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CROSS-IMPACT ANALYSIS OF FACTORS INFLUENCING URBAN LAND PRICE: CASE OF CHIANG MAI CITY |
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| รหัสดีโอไอ | |
| Creator | Thitipong Chiracharoenwong, Puttipol Dumrongchai, Poon Thiengburanathum, Praopun Asasuppakit |
| Title | CROSS-IMPACT ANALYSIS OF FACTORS INFLUENCING URBAN LAND PRICE: CASE OF CHIANG MAI CITY |
| Contributor | - |
| Publisher | TuEngr Group |
| Publication Year | 2563 |
| Journal Title | International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies |
| Journal Vol. | 11 |
| Journal No. | 13 |
| Page no. | 11A13G: 1-15 |
| Keyword | Land price change, Influencing factor, Monte-Carlo technique, Infrastructure project development, Land acquisition valuation, Cross-Impact Analysis (CIA), Chiang Mai Comprehensive Plan, Cross-impact index, Land price probability change. |
| URL Website | http://TuEngr.com/Vol11_13.html |
| Website title | ITJEMAST V11(13) 2020 @ TuEngr.com |
| ISSN | 2228-9860 |
| Abstract | This study identifies factors affecting urban land price and analyzes interrelationship and probability of these factors. Chiang Mai city was used as a practical case in this study. The EDFR and CIA techniques were applied to achieve these objectives. Ten experts from public and private sectors with more than ten years' experience in land price evaluation and real estate development in Chiang Mai city were invited to be an expert panel. The results of this study revealed ten factors affecting land price in Chiang Mai city, and the most important factors are housing demand, accessibility, and distance to the city center. Three events of each influencing factor; optimistic, pessimistic, and most probable, with its occurrence and conditional probability, were determined. The Monte-Carlo technique was applied to random future situations. Thirteen scenarios occurred as a result of the scenario simulation. The change in probability of each event was a result of an interaction of its influencing factors. The event with many interrelated factors had more changing in its probability; for example, urban land price. From this study, the identified factors affecting urban land prices of the Chiang Mai city can be used as variables in land price-determination for support decision-making in the urban planning and urban infrastructure project development. |
