• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.153-160
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• 2012

This study investigates how discrete choice analysis can be applied to health care operations. Discrete choice analysis helps to understand the complex decision-making process of purchasing expensive medical equipments by identifying relative weights that decision makers impose on each attribute through simple virtual choice experiments. We also verified the usefulness of applying discrete choice analysis to the purchase of medical equipments with empirical evidence.

• Proceedings of the Technology Innovation Conference
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• 2003.02a
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• pp.173-190
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• 2003

Demand forecasting is essential in establishing national and corporate strategy as well as the management of their resource. We forecast demand for multi-generation product using discrete choice model combining diffusion model The discrete choice model generally captures consumers'valuation of the product's qualify in the framework of a cross-sectional analysis. We incorporate diffusion effects into a discrete choice model in order to capture the dynamics of demand for multi-generation products. As an empirical application, we forecast demand for worldwide DRAM (dynamic random access memory) and each of its generations from 1999 to 2005. In so doing, we use the method of 'Technological Forecasting'for DRAM Density and Price of the generations based on the Moore's law and learning by doing, respectively. Since we perform our analysis at the market level, we adopt the inversion routine in using the discrete choice model and find that our model performs well in explaining the current market situation, and also in forecasting new product diffusion in multi-generation product markets.

• Current Photovoltaic Research
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• v.10 no.4
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• pp.121-132
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• 2022

The need for floating photovoltaic is being emphasized to expand renewable energy but low residents' acceptance is a major obstacle to the deployment of floating photovoltaic. Using the discrete choice experiment, this study analyzed the preferences for community-based floating photovoltaic projects and proposed a method to increase the residents' acceptance of floating photovoltaic projects. The estimates of the marginal willingness to accept (MWTA) of the distance, the coverage ratio, the landscape, the project owner (public institution), and the project owner (large company) are -0.69%p/km, 0.13%p/%p, -0.57%p, -2.95%p, -1.73%p, respectively. According to the result of simulation analysis, the residents' acceptance is significantly higher when the project is operated by a public institution, with a choice probability of 58%, than when the project is operated by a private company, with a choice probability of 29%, 12% for a large and small company, respectively. In addition, as a result of the analysis of the expected returns, the results show that the closer the distance from the residence to the power plant, the higher the expected return.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.387-394
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• 2006

In Korea, a proton linear accelerator complex is being built as a part of the 21st Century Frontier Projects. Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely. This study shows the method can be applied to the benefit assessment of the proton accelerator complex. Using the discrete choice CVM method, this study estimates the willingness-to-pay (WTP) of a would-be user for the proton accelerator complex as 20,133 won per month.

• Proceedings of the Technology Innovation Conference
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• 2006.02a
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• pp.264-297
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• 2006

In this paper, we attempt to analyze consumer preference for the alternative-fuel vehicles based on data from a stated preference using the conjoint analysis. Five possible fuel types (gasoline, diesel, CNG, LPG, Hybrid (electricity+gasoline)) are covered in conjoint cards. To estimate and analyze consumer preference, discrete choice model is used. Specifically, Bayesian mixed logit model is used. Based on estimating results, we discuss the business strategy and policy for the alternative fuel vehicle.

• Korean Management Science Review
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• v.29 no.2
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• pp.91-103
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• 2012

Revenue management problems originated in the 1970's in the context of the airline industry have been successfully introduced in airline industries. It has started on the capacity control by booking classes for available seats, and has been recognized as a powerful tool to maximize the total revenue. Changing customer behavior and airline market environments, however, has required a new mechanism for improving the revenue. Dynamic pricing is one of innovative tools which is to adjust prices according to the market status. In this paper, we consider a dynamic pricing and seat control problem for discrete time horizon. The problem can be modeled as a stochastic programming problem. Applying the linear approximation technique and given the price set for each time, we suggest a mixed Integer Programming model to solve our problem efficiently. From the simulation results, we can find our model makes good performance and can be expanded to other comprehensive problems.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.209-216
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• 2003

Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely; an example is environmental good. A dichotomous choice approach, the most popular type of CVM in environmental economics, employs binary discrete choice models as statistical estimation models. In this paper, we propose a semiparametric dichotomous choice CVM method using local linear model of Fan and Gijbels (1996) in which probability distribution of error term is specified parametrically but latent structural function is specified nonparametrically. The computation procedures of the proposed method are illustrated with a simple design of simulations.

• Environmental and Resource Economics Review
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• v.21 no.2
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• pp.237-269
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• 2012

This study applies a discrete-continuous choice model to a national survey data set of automobile uses to investigate the potential impacts of a bonus-malus system for new cars in Korea. Not only the impacts on the discrete choice of automobile type and class but also those on the continuous decision making of car operation are analyzed. The characteristics of automobiles and individuals that determine car choice and operation are identified. The simulation based on the estimation result shows that an appropriately designed bonus-malus system can induce a reduction in energy consumption and $CO_2$ emission substantially without additional government expenditure.

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.349-354
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• 2004

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.