• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.47-56
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• 2015

Automated detection of interesting web pages could be used in many different application domains. Determining a user's interesting web pages can be performed implicitly by observing the user's behavior. The task of distinguishing interesting web pages belongs to a classification problem, and we choose white box learning methods (fixed effect logit regression and support vector machine) to test empirically. The result indicated that (1) fixed effect logit regression, fixed effect SVMs with both polynomial and radial basis kernels showed higher performance than the linear kernel model, (2) a personalization is a critical issue for improving the performance of a model, (3) when asking a user explicit grading of web pages, the scale could be as simple as yes/no answer, (4) every second the duration in a web page increases, the ratio of the probability to be interesting increased 1.004 times, but the number of scrollbar clicks (p=0.56) and the number of mouse clicks (p=0.36) did not have statistically significant relations with the interest.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.873-900
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• 2007

Non-market valuation studies tend to assume that individual households have homogeneous preferences for a non-market good to value. However, since the preferences for non-market goods, especially environmental goods are more likely to be heterogeneous by nature, it may be more appropriate to assume heterogeneous preferences for non-market goods, which may in turn may lead to reduced biases in the WTP estimation. This study investigate the extent to which individual households have heterogeneous preferences for reduced concentrations of radon, a radioactive indoor air pollutant, for road safety, and for nuclear power safety. We also analyze the effect of heterogeneity assumption on the results of model and WTP estimation. Using the choice experiments and mixed logit models, we found that allowing for heterogeneous preferences improved model fitness and that there existed heterogeneous preferences for both reduced radon concentration and road safety, albeit not for nuclear power safety. The mean WTP for reduced radon concentrations and road safety increased by factors of 2.44 and l.74 respectively with the models allowing for heterogeneous preferences.

• Journal of Agricultural Extension & Community Development
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• v.20 no.2
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• pp.555-585
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• 2013

This study aims to analyze affecting factors on life satisfaction level of the women and partial effects using Ordered Logit Model. For this purpose, socio-economic factors are selected as major independent factors. And the data used was from the third 'Korea Welfare Panel Study'. Analysis shows that social life factors such as the satisfaction of leisure activities, social relationships, family member communication, and positive attitude to life had positive effects with the life satisfaction level of the women. However, economic factors such as home ownership, disposable income had a lower positive impact compared to social life factors. While, satisfaction level of women is negatively related with family member discordance, and classified low-income families. On the basis of these results, government should pay more attention to improve facilities and software that could meet women's needs of social life satisfaction.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.04a
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• pp.83-107
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• 2001

The contingent valuation method used survey questions to elicit people's preferences for public goods by finding out what they would be willing to pay for specified improvement in them. The method is thus aimed at eliciting their willingness to pay in money amounts. It circumvents the absence of markets for public goods by presenting consumers with hypothetical markets in which they have the opportunities to buy the good in question. The hypothetical markets may be modeled after either a private goods market or a political market. Respondents are presented with material, often in the course of a personal interview conducted face to face. An on-site survey was conducted to 1107 randomly selected P-mountain users using a dichotomous choice questionnaire for the contingent valuation method. Seventeen different bid sets were chosen ranging from the lowest bid of 300won to the highest bid of 2,100won to elicit a reasonable entrance fee in the suggested bid had been determined, and the expected value of willingness to pay was estimated using binary-logit model. The average public value of P-mountain per individual user was estimated to be 1,055.92won∼1,995.61won according to the binary-logit model. The economic value of this P-mountain which includes both use value and existence value can be determined by aggregating the average value giving total willingness to pay for the entire population, in this case 5.491 billion ∼ 10.377 billion.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.63-74
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• 2007

Traffic information provision plays an important role in increasing the efficiency of network operation and in providing convenience for roadway users. As a typical device for disseminating real-time traffic information for collective general public, VMS is a prevalent device nowadays and it is being expanded. However, the actual monetary value of traffic information is not quantified up to now. The previous studies regarding VMS traffic information are mainly focused on the behavioral aspects of road users such as departure time and route choices under traffic information provision conditions. This paper tried to estimate the monetary value of VMS traffic information using discrete choice theory and logit model through the stated preference study(SP). The methodological framework adopted in this paper can also be used in evaluating the monetary value of other traffic information providers including PDA, CNS, and mobile phone.

• Journal of Climate Change Research
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• v.5 no.1
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• pp.37-46
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• 2014

The purpose of this study is to analyze the determinants affecting Korean farmers' perception to climate change using multinomial logit and ordered logit model. The major findings of this study are summarized as follows. First, the results indicate that 85.7 percent of farmers have perceived climate change and 85.8 percent of farmers have anticipated that the impact of climate change on agriculture within 10 years. Second, the results show that farming experience, successor to farming, use of computer have a significant impact on expectation to climate change. Finally, the findings also indicate that sex, age, and education have a significant impact on expectation of the mean temperature to climate change.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.109-119
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• 2007

Increasingly, the emphasis in regional Passenger rail Planning is finding ways to more efficiently use existing facilities, with particular attention being Paid to Policies designed to spread Peak-Period travel demand more evenly throughout the week with consideration of train classification. In this context the individual's choice of time to travel is of crucial significance. This paper investigates the use of multinomial logit analysis to model ridership by rail classification using data collected for travel from Seoul to Busan during the one week in October 2004. The Particular model form that was successfully calibrated was the multinomial logit (MNL) model : it describes the choice mechanism that will Permit rail systems and operations to be planned on a more reliable basis. The assumption of independently and identically distributed(IID) error terms in the MNL model leads to its infamous independence from irrelevant alternatives (IIA) property. Relaxation of the IID assumption has been undertaken along a number or isolated dimensions leading to the development of the MNL model. For business and related rail travel patterns, the most important variables of choice were time and frequency to the chosen destination. The calibrated model showed high agreement between observed and Predicted market shares. The model is expected to be of use to railroad authorities in Planning and determining business strategies in the Increasingly competitive environment or regional rail transport.

• The Korean Journal of Food And Nutrition
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• v.22 no.3
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• pp.338-344
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• 2009

This study analyzed consumers' willingness to pay for price increases to avoid the purchase of GM foods by the expansion of GMO labeling. The subjects were asked about their knowledge of GM, concerns of potential hazards, and sources of obtained GM information. The logit model was employed and marginal effects were calculated to interpret the results. The results showed that consumers who perceived the safety of GM technology were less likely to pay for price increases, while consumers who had concerns about GM foods were more likely to pay. In addition, the study demonstrated that consumers residing in urban areas and with low levels of education and income were also less likely to pay for price increases.

• Korean Journal of Organic Agriculture
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• v.25 no.4
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• pp.699-710
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• 2017

This study analyze the willingness to pay for customized agricultural products to diabetes. For this purpose, a survey was carried out for patients with diabetes 212 patients. The main results are as follows. First, the survey found that the interest in health and food was found to be very high in 93.9 % and 85.9 % respectively. This means that there is sufficient market potential if customized food and diets for diabetes are developed. Second, the Logit analysis showed that influential factor for the willingness to pay for a customized diet. The higher the risk, the better the health outcomes, the higher the likelihood that the higher the level of income, the more likely it is to purchase a product for a diabetic food package. Third, the average amount of willingness to pay for the customized food for diabetes patients was 7,823.5 won and the truncated average value was 6,953.3 won.