• Korean Management Science Review
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• v.22 no.1
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• pp.179-197
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• 2005

This study examines market acceptance for DMB service, one of the touted new business models in Korea's next-generation mobile communications service market, using adoption end diffusion of innovation as the theoretical framework. Market acceptance for DMB service was assessed by predicting the demand for the service using the Bass model, and the demand variability over time was then analyzed by integrating the innovation adoption model proposed by Rogers (2003). In our estimation of the Bass model, we derived the coefficient of innovation and coefficient of imitation, using actual diffusion data from the mobile telephone service market. The maximum number of subscribers was estimated based on the result of a survey on satellite DMB service. Furthermore, to test the difference in diffusion pattern between mobile phone service and satellite DMB service, we reorganized the demand data along the diffusion timeline according to Rogers' innovation adoption model, using the responses by survey subjects concerning their respective projected time of adoption. The comparison of the two demand prediction models revealed that diffusion for both took place forming a classical S-curve. Concerning variability in demand for DMB service, our findings, much in agreement with Rogers' view, indicated that demand was highly variable over time and depending on the adopter group. In distinguishing adopters into different groups by time of adoption of innovation, we found that income and lifestyle (opinion leadership, novelty seeking tendency and independent decision-making) were variables with measurable impact. Among the managerial variables, price of reception device, contents type, subscription fees were the variables resulting in statistically significant differences. This study, as an attempt to measure the market acceptance for satellite DMB service, a leading next-generation mobile communications service product, stands out from related studies in that it estimates the nature and level of acceptance for specific customer categories, using theories of innovation adoption and diffusion and based on the result of a survey conducted through one-to-one interviews. The authors of this paper believe that the theoretical framework elaborated in this study and its findings can be fruitfully reused in future attempts to predict demand for new mobile communications service products.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.23-29
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• 2013

This paper presents inventory models for fresh agriculture products with time-varying deterioration rate. Due to the particularity of fresh agriculture products, the demand rate is a function that depends on sale price and freshness. The deterioration rate increases with time and is assumed to be a time-varying function. In the models, the inventory cycle may be constant or variable. The optimal solutions of models are discussed for different freshness and the deterioration rate. The results of experiments show that the profit depends on the freshness and deterioration rate of products. With the increasing inventory cycle, the sale price and profit increase at first and then start decreasing. Furthermore, when the inventory cycle is variable, the total profit is a binary function of the sale price and inventory cycle. There exist unique sale price and inventory cycle such that the profit is optimal. The results also show that the optimal sale price and inventory cycle depend on the freshness and the deterioration rate of fresh agriculture products.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4519-4533
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• 2015

Hypertext Transfer Protocol (HTTP) adaptive streaming has become a new trend in video delivery. An HTTP adaptive streaming client needs to effectively estimate resource availability and demand. However, due to the bitrate of the video encoded in variable bitrate (VBR) mode, a bitrate mismatch problem occurs. With the rising demand for mobile devices, the likelihood of cases where two or more HTTP adaptive streaming clients share the same network bottleneck and competing for available bandwidth will increase. These mismatch and competition issues lead to network congestion, which adversely affects the Quality of Experience (QoE). To solve these problem, we propose a video rate adaptation scheme for the HTTP video streaming to guarantee and optimize the QoE. The proposed scheme estimates the available bandwidth according to the bitrate of each segment and also schedules the segment request time to expedite the response to the bandwidth variation. We used a multi-client simulation to prove that our scheme can effectively cope with drastic changes in the connection throughput and video bitrate.

• Journal of Navigation and Port Research
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• v.35 no.2
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• pp.159-165
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• 2011

The aim of paper is to calculate the optimized size of Mobile Harbor(MH) which would be operated in South Korea coast area. MH is the combined entity which has the function of both ship and container port. In estimating the optimized size, the total cost concept is applied to the different size of MH. Trade-off factors for calculating total cost are MH cost and the over-capacity lost cost. The factors for MH cost estimation are the cargo demand, distance from origin to destination, voyage route and MH's fixed and variable cost in both sailing and port. The other cost is the over-capacity lost cost which is occurred from dead space in case of oversize compared with a voyage demand. The alternatives for the least cost are 250TEU, 500TEU, 750TEU and 1,000TEU sized vessel. The result of research is that 250TEU sized vessel is optimized in a South Korea costal service. If the coastal area be separated in terms of voyage distance or the specific area in considering trade, the optimized size is changed depending upon distance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.81-91
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• 2019

Although the number of users of urban railways is greatly influenced by the land use plan around the railway station, Korea has been studying this problem in a small scale, so that the entrance width is uniformly calculated irrespective of the land use plan, And there is little deviation. Therefore, this study aims to establish a demand estimation model for the entrance and exit of urban railway stations. For this purpose, the demand, land use area, and socioeconomic indicators for each of the 20 urban railway stations were surveyed at 200m and 500m Regression model. The model is based on the assumption that the dependent variable (response variable) of the model is set to 1 day, peak 1 hour, peak time 5 minutes, Education, and park) and socioeconomic indicators (population, employer, employee, and student) as independent variables (explanatory variables). As a result, it was analyzed that the fit of the model is more statistically significant when the use area of the land use by 500 meters of the center radius of the city rail is used as an independent variable and the demand for the daily use of the railway station is used as a dependent variable. The purpose of this study is to estimate the optimal size of urban railway entrance in order to improve the mobility of the user and the transportation weak in urban railway station.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.3
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• pp.23-35
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• 2013

It is very important that the calculation of railroad track capacity in infrastructure investment analysis and train operation planning. The dwelling time is one of the factors that influence in railroad track capacity. Current research in dwelling time has been focusing on theoretical investigation, the state of the research in effective variable (dwelling time etc) is insufficient. In this paper, we clearly draw the concept of railroad track capacity and the estimate on modeling of relationship railway demand and dwelling time. Also, we compare and analyze the variation of railroad track capacity according to transit railway demand in Gyeongin Line (Guro~Inchon). This paper is expected to contribute for improving on the in-using equations and methods in train operation planning as well as for improving level of service on railway user.

• Journal of The Korea Institute of Healthcare Architecture
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• v.23 no.1
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• pp.7-14
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• 2017

Purpose: Since the large hospitals are one of the most intensive energy users among building types in Korea, it is important to investigate and apply appropriate energy conservation measures. There are many researches on energy conservation measures for HVAC system in hospitals, but only few useful guidelines for envelope design variables were existed. The building envelope is one of the important factors to building energy consumption and patients' comfort. The purpose of this study is to suggest the most influential envelope design variables for each end-use energy demand. Methods: 100 samples were generated by LHS(Latin Hypercube Sampling) method. After energy performance simulation, global sensitivity analysis was performed by the regression method. DesignBuilder, Simlab 2.2 and JEPlus were used in this process. Results: The most influencing variables are SHGC, SHGC and VT for heating, cooling, and lighting, respectively. However, the most influencing variable for total energy demand is WWR(Window to Wall Ratio). The analysis was conducted based on the coefficient of variance results. Implications: The six envelop design variables were ranked according to the end-use energy demand.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.385-393
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• 2021

This study investigates the effect of infrastructure, economic sectors and its status, foreign direct investment and private investment, as well as the role of political stability in enhancing the tourism demand in the ASEAN region. The research collected the secondary data from the World Bank database and the UNWTO website of 10 ASEAN countries over 17 years from 2000 to 2016. Applying the generalized method of moments, this research found that, "private investment", "economic sectors", "exchange rate and infrastructure measured by "using of the internet" can increase the tourism demand of a country in the ASEAN region. This research provided evidence indicating that the "foreign direct investment" and "inflation" are two detrimental factors for tourist attraction. The major finding confirmed the positive role of "political stability" in increasing tourist arrivals. First, attracting tourists to a country always poses many challenges to its government. It has been observed in the past decades that though there were many documents, which confirmed that industry can help in promoting tourism, very few studies investigated the role of both agriculture and manufacturing sectors in tourism promotion. Secondly, there are only a few studies which verifies the stability of the political system to the tourism demand in the ASEAN region and that this variable (political stability) has the strongest impact.