Evaluating Housing in Urban Planning Using TOPSIS Technique: Cities of Isfahan Province

• Autorzy: Maliheh Izadi , Mehdi Jafari Vardanjani , Hamidreza Varesi
• Języki publikacji: EN

Abstrakty

EN

The index of housing serves as an important tool in planning for housing so that the parameters affecting housing can be recognized and any planning process is facilitated. Aim. The purpose of the study is to investigate and to evaluate the situation of the housing in cities of Isfahan province. The study is applied and descriptive-analytic in terms of the method. 39 indices were collected in the housing sector. Then the rate of the prosperity and the ranking of the cities were evaluated using TOPSIS method. Prosperity has been defined here as an important index of housing which reflects the welfare of residents. Cities were then categorized into six levels: Very important, Important, Partially important, Moderate, Poor, Very poor in terms of prosperity. Results and conclusions. The results from the study indicate an imbalance in studied indices in the cities, and a clear disparity between the levels of prosperity in the cities, and only the city of Isfahan is in the group of very prosperous with a rate of 0.813. (original abstract)

Słowa kluczowe

PL

Planowanie przestrzenne; Urbanizacja; Planowanie przestrzenne miasta; Mieszkania; Zamożność społeczeństwa; Metoda TOPSIS

EN

Spatial planning; Urbanisation; Town spatial planning; Dwellings; Society affluence; Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

• Czasopismo: Bulletin of Geography. Socio-economic Series
• Rocznik: 2021
• Numer: No. 51
• Strony: 25-34

Twórcy

autor

Maliheh Izadi

• University of Isfahan, Iran

autor

Mehdi Jafari Vardanjani

• Technical and Vocational University (TVU), Iran

autor

Hamidreza Varesi

• University of Isfahan, Iran

Bibliografia

• Abdel-Basset, M., Saleh, M., Gamal, A., & Smarandache, F. (2019). An approach of TOPSIS technique for developing supplier selection with group decision making under type-2 neutrosophic number. Applied Soft Computing, 77, 438-452. doi:https://doi.org/10.1016/j.asoc.2019.01.035.
• Adabre, M. A., & Chan, A. P. C. (2019). Critical success factors (CSFs) for sustainable affordable housing. Building and Environment, 156, 203-214. doi:https://doi.org/10.1016/j.buildenv.2019.04.030.
• Afsoon, M., & Habib, F. (2016). Explaining the role of cultural, social and economic factors on quality of residence in urban neighborhoods: A case study of Kerman. Journal of Geography and Regional Planning, 9, 59-69. doi:10.5897/JGRP2016.0559.
• Asfour, O. S. (2017). The role of land planning policies in supporting housing affordability: The case of the Gaza Strip. Land Use Policy, 62, 40-48. doi:https://doi.org/10.1016/j.landusepol.2016.12.018.
• Bartik, T. (1988). Measuring the Benefits of Amenity Improvements in Hedonic Price Models. Land Economics, 64(2), 172-183.
• Cavallaro, F. (2010). A comparative assessment of thin-film photovoltaic production processes using the ELECTRE III method. Energy Policy, 38(1), 463-474. doi:https://doi.org/10.1016/j.enpol.2009.09.037.
• Chen, S.-M., & Han, W.-H. (2018). An improved MADM method using interval-valued intuitionistic fuzzy values. Information Sciences, 467, 489-505. doi:https://doi.org/10.1016/j.ins.2018.07.062.
• Freeman, A. M. (1981). Hedonic prices, property values and measuring environmental benefits: a survey of the issues Measurement in public choice (pp. 13-32): Springer.
• Gallent, N., & Robinson, S. (2011). Local perspectives on rural housing affordability and implications for the localism agenda in England. Journal of Rural Studies, 27(3), 297-307. doi:https://doi.org/10.1016/j.jrurstud.2011.05.004.
• Horsch, E. J., & Lewis, D. J. (2008). The Effects of Aquatic Invasive Species on Property Values: Evidence from a Quasi-Random Experiment. Retrieved from https://ideas.repec.org/p/ags/aaea08/6199.html.
• Judge, M., Warren-Myers, G., & Paladino, A. (2019). Using the theory of planned behaviour to predict intentions to purchase sustainable housing. Journal of Cleaner Production, 215, 259-267. doi:https://doi.org/10.1016/j.jclepro.2019.01.029.
• Khoshakhlagh, R. (1999). Housing demand function estimated using pricing models. Economic Research, 55, 99-117.
• Lin, H.-T. (2010). Fuzzy application in service quality analysis: An empirical study. Expert Systems with Applications, 37(1), 517-526. doi:https://doi.org/10.1016/j.eswa.2009.05.030.
• Makinde, O. O. (2015). Influences of socio-cultural experiences on residents' satisfaction in Ikorodu low-cost housing estate, Lagos state. Environment, Development and Sustainability, 17(1), 173-198. doi:10.1007/s10668-014-9545-6.
• Maleki, S. (2003). The role of social indicators in development planning (In Persian). Housing and the Housing Foundation of Islamic Revolution.
• Marquez, E., Dodge Francis, C., & Gerstenberger, S. (2019). Where I live: A qualitative analysis of renters living in poor housing. Health & Place, 58, 102143. doi:https://doi.org/10.1016/j.healthplace.2019.05.021.
• Mitchell, R. E. (1976). Cultural and Health Influences on Building, Housing, and Community Standards: Cost Implications for the Human Habitat. Human Ecology, 4(4), 297-330.
• Muriel, T., Abdelhak, N., Gildas, A., & François, B. (2008). Évaluation des bénéfices environnementaux par la méthode des prix hédonistes : une application au cas du littoral. Economie & Prévision, 0(4), 47-62.
• Ortiz, S. E., & Johannes, B. L. (2018). Building the case for housing policy: Understanding public beliefs about housing affordability as a key social determinant of health. SSM - Population Health, 6, 63-71. doi:https://doi.org/10.1016/j.ssmph.2018.08.008.
• Patrick, C. F., & Wade, R. R. (1994). The Effects of Refineries on Neighborhood Property Values. Journal of Real Estate Research, 9(3), 319-338.
• Richard, A. (2008). Housing policy in developing countries. The importance of the informal economy. Retrieved from https://ideas.repec.org/p/ucr/wpaper/200801.html.
• Roszkowska, E. (2011). MULTI-CRITERIA DECISION MAKING MODELS BY APPLYING THE TOPSIS METHOD TO CRISP AND INTERVAL DATA. Multiple Criteria Decision Making, 6, 200-230.
• Sendich, E., & American planning, a. (2006). Planning and urban design standards. Hoboken (N.J.): Wiley.
• Siqueira-Gay, J., & Sánchez, L. E. (2019). Mainstreaming environmental issues into housing plans: the approach of Strategic Environmental Assessment. Environmental Impact Assessment Review, 77, 145-153. doi:https://doi.org/10.1016/j.eiar.2018.12.005.
• Statisrical-center-of-Iran. (2018). Population and Housing Cencuses. Retrieved from https://www.amar.org.ir/english/Population-and-Housing-Censuses.
• Wolman, H. (2014). The Politics of Housing in Older Urban Areas. Edited by Robert E. Mendelson and Michael A. Quinn. (New York: Praeger, 1976. Pp. xxii + 261. $20.00.). American Political Science Review, 72(1), 274-275. doi:10.2307/1953662.
• Won Kim, C., Phipps, T. T., & Anselin, L. (2003). Measuring the benefits of air quality improvement: a spatial hedonic approach. Journal of Environmental Economics and Management, 45(1), 24-39. doi:https://doi.org/10.1016/S0095-0696(02)00013-X.
• Xia, H.-C., Li, D.-F., Zhou, J.-Y., & Wang, J.-M. (2006). Fuzzy LINMAP method for multiattribute decision making under fuzzy environments. Journal of Computer and System Sciences, 72(4), 741-759. doi:https://doi.org/10.1016/j.jcss.2005.11.001

Identyfikatory

DOI

10.1515/29195