• Transportation Technology and Policy
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• v.6 no.3
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• pp.205-208
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• 2009

• Environmental and Resource Economics Review
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• v.21 no.4
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• pp.921-945
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• 2012

Conditional Logit (CL) model is widely used since its model estimation and interpretation of results of the model is relatively easy, on the other hand, it has the limit of preference heterogeneity of respondents being not fully considered. In this study we used the two models, Mixed Logit (ML) Model and Latent Class Model (LCM) to explain preference heterogeneity of respondents for protection for Boryeong Dam wetland. As a result of the examination for heterogeneity in Boryeong city and six metropolitan areas, we found there was significant difference between two regions. While there was explicit preference heterogeneity within respondents in Boryeong city, we found little heterogeneity within respondents in six metropolitan areas. Thus in the case of six metropolitan areas, CL model can be used for parameter estimation while in the case of Boryeong city, WTP estimates are based on parameter estimates from ML model to reflect the heterogeneity within respondents. Additionally, ML model with interaction and 2-class LCM for respondents in Boryeong city were used to explain the sources of the heterogeneity. The ML model with interaction has advantage of explaining individual unobserved heterogeneity. However The comarison between these two models reflects the fact that LCM provided added information that was not conveyed in the ML model with interaction. Thus, Preference heterogeneity within respondents in this study may be better explained by class level through LCM rather than indiviual level through ML model.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.695-723
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• 2018

Recently, extreme weather due to climate change has become more frequent, and increase of fine dust has worsen air quality in Korea. Therefore, not only negative perception on coal-fired power generation is dominant, but also the social acceptance of nuclear power generation declines. This study aims at deriving consumer preferences on the mid and long term power mix with various energy sources. Willingness to pay for each generation source was estimated and the preference heterogeneity of consumers was examined by using mixed logit and latent class models. Mixed logit estimation results show that the preference heterogeneity of consumers is especially large for the nuclear power relative to renewable or coal energy. According to the estimation results from the latent class model, group 1 prefers renewable energy while group 2 prefers coal energy. Group 3 shows lexicographic preference which means restricted rationality. As for the policy implication, it is necessary to understand the preference heterogeneity of consumer groups in planning the mid to long term power mix.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.49-65
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• 2023

In response to the growing global concern for the environment, the international community has recently committed to achieving 'carbon neutrality.' As a result, numerous studies have been conducted on mode choice models that include carbon emissions as a variable. However, few studies have established a correlation between individual preferences and carbon emissions. In this study, a new mode of transportation named sustainable public transit (SPT), incorporating carbon-reducing transport options like electric scooters, is proposed. Analyzing the individual preferences of commuters on carbon emissions through factor analysis, a stated preference (SP) survey was conducted. A mode choice model for SPT was constructed using multinomial logit models. The results of the analysis showed that gender, income, and specific preferences, such as a passion for exploring new routes, a preference for intermodal transfers, knowledge of carbon reduction, and carbon reduction practices, significantly influence latent preferences for SPT. Therefore, this study is significant as it considers carbon emissions as an attribute variable during the construction of mode choice models and reflects the individual preference variables associated with carbon reduction.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.99-107
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• 2010

Analyzing mode choice among transportation demand estimate procedures is complicated and understanding characteristics of travelers is also difficult. Generally, it is well known that traveler choose mode considering psychometric factors and characteristic besides socio-demographic indicators. Accordingly, many researches has investigated on methodology that can be applied in mode choice to reflect psychometric factor or specific preference. Latent Class Analysis among various studies is recognized as the theoretically potential approach. This study focuses on class segmented using latent class cluster to analyze impact that included psychometric factors and characteristics on mode choice. It also provides evidence that mode choice model for each class and mode choice model not considering latent class are different. This study based on citizen's stated preference and revealed preference on a new transit on the Han river shows that latent class cluster analysis is the potential approach considering latent preference.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.59-67
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• 2013

In this paper, we propose the LAR_CF, latent attribute rating-based collaborative filtering, that is robust to data sparsity problem which is one of traditional problems caused of decreasing rating prediction accuracy. As compared with that existing collaborative filtering method uses a preference rating rated by users as feature vector to calculate similarity between objects, the proposed method improves data sparsity problem using unique attributes of two target objects with existing explicit preference. We consider MovieLens 100k dataset and its item attributes to evaluate the LAR_CF. As a result of artificial data sparsity and full-rating experiments, we confirmed that rating prediction accuracy can be improved rating prediction accuracy in data sparsity condition by the LAR_CF.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.581-586
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• 2007

정부의 IT839정책과 함께 유비쿼터스 환경이 실현되고 있는 요즘, 홈 네트워크 산업은 크게 성장하고 있는 추세이다. 이에 발맞추어 홈네트워크 산업의 활성화를 위해 정책 제안이나 현황 보고와 같은 연구들이 많이 이루어졌다. 그러나 이용자들의 입장에서 홈네트워크 서비스에 대한 관심이나 선호분포에 관한 연구는 부족하다. 따라서 븐 연구의 목적은 홈네트워크 서비스들에 대한 이용자들의 선호도를 조사하는데 있다. 이를 위해 먼저 다양한 홈네트워크 서비스들을 특성에 따라 분류한 후 잠재 이용자들을 대상으로 각 서비스에 대한 호감도를 조사하였다. 그 후 잠재 이용자들의 특성에 따라 홈네트워크 서비스들과 대응일치분석(Correspondence Analysis)을 하였다. 연구 결과 모든 잠재 이용자들이 안전관련 서비스에 높은 관심을 표하였으며 특히 고령일수록 그 관심은 더 높게 나타났다. 그리고 인터넷을 거의 사용하지 않는 집단은 홈네트워크 서비스에 낮은 관심을 보였다.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.357-366
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• 2013

This study investigates to explain preference heterogeneity of respondents for economic valuation in washland of Upo wetland using Mixed Logit Model and Latent Class Model. Mixed Logit Model showed respondent heterogeneity in the attributes of wetland area and funds as well as some alternatives violated IIA assumption. 2-class Latent Class Model for respondents were used to explain the sources of the heterogeneity. Class 1 respondents who are located relatively close to Upo wetland had more experience and knowledge of Upo wetland and better understood the information suggested in the questionnaire than class 2 respondents in mostly metropolitan area of Seoul, Incheon.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.135-136
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• 2016

최근 각종 사물인터넷 제품이 시장에 출시되면서 관련 업체들은 시장 선점을 위해 표준화 플랫폼 분야에서 경쟁을 벌이고 있다. 또한 이동통신 3사를 중심으로 가정용 사물인터넷 서비스를 앞 다투어 출시하면서 시장을 뜨겁게 달구고 있다. 대표적 출시된 서비스는 스마트홈 관련 서비스가 있다. 이동통신 기반 사물인터넷 서비스는 초기 단계에 머물고 있으며 지속적으로 다양한 서비스가 출시될 것으로 예상된다. 이러한 시점에 이미 출시된 서비스를 중심으로 사물인터넷 서비스에 대한 선호도 분석을 기획하게 되었다. 새로운 제품이나 서비스가 출시되는 경우에 잠재적인 구매자들이 제품 및 서비스가 어떠한 속성에 영향을 받아 그 제품이나 서비스를 선택하게 되는지에 대한 연구는 연구자에게 매우 흥미로운 주제이다. 따라서 문헌분석과 시장조사를 통해 사물인터넷 서비스를 고찰하여 선호도 분석 개념모델을 완성하고자 한다. 또한 이동통신 3사에 근무하는 직원(전문가)를 중심으로 설문을 통해 선호도 분석을 하고자 한다. 분석결과를 바탕으로 연구의 한계와 이론적 실무적 시사점을 제시하고자 한다.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.133-142
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• 2008

The term, travel time reliability, refers to variations in journey time that travelers cannot predict. This issue has been one of the main research topics in transport studies. This paper, especially, investigates the value of travel time reliability. The marginal substitution rate method is suggested as the way for the valuation and travelers' stated preference data are collected based on a choice experiment. A mode choice model is estimated using the data surveyed. The parameters of travel costs and travel time reliability from the model are used to calculate the marginal substitution rate that is interpreted as the value of travel time reliability. The value is arranged by travel areas of intercity and urban trips and by journey purposes of working and non-working types. The result of this research is expected to be helpful of conducting more cautious economic feasibility studies of transport schemes.