Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile
Abstract
Nowadays, cities are developing differently according to their needs, limitations and certain strategic plans. Moreover, conurbation areas will be more common in so many countries like Chile when there are two or more cities developing one next to another, leaning on each other. In this atmosphere, typical residents live in a region or a neighborhood based on certain criteria, so they know how and where they are going to live. From another point of view, a newcomer is usually faced with a city full of contrasts which make things completely and surprisingly complicated. In order to illustrate this, a real case was selected based on the research field, qualitative and quantitative (real) data. The Coquimbo-La Serena conurbation and it’s regions as “Comuna (in Chile)” is a really suitable case to show the complexity of the study. In order to face the challenge, a new hybrid Multiple-Attribute Decision-Making (MADM) method is introduced based on the Best-Worst Method (BWM) and Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA). The five best different neighborhoods as Comunas of the conurbation were analyzed based on the two main scenarios: having a private car or using only public transportation. To obtain more reliable results, a sensitivity analysis was made so as to determine the behavior of the proposed model against weight changes. Besides, the final results were compared with the other MADM methods, for example: Multi-Attributive Border Approximation Area Comparison (MABAC), VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) and COmbinative Distance-based ASsessment (CODAS).
Keyword : neighborhood, locating, newcomer, evaluation, MADM, BWM, MAIRCA
How to Cite
Hashemkhani Zolfani, S., Ecer, F., Pamučar, D., & Raslanas, S. (2020). Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile. International Journal of Strategic Property Management, 24(2), 102-118. https://doi.org/10.3846/ijspm.2020.11543
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Ahmad, N. (1992). Choice of location and mobility behaviour of migrant households in a Third World city. Urban Studies, 29(7), 1147-1157. https://doi.org/10.1080/00420989220081091
Akkoc, R., & Alexander, H. (2015, September). Chile earthquake: 10 people killed and a million evacuated − as it happened. The Telegraph, 17.
Ardayfio-Schandorf, E. (2012). Urban families and residential mobility in Accra. In E. A-Schandorf, P. W. K. Yankson, & M. Bertrand (Eds.), Mobile city of Accra: urban families, housing and residential practices (pp. 47-72). Dakar: Codesria.
Badi, I., & Ballem, M. (2018). Supplier selection using rough BWM-MAIRCA model: a case study in pharmaceutical supplying in Libya. Decision Making: Applications in Management and Engineering, 1(2), 15-32. https://doi.org/10.31181/dmame1802016b
Badri Ahmadi, H., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method. Resources, Conservation and Recycling, 126, 99-106. https://doi.org/10.1016/j.resconrec.2017.07.020
Bailey, A. J., Blake, M. K., & Cooke, T. J. (2004). Migration, care, and the linked lives of dual-earner households. Environment and Planning A, 36(9), 1617-1632. https://doi.org/10.1068/a36198
Baláž, V., Williams, A. M., & Fifeková, E. (2016). Migration decision making as complex choice: eliciting decision weights under conditions of imperfect and complex information through experimental methods. Population, Space and Place, 22(1), 36-53. https://doi.org/10.1002/psp.1858
Brown, L. A., & Moore, E. G. (1970). The intra-urban migration process: a perspective. Geografiska Annaler, 52B, 1-13. https://doi.org/10.1080/04353684.1970.11879340
Cetinkaya, C., Özceylan, E., Erbaş, M., & Kabak, M. (2016). GISbased fuzzy MCDA approach for siting refugee camp: a case study for southeastern Turkey. International Journal of Disaster Risk Reduction, 18, 218-231. https://doi.org/10.1016/j.ijdrr.2016.07.004
Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of suppliers based on using the R’AMATELMAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101-129. https://doi.org/10.1016/j.jclepro.2018.02.186
Chiang, L. H. N., & Hsu, J. C. R. (2005). Locational decisions and residential preferences of Taiwanese immigrants in Australia. GeoJournal, 64(1), 75-89. https://doi.org/10.1007/s10708-005-3927-0
Chitsaz, N., & Azarivand, A. (2016). Water scarcity management in arid regions based on an extended multiple criteria technique. Water Resources Management, 31(1), 233-250. https://doi.org/10.1007/s11269-016-1521-5
Ciavarella, M., Carbone, G., & Vinogradov, V. (2018). A critical assessment of Kassapoglou’s statistical model for composites fatigue. Facta Universitatis, Series: Mechanical Engineering, 16(2), 115-126. https://doi.org/10.22190/FUME180321014C
Dökmeci, V., & Berköz, L. (2000). Residential-location preferences according to demographic characteristics in Istanbul. Landscape and Urban Planning, 48(1-2), 45-55. https://doi.org/10.1016/S0169-2046(99)00080-8
Drakaki, M., Gören, H. G., & Tzionas, P. (2018). An intelligent multi-agent based decision support system for refugee settlement siting. International Journal of Disaster Risk Reduction, 31, 576-588. https://doi.org/10.1016/j.ijdrr.2018.06.013
Earnhart, D. (2002). Combining revealed and stated data to examine housing decisions using discrete choice analysis. Journal of Urban Economics, 51(1), 143-169. https://doi.org/10.1006/juec.2001.2241
Ecer, F. (2015). Performance evaluation of internet banking branches via a hybrid MCDM model under fuzzy environment. Economic Computation and Economic Cybernetics Studies and Research, 49(2), 211-230.
Ecer, F. (2018). An integrated fuzzy AHP and ARAS model to evaluate mobile banking services. Technological and Economic Development of Economy, 24(2), 670-695. https://doi.org/10.3846/20294913.2016.1255275
Gigović, L., Pamučar, D., Bajić, Z., & Milićević, M. (2016). The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots. Sustainability, 8(4), 372. https://doi.org/10.3390/su8040372
Ginevičius, R. (2011). A new determining method for the criteria weights in multi-criteria evaluation. International Journal of Information Technology & Decision Making, 10(6), 1067-1095. https://doi.org/10.1142/S0219622011004713
Głuszak, M. (2015). Multinomial logit model of housing demand in Poland. Real Estate Management and Valuation, 23(1), 8489. https://doi.org/10.1515/remav-2015-0008
Gluszak, M., & Marona, B. (2017). Discrete choice model of residential location in Krakow. Journal of European Real Estate Research, 10(1), 4-16. https://doi.org/10.1108/JERER-01-2016-0006
Gupta, H., & Barua, M. K. (2016). Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method. Technological Forecasting and Social Change, 107, 69-79. https://doi.org/10.1016/j.techfore.2016.03.028
Hanafi, M. H., Mazree, A. S., Umar, M. U., & Ahmad, H. (2018). Neighborhood factors contributing to the household mobility: apartments in Malaysia. Environment-Behaviour Proceedings Journal, 3(7), 307-317. https://doi.org/10.21834/e-bpj.v3i7.1236
Hashemkhani Zolfani, S., Yazdani, M., & Zavadskas, E. K. (2018). An extended stepwise weight assessment ratio analysis (SWARA) method for improving criteria prioritization process. Soft Computing, 22(22), 7399-7405. https://doi.org/10.1007/s00500-018-3092-2
Hashemkhani Zolfani, S., Zavadskas, E. K., Khazaelpour, P., & Cavallaro, F. (2018). The multi-aspect criterion in the PMADM outline and its possible application to sustainability assessment. Sustainability, 10(12), 4451. https://doi.org/10.3390/su10124451
Haybatollahi, M., Czepkiewicz, M., Laatikainen, T., & Kyttä, M. (2015). Neighbourhood preferences, active travel behaviour, and built environment: an exploratory study. Transportation Research Part F: Traffic Psychology and Behaviour, 29, 57-69. https://doi.org/10.1016/j.trf.2015.01.001
Husain, K., Rashid, M., Vitković, N., Mitić, J., Milovanović, J., & Stojković, M. (2018). Geometrical models of mandible fracture and plate implant. Facta Universitatis, Series: Mechanical Engineering, 16(2), 369-379. https://doi.org/10.22190/FUME170710028H
Ioannides, Y. M., & Kan, K. (1996). Structural estimation of residential mobility and housing tenure choice. Journal of Regional Science, 36(3), 335-363. https://doi.org/10.1111/j.1467-9787.1996.tb01107.x
Jabareen, Y. (2005). Culture and housing preferences in a developing city. Environment and Behavior, 37(1), 134-146. https://doi.org/10.1177/0013916504267640
Kahraman, Y. R. (2002). Robust sensitivity analysis for multi-attribute deterministic hierarchical value models. Ohio: Storming Media.
Kauko, T. (2007). An analysis of housing location attributes in the inner city of Budapest, Hungary, using expert judgements. International Journal of Strategic Property Management, 11(4), 209-225. https://doi.org/10.3846/1648715X.2007.9637570
Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new stepwise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. https://doi.org/10.3846/jbem.2010.12
Kirkwood, C. W. (1997). Strategic decision making: multi-objective decision analysis with Spreadsheets. Belmont: Duxbury Press.
Li, P., & Tu, Y. (2011). Behaviors on intra-urban residential mobility: a review and implications to the future research (IRES working paper Series). Retrieved from https://pdfs.semanticscholar.org/1ac6/323cf2f1e695c49664b0996a43253e586b2a.pdf
Lux, M., Samec, T., Bartos, V., Sunega, P., Palguta, J., Boumová, I., & Kážmér, L. (2018). Who actually decides? Parental influence on the housing tenure choice of their children. Urban Studies, 55(2), 406-426. https://doi.org/10.1177/0042098016646665
Mamak Ekinci, E. B., & Can, G. F. (2018). Algılanan iş yükü ve çalışma duruşları dikkate alınarak operatörlerin ergonomik risk düzeylerinin çok kriterli karar verme yaklaşımı ile değerlendirilmesi [Evaluation of workers’ ergonomic risk levels considering working postures and perceived workload with multi-criteria decision making approach]. Ergonomi, 1(2), 7791. https://doi.org/10.33439/ergonomi.478732
Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustainable housing affordability. Omega, 59(part B), 146-156. https://doi.org/10.1016/j.omega.2015.05.013
Mulliner, E., Smallbone, K., & Maliene, V. (2013). An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega, 41(2), 270-279. https://doi.org/10.1016/j.omega.2012.05.002
Nawaz, F., Rajabi Asadabadi, M., Khalid Janjua, N., Khadeer Hussain, O., Chang, E., & Saberi, M. (2018). An MCDM method for cloud service selection using a Markov chain and the best-worst method. Knowledge-Based Systems, 159, 120-131. https://doi.org/10.1016/j.knosys.2018.06.010
Niedomysl, T. (2008). Residential preferences for interregional migration in Sweden: demographic, socioeconomic, and geographical determinants. Environment and Planning A, 40(5), 1109-1131. https://doi.org/10.1068/a39177
Nikolić, V., Milovančević, M., Petković, D., Jocić, D., & Savić, M. (2018). Parameters forecasting of laser welding by the artificial intelligence techniques. Facta Universitatis, Series: Mechanical Engineering, 16(2), 193-201. https://doi.org/10.22190/FUME180526025N
Nuuter, T., Lill, I., & Tupenaite, L. (2015). Comparison of housing market sustainability in European countries based on multiple criteria assessment. Land Use Policy, 42, 642-651. https://doi.org/10.1016/j.landusepol.2014.09.022
Opoku, R. A., & Abdul-Muhmin, A. G. (2010). Housing preferences and attribute importance among low-income consumers in Saudi Arabia. Habitat International, 34(2), 219-227. https://doi.org/10.1016/j.habitatint.2009.09.006
Pamučar, D., Stević, Z., & Sremac, S. (2018a). A new model for determining weight coefficients of criteria in MCDM models: full consistency method (FUCOM). Symmetry, 10(9), 393. https://doi.org/10.3390/sym10090393
Pamučar, D., Vasin, L., & Lukovac, L. (2014). Selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MAIRCА model. In XVI International Scientific-expert Conference on Railway (pp. 89-92). Railcon.
Pamučar, D., Božanić, D., Lukovac, V., & Komazec, N. (2018b). Normalized weighted geometric bonferroni mean operator of interval rough numbers – application in interval rough DEMATEL-COPRAS. Facta Universitatis, Series: Mechanical Engineering, 16(2), 171-191. https://doi.org/10.22190/FUME180503018P
Pamučar, D., Mihajlović, M., Obradović, R., & Atanasković, P. (2017). Novel approach to group multi-criteria decision making based on interval rough numbers: hybrid DEMATELANP-MAIRCA model. Expert Systems with Applications, 88, 58-80. https://doi.org/10.1016/j.eswa.2017.06.037
Popović, M., Kuzmanović, M., & Savić, G. (2018). A comparative empirical study of Analytic Hierarchy Process and Conjoint analysis: literature review. Decision Making: Applications in Management and Engineering, 1(2), 153-163. https://doi.org/10.31181/dmame1802160p
Ren, H., Folmer, H., & Van der Vlist, A. J. (2018). The impact of home ownership on life satisfaction in urban China: a propensity score matching analysis. Journal of Happiness Studies, 19(2), 397-422.
Ren, J., Liang, H., & Chan, F. T. S. (2017). Urban sewage sludge, sustainability, and transition for Eco-City: multi-criteria sustainability assessment of technologies based on best-worst method. Technological Forecasting and Social Change, 116, 29-39. https://doi.org/10.1016/j.techfore.2016.10.070
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: some properties and a linear model. Omega, 62, 126130. https://doi.org/10.1016/j.omega.2015.12.001
Rezaei, J., Hemmes, A., & Tavasszy, L. A. (2017). Multi-criteria decision-making for complex bundling configurations in surface transportation of air freight. Journal of Air Transport Management, 61, 95-105. https://doi.org/10.1016/j.jairtraman.2016.02.006
Rezaei, J., van Roekel, W. S., & Tavasszy, L. A. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158169. https://doi.org/10.1016/j.tranpol.2018.05.007
Rezaei, J., Wang, J., & Tavasszy, L. A. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42, 9152-9164. https://doi.org/10.1016/j.eswa.2015.07.073
Rossi, P. (1955). Why families move: a study of the social psychology of urban residential mobility. New York: The Free Press.
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill. https://doi.org/10.21236/ADA214804
Saaty, T. L. (1996). Decision making with dependence and feedback: the analytic network process. Pittsburgh: RWS Publications.
Said, R., Majid, R. A., & Nozin, A. S. (2016, April). Assessment of sustainable housing affordability in Malaysia based on people’s perception using COPRAS method. In International Real Estate Research Symposium (IRERS) (pp. 1-18), Kuala Lumpur, Malaysia.
Salimi, N., & Rezaei, J. (2016). Measuring efficiency of university-industry Ph.D. projects using best worst method. Scientometrics, 109(3), 1911-1938. https://doi.org/10.1007/s11192-016-2121-0
Salimi, N., & Rezaei, J. (2018). Evaluating firms’ R&D performance using best worst method. Evaluation and Program Planning, 66, 147-155. https://doi.org/10.1016/j.evalprogplan.2017.10.002
Salinas, C. X., Gironás, J., & Pinto, M. (2016). Water security as a challenge for the sustainability of La Serena-Coquimbo conurbation in northern Chile: global perspectives and adaptation. Mitigation and Adaptation Strategies for Global Change, 21(8), 1235-1246. https://doi.org/10.1007/s11027-015-9650-3
Squeo, F. A., Aravena, R., Aguirre, E., Pollastri, A., Jorquera, C. B., & Ehleringer, J. R. (2006). Groundwater dynamics in a coastal aquifer in north-central Chile: implications for groundwater recharge in an arid ecosystem. Journal of Arid Environments, 67, 240-254. https://doi.org/10.1016/j.jaridenv.2006.02.012
Stanujkić, D., & Karabašević, D. (2018). An extension of the WASPAS method for decision-making problems with intuitionistic fuzzy numbers: a case of website evaluation. Operational Research in Engineering Sciences: Theory and Applications, 1(1), 29-39. https://doi.org/10.31181/oresta19012010129s
Tianlin, D., Jianzhong, G., Fang, W., & Renjian, Z. (2019). Application of Entropy-based multi-attribute decision-making method to structured selection of settlement. Journal of Visual Communication and Image Representation, 58, 220-232. https://doi.org/10.1016/j.jvcir.2018.11.026
Van de Kaa, G., Janssen, M., & Rezaei, J. (2018). Standards battles for business-to-government data exchange: identifying success factors for standard dominance using the Best Worst Method. Technological Forecasting and Social Change, 137, 182-189. https://doi.org/10.1016/j.techfore.2018.07.041
Viteikienė, M., & Zavadskas, E. K. (2007). Evaluating the sustainability of Vilnius city residential areas. Journal of Civil Engineering and Management, 13(2), 149-155. https://doi.org/10.3846/13923730.2007.9636431
Wang, D., & Li, S. M. (2004). Housing preferences in a transitional housing system: the case of Beijing, China. Environment and Planning A, 36(1), 69-87. https://doi.org/10.1068/a35263
Yadav, G., Mangla, S. K., Luthra, S., & Jakhar, S. (2018). Hybrid BWM-ELECTRE-based decision framework for effective offshore outsourcing adoption: a case study. International Journal of Production Research, 56(18), 6259-6278. https://doi.org/10.1080/00207543.2018.1472406
Zavadskas, E. K., Cavallaro, F., Podvezko, V., Ubarte, I., & Kaklauskas, A. (2017). MCDM assessment of a healthy and safe built environment according to sustainable development principles: a practical neighborhood approach in Vilnius. Sustainability, 9(5), 702-731. https://doi.org/10.3390/su9050702
Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir Elektrotechnika, 6(122), 3-6. https://doi.org/10.5755/j01.eee.122.6.1810
Akkoc, R., & Alexander, H. (2015, September). Chile earthquake: 10 people killed and a million evacuated − as it happened. The Telegraph, 17.
Ardayfio-Schandorf, E. (2012). Urban families and residential mobility in Accra. In E. A-Schandorf, P. W. K. Yankson, & M. Bertrand (Eds.), Mobile city of Accra: urban families, housing and residential practices (pp. 47-72). Dakar: Codesria.
Badi, I., & Ballem, M. (2018). Supplier selection using rough BWM-MAIRCA model: a case study in pharmaceutical supplying in Libya. Decision Making: Applications in Management and Engineering, 1(2), 15-32. https://doi.org/10.31181/dmame1802016b
Badri Ahmadi, H., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method. Resources, Conservation and Recycling, 126, 99-106. https://doi.org/10.1016/j.resconrec.2017.07.020
Bailey, A. J., Blake, M. K., & Cooke, T. J. (2004). Migration, care, and the linked lives of dual-earner households. Environment and Planning A, 36(9), 1617-1632. https://doi.org/10.1068/a36198
Baláž, V., Williams, A. M., & Fifeková, E. (2016). Migration decision making as complex choice: eliciting decision weights under conditions of imperfect and complex information through experimental methods. Population, Space and Place, 22(1), 36-53. https://doi.org/10.1002/psp.1858
Brown, L. A., & Moore, E. G. (1970). The intra-urban migration process: a perspective. Geografiska Annaler, 52B, 1-13. https://doi.org/10.1080/04353684.1970.11879340
Cetinkaya, C., Özceylan, E., Erbaş, M., & Kabak, M. (2016). GISbased fuzzy MCDA approach for siting refugee camp: a case study for southeastern Turkey. International Journal of Disaster Risk Reduction, 18, 218-231. https://doi.org/10.1016/j.ijdrr.2016.07.004
Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of suppliers based on using the R’AMATELMAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101-129. https://doi.org/10.1016/j.jclepro.2018.02.186
Chiang, L. H. N., & Hsu, J. C. R. (2005). Locational decisions and residential preferences of Taiwanese immigrants in Australia. GeoJournal, 64(1), 75-89. https://doi.org/10.1007/s10708-005-3927-0
Chitsaz, N., & Azarivand, A. (2016). Water scarcity management in arid regions based on an extended multiple criteria technique. Water Resources Management, 31(1), 233-250. https://doi.org/10.1007/s11269-016-1521-5
Ciavarella, M., Carbone, G., & Vinogradov, V. (2018). A critical assessment of Kassapoglou’s statistical model for composites fatigue. Facta Universitatis, Series: Mechanical Engineering, 16(2), 115-126. https://doi.org/10.22190/FUME180321014C
Dökmeci, V., & Berköz, L. (2000). Residential-location preferences according to demographic characteristics in Istanbul. Landscape and Urban Planning, 48(1-2), 45-55. https://doi.org/10.1016/S0169-2046(99)00080-8
Drakaki, M., Gören, H. G., & Tzionas, P. (2018). An intelligent multi-agent based decision support system for refugee settlement siting. International Journal of Disaster Risk Reduction, 31, 576-588. https://doi.org/10.1016/j.ijdrr.2018.06.013
Earnhart, D. (2002). Combining revealed and stated data to examine housing decisions using discrete choice analysis. Journal of Urban Economics, 51(1), 143-169. https://doi.org/10.1006/juec.2001.2241
Ecer, F. (2015). Performance evaluation of internet banking branches via a hybrid MCDM model under fuzzy environment. Economic Computation and Economic Cybernetics Studies and Research, 49(2), 211-230.
Ecer, F. (2018). An integrated fuzzy AHP and ARAS model to evaluate mobile banking services. Technological and Economic Development of Economy, 24(2), 670-695. https://doi.org/10.3846/20294913.2016.1255275
Gigović, L., Pamučar, D., Bajić, Z., & Milićević, M. (2016). The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots. Sustainability, 8(4), 372. https://doi.org/10.3390/su8040372
Ginevičius, R. (2011). A new determining method for the criteria weights in multi-criteria evaluation. International Journal of Information Technology & Decision Making, 10(6), 1067-1095. https://doi.org/10.1142/S0219622011004713
Głuszak, M. (2015). Multinomial logit model of housing demand in Poland. Real Estate Management and Valuation, 23(1), 8489. https://doi.org/10.1515/remav-2015-0008
Gluszak, M., & Marona, B. (2017). Discrete choice model of residential location in Krakow. Journal of European Real Estate Research, 10(1), 4-16. https://doi.org/10.1108/JERER-01-2016-0006
Gupta, H., & Barua, M. K. (2016). Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method. Technological Forecasting and Social Change, 107, 69-79. https://doi.org/10.1016/j.techfore.2016.03.028
Hanafi, M. H., Mazree, A. S., Umar, M. U., & Ahmad, H. (2018). Neighborhood factors contributing to the household mobility: apartments in Malaysia. Environment-Behaviour Proceedings Journal, 3(7), 307-317. https://doi.org/10.21834/e-bpj.v3i7.1236
Hashemkhani Zolfani, S., Yazdani, M., & Zavadskas, E. K. (2018). An extended stepwise weight assessment ratio analysis (SWARA) method for improving criteria prioritization process. Soft Computing, 22(22), 7399-7405. https://doi.org/10.1007/s00500-018-3092-2
Hashemkhani Zolfani, S., Zavadskas, E. K., Khazaelpour, P., & Cavallaro, F. (2018). The multi-aspect criterion in the PMADM outline and its possible application to sustainability assessment. Sustainability, 10(12), 4451. https://doi.org/10.3390/su10124451
Haybatollahi, M., Czepkiewicz, M., Laatikainen, T., & Kyttä, M. (2015). Neighbourhood preferences, active travel behaviour, and built environment: an exploratory study. Transportation Research Part F: Traffic Psychology and Behaviour, 29, 57-69. https://doi.org/10.1016/j.trf.2015.01.001
Husain, K., Rashid, M., Vitković, N., Mitić, J., Milovanović, J., & Stojković, M. (2018). Geometrical models of mandible fracture and plate implant. Facta Universitatis, Series: Mechanical Engineering, 16(2), 369-379. https://doi.org/10.22190/FUME170710028H
Ioannides, Y. M., & Kan, K. (1996). Structural estimation of residential mobility and housing tenure choice. Journal of Regional Science, 36(3), 335-363. https://doi.org/10.1111/j.1467-9787.1996.tb01107.x
Jabareen, Y. (2005). Culture and housing preferences in a developing city. Environment and Behavior, 37(1), 134-146. https://doi.org/10.1177/0013916504267640
Kahraman, Y. R. (2002). Robust sensitivity analysis for multi-attribute deterministic hierarchical value models. Ohio: Storming Media.
Kauko, T. (2007). An analysis of housing location attributes in the inner city of Budapest, Hungary, using expert judgements. International Journal of Strategic Property Management, 11(4), 209-225. https://doi.org/10.3846/1648715X.2007.9637570
Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new stepwise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. https://doi.org/10.3846/jbem.2010.12
Kirkwood, C. W. (1997). Strategic decision making: multi-objective decision analysis with Spreadsheets. Belmont: Duxbury Press.
Li, P., & Tu, Y. (2011). Behaviors on intra-urban residential mobility: a review and implications to the future research (IRES working paper Series). Retrieved from https://pdfs.semanticscholar.org/1ac6/323cf2f1e695c49664b0996a43253e586b2a.pdf
Lux, M., Samec, T., Bartos, V., Sunega, P., Palguta, J., Boumová, I., & Kážmér, L. (2018). Who actually decides? Parental influence on the housing tenure choice of their children. Urban Studies, 55(2), 406-426. https://doi.org/10.1177/0042098016646665
Mamak Ekinci, E. B., & Can, G. F. (2018). Algılanan iş yükü ve çalışma duruşları dikkate alınarak operatörlerin ergonomik risk düzeylerinin çok kriterli karar verme yaklaşımı ile değerlendirilmesi [Evaluation of workers’ ergonomic risk levels considering working postures and perceived workload with multi-criteria decision making approach]. Ergonomi, 1(2), 7791. https://doi.org/10.33439/ergonomi.478732
Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustainable housing affordability. Omega, 59(part B), 146-156. https://doi.org/10.1016/j.omega.2015.05.013
Mulliner, E., Smallbone, K., & Maliene, V. (2013). An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega, 41(2), 270-279. https://doi.org/10.1016/j.omega.2012.05.002
Nawaz, F., Rajabi Asadabadi, M., Khalid Janjua, N., Khadeer Hussain, O., Chang, E., & Saberi, M. (2018). An MCDM method for cloud service selection using a Markov chain and the best-worst method. Knowledge-Based Systems, 159, 120-131. https://doi.org/10.1016/j.knosys.2018.06.010
Niedomysl, T. (2008). Residential preferences for interregional migration in Sweden: demographic, socioeconomic, and geographical determinants. Environment and Planning A, 40(5), 1109-1131. https://doi.org/10.1068/a39177
Nikolić, V., Milovančević, M., Petković, D., Jocić, D., & Savić, M. (2018). Parameters forecasting of laser welding by the artificial intelligence techniques. Facta Universitatis, Series: Mechanical Engineering, 16(2), 193-201. https://doi.org/10.22190/FUME180526025N
Nuuter, T., Lill, I., & Tupenaite, L. (2015). Comparison of housing market sustainability in European countries based on multiple criteria assessment. Land Use Policy, 42, 642-651. https://doi.org/10.1016/j.landusepol.2014.09.022
Opoku, R. A., & Abdul-Muhmin, A. G. (2010). Housing preferences and attribute importance among low-income consumers in Saudi Arabia. Habitat International, 34(2), 219-227. https://doi.org/10.1016/j.habitatint.2009.09.006
Pamučar, D., Stević, Z., & Sremac, S. (2018a). A new model for determining weight coefficients of criteria in MCDM models: full consistency method (FUCOM). Symmetry, 10(9), 393. https://doi.org/10.3390/sym10090393
Pamučar, D., Vasin, L., & Lukovac, L. (2014). Selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MAIRCА model. In XVI International Scientific-expert Conference on Railway (pp. 89-92). Railcon.
Pamučar, D., Božanić, D., Lukovac, V., & Komazec, N. (2018b). Normalized weighted geometric bonferroni mean operator of interval rough numbers – application in interval rough DEMATEL-COPRAS. Facta Universitatis, Series: Mechanical Engineering, 16(2), 171-191. https://doi.org/10.22190/FUME180503018P
Pamučar, D., Mihajlović, M., Obradović, R., & Atanasković, P. (2017). Novel approach to group multi-criteria decision making based on interval rough numbers: hybrid DEMATELANP-MAIRCA model. Expert Systems with Applications, 88, 58-80. https://doi.org/10.1016/j.eswa.2017.06.037
Popović, M., Kuzmanović, M., & Savić, G. (2018). A comparative empirical study of Analytic Hierarchy Process and Conjoint analysis: literature review. Decision Making: Applications in Management and Engineering, 1(2), 153-163. https://doi.org/10.31181/dmame1802160p
Ren, H., Folmer, H., & Van der Vlist, A. J. (2018). The impact of home ownership on life satisfaction in urban China: a propensity score matching analysis. Journal of Happiness Studies, 19(2), 397-422.
Ren, J., Liang, H., & Chan, F. T. S. (2017). Urban sewage sludge, sustainability, and transition for Eco-City: multi-criteria sustainability assessment of technologies based on best-worst method. Technological Forecasting and Social Change, 116, 29-39. https://doi.org/10.1016/j.techfore.2016.10.070
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: some properties and a linear model. Omega, 62, 126130. https://doi.org/10.1016/j.omega.2015.12.001
Rezaei, J., Hemmes, A., & Tavasszy, L. A. (2017). Multi-criteria decision-making for complex bundling configurations in surface transportation of air freight. Journal of Air Transport Management, 61, 95-105. https://doi.org/10.1016/j.jairtraman.2016.02.006
Rezaei, J., van Roekel, W. S., & Tavasszy, L. A. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158169. https://doi.org/10.1016/j.tranpol.2018.05.007
Rezaei, J., Wang, J., & Tavasszy, L. A. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42, 9152-9164. https://doi.org/10.1016/j.eswa.2015.07.073
Rossi, P. (1955). Why families move: a study of the social psychology of urban residential mobility. New York: The Free Press.
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill. https://doi.org/10.21236/ADA214804
Saaty, T. L. (1996). Decision making with dependence and feedback: the analytic network process. Pittsburgh: RWS Publications.
Said, R., Majid, R. A., & Nozin, A. S. (2016, April). Assessment of sustainable housing affordability in Malaysia based on people’s perception using COPRAS method. In International Real Estate Research Symposium (IRERS) (pp. 1-18), Kuala Lumpur, Malaysia.
Salimi, N., & Rezaei, J. (2016). Measuring efficiency of university-industry Ph.D. projects using best worst method. Scientometrics, 109(3), 1911-1938. https://doi.org/10.1007/s11192-016-2121-0
Salimi, N., & Rezaei, J. (2018). Evaluating firms’ R&D performance using best worst method. Evaluation and Program Planning, 66, 147-155. https://doi.org/10.1016/j.evalprogplan.2017.10.002
Salinas, C. X., Gironás, J., & Pinto, M. (2016). Water security as a challenge for the sustainability of La Serena-Coquimbo conurbation in northern Chile: global perspectives and adaptation. Mitigation and Adaptation Strategies for Global Change, 21(8), 1235-1246. https://doi.org/10.1007/s11027-015-9650-3
Squeo, F. A., Aravena, R., Aguirre, E., Pollastri, A., Jorquera, C. B., & Ehleringer, J. R. (2006). Groundwater dynamics in a coastal aquifer in north-central Chile: implications for groundwater recharge in an arid ecosystem. Journal of Arid Environments, 67, 240-254. https://doi.org/10.1016/j.jaridenv.2006.02.012
Stanujkić, D., & Karabašević, D. (2018). An extension of the WASPAS method for decision-making problems with intuitionistic fuzzy numbers: a case of website evaluation. Operational Research in Engineering Sciences: Theory and Applications, 1(1), 29-39. https://doi.org/10.31181/oresta19012010129s
Tianlin, D., Jianzhong, G., Fang, W., & Renjian, Z. (2019). Application of Entropy-based multi-attribute decision-making method to structured selection of settlement. Journal of Visual Communication and Image Representation, 58, 220-232. https://doi.org/10.1016/j.jvcir.2018.11.026
Van de Kaa, G., Janssen, M., & Rezaei, J. (2018). Standards battles for business-to-government data exchange: identifying success factors for standard dominance using the Best Worst Method. Technological Forecasting and Social Change, 137, 182-189. https://doi.org/10.1016/j.techfore.2018.07.041
Viteikienė, M., & Zavadskas, E. K. (2007). Evaluating the sustainability of Vilnius city residential areas. Journal of Civil Engineering and Management, 13(2), 149-155. https://doi.org/10.3846/13923730.2007.9636431
Wang, D., & Li, S. M. (2004). Housing preferences in a transitional housing system: the case of Beijing, China. Environment and Planning A, 36(1), 69-87. https://doi.org/10.1068/a35263
Yadav, G., Mangla, S. K., Luthra, S., & Jakhar, S. (2018). Hybrid BWM-ELECTRE-based decision framework for effective offshore outsourcing adoption: a case study. International Journal of Production Research, 56(18), 6259-6278. https://doi.org/10.1080/00207543.2018.1472406
Zavadskas, E. K., Cavallaro, F., Podvezko, V., Ubarte, I., & Kaklauskas, A. (2017). MCDM assessment of a healthy and safe built environment according to sustainable development principles: a practical neighborhood approach in Vilnius. Sustainability, 9(5), 702-731. https://doi.org/10.3390/su9050702
Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir Elektrotechnika, 6(122), 3-6. https://doi.org/10.5755/j01.eee.122.6.1810