role in the exchange process by providing products for consumption. Merchandisers must still understand customer demands, analyze sale trends, select and present salable products. However, due to the competitive pressures in the apparel industry and the innovations required under QR business systems, the demands placed on merchandisers are changing. The purpose of this study is to present of the direction for fashion merchandising education. The direction for fashion merchandising are education summarized as follows; 1) Merchandising technology is the systematic application of information technology and Telecomunications to planning, developing, and presenting product lines in ways that reflect social and cultural value. Statistic Methods are developed and used to analyze data arising from a wide variety of applications. 2) Merchandising technology is to practise the technical and economic aspects of apparel production. Analysis of specific apparel manufacturing and management issues such as efficient manufacturing methods. 3) Merchandising technology is to forecast fashion trend according to consumer preference. Culture influences what people purchase and how those items are used forecasting fashion trend. 4) Merchandising technology is to practise communication skills used in formal and informal organization including interviews in particular language suited to their own business and professionnal careers. 5) Merchandising technology is to planning merchandise budgets and merchandise assortments based on more diverse forms of information. 6) Merchandising technology is to use techniques related hardware and software. 7) Merchandising technology is to learn participate in internship programs.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.201-214
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• 2008

IPTV services, as the convergence service of communication and broadcasting, are regarded as the essential information communication media in the New Economy era by providing the consumers with various services through the collaboration among communications, broadcasting and many of other media service providers. The research starts with recognition that, in the new media era, where communication and broadcasting are converging, there are endless demands for new services and various contents, which are driving forces behind the business model of IPTV. In other words, the research expected that customer satisfaction and purchase intention would be different according to the service quality(contents). It was expected that the difference of the perceived service quality(contents) could cause the difference of the process of adopting new technologies. The study on how consumers are satisfied with services provided, and which factors of the service quality have a more significant effect on consumer satisfaction will provide very valuable information for forecasting future trends in the IPTV market. The research tried to investigate factors which influence on consumer satisfaction and loyalty through an empirical survey with real users of IPTV services. Based on the results, the research suggested effective ways of diffusing IPTV.