• Asia Marketing Journal
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• v.8 no.1
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• pp.1-17
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• 2006

A couple of previous studies have warned against the use of homogeneous choice models in assessing the effect of reference price since unaccounted for response heterogeneity may result in spurious reference price effects(Chang, Siddarth and Weinberg 1999; Bell and Lattin 2000). According to Meyer and Kahn(1991), not accounting for consideration set heterogeneity may also bias the effect parameters in the choice model. Therefore, failure to account for these two sources of bias, in fact, have cast doubt on the empirical support for reference price effects in general. In view of aforementioned potential sources of bias, the author investigates the robustness of loss aversion effect in the reference-dependent model after accounting for heterogeneity in response as well as consideration set. The proposed model defines individual household's consideration set based on the posterior distribution of preference obtained from the Empirical Bayes approach. In addition, the same posterior distribution is used to form household-specific reference prices. Response heterogeneity correction is carried out via the Latent Class approach. The proposed model outperforms the Reference-Dependent model that includes the reference price measure most often employed in the previous studies. This implies that as a way of simplifying decision task, consumers restrict their consideration set to a subset of available brands not only in making a brand choice but also in forming reference prices.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.4
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• pp.181-192
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• 2003

We developed a mathematical simulation model to portray the vertical distribution of soil water from the measured weather data and the known soil hydraulic properties, and then compared simulation results with the periodically measured soil water profiles obtained on Jungdong sandy loam to verify the model, In this model, we solved potential-based Richards' equation by the implicit finite difference method superimposed on the predictor-corrector scheme. We presumed that: soil hydraulic properties are homogeneous; soil water flows isothermally; hysteresis is not considered; no vapor flows; no heat transfers into the soil profiles; and water added to soil surface is distributed along the soil profile following partial displacement principle. The input data were broadly classified into two groups: (1) daily weather data such as rainfall, maximum and minimum air temperatures, relative humidity and solar radiation and (2) soil hydraulic data to approximate unsaturated hydraulic conductivity and water retention. Each hydraulic polynomial function approximated using the Chebyshev polynomial and least square difference technique in tandem showed a fairly good fit of the given set of data. Vertical distribution of soil water as approximations to the Richards' equation subject to changing surface and phreatic boundaries was solved numerically during 53 days with a comparatively large time increment, and this pattern agreed well with field neutron scattering data, except for the surface 0.1 m slab.

• Journal of Preventive Medicine and Public Health
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• v.23 no.1 s.29
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• pp.11-21
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• 1990

This study refers to the problem of long-term inpatient flow in a general hospital. In this study, a queueing simulation model was developed for the two departments in the hospital with a homogeneous case mix and relatively many long-term inpatients in order to increase the turnover rate and hospital charges. Before the simulation n, the model was verified by the Kolmogorov-Smirnov test. The following results were generated by three alternative models of the special bed policies. 1. Alternative I : When long term inpatients were admitted to the wards belonging to departments A and B without transfer to other departments and special beds, the average turn-over rate decreased by 2-4% and the average hospital charges decreased by 70 million won. 2. Alternative II : When long-term inpatients were transferred to department C but the transfer of wards was determined by department C in order of clinical need, the average turnover rate increased by 4-13% but the average hospital charges decreased by 30 million won. This result was not greatly different from the present state. 3. Alternative III : When long-term inpatients were transferred to the special wards and department C simultaneously, the increase in the average turnover rate and hospital charges was equivalent to the increase of two beds in the special wards. When the special wards were allocated 16 beds, the average turnover rate of departments A and B increased by about 55% and 20% respectively. Also, the hospital charges increased by about 0.44 billion won. As a result, transfer to department C and the use of 16 beds in the special wards for long-term inpatients of departments A and B is expected to maximize the hospital revenue. However, as the above special bed policy can not increase the turnover rate above 60%, there is a need for a more comprehensive policy to further increase the rate. The development of an elaborate model should include the number of long-term inpatients in all clinical departments, the special wards system or an increase of hospital beds to handle admission needs, and the resources of the hospital by department. When the alternatives are evaluated, a cost-benefit analysis in addition to the turnover rate and the hospital charges should be considered.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.127-140
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• 2010

The benefit that a consumer derives from the use of a good often depends on the number of other consumers purchasing the same goods or other compatible items. This property, which is known as network externality, is significant in many IT related industries. Over the past few decades, network externalities have been recognized in the context of physical networks such as the telephone and railroad industries. Today, as many products are provided as a form of system that consists of compatible components, the appreciation of network externality is becoming increasingly important. Network externalities have been extensively studied among economists who have been seeking to explain new phenomena resulting from rapid advancements in ICT (Information and Communication Technology). As a result of these efforts, a new body of theories for 'New Economy' has been proposed. The theoretical bottom-line argument of such theories is that technologies subject to network effects exhibit multiple equilibriums and will finally lock into a monopoly with one standard cornering the entire market. They emphasize that such "tippiness" is a typical characteristic in such networked markets, describing that multiple incompatible technologies rarely coexist and that the switch to a single, leading standard occurs suddenly. Moreover, it is argued that this standardization process is path dependent, and the ultimate outcome is unpredictable. With incomplete information about other actors' preferences, there can be excess inertia, as consumers only moderately favor the change, and hence are themselves insufficiently motivated to start the bandwagon rolling, but would get on it once it did start to roll. This startup problem can prevent the adoption of any standard at all, even if it is preferred by everyone. Conversely, excess momentum is another possible outcome, for example, if a sponsoring firm uses low prices during early periods of diffusion. The aim of this paper is to analyze the dynamics of the adoption process in markets exhibiting network effects by focusing on two factors; switching and agent heterogeneity. Switching is an important factor that should be considered in analyzing the adoption process. An agent's switching invokes switching by other adopters, which brings about a positive feedback process that can significantly complicate the adoption process. Agent heterogeneity also plays a important role in shaping the early development of the adoption process, which has a significant impact on the later development of the process. The effects of these two factors are analyzed by developing an agent-based simulation model. ABM is a computer-based simulation methodology that can offer many advantages over traditional analytical approaches. The model is designed such that agents have diverse preferences regarding technology and are allowed to switch their previous choice. The simulation results showed that the adoption processes in a market exhibiting networks effects are significantly affected by the distribution of agents and the occurrence of switching. In particular, it is found that both weak heterogeneity and strong network effects cause agents to start to switch early and this plays a role of expediting the emergence of 'lock-in.' When network effects are strong, agents are easily affected by changes in early market shares. This causes agents to switch earlier and in turn speeds up the market's tipping. The same effect is found in the case of highly homogeneous agents. When agents are highly homogeneous, the market starts to tip toward one technology rapidly, and its choice is not always consistent with the populations' initial inclination. Increased volatility and faster lock-in increase the possibility that the market will reach an unexpected outcome. The primary contribution of this study is the elucidation of the role of parameters characterizing the market in the development of the lock-in process, and identification of conditions where such unexpected outcomes happen.

• Journal of the Korean Electrochemical Society
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• v.17 no.1
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• pp.71-77
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• 2014

The performance of catalysts for the recombination of oxyhydrogen gas was measured and compared with the results obtained from theoretical model. The oxyhydrogen gas was generated by the electrolysis cell and recombined through the fixed bed catalytic reactor. The yield that is the ratio of water-amount produced to the water-amount consumed in the electrolysis cell was increased with the increase of KOH concentration in electrolysis cell and the applied current. The catalyst 1 showed the best performance and the yield was under 60 %. The faradic yield calculated by Faraday's law showed about 100% in maximum with catalyst 1. The production rate of water generated by the recombination was 5-40 g/day dependent on the flow rate of mixed gas. Considering the results calculated from the pseudo-homogeneous catalytic reactor model, the hot point inside the reactor was moved to the direction of outlet and the maximum temperatures were $440-480^{\circ}K$ when the gas flow rate increased. The production rate of water calculated from the theoretical model showed good agreement with experimental results below the flow rate of $0.5cm^3/sec$, but there were much differences above that flow rate.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.131-143
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• 2010

This study has aimed to develop accident modification factor(AMF) for rural two-lane roadway segments. Accident Modification Factor is a coefficient to assess roadway safety as reflecting characteristics of homogeneous roadway. It estimates accident frequency of roadway segments with developed base model and exposure. We found on items of such factors as crosswalk, driveway density, topography characteristic, land use and median through statistical models and literature review. To develop accident modification factors, we used statistical model methods and analyses of applicability and expert judgement method were practiced to validate it. Although expert judgement for land use item was questionable, most items were rated acceptable. Result of comparative analysis revealed crash frequencies of IHSDM and KHSEM were most similar with actual. However, accident distribution of KHSEM was more proper than IHSDM. Also overall estimated values of RSDS were found to be overestimated.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.191-209
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• 2011

In a buyer-seller transaction process, 'value for money,' a measure of quality-price-ratio, is one of the most important criteria for buyers' purchasing decisions. The purpose of this paper is to suggest a method which helps online shoppers choose the best of several sellers offering homogeneous goods. We suggest FDH (free disposal hull) model, an applied model of data envelopment analysis (DEA), for online buyer-seller transactions and verify it with the data from an Internet comparison shopping site. For this purpose, we analyze consumer choice behaviors by examining how consumers respond to different sale conditions such as price, brand, or delivery time. Then, we implement a seller recommendation system to support buyers' purchasing decisions. We expect our FDH model to provide valuable information for rational buyers who want to pay the least price for high quality products/services and to be used in implementing automated evaluation processes in micro transactions. Moreover, we expect that our results can be utilized for sellers' benchmarking strategies which help sellers be more competitive by showing them how to attract buyers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3729-3744
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• 2011

As the size of structures become larger by civil and architectural structures becoming large, deeply underground, and high-rise, the conditions of underground foundation vary according to the location that the lack of bearing capacity locally because of ununiform of foundation in some parts is frequent. Generally, when the foundation is not homogeneous, the acquisition of safety through applying the most conservative foundation method possible becomes the focus to secure the stability of the superstructures. It is considered as because of inability to verify the application and stability and application of construction of different foundations through an outlined review because of lack of study in case of different foundation of mixed use of direct foundation and pile foundation. Therefore, through measurement interpretation of the different foundation in which the direct foundation and pile foundation are mixed in use, the grounds in which the hypothetical bearing capacity changes dramatically was modeled to evaluate the applicability of different foundations. Also, based on the results of measurement interpretation, various foundations are created by using plaster, Joomunjin standard soil, and rubble to conduct an indoor model test to compare and analyze the movement of pile foundation and different foundations. Based on such research results, the stability and applicability of the different foundations which is more efficient and economical than the existing foundations in case of grounds in which the bearing capacity changes dramatically by comparing and analyzing the different foundations (direct foundation + pile foundation) with the conservative pile foundation and mat foundation. As a result, when the different foundation is applied, the overall settlement amount increased than the conservative pile foundation. However, the difference was very minute and it has been confirmed to be no issue as a result of assessment of stability of the differential settlement of structures through critical angle displacement.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.3
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• pp.231-246
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• 2012

Recently, the construction of tunnel frequently involves neighboring weak ground conditions. In this case, the stabilized ground could be relaxed by the excavation of tunnel. This will create issues in terms of stability of tunnel. Major factors determining the stability of tunnel can be the direction (angle) of weak zone, the distance between tunnel and boundary of weak zone and so on. In this study, by quantifying the displacement and crack propagation during the excavation of tunnel constructed neighboring weak zone, the influence of the direction of weak zone and the distance between tunnel and boundary of weak zone on the mechanical behavior of tunnel is investigated. A series of experimental scaled model tests by changing the direction of weak zone and the distance between tunnel and boundary of weak zone, are performed and analyzed under the condition of homogeneous material. The results show that as the angle between ground surface and boundary of weak zone moves from horizontal to perpendicular plane, displacement near tunnel increases. An increased distance between tunnel and boundary of weak zone induces displacements near tunnel to decrease and stabilizes beyond a certain level of distance. These findings verify and extend the earlier studies quantitatively. Finally, an appropriate distance between tunnel and boundary of weak zone according to the angle of weak zone is justified. This fundamental insight provides the basis for a more rational design of tunnel neighboring weak ground conditions.