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The objective of this study is to determine if the appraised unit value ($/sf) of unimproved land parcels in Houston, Texas could be predicted by a regression equation containing a group of independent variables that represent LEED transportation access criteria and the area of a land parcel. The independent variables, number of bus stops, number of rail stops and parcel area, were all found to contribute significantly to the independent variable, appraised unit value of a parcel. The observational unit was properties in Houston, Texas that were unimproved (had zero improvement value). Findings suggest that the acceptance criteria for the LEED green building rating system regarding public transportation access have a significant influence on the appraised value in dollars per square foot of the subject properties. Based on the sample median lot size of 5,300 square feet, the predicted lot value increases dramatically in proportion to the number of qualifying light rail stations and decreases marginally in proportion to the number of qualifying bus stops. Since the regression model and each independent variable were all significant at p<0.05 and the adjusted R-square was near 0.50, the study objective was deemed to have been answered in the affirmative. Keywords: sustainable development; LEED; public transportation access; sustainable site; regression analysis 1. Introduction The aim of this study is to predict the appraised Awareness of sustainability and the environment has values (in dollars per square foot) of unimproved led to the emergence of various voluntary standards parcels in Harris County, Texas, based on the LEED for buildings such as LEED (USA). These standards sustainable rating for Public Transportation Access. claim to be market driven and serve as environmental The population of interest was parcels which were building assessment methods. For these approaches within one mile outside of Beltway 8, which encircles to be viable as well as successful, it is essential to Texas. Parcels, randomly selected, were unimproved. find out if the value of green projects incorporates As specified by the Harris County Appraisal District, environmental costs and benefits. "Green buildings" these parcels had zero improvement value. Each parcel have gained popularity in some sectors of the economy served as an observational unit for data collection and in response to pricing signals. Little empirical evidence analysis. The theme of this research was quantitative is available to support the idea that commercial real and the data gathered was analyzed using appropriate estate prices incorporate sustainability characteristics statistical tools. If the suggested model indicates a despite the financial and environmental benefits of significant relationship between unit value (dollars building sustainability. Unfortunately, very few studies per square foot) of land and LEED rating, property have attempted to gauge the price effects of green market value will be consistent with the LEED building ratings (Fuerst and McAllister 2011; Lee and public transportation access criteria. Knowledge of Yeom 2012). potentially increased property values may encourage project developers to site their projects where public transportation is accessible. *Contact Author: Kiyoung Son, Assistant Professor, 2. Literature Review School of Architecture, University of Ulsan, 93 Daehakro, 2.1 Sustainable Land Development Ulsan, 680-749, Republic of Korea Various perspectives have been contemplated to Tel: +82-52-259-2788 Fax: +82-52-259-1690 answer questions like "Why do organizations adopt E-mail: email@example.com voluntary, environmental standards?" and "What is the ( Received April 2, 2014 ; accepted October 31, 2014 ) Journal of Asian Architecture and Building Engineering/January 2015/111 105 societal value of such standards?" Organizations might unimproved land with zero improvement value was be motivated to adopt innovations, including voluntary considered. standards because they want to be recognized for Houston, Texas is ranked as the fourth most their commitment to environmental issues in their populous city in the United States (City of Houston, industry (Lee and Yeom 2009). They might want to 2009). Since 1999, Houston has alternated its position communicate something about their practices to the with Los Angeles for being the most polluted city in outside world, including regulators, customers and the United States (Wilson 2007). Along with pollution the public. On the other hand, adoption may be driven caused by petrochemical and power plants, Houston by the pursuit of elemental benefits, meaning that faces severe pollution caused by automobiles. The the organization anticipates actual economic and/or prime reason for the pollution is congested highways, environmental benefits that are a direct result of the which are due to enormous population-growth in the standards, regardless of perceptions of the outside last decade. According to U.S Census Bureau (2000) world (Corbett and Muthulingam 2007). statistics, the population of Houston has increased by USGBC, through its publication LEED for New 19.7% from 1990 to 2000. People are forced to move Construction Version 3.0, presents sustainable site further out into the surrounding suburbs in search of guidelines and encourages using these metrics to make affordable housing. As a result, the city's population decisions regarding sustainable land development is facing increasingly longer commutes between (USGBC 2009). As mentioned earlier, this rating home, work and leisure. Houston is now spread over a system helps to make decisions regarding land significant area. This poses a challenge for authorities, development/restoration projects in such a way that who are responsible for implementing measures to the local ecosystem is preserved. Sustainability of reduce pollution. land development/restoration projects optimizes According to the U.S. Census Bureau (2000) data, economic value while preserving the environment mean travel time to work is 27 minutes. This data (USGBC 2011). Unfortunately, there are very few also shows that 77.8% drove alone and 12.7% car- studies which attempt to understand the economic pooled with private automobiles. This has put local worth of this voluntary rating system. This paper government under constant pressure to keep the focuses on identifying the relationship between the infrastructure, such as highways, roads, and public LEED sustainability rating (Public Transportation transit, operating well. New highways are under Access) and the economic worth of the land. If there construction and more road lanes are added to existing is no meaningful relationship between these variables, highways to meet the current needs of the public and then it may be difficult to justify the motivation of to provide adequate capacity for the future. U.S Census organizations to adopt these voluntary standards. data suggests that people prefer private automobiles to Moreover, it will be difficult to encourage sustainable the existing mass transit system. This might be because land development/restoration projects for economic existing transit facilities are somewhat inefficient or reasons. that they have limited connectivity. Local authorities Sales price information is difficult to gather. Also, in Houston are considering efficient mass transit infrequency of sales makes the parcels incomparable systems to reduce pollution caused by automobile use. on a value basis. This infrequency makes it difficult to LEED encourages developers to select sites that have know the amount at which any given land will transact convenient access to mass transportation networks at any given time (Rappaport 2007). Hence, appraised (USGBC 2009). value of parcels appeared to be the best alternative Transportation/utilities to make meaningful comparisons. "No two houses (3%) Agricultural Office (3%) (1%) Open water are the same. The specific combination of attributes, No data (4%) (1%) Commercial both locational and physical, associated with any (4%) Undeveloped Multi-family building determines that building's quality" (Choi and (24%) (4%) Cho 2014). Heterogeneity among buildings makes Public/institutional (5%) comparisons difficult if not impossible. Industrial In addition, the appraised land value can be affected (7%) Parks/open space (24%) by economic conditions such as inflation (or deflation) Roads over time. To effectively control this factor, the studied (15%) Single-family (21%) data were limited to parcels for "unimproved" lands Source: City of Houston Planning and Development Department, 2008) only. The real property values consist of land plus any improvements attached to the land (Son et al. 2013). Fig.1. Land Use Distribution in the City of Houston Fig. 1. Land Use Distribution in the City of Houston Externalities like the economic condition may affect the value of improved lands. As this study focuses Houston has the largest area, 618 square miles, of on the appraised value of unimproved lands, changes all major US cities. Houston is the largest city in Texas in the value of lands associated with time-variability in terms of population, size and number of persons per can be minimized. Therefore, for this study, only square mile. Between 1990 and 2000, Houston had a 106 JAABE vol.14 no.1 January 2015 Hee Su Han very small (1.2%) increase in owner occupied units. light rail or subway station. Also, the housing value increased by 1.05% from 1990 2) Locate project within ¼ mile walking distance to 2000 (City of Houston Planning and Development (measured from a main building entrance) of one or Department 2008). The pie-chart (see Fig.1.) shows more stops for two or more public bus lines usable by land use distribution in the City of Houston. In 2000, building occupants. vacant and undeveloped land accounted for 24% (i.e. 91,370 acres) of the total land use in the city. This 3. Hypothesis and Data Collection largest single land use classification is followed by 3.1 Hypothesis single-family residential use. The linear regression model tested the predictability Almost 1/3 of the City's vacant land is located south of the unit value of a parcel using the area of the of Loop 610, accounting for 29,008 acres in total. parcel, number of bus stops and number of rail stations Vacant land inside Loop 610 is comprised of small that met LEED criteria for that parcel. The model parcels distributed with mixed uses. Vacant parcels was used only for those parcels that qualified for located towards the city boundaries tend to be large, LEED credit. The model had one dependent variable; causing discontinuities in the patterns of urbanization appraised value/square foot of a parcel. The following (C i t y o f Hou st on Pl a nni ng a nd De ve l op m e nt were independent variables which were considered as Department 2008). This land use pattern is important to predictors of the dependent variable: consider since this research study included only vacant parcels. Independent Variable 1: Number of bus stops which 2.2 LEED for New Construction met the LEED criteria In 2000, the U.S Green Building Council (USGBC) Independent Variable 2: Number of rail stations released a rating system called the Leadership in which met the LEED criteria Energy and Environmental Design (LEED) for Independent Variable 3: Area of parcel, measured in New Construction (LEED-NC). This rating system square feet along with focusing on the building operational and maintenance issues, addresses the different project Here, the hypothesis to be tested was that this development/delivery processes that exist in the US model was statistically significant and was capable of building design and construction market (USGBC predicting the appraised value per square foot of the 2009). parcel using the independent variables. This LEED-NC addresses the environmental Appraised Value/square foot of a parcel=β + β 0 1 impacts of site and materials selection, demolition, (Number of bus stops for a given parcel that met LEED and construction. Since its launch in 2000, over 4,000 criteria) + β (Number of rail stations for a given parcel building projects have certified for LEED-NC in the that met LEED criteria) + β (Area of parcel) + ε. U.S. (USGBC 2011). The primary goal of LEED- NC is to promote healthful, durable, affordable, and β = intercept, appraised value per square foot of a environmentally sound practices in building design parcel when neither bus stops nor rail stations and construction (USGBC 2009). LEED-NC levels are met the LEED criteria awarded according to the following: β = partial slope for number of bus stops or expected 1) Certified: 40-49 credits change in appraised value per square foot of a 2) Silver 50-59 credits parcel when one more bus stop which met the 3) Gold 60-79 credits LEED criteria was added to the parcel while 4) Platinum: 80 points and above controlling other independent variables LEED-NC addresses seven categories such β = partial slope for number of rail stations or as Sustainable sites, water efficiency, energy expected change in appraised value per square and atmosphere, materials and resources, indoor foot of a parcel when one more rail station environmental quality, innovation in design, and which met the LEED criteria was added to regional priority (Joshi 2009). Among them, in the parcel while controlling other independent Sustainable Sites Credits (SSC), there are eight credits variables such as a) site selection, b) community connectivity, c) β = partial slope for area of parcel brownfield redevelopment, d) alternative transportation, ε = error e) site development, f) storm water design, g) heat island effect, and h) light pollution reduction. This SSC This model was derived from a sample of 150 consists of 26 credits out of 110. Among SSC, this parcels that included the number of bus stops and study has focused on credit 4.1: Public Transportation rail stations which were within the qualifying LEED Access (PTA). The credit has the following aspects: distances. 1) Locate project within ½ mile walking distance 3.2 Population of Interest (measured from a main building entrance) of an As shown in Fig.2.(a), the study parcels were within existing or planned and funded- commuter light rail, one mile outside of Beltway 8 encircling and within JAABE vol.14 no.1 January 2015 Hee Su Han 107 the city limits of Houston, Texas. The population of interest contained only parcels which were unimproved. According to the Harris County Appraisal Data, parcels with zero improvement value were considered unimproved. All these parcels formed the population of interest for this research. 3.3 Sample Selection From the population of unimproved parcels, all parcels that met LEED criteria for public transportation were listed. A random selection of 150 parcels, which qualified for LEED rating for Public Transportation (a) Access, was made. These parcels formed the treatment (a) (a) (a) (a) group. Likewise, 150 paired parcels, which did not qualify for LEED rating, and were located in the vicinity of each parcel of the treatment group, were selected. These parcels were a part of the control group for analysis purposes. Therefore, a total of 150 pairs of properties were selected for this study. Half of them qualified for the LEED Public Transportation Access rating and the other half did not. 4. Collection Method 4.1 Population Mapping (b) The parcels in this study lie within one mile outside (b) (b) (b) of Beltway 8, which encircles Houston, Texas. This (b) population will be represented on a map using GIS. In addition, appraised values of all the parcels selected in the previous step were recorded using Harris County Appraisal District data. To collect this information, a 13-digit parcel ID was used and the appraised value was retrieved. All parcels which had zero improvement value were then listed. This list consisted of all parcels with zero improvement value. The population so obtained was considered for this research. 4.2 Selection of Treatment Group A GIS file containing all population parcels was then projected on the Arc Map. Transportation maps (c) (c) (c) (c) of bus stops and light rail stations were obtained from (c) the Houston-Galveston Area Council (HGAC 2009). These maps were then layered over the population map. This defined the location of all bus stops and light rail stations with respect to the population considered. Fig.2.(b) illustrates this procedure graphically. In order to select the treatment group, the buffer function of GIS was used. The parcels which were within a quarter mile (measured from the centroid of the parcel) of bus stops and/or within half a mile of light rail stations were selected. Fig.2.(c) and (d) are a pictorial presentation of this procedure. (d) All these selected parcels met LEED criteria for (d) (d) (d) public transportation. While collecting data, it was (d) Fig.2. Mapping Process found that a few of the parcels which qualified for Fig. 2. Mapping Process Fig. 2. Mapping Process The firstFig. 2. Mapping Process group consisted of all parcels which had LEED credit had both bus stop and light rail stations Fig. 2. Mapping Process both bus stops and light rail stations within qualifying within qualifying distances. The rest of the parcels distances. All the parcels in the second group were either met bus stop distance criteria or light rail located within a quarter mile of a bus stop. All parcels distance criteria. So, three groups of LEED qualifying in the third group were located within half a mile parcels were formed for the analysis. 108 JAABE vol.14 no.1 January 2015 Hee Su Han of a light rail station. In this study, 50 parcels were randomly selected from each of the three groups. Thus, a total of 150 parcels were randomly selected. This formed the sample of interest for this research. 4.3 Area of Parcels and Number Data The area of all 150 parcels was obtained from Harris County Appraisal District public data which contained 13-digit parcel IDs. Also, using the centroids of parcels as reference points, the distance to transit points was calculated. An Excel matrix model was created using the spherical law of cosines. With the help of the matrix model, the number of bus stops and/or light rail -2.5 0 2.5 5.0 stations that met LEED criteria for each parcel was calculated. 5. Data Analysis Fig. 3. Test of Normality Fig.3. Test of Normality 5.1 Descriptive Statistics According to Table 1., the dependent variable unit 5.3 Transformation of Dependent Variable value, ($/SF), had a mean value of about $27.25 per Since formal assumptions to carry out regression square foot and a median value of $17.00 per square were not met, the dependent variable (unit value) foot. The lowest unit value was about $0.05 per square was transformed. A Box-Cox transformation was foot and the highest was $175.00 per square foot. There used to find the appropriate transformation. Box- were a few parcels that had a very high unit value per Cox suggested two possible transformations for square foot in the sample. The independent variable the dependent variable. For analysis purposes, the Area, (SF), had a mean of about 13,536 square feet and following transformation was used. a median of 5,300 square feet. The lowest value was 41 square feet and the highest value was 458,251 square 0.3 Transformed Unit Value = (Original Unit Value) feet. Few of the parcels had a very high value for the land area associated with them. The area considered for 5.4 Regression Analysis this set of results was 0.51% of the total undeveloped The following model was considered after the land area of the City of Houston. The appraised value, transformation: ($), had a mean value of about $311,638 and a median of $91,590. It ranged from $62 to $13,568,900. Parcels Transformed Unit Value = β + β (Number of bus 0 1 with these lowest and highest appraised values met all stops) + β (Number of light rail stations) + β (Area) 2 3 the criteria to be in the population. These parcels had + ε zero improvement value and qualified for LEED public transportation access credit. Table 2. shows the ANOVA table of the transformed model. From the p-value obtained from the analysis, Table 1. Descriptive Statistics for Unit Value ($/SF) a statistically significant linear relationship existed Contents Unit Value Area Appraised Value between dependent and independent variables. A Mean 27.24 13,535.81 311,637.61 transformed unit value for the parcels was found to Minimum 0.05 41 62 Maximum 175 458,251 13,568,900 be linearly related to the area, number of bus stops Standard and number of rail stations. Because this relationship 27.56 44,894.53 1.15 existed, the multiple regression correlation value was deviation Skewness 2.17 8.07 10.34 also significant. Kurtosis 7.72 72.24 117.39 Table 2. ANOVA and Adjusted R Square 5.2 Diagnostics Sum of Mean Model df F Siq. Since the sample size for this model was more than squares square 50, the Kolmogorov Smirnov significance value was Regression 52.20 3 17.40 49.25 0.00 used for testing the normality of residuals. p = 0.000 < Residual 51.58 146 0.35 Total 103.78 149 0.05 (alpha level) for the Kolmogorov-Smirnov test of a. Predictors: (Constant), Area, Number of rail stations, normality proved that residuals were not normal (see Number of bus stops Fig.3.). Hence, the normality test failed because of the b. Dependent Variable: Transformed Unit Value residuals from the initial regression when the original values for the dependent variable were used. Also, a Adjusted R- square for this model was 0.493. That histogram of standardized residuals showed a non- is 49.3% of the variability in the transformed unit normal distribution of residuals. value of parcels could be explained by the independent JAABE vol.14 no.1 January 2015 Hee Su Han 109 variables. Even though all independent variables were the research hypothesis, which stated that the model found to be significant predictors, they were not as was appropriate and that number of bus stops, number powerful as one might hope. About half, 49.3%, of of light rail stations and area were significant predictors the variability in the transformed unit value of parcels of the transformed unit value of a parcel, was accepted. could be explained by these independent variables, This model demonstrates a significant relationship whereas 50.7% of the variability was due to other between the transformed unit value of parcels and unknown factors not considered in this research. the measurements required to earn LEED credit. Independent variables used in this model, namely Table 3. Coefficients the number of bus stops meeting LEED criteria, the Unstandardized Coefficients number of light rail stations meeting LEED criteria and Model t Siq. area, together accounted for 49.3% of the variability B Std. Error in the transformed unit value of the parcels. These (Constant) 1.873 0.068 27.422 0.000 variables emerged as significant predictors but were NumBus -0.015 0.005 -3.004 0.003 not very powerful since 50.7% of the variation in the NumRail 0.426 0.043 9.980 0.000 Area -2.522E-6 0.000 -2.301 0.023 transformed unit value was explained by other factors which were not considered in this research. Parameter estimates showed that all three Therefore, to find best-fit models for predicting the independent variables, number of bus stops, number appraised unit value of parcels in Harris County, it of rail stations and area, were significant predictors is meaningful to use other possible variables such as of transformed unit value of a parcel. The number of other LEED criteria, household income, the level of rail stations meeting LEED criteria for a given parcel education, etc. had the greatest effect on the transformed unit value as compared to other independent variables in the model. 6. Conclusions For the model, predictability of transformed unit value of a parcel meeting LEED criteria using the number of transit points, i.e. bus stops and light rail stations (located within the qualifying LEED distances) and area was calculated. According to the results, an increase in the number of light rail stations led to an increase in the transformed unit value of a parcel. The number of bus stops which met LEED criteria for a given parcel had a completely opposite effect. Based on the sample median lot size of 5,300 square feet, the predicted lot value increases dramatically in proportion to the number of qualifying light rail stations and decreases marginally in proportion to the number of qualifying bus stops. This effect can be clearly seen in Table 4. for a lot with an area held constant at the sample median of 5,300 square feet. Fig.4. Fig. 4. Actual Actual Unit V Unit Val alue ue Vs. Pre Vs. Predicted dicted Unit Unit V Value alue As the number of rail and bus stops are varied over A predictive equation was obtained for the a range of zero to four bus stops and zero to two rail transformed unit value and un-transformed unit value. stops, the predicted value of the parcel is calculated. In This model used the best estimates of the population every case, the value of the median lot increases when parameters. Also, actual unit value and predicted unit the number of rail stops increases and decreases when value were compared (see Fig.4.). the number of bus stops increases. For example the predicted value for a median sized lot of 5,300 square Predicted Transformed Unit value= 1.873 -0.015 feet with no bus stop or rail stop is $41,915. The (NumBus) + 0.426 (NumRail) – 0.000002522 (area) same size lot with no bus stops and one rail stop has a predicted value of $83,361. The lot value is almost Predicted Un-Transformed Unit value= 1.873 doubled by adding access to a qualified rail stop. -0.015 (NumBus) + 0.426 (NumRail) – 0.000002522 Therefore, it can be concluded that the number of rail (1/0.3) (area) stops has significant effect on the value of parcels in Harris County. 5.5 Discussion For the same lot size with a value of $41,915 with The multiple regression analysis showed that access to neither a bus nor rail stop, the difference is both number of bus stops and area were significant noticeable relative to the addition of a bus stop rather predictors of the transformed unit value. For this than a rail stop. With zero rail stops and one bus model, the ANOVA test p value was 0.000. Therefore, stop, the predicted value is $40,798. This is a drop in 110 JAABE vol.14 no.1 January 2015 Hee Su Han 15 3) Lee, K. and Yeom, D. (2009) Comparative Research of Residents' Table 4. Bus and Rail Stop Effect on Value Satisfaction Level between Green Building-Certified Apartment Bus Stops Rail Stops Predicted Value Complexes and General Apartment Complexes in Korea, Journal 0.00 0.00 $41,915 of Asian Architecture and Building Engineering, 8(2), pp.423-430. 1.00 0.00 $40,798 4) Corbett, C. J., and Muthulingam, S. (2007). "Adoption of 2.00 0.00 $39,703 Voluntary Environmental Standards: The Role of Signaling and 3.00 0.00 $38,628 Intrinsic Benefits in the Diffusion of the LEED Green Building 4.00 0.00 $37,574 Standards." UCLA Institute of the Environment and Sustainability. Retrieved April 8, 2013. http://www.environment.ucla.edu/ccep/ 0.00 1.00 $83,361 research/article.asp?parentid=752 1.00 1.00 $81,552 5) U.S Green Building Council (USGBC). (2009). "LEED-NC for 2.00 1.00 $79,770 New Construction Reference Guide Version 3.0." Report. U.S 3.00 1.00 $78,015 Green Building Council (USGBC). Washington D.C. 4.00 1.00 $76,288 6) U.S. Green Building Council (USGBC). (2011). "LEED Projects 0.00 2.00 $147,360 & Case Studies." USGBC, Retrieved June 3, 2013. http://www. 1.00 2.00 $144,660 usgbc.org/LEED/Project/ 7) Rappaport, j. (2007). "Comparing Aggregate Housing Price 2.00 2.00 $141,995 Measures." Business Economics, 42(4), pp.55-65. 3.00 2.00 $139,365 8) Choi, J. and Cho, T. (2014) Comparing perception concerning the 4.00 2.00 $136,769 importance of apartment complex components between consumers and housing providers, Journal of Asian Architecture and Building predicted value of over $1,100 due to adding one bus Engineering. 13(1), pp.109-116. stop. The difference between adding one bus stop and 9) Son, K., Lee, S., Lim, C. and Kim, S. (2013) Economic Analysis adding one rail stop is $42,563. of Korea Green Building Certification System in the Capital Area This pattern may be particular to Houston because Using House-Values Index, Journal of Asian Architecture and Building Engineering. 13(2), pp.475-481. the light rail stations are concentrated more towards the 10) City of Houston. (2009). "Houston Facts and Figures." City of center of the city, i.e. downtown area, rather than being Houston, Retrieved February 4, 2013. http://www.houstontx.gov/ distributed all over the city. On the other hand, bus abouthouston/houstonfacts.html stops are located all over the city. Area was found to be 11) Wilson, J. (2007). "Getting the Big Picture on Houston's Air a significant predictor of the transformed unit value. As Pollution." National Aeronautics and Space Administration. Retrieved March 3, 2013. http://www.nasa.gov/vision/earth/every the plot area increased, the transformed unit value of a daylife/archives/HP_ILP_Feature_03.html parcel went down. 12) U.S. Census Bureau. (2000). "United States Census 2000." U.S. The model suggested that selection characteristics Department of Commerce. Retrieved February 8, 2013. http:// of the LEED green building rating system for public www.census.gov/main/www/cen2000.html transportation access influences the appraised value of 13) City of Houston Planning and Development Department. (2008). "Houston Land Use and Demographic Profile." City of Houston properties. This finding further implies that the market eGovernment Center. Retrieved January 13, 2013. http://www. indirectly considers the economic effect of the LEED houstontx.gov/planning/planning_studies/ludem.html rating system even though this assessment method does 14) Joshi B. (2009) Prediction of unit value of unimproved parcels of not explicitly include financial aspects in the evaluation Harris County, Master's thesis, Texas A&M University, College framework. This research suggests that a sustainable Station, TX, USA. 15) Houston-Galveston Area Council. (2009). "Regional Data & GIS feature of a site may be related to the economic worth Services, Houston-Galveston Area Council." Retrieved July 17, of a related land development project. This could 2013. http://www.h-gac.com/rds/gis/clearinghouse/default.asp encourage new sustainable land development projects. This is the first investigation of its kind. Future studies will need to identify other factors that could explain more of the variation in the unit value of parcels. Also, the findings of this research were based on the City of Houston. Future studies could focus on other cities. Acknowledgement This work was supported by the 2014 Research Fund of University of Ulsan. References 1) Fuerst, F., and McAllister, P. (2011). "Green Noise or Green Value? Measuring the Effects of Environmental Certification on Office Property Values." Real Estate Economics, 39(1), pp.45-69. 2) Lee, K. and Yeom, D. (2012) Comparative research of residents' satisfaction level in KGBCC-Certified apartments in Korea, Journal of Asian Architecture and Building Engineering, 11(1), pp.55-62. JAABE vol.14 no.1 January 2015 Hee Su Han 111
Journal of Asian Architecture and Building Engineering – Taylor & Francis
Published: Jan 1, 2015
Keywords: sustainable development; LEED; public transportation access; sustainable site; regression analysis
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