Settlement-Preference Patterns and Characteristics of Households in Urban Renewal Area <br />Jinkyung LEE, Seungil LEE, Ky...
Contents<br />Housing Issues in Seoul<br />Research Questions<br />Method and Model<br />Data<br />Estimation Results<br /...
Housing Issues in Seoul<br />3<br />Decreasing housing stocks available for low income groups  by urban redevelopment proj...
4<br />Research Questions<br />What are preference factors of resettlement in Urban Renewal Area (URA) ?<br />    Identify...
Method<br />5<br />The polytomous logistic regression model (PLRM) is selected to test the attitude-need recognition relat...
Model<br />6<br />For dependent variables with some number of categories M, this requires the calculation of M-1 equations...
Model<br />7<br />Where the subscript k refers, as usual, to specific independent variables X and the subscript h refers t...
Model<br />8<br />For the five-category dependent variable, the PLRM in this study was expressed with four log-linear func...
Variable of PLRM<br />9<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
Data<br />10<br />The data was collected by the Seoul Government Residential Improvement Committee (SGRIC) in 2008 to inve...
Data: Sample profile<br />11<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
12<br />Estimation Results<br />PLRM relied on maximum likelihood procedures to estimate the model coefficient. The model ...
Estimation Results<br />13<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
Findings<br />14<br />When household head’s job location is nearby of original site, respondents are more likely to prefer...
Discussion<br />15<br />Because householders in URA prefer to move to a nearby village, the sudden increase in demand due ...
Settlement-Preference Patterns and Characteristics of Households in Urban Renewal Area <br />감사합니다 !<br />Thank You!<br />...
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Settlement-Preference Patterns and Characteristics of Households in Urban Renewal Area - Jinkyung LEE, Seungil LEE, Kyuil KIM - Institute of Urban Sciences, Univ. of Seoul, Korea

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Settlement-Preference Patterns and Characteristics of Households in Urban Renewal Area - Jinkyung LEE, Seungil LEE, Kyuil KIM -

  1. 1. Settlement-Preference Patterns and Characteristics of Households in Urban Renewal Area <br />Jinkyung LEE, Seungil LEE, Kyuil KIM<br />Institute of Urban Sciences, Univ. of Seoul, Korea<br />Mar. 24, 2010<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  2. 2. Contents<br />Housing Issues in Seoul<br />Research Questions<br />Method and Model<br />Data<br />Estimation Results<br />Findings and Discussion<br />2<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  3. 3. Housing Issues in Seoul<br />3<br />Decreasing housing stocks available for low income groups by urban redevelopment projects, <br />High rent, lack of affordability of low-income families,<br />An excessive polarization: a gap of housing affordability between income groups, <br />A localized imbalance between demand and supply of housing.<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  4. 4. 4<br />Research Questions<br />What are preference factors of resettlement in Urban Renewal Area (URA) ?<br /> Identifying expected preference factors of URA<br />Is there the relationship between the elements of the settlement pattern and some household’s characteristics in URA ? <br /> Examining characteristics among them<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  5. 5. Method<br />5<br />The polytomous logistic regression model (PLRM) is selected to test the attitude-need recognition relationship in URA. <br />PLRM may be extended beyond the analysis of dichotomous variables to the analysis of categorical (nominal or ordinal) dependent variables with more than two categories. <br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  6. 6. Model<br />6<br />For dependent variables with some number of categories M, this requires the calculation of M-1 equations, one for each category relative to the reference category, to describe the relationship between the dependent variable and the independent variables. For each category of the dependent variable except the reference category, we may write the equation 2 . <br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  7. 7. Model<br />7<br />Where the subscript k refers, as usual, to specific independent variables X and the subscript h refers to specific values of the dependent variable Y. For the reference category, g0(X1, X2, …, Xk) = 1. The probability that Y is equal to any value h other than the excluded value h0 can be written by the equation 3<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  8. 8. Model<br />8<br />For the five-category dependent variable, the PLRM in this study was expressed with four log-linear functions as follows:<br />where, <br />pi = probability of event i for i =1,2,3,4,5 <br />β1js, β2js, β3js, and β4js are parameters with 0 ≤ j ≤ m<br />Xks are independent variables with 1 ≤ k ≤ m<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  9. 9. Variable of PLRM<br />9<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  10. 10. Data<br />10<br />The data was collected by the Seoul Government Residential Improvement Committee (SGRIC) in 2008 to investigate dwelling situations in URA and to develop policies improving their problems. <br />The households data of this survey was selected by systematic sampling among households living in 28 URA or owners of houses there. A systematic sampling method was used to select the representative samples. <br />The respondents were eligible respondents who were willing to participate in face-to-face, in-home interviews. A total of 1,014 in-home personal interviews were conducted. <br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  11. 11. Data: Sample profile<br />11<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  12. 12. 12<br />Estimation Results<br />PLRM relied on maximum likelihood procedures to estimate the model coefficient. The model worked fairly well, as indicated by the statistically significant model Chi-square and the McFadden R2 of 0.060. PLRM had -2LL(0) of 419.570 and -2LL(k) of 357.809. <br />The Chi-square was 61.760 with p-value of 0.005 in 36 df, which indicated a very good overall model fit. To evaluate goodness of fit of the model, SPSS computed two measures of the pseudo-variance explained, Cox and Snell R2 of 0.109 and Negelkerke R2 of 0.121. <br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  13. 13. Estimation Results<br />13<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  14. 14. Findings<br />14<br />When household head’s job location is nearby of original site, respondents are more likely to prefer nearby. Especially, settlement-preference in same district, household head’s job location is impact factor. <br />Low income households and high income households intend to prefer settlement within the Seoul. <br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  15. 15. Discussion<br />15<br />Because householders in URA prefer to move to a nearby village, the sudden increase in demand due to redevelopment projects, can lead to an increase in the house price for rent or buying. <br />Renewal development projects needs to be transferred private initiatives to public initiatives, public sectors should intervene directly and/or indirectly in the projects to secure confidence and drive out absurdities. <br />Public sectors can expect a filtering effect as the supply of diverse types of houses for original householders including low income.<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />
  16. 16. Settlement-Preference Patterns and Characteristics of Households in Urban Renewal Area <br />감사합니다 !<br />Thank You!<br />ありがとうございます !<br />ICCSA 2010 INTERNATIONAL CONFERENCE, Fukuoka, Japan <br />

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