1# RECORD b34f2af5cff586af9757e0b66b7191bb692373e42# TITLE: Determinants of New Condominium Prices near MRT Orange Line Stations: Case study of Estimating Housing Affordability in Bangkok, Thailand3# YEAR: 2025.0 VENUE: Hong Kong Journal of Social Sciences DOI: 10.55463/hkjss.issn.1021-3619.64.294# AUTHORS: Pornraht Pongprasert5# PAGES: 13 CANDIDATE TABLE PAGES (1-based): [9]6# ABSTRACT: This research aims to analyze the factors influencing the pricing of condominium projects along the Mass Rapid Transit (MRT) Orange Line, an electric train expected to start operations in 2025. As the main heavy rail line connecting the Eastern Bangkok suburbs with the city’s New Central Business District (New CBD), the Orange Line has significant implications for urban development. To promote land development opportunities, Bangkok’s city plan has undergone changes along the Orange Line corridor, particularly on the Ramkhamhaeng Road, which is anticipated to drive up land prices.This study examines how condominium prices may fluctuate when various factors are considered, such as proximity to MRT stations, main roads, expressway access points, private facilities, operator reliability, and the cost of common areas. The research equips real estate developers with a comprehensive understanding of these determinants to guide project development and pricing strategies aligned with market conditions. Condominium buyers can leverage accurate pricing information to make informed decisions, while real estate investors can incorporate these insights into their investment strategies. Additionally, the Revenue Department could use the data to inform land tax policies. The hedonic price model was used to determine the factors influencing the prices of condominiums along the Orange Line. The research samples are 28 brand-new condominium properties that are located only one kilometer away from the MRT stations of the Orange Line, and most of them are new condominiums that were constructed in less than 5 years. A total of 17 factors, grouped into three categories—locational, physical, and neighborhood characteristics—were evaluated using regression analysis. The findings reveal that three key factors significantly impact the prices of condominium units: floor level, distance from the train station, and distance from department stores.789===== PAGE 1 (score 11, numeric-paren 0, table-words 0, var-words 11) =====1011香港社會科學學報 12HONG KONG JOURNAL OF SOCIAL SCIENCES 13最新第64 期 (2024 年秋/冬季) 14 Vol. 64 Autumn/Winter 2024 15 Copyright: © 2025 by the authors. HKJSS 16This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 17License (https://creativecommons.org/licenses/by-nc-nd/4.0/) 18Available online at www.hkjoss.com 19Research article20 https://doi.org/10.55463/hkjss.issn.1021-3619.64.29 21Determinants of New Condominium Prices near MRT Orange Line Stations: 22Case study of Estimating Housing Affordability in Bangkok, Thailand 23Pornraht Pongprasert1 24 *, Rungsee Benjaanunphong2 251Department of Real Estate Business, Thammasat Business School, Thammasat University, Thailand 262Pricewaterhouse Coopers ABAS Ltd., Bangkok, Thailand 27* Correspondence: pоrnrаht@tbs.tu.ac.th28Abstract:29This research aims to analyze the factors influencing the pricing of condominium30projects along the Mass Rapid Transit (MRT) Orange Line, an electric train expected31to start operations in 2025. As the main heavy rail line connecting the Eastern32Bangkok suburbs with the city’s New Central Business District (New CBD), the33Orange Line has significant implications for urban development. To promote land34development opportunities, Bangkok’s city plan has undergone changes along the35Orange Line corridor, particularly on the Ramkhamhaeng Road, which is anticipated36to drive up land prices. This study examines how condominium prices may fluctuate37when various factors are considered, such as proximity to MRT stations, main roads,38expressway access points, private facilities, operator reliability, and the cost of39common areas. The research equips real estate developers with a comprehensive40understanding of these determinants to guide project development and pricing41strategies aligned with market conditions. Condominium buyers can leverage42Keywords: 43Central Business District (CBD), 44Mass Rapid Transit (MRT) Orange 45Line, 46condominium prices, 47housing affordability, 48Bangkok 49Article History: 50Received: October 14, 2024 51Revised: November 12, 2024 52Accepted: January 15, 2025 53Published: February 6, 2025 545556===== PAGE 9 (score 40, numeric-paren 5, table-words 6, var-words 13) =====5758 327 59kilometers, the closest was 150 meters from Police 60Station and the farthest was 4.2 kilometers, the closest 61was 120 meters from Fire Station and the farthest was 624 kilometers, the closest was 120 meters from Fire 63Station and the farthest was 4 kilometers, the minimum 64number of units was 196 units and the maximum 65number of units was 1,942 units, the minimum number 66of floors was 8 floors and the maximum number of 67floors was 61 floors, the minimum number of carpark 68was 30 percents and the maximum number of floors 69was 55 percents, facilities include a fitness center, 70swimming pool, and co-working space and not 71include, the project owner is a listed company and a 72non-listed company, the minimum fees was 33 baht 73per sq.m. per month (around 0.95 USD per sq.m. per 74month) and the maximum fees was 60 baht per sq.m. 75per month (around 1.72 USD per sq.m. per month), the 76Floor Area Ratio (FAR) in the land maps range from 772.5 to 7. 78Table 2. Summary of descriptive data (compiled by the authors) 79No. 80Variable codes (unit) 81Mean 82S.D.83Min 84Max 851 86Dist. Train (m.) 87324.64 88317.25 890.00 90950.00 912 92Dist. Road (m.) 9365.54 94188.22 950.00 96900.00 973 98Dist. Exp (m.) 992,378.93 1001,682.80 101280.00 1026,000.00 1034 104Dist. New CBD (m.) 1057,397.50 1066,050.26 107230.00 10820,700.00 1095 110Dist. Dep (m.) 1111,143.21 1121,183.19 113150.00 1144,500.00 1156 116Dist. Con (m.) 117262.50 118247.81 1190.00 120900.00 1217 122Dist. Market (m.) 123933.93 124648.93 125300.00 1263,400.00 1278 128Dist. Hospital (m.) 1292,204.29 1301,200.21 13170.00 1324,700.00 1339 134Dist. Police (m.) 1352,691.07 136960.91 137150.00 1384,200.00 13910 140Dist. Fire (m.) 1412,332.88 142949.70 143120.00 1444,000.00 14511 146No. Unit (units) 147991.54 148562.68 149196.00 1501,942.00 15112 152No. Floor (floors) 15327.04 15413.48 1558.00 15661.00 15713 158Car Park (percentage) 15943.89 1607.93 16130.00 16255.00 16314 164Facilities 1650.93 1660.26 1670.00 1681.00 16915 170Brand 1710.71 1720.46 1730.00 1741.00 17516 176Fee (the baht) 17747.50 1788.88 17933.00 18060.00 18117 182FAR 1835.46 1841.41 1852.50 1867.00 1874.2 188Empirical Results 189To determine condominium pricing, the researcher 190collected data on three variables: the number of floors 191and distance from the MRT station. and the distance 192from the retail centers. Using the ordinary least squares 193method (OLS), a sample of 28 projects was analyzed 194to determine the statistical significance of each 195variable. The following equation was used in this 196study: 197Price = C + β1Floor + β2Dist. Train + β3Dist. Dep 198Table 3. The result of the regression analysis (compiled by the authors) 199Variables 200Coefficient 201t 202VIF 203Un. Std. B 204Std. Error 205Std. B 206Constant 207-862,990.71208867,065.95 209-1.00*2101.03 211Physical characteristics 212of buildings 213Floor 214113,861.30 21524,185.98 216 0.57 217 4.71** 218Location Features 219Dist. Train 2204,313.71 2211,019.81 222 0.51 223 4.23** 2241.01 225Dist. Dep 226640.05 227274.31 228 0.28 229 2.33* 2301.02 231Note: R-Square = 0.66, Adjusted R-Square = 0.62; F = 5.44, Durbin-Watson (D.W.) 2.30 232*p-value < 0.05, **p-value < 0.01233Based on the data analysis findings in accordance 234with Table 3, the research results of the variables 235influencing condominium prices reveal hidden costs 236that have an impact on the price of condominiums in 237Orange Line real estate developments. The predicted 238R-Square value of the linear model for this instance is2390.66 or 66.1%, reliable at explaining changes in price.240It can be described as the price of a condominium241increases by 113,861.30 baht (3,265.03 USD) as the242number of floors increases by one. The project’s243distance from the MRT station was one meter longer 244but not more than 1 km, which resulted in a 4,313.71 245baht (123.70 USD) rise in the price of the 246condominium. The price of the condominium 247increased by 640.05 baht (18.35 USD) because of a 248one-meter increase in the distance between the 249department store and the condominium. This can be 250expressed as follows: 251252253===== PAGE 10 (score 26, numeric-paren 2, table-words 4, var-words 14) =====254255Pongprasert & Benjaanunphong. Determinants of New Condominium Prices near MRT Orange Line’s Stations: Case study of Estimating the 256Housing Affordability in Bangkok, Thailand, Vol. 64 Autumn/Winter 2024 257Price = -862,990.71 + (β1=113,861.30) Floor + 258(β2=4,313.71) Dist. Train + (β3=640.05) Dist. Dep 259In addition, condominium prices can be estimated 260using the following equation, which substitutes for the 261average of several factors: 262Price = -862,990.71 + 113,861.30 (27.04) + 4,313.71 263(324.64) + 640.05 (1,143.21) 264The price = 4,347,933.22 baht (124,679.07 USD) 265This can be explained by the fact that condominium 266Projects along the Orange Line generally have 27.04 267floors, are located 324.64 meters from the MRT 268station, and are located 1,143.21 meters from the 269department stores. The price per unit is expected to be 2704,347,933.22 baht (124,679.07 USD). The exchange 271rate was obtained from the Bank of Thailand (BOT) on 272November 25, 2024, : :1 USD = 34.8730. 273Furthermore, the Durbin-Watson (D.W.) value is 2742.30, falling between 1.5 and 2.5, meaning that 275autocorrelation is not an issue for this linear model 276(Durbin and Watson, 1951). 277The level or magnitude of the correlation can be 278determined by examining the data in the Correlation 279Analysis table, which studies the relationship between 280two or more variables. If the correlation coefficient is 281closer to 1 or 1, indicating a strong degree of 282relationship, the number of correlation coefficients is 283used. On the other hand, if the value is around zero, it 284indicates little to no relationship. When the correlation 285coefficient for every subject was less than 0.8, it was 286considered acceptable to conduct additional analyses. 287The Variance Inflation Factor (VIF) estimator's 288variance, which is used to determine the severity of the 289issue, is displayed in the table based on the data. 290Because none of the three exceeded 10, they all fell 291within the set of parameters that could have been used 292in the research. 293Compared to previous studies, this study found the 294same findings as those of Lind and Hwang (2003) and 295Thamrongsrisook (2011), that the number of floors in 296the condominium project has a positive impact on the 297prices of condominium units. Similarly, the key 298research outcomes of Des Rosiers et al. (1996), Bible 299and Hsieh (2011), and Kulkosa (2016) are that the 300significant factor of the distance between the 301condominium project and the MRT station affects the 302price of the condominium. In addition, this research 303outcome found a similar significant factor of distance 304between the condominium project and department 305store, which affects the price of condominium units 306(Kulkosa, 2016). 3075. Conclusion and Recommendations308The growth in condominium prices along the mass309transit station in Bangkok, Thailand, is continuously 310increasing. Prices tend to grow rapidly, and they are 311difficult to predict, especially the prices of 312condominiums in the proximity of urban rail transit 313stations in Bangkok CBD. If they are much higher, 314fewer people can afford to rent or purchase to live near 315the transit stations. This study aims to identify the 316factors affecting the prices of condominiums along the 317MRT Orange Line, the newest urban transit line in 318Bangkok. In the research outcome, it is found that 3 319variables affecting to the price of condominiums along 320the MRT Orange Line. These are the floor levels in the 321condominium project, the distance between the 322condominium project and MRT station, and the 323distance between the condominium project and 324department store. All of these factors have a positive 325impact on condominium prices. 326If condominiums along the MRT Orange Line have 327a lower number of floors (low-rise condominium 328projects), are not located at the closest distance to the 329MRT station (but within walkable distance), and are 330located farther from the department store, the price 331would be cheaper, and more people can afford the 332price of residences located near MRT stations. 333Additionally, real estate developers interested in 334developing high-rise residential projects along the 335Orange Line train, such as Rama 9, Ramkhamhaeng, 336Lam Sali, and Min Buri, can use these research 337findings as a guide to determine the preliminary selling 338price and conduct marketing strategy analysis. 339Planning includes determining the best site for the 340project, calculating how many stories the building will 341need, 342and 343effectively 344marketing 345and 346pricing 347condominiums to meet demand. Customers who want 348to buy condominiums near the Orange Line train for 349speculative purposes or habitation will benefit from 350this. The research outcomes can be used as a basis for 351choosing a project that best fits their financial 352situation, and can provide them with the current 353market prices for the condominiums along the Orange 354Line train, allowing them to compare them properly to 355other projects. The ability to use the data to analyze 356trends in the reasonableness of the company's profits 357through the costs that the company has expected to 358invest and the sales revenue that the company expects 359to receive is advantageous to investors who spend 360shares of real estate development companies that have 361plans to invest in real estate projects along the Orange 362Line. To collect land taxes, the Revenue Department 363will benefit from using the data to examine the value 364of condominiums along the Orange Line. 365Authors’ Contributions 366Conceptualization, 367P.P.; 368methodology, 369P.P.; 370software, R.B.; validation, P.P.; formal analysis, P.P.; 371investigation, C.N.; resources, A.C.; data collection, 372R.B.; data curation, R.B.; writing—original draft373preparation, all authors contributed equally; writing—374review 375and 376editing, 377P.P.; 378visualization, 379R.B.;380 328381