• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.191-196
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• 2015

There have been many studies on statistical forecasting on firm's performance and stock price by applying various financial indicators such as debt ratio and sales growth rate. Selecting predictors for constructing a prediction model among the various financial indicators is very important for precise prediction. Most of the previous studies applied variable selection algorithms for selecting predictors. However, the variable selection algorithm is considered to be at risk of eliminating certain amount of information from the indicators that were excluded from model construction. Therefore, we propose a firm's performance prediction model which principal component analysis is applied instead of the variable selection algorithm, in order to reduce dimensionality of input variables of the prediction model. In this study, we constructed the proposed prediction model by using financial data of American IT companies to empirically analyze prediction performance of the model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1234-1243
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• 2021

This study intends to provide a forecast of the diffusion of countries participating in a newly proposed G to G mechanism named as the "International Defense Industry Cooperation Program of Korea", modeled after the U.S. Foreign Military Sales(FMS). For this purpose, the study analyses 40 years of statistical data of U.S. FMS customers to find two parameters, coefficient of innovation and imitation, which explain the diffusion in FMS customers. Furthermore, the study forecasts the diffusion in international participation to the proposed mechanism taking account of the differences in the level of government competitiveness and the strength of defense industrial base of Korea and the U.S. This study also provides recommendations for accelerating the desired outcomes under the new program. While Korea is likely to have relative advantages over 'imitators' in the international market, it will need to gain competitiveness in high-level capabilities going beyond the realm of medium-high level systems, and present attractive alternatives for offsets.

• The Journal of Bigdata
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• v.5 no.2
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• pp.111-120
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• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.21-30
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• 2016

The current PF project is entirely relying on construction company's credibility. As such, it has increased a negative and bad recognition in domestic real estate economy. In addition, PF experts has a perception that a project's safety of future cash flow profitability is more important than the construction company's credibility. So many PF experts make an effort in order to set aside safe project structure of PF and analyse systematically the risks of the project. In common feasibility study of the PF Project, financial specialists and real estate specialists are forecasting and evaluating the suitability of the project through reviewing the development profit from the project of sales. However, cash flow analysis and evaluation from the perspective of mid-sized construction companies are still in the primary level. Therefore, this study has analysed the current feasibility study and go/no go decision making procedures. Then the authors have a new cash flow analysis method from the perspective of mid-sized construction companies, by improving the feasibility study and go/no go decision making procedures.

• Journal of Distribution Research
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• v.14 no.1
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• pp.45-65
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• 2009

As a number of people using the internet for their shopping steadily rises, it is increasingly important for retailers to understand why consumers decide to buy products via online or offline. The main purpose of this study is to develop and test a model that enhance our understanding of how consumers respond future online and offline channels for their purchasing. Rather than merely adopting statistical models like most other studies in this field, the present study develops a model that combines double-cohort method with multinomial logit model. It is desirable if one can adopt an overall encompassing criterion in the study of consumer behaviors form diverse sales channels. This study uses the concept of cohort or aging to enable this comparison. It enables us to analyze how consumers respond to online and offline channels as people aged by measuring their shopping behavior for an online and offline retailers and their subsequent purchase intentions. Based on some empirical findings, this study concludes with policy implications and some necessary fields of future studies desirable.

• Korean Journal of Construction Engineering and Management
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• v.18 no.4
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• pp.3-16
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• 2017

Forecasting cash flow is very important but is difficult and complicated to analysis in high-rise development projects. And An expected value which was forecasted on the early stage is likely to fluctuate due to uncertainties around such complicated huge project to consider the probable uncertainty. There are not objectified method which are able to cope with uncertainty of project, and feasibility study based on selected financial analysis does not include liquidity of cash flow. Through such a stochastic method, developer can cope with cash flow fluctuation and set up a financial plan. Also this study is meaningful for laying the foundation for high-rise development project and feasibility study as well as the suitability and accuracy of feasibility study. Analysis showed that NPV and IRR include residential apartments shows surplus revenue as return of apartments offset deficit of hotel and office. Factors influencing the project feasibility for high-rise development project are sales account of $1^{st}$ year and annual vacancy rate of office.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• The Journal of Natural Sciences
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• v.10 no.1
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• pp.199-208
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• 1998

This study forecasts the trend of ethnic theme through market survey, concentrating on Los Angeles market. First, the background of ethnic theme was examined, and the present situation of shops, department sores, and headquarter was also surveyed. After that, fashion trend suitable for market was suggested by analyzing the life style of consumers through zip code. The results of the study are as follows. The conspicuous trend of '97 F/W retail stores is ethnic. This reaction to complicated modern life, and symbolizes the desirable evaluation on the simpleness of basic life and nature. The model of ethnic design is identified in natural clothing, primitive arts, ethnic culture and African theme. In short, this ethnic fashion is expressed as simpleness, naturalism convenience and freedom. On the other hand, the standard of general department stores such as Broadway and Robinson May which are the headquarter of this trend is to satisfy various consumers with various styles. Ethnic goods from Broadway has not arrived at the top for its introducing step. To elevate sales of these goods, promotion through VMD and suggesting various ethnic goods should be done. Besides, when analyzing the consumers of Beverly center Broadway, the target of these goods are mostly professional young people in their 25-34 and 35-44. The life style of these people emphasizes sophisticated life in aspects such as job-oriented activities, and up-to-date fashion. Especially, image is very important. They want individuality different from others. These images are diversified from simpleness, naiveness to sexy character. Accordingly, suggesting fashion trend satisfying the demand of consumers through market survey will make fashion market create infinite possibilities.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of Distribution Research
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• v.5 no.2
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• pp.49-68
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• 2001

In this chapter, we summarize the results on the optimal location selection and present limitation and direction of research. In order to reach the objective, this study selected and tested the interaction model which obtains the value of co-ordinates on location selection through the optimization technique. This study used the original variables in the model, but the results indicated that there is difference in reality. In order to overcome this difference, this study peformed market survey and found the new variables (first data such as price, quality and assortment of goods, and the second data such as aggregate area, and area of shop, and the number of cars in the parking lot). Then this study determined an optimal variable by empirical analysis which compares an actual value of market share in 1988 with the market share yielded in the model. However, this study found the market share in each variables does not reflect a reality due to an assumption of λ-value in the model. In order to improve this, this study performed a sensitivity analysis which adds the λ value from 1.0 to 2.9 marginally. The analyzed result indicated the highest significance with the market share ratio in 1998 at λ of 1.0. Applying the weighted value to a variable from each of the first data and second data yielded the results that more variables from the first data coincided with the realistic rank on sales. Although this study have some limits and improvements, if a marketer uses this extended model, more significant results will be produced.