• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.36-49
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• 2016

A subway system is one of the major transportation modes at a metropolitan area. When it meets the other lines, the metro station, so-called transferring station, is usually threatened by severe pedestrian congestion and safety issue of transit users including the transportation vulnerable. Although transportation planners forecast travel demand at the beginning, it is not easy to predict pedestrian flows precisely for a long term if land use plans have dramatically changed. Due to expensive costs, structural extension of metro stations is limited. Therefore, it requires efficient and technical improvements as meeting the demand of pedestrian and physical characteristics. In this study, the core mechanism of pedestrian movement-based simulation model was introduced and evacuation scenarios were analyzed with the developed model. As a result, the multiple optimal routes for unexpected events at the solid space of the multiple stories are easily searched through the simulator and in the case of Sadang Station, travel time can be reduced by 60% when the evacuation information and intuitive design are provided.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.85-91
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• 2021

In contrast to standard train tracks, tramlines are often set along public roads, with trams running among pedestrians and other vehicles. In some cities and towns, trams and buses share the same routes and stations. Under the current investment appraisal system, trams are classified into light rail when predicting traffic demand and calculating benefits, but in the case of non-capital areas, it is notable that the origin-destination and transit lines of buses are not provided in the Korea Transport Database distribution data. Due to this problem, it is difficult to reflect proper mode changing behaviors between route buses and trams. This study examines the impact on tramlines of bus routes that are not currently considered in non-capital areas. Following an analysis of the effect of tram projects according to whether bus routes are considered or not, an improvement in methodology is proposed. Through this study, it is expected that the investment appraisal system for the planning of new tramlines will be improved in the future.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.229-236
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• 2021

There has been a lot of research on the real estate market, but a lack of research on the supply and demand of housing supply in each region, reflecting the changes in population growth and supply. It is calculated as the transition probability of the Markov chain model by reflecting the data on the number of houses per 1,000 people in the past 35 years and the forecast data for population change by region, in terms of supply (housing) to demand (population) for factors on the real estate market. According to the calculation results of the real estate market by region, the housing supply to the metropolitan area such as Gyeong-gi, Incheon, and Seoul is expected to be insufficient for a considerable period of time, considering the population changes by region. To stabilize the real estate market, it was confirmed that it was necessary to actively apply the differentiation of housing supply by region. It is meaningful in terms of verifying long term trends in the real estate market by region that reflect the prediction of population change, and it is expected that the methods used in this study will be practical through the analysis results using the historical data.

• The Journal of Bigdata
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• v.8 no.2
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• pp.189-200
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• 2023

At the beginning of the COVID-19 pandemic, Korea's wine market had shrunk as other countries. However, right after the pandemic, Korea's imported wine consumption had been increased 69.6%. Because of the ban on overseas travel, wine was consumed in the domestic market. And consumption of high-end wines were increased significantly due to revenge spending and home drinking. However, from 2022 Korea's wine market has begun to shrink sharply again. Therefore this study forecasts the size of imported wine market by 2032 to provide useful information to wine related business entities. KITA(Korea International Trade Association)'s 95 time-series data per quarter from Q1 of 2001 to Q3 of 2023 was utilized in this research. The accuracy of model was tested based on value of MAPE. And ARIMA model was chosen to forecast the size of market value and Winter's multiplicative model was used for the size of market volume. The result of ARIMA model for the value (MAPE=10.56%) shows that the size of market value in 2032 will be increased up to USD $1,023,619, CAGR=6.22% which is 101% bigger than its size of 2023. On the other hand, the volume of imported wine market (MAPE=10.56%) will be increased up to 64,691,329 tons, CAGR=-0.61% which is only 15.12% bigger than its size of 2023. The result implies that the value of Korea's wine market will continue to grow despite the recent decline. And the high-end wine market will account for most of the increase.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.870-876
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• 2005

The multiple regression models which have two factors(population and commercial area) have been used to forecast the water demand in the future. But, the coefficient of population had a negative value because proper regional classification wasn't performed, and it is not reasonable because the population must be a positive factor. So, the regional classification was performed by principal component and cluster analysis to solve the problem. 6 regional characters were transformed into 4 principal components, and the areas were divided into two groups according to cluster analysis which had 4 principal components. The new regression models were made by each group, and the problem was solved. And, the future water demands were estimated by three scenarios(Active, moderate, and passive one). The increase of water demand ore $89.034\;m^3/day$ in active plat $49,077\;m^3/day$ in moderate plan, and $19,996\;m^3/day$ in passive plan. The water supply ability as scenarios is enough in water treatment plant, however, 2 reservoirs among 4 reservoirs don't have enough retention time in all scenarios.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.223-252
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• 2008

In this study, we attempt to propose a choice-based diffusion model with switching cost, which can be used to forecast the dynamic substitution and competition among previous and new products at both individual-level and aggregate level, especially when market data for new products is insufficient. Additionally, we apply the proposed model to the empirical case of substitution and competition among Analog Cable TV that represents previous fixed charged broadcasting service and Digital Cable TV and Internet Protocol TV (IPTV) that are new ones, verify the validities of our proposed model, and finally derive related empirical implications. For empirical application, we obtained data from survey conducted as follows. Survey was administered by Dongseo Research to 1,000 adults aging from 20 to 60 living in Seoul, Korea, in May of 2007, under the title of 'Demand analysis of next generation fixed interactive broadcasting services'. Conjoint survey modified as follows, was used. First, as the traditional approach in conjoint analysis, we extracted 16 hypothetical alternative cards from the orthogonal design using important attributes and levels of next generation interactive broadcasting services which were determined by previous literature review and experts' comments. Again, we divided 16 conjoint cards into 4 groups, and thus composed 4 choice sets with 4 alternatives each. Therefore, each respondent faces 4 different hypothetical choice situations. In addition to this, we added two ways of modification. First, we asked the respondents to include the status-quo broadcasting services they subscribe to, as another alternative in each choice set. As a result, respondents choose the most preferred alternative among 5 alternatives consisting of 1 alternative with current subscription and 4 hypothetical alternatives in 4 choice sets. Modification of traditional conjoint survey in this way enabled us to estimate the factors related to switching cost or switching threshold in addition to the effects of attributes. Also, by using both revealed preference data(1 alternative with current subscription) and stated preference data (4 hypothetical alternatives), additional advantages in terms of the estimation properties and more conservative and realistic forecast, can be achieved. Second, we asked the respondents to choose the most preferred alternative while considering their expected adoption timing or switching timing. Respondents are asked to report their expected adoption or switching timing among 14 half-year points after the introduction of next generation broadcasting services. As a result, for each respondent, 14 observations with 5 alternatives for each period, are obtained, which results in panel-type data. Finally, this panel-type data consisting of $4{\ast}14{\ast}1000=56000$observations is used for estimation of the individual-level consumer adoption model. From the results obtained by empirical application, in case of forecasting the demand of new products without considering existence of previous product(s) and(or) switching cost factors, it is found that overestimated speed of diffusion at introductory stage or distorted predictions can be obtained, and as such, validities of our proposed model in which both existence of previous products and switching cost factors are properly considered, are verified. Also, it is found that proposed model can produce flexible patterns of market evolution depending on the degree of the effects of consumer preferences for the attributes of the alternatives on individual-level state transition, rather than following S-shaped curve assumed a priori. Empirically, it is found that in various scenarios with diverse combinations of prices, IPTV is more likely to take advantageous positions over Digital Cable TV in obtaining subscribers. Meanwhile, despite inferiorities in many technological attributes, Analog Cable TV, which is regarded as previous product in our analysis, is likely to be substituted by new services gradually rather than abruptly thanks to the advantage in low service charge and existence of high switching cost in fixed charged broadcasting service market.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.105-117
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• 2016

Recently the passenger of railway satisfaction levels are lowered. the reason why the railway station was built without considering the increased passenger due to diversification(transfer, shopping, and etc.) of the domestic railway station infrastructure. Especially, in case of KTX Gwangju-Songjeong Station, the number of its passenger has been increased about more than three times since its opening in 2015, so that there are much inconvenience generated in the station congested with passengers. his study aims to excute using Pedestrian simulation and Design Hourly Factor concepts of Highway Engineering, in order to designing the optimum area through the passenger demand forecast for each station. For this analysis was divided into the second stage. Frist, the railway passenger was calculated by using the methodology of Design Hourly Factor that is used during road design in the aspect of traffic engineering. Second, we tried to analyze the level of service in each railway station facility through the pedestrian simulation. Analytical results show that utilizing pedestrian simulation provides verification for calculation of LOS of each railway station facility. Therefore, In the future when designing railway station of facilities will be possible to suggest the facilities area based on LOS.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.46-52
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• 2017

Social attention to information security field is inspired, and manpower demand forecast of this area is getting high. This study surveyed information security knowledge of practitioners who work in a field of information security such as computer and network system. We analyzed a connection between survey data, information protection job system that was suggested by NICE, IT skills that NCS and KISA classified and security field classification system. Base on data that analyzed, this study suggests a curriculum that trains professional manpower who perform duties in the field of information security. Suggested curriculum can be applied to 2 year college, 3 year college and 4 year college. Suggested curriculum provides courses that students who want to work in a field of information security must learn during the college. Suggested courses are closely connected to a related field and detailed guideline is indicated to each course to educate. Suggested curriculum is required, and it combines a theoretical education that become basis and a practical education so that it is not weighted to learn theory and is not only focusing on learning simple commands. This curriculum is established to educate students countermeasures of hacking and security defend that based on scenario that connected to executive ability. This curriculum helps to achieve certificates related to a field more than paper qualification. Also, we expect this curriculum helps to train convergent information security manpower for next generation.