• Journal of Urban Science
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• v.9 no.2
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• pp.63-68
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• 2020

In recent years, the planning of livable communities has emerged as a new paradigm. The concept of livable communities is related to both the spatial balance of working, playing, and living and the promotion of green modes of transportation, such as walking and biking. This study uses a disaggregate travel survey conducted by the Seoul Metropolitan Area in 2006. I applied a multi-level random intercept logit model to estimate the effects of land-use characteristics on the choice of green modes, holding a traveler's socio-demographic characteristics constant. The empirical results show that higher density and more mixed land-use development encourages people to walk and bike even when individuals have the same socio-economic characteristics. This paper demonstrates that land-use planning by itself can play a role in the creation of livable cities and the decline of greenhouse gas production.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.129-137
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• 2002

This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but considered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.25-33
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• 2001

This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but condisered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

• Land and Housing Review
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• v.11 no.2
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• pp.1-14
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• 2020

The aim of this study is to empirically identify the differentiating characteristics of determinant factors on sing-person households' commuting mode choice compared to multi-person households' one in order to establish the customized police directions to decrease private car use in commuting. While the study use the 2% sample survey data on the population and housing in 2015, it employ multinomial logit models on relative choice probability of such alternative commuting modes as bus, subway or rail, and walking, rather than driving. As potential determinant factors, the study employs demographic, socio-economic, and housing and residential one for both models of single-person and multi-person households. The study finds that the behavior of commuting mode choice has distinctive difference by gender, marriage status, physical activity constraint, job type, residential period in current housing of the single-person household's workers compared to the multi-person households' ones. Based on the findings, the study deduce ten commuting policy directions customized for the single-person household.

• Journal of Korean Society of Rural Planning
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• v.16 no.1
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• pp.49-62
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• 2010

As people get aged, we need to pay more attention to the elderly living condition with respect to welfare policy. The present study focuses on housing condition of elderly people living in rural area, and analyzes its determinants, periodical difference, and regional disparities, incorporating an index of minimum housing standard. This study applies multi-level logit model that has a strong statistical advantage that can take random aspects of household and regional context into account. We found that married couple household, presence of economically-active family members, higher education, specialized profession, migration and higher level of land price tend to lower the probability of residing in substandard housings. We also found that housing conditions for elderly people prove to be different by regions and it is particularly noticeable in mountainous rural areas in Gyeongsangnam-do and Gyeongsangbuk-do with the poorest elderly housing conditions. Results also implies that housing welfare policies should be implemented differently considering the target groups based on regional differences. We conclude with some additional policy implications for the elderly living in rural areas.

• Journal of Korean Society of Transportation
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• v.15 no.4
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• pp.35-51
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• 1997

The main objective of this research is to develop urban workers' daily travel pattern choice model. For this research, a hovel pattern choice model was empirically estimated by using a survey data collected from Kyongsan and Yeungchun City. For this research, a nested logit model structure was employed. For the model specification, it is hypothesized that urban workers' daily travel pattern choice behavior is represented by two stages of choices with single-destination or multi destination travel pattern choice as the higher stage, and the number of tours as the lower stage. The urban workers' daily travel pattern choice model developed in this research yields intuitively reasonable results. From the empirical results, it is found to be sensible to represent urban workers' daily travel patterns as the nested logit model structure Hypothesized in this research. furthermore, future directions of model development are suggested.

• Journal of Environmental Impact Assessment
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• v.19 no.2
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• pp.117-125
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• 2010

Korea's researchers have recently studied the prediction of forest change, but they have not considered landuse/cover change compared to distribution of forest vegetation. The purpose of our study is to predict forest vegetation based on landuse/cover change on the Korean Peninsula in the 2090's. The methods of this study were Multi-layer perceptrom neural network for Landuse/cover (water, urban, barren, wetland, grass, forest, agriculture) change and Multinomial Logit Model for distribution prediction for forest vegetation (Pinus densiflora, Quercus Spp., Alpine Plants, Evergreen Broad-Leaved Plants). The classification accuracy of landuse/cover change on the Korean Peninsula was 71.3%. Urban areas expanded with large cities as the central, but forest and agriculture area contracted by 6%. The distribution model of forest vegetation has 63.6% prediction accuracy. Pinus densiflora and evergreen broad-leaved plants increased but Quercus Spp. and alpine plants decreased from the model. Finally, the results of forest vegetation based on landuse/cover change increased Pinus densiflora to 38.9% and evergreen broad-leaved plants to 70% when it is compared to the current climate. But Quercus Spp. decreased 10.2% and alpine plants disappeared almost completely for most of the Korean Peninsula. These results were difficult to make a distinction between the increase of Pinus densiflora and the decrease of Quercus Spp. because of they both inhabit a similar environment on the Korean Peninsula.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• East Asian Journal of Business Economics (EAJBE)
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• v.4 no.2
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• pp.1-11
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• 2016

This study investigated commercial power theory of traditional market through the analysis of literature review. Consumers' store selection models are made up a theory based on normative hypothesis, theory of mutual reaction, utility function estimation model, and cognitive-behavioral model. Detailed models are as follows. Normative hypothesis based theory is divided into Reilly's retail gratification theory and Converse's revised retail g ratification theory. Interaction theory is composed of Huff's probability gratification theory, MCI model and Multi-nominal Logit Model (MNL model). There are four models in retail organization position theory such as central place theories, single store position theory, multi store position - assign model, and retail growth potential model. In case of single store position theory, theoretical and empirical techniques have developed for a decision to optimum single store position. Those are like these, a check list, the most simple and systematic method, analogy, and microanalysis technique. Aforementioned models are theoretical and mathematical commercial power measurement and/or model. The study has rather limitations because the variation factors included in formula are only a part of actual commercial power. Therefore, further study shall be made continuously to commercial power areas and variables.

• The Korean Journal of Community Living Science
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• v.21 no.4
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• pp.619-631
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• 2010

The purpose of this study is to segment and examine urban farmers behavior by applying a two-step cluster analysis and multi-nominal logit model. The data were collected by a telephone survey with two-staged stratified random sampling in the cities around the country for the purpose of acquiring representative data. Respondents were asked to describe their awareness of urban agriculture, their agricultural activity, and sociodemographic characteristics. Among 2,000 cases, 381 cases(19.1%) which were of participants in urban agriculture were analysed in SPSS. From the findings, 27.3% of respondents had heard the word 'urban agriculture', and 25.5% of them regarded themselves as urban farmers. Four different clusters were derived from two-step clusters based on motive, place, companion, area and hours. They were 'Large scale hobby farming(cluster 1)', ‘Weekend farm/ hobby farming(cluster 2)', 'Land/ Self-supporting farming(cluster 3)', and 'Small scale hobby farming(cluster 4)'. The result of multinomial logistic regression showed that there were significant differences among these four segmented groups in terms of age, city size and housing type. In other words, there is quite a possibility that urbanites select different urban farming types according to their socio-demographic profiles. Therefore, the urbanite profiles can be used as the basis for promoting policy of several urban agriculture types. According to the result, policy directions for facilitating urban agriculture were presented.