Скачать презентацию A study of sale price and marketing time Скачать презентацию A study of sale price and marketing time

c3f73ce45ff5492c4d86e6dff48649d0.ppt

  • Количество слайдов: 13

A study of sale price and marketing time for the new housing building Dr. A study of sale price and marketing time for the new housing building Dr. Ming-Yi Huang National Pingtung Institute of Commerce, Taiwan

Introduction 1. In the past research, used houses are targeted by most of literatures. Introduction 1. In the past research, used houses are targeted by most of literatures. Therefore, they can’t provide new housing buildings with reasonable explanation. 2. Transaction data of used house is mainly a single product and new housing building is a set of combined product

New housing building V. S Used house Item Quantity New housing building 80 units New housing building V. S Used house Item Quantity New housing building 80 units 20 F / 4 units on every floor Used house one unit Age Zero Over one transaction Quality Homogeneous Heterogeneous Product combination Picture Room 2 r, 3 r, 4 r Price Low, Middle, High Area Low, Middle, High -

3. There are many differences between a new housing building sold by developer and 3. There are many differences between a new housing building sold by developer and a used house sold by the real estate brokerage. 4. The study focuses how to sell all product of new housing building in the shortest time and position room combination ratio, price and area? 5. When room combination ratio, price and area deviate from normal distribution, does the distance of deviation influence sales time of a new housing building?

Methodology Data § The new housing building located in Kaohsiung, the second metropolis in Methodology Data § The new housing building located in Kaohsiung, the second metropolis in Taiwan. § 192 samples collected from 2001 to 2006. Model § K-mean method of cluster analysis

§ Formula of measuring deviation where Xβi is the proportion of room I, Xαi § Formula of measuring deviation where Xβi is the proportion of room I, Xαi is the proportion of normal room I § Simultaneous-equation model (1) (2)

List of variables Variable Description LOC Number of parks and schools within a radius List of variables Variable Description LOC Number of parks and schools within a radius of 500 m 2 TIME(TM) Marketing time, days PRICE(P) Sales price, USD DEVELOPER Type of developer of a new housing building. Famous developer, DEVELOPER=1, otherwise DEVELOPER=0; Normal DEVELOPER, DEVELOPER=1, otherwise DEVELOPER=0; base on new DEVELOPER. PDIST The distance of price which deviates from normal housing AREA Total floor area of one unit; m 2 FLA Total floor area of a new housing building; m 2 UTILITY Total area of public space / Total floor area of a new housing building, % PARKING Parking space / total units of a new housing building, % CYCLE Business cycle index FLOOR Number of floor heights ROOMDIST The distance of room combination ratio which deviates from normal housing SUM Total sales amount ADIST The distance of area which deviates from normal housing

Descriptive Statistics (N=192) Descriptive Statistics (N=192)

Empirical results Results obtained from area (m 2) Variable Type Cluster F Sig. 139. Empirical results Results obtained from area (m 2) Variable Type Cluster F Sig. 139. 59 56. 267 0. 000*** 127. 05 191. 4 53. 910 0. 000*** 201. 3 257. 4 142. 050 0. 000*** F Sig. Cluster B Cluster C 2 ROOM 81. 51 89. 1 3 ROOM 117. 81 4 ROOM Area Cluster A 151. 8 Results obtained from Room (%) Variable Type Cluster B Cluster C 2 ROOM 0. 6 0. 19 0 221. 02 0. 000*** 3 ROOM 0. 3 0. 58 0. 2 131. 54 0. 000*** 4 ROOM Room Cluster A 0. 1 0. 22 0. 8 269. 34 0. 000*** F Sig. 476. 8 0. 000*** Results obtained from Price (USD / m 2 ) Variable Price Cluster A Cluster B Cluster C 3, 317 4, 185 5, 952

Results obtained from 2 SLS and 3 SLS Variable 2 SLS 3 SLS Property Results obtained from 2 SLS and 3 SLS Variable 2 SLS 3 SLS Property Price Marketing Time . 930(. 267)*** 9. 025(3. 306)*** . 907(. 267)*** 9. 368(3. 389)*** LOC . 098(. 021) -. 166(. 126) . 097(. 021)*** -. 156(. 130) TIME . 158(. 045)*** - . 160(. 045)*** - PRICE - -3. 838(2. 200)* - -4. 055(2. 255)* Famous developer . 114(. 041)*** - . 133(. 040)*** - Normal developer . 014(. 030) - . 029(. 029) - PDIST - . 385(. 146)*** - . 359(. 148)** AREA . 003(. 001)*** . 022(. 011)** . 003(. 001)*** . 024(. 011)** - . 266(. 144)* - . 284(. 142)** UTILITY . 285(. 696) 13. 614(4. 361)*** . 269(. 699) 13. 821(4. 472)*** PARKING . 259(. 131)** -2. 444(. 458)*** . 260(. 131)** -2. 430(. 467)*** CYCLE . 001(. 000) . 012(. 006)** FLOOR . 000(. 000) - ROOMDIST - 3. 139(. 800)*** - 3. 276(. 810)*** SUM - . 519(. 000) - -. 537(. 000) ADIST - . 000(. 000)** Adj R 2 . 105 0. 284 . 0972 . 240 Constant FLA

Conclusion u The relationship of sales time and sales price 1. The influence of Conclusion u The relationship of sales time and sales price 1. The influence of sales time on sales price is positive. It means that sales time will increase with higher sales price. 2. The influence of sales price on sales time is negative. It means that sales price will be higher with shorter time on sale.

u The deviation of room combination ratio, price and area 1. When room combination u The deviation of room combination ratio, price and area 1. When room combination ratio deviates from normal distribution, it will increase sales time. 2. When price combination ratio deviates from normal distribution, it will increase sales time. 3. When area combination ratio deviates from normal distribution, it will increase sales time.

§ Thanks for your listening ! § Thanks for your listening !