Factors influencing urban investment attractiveness: an FCM-SD approach
Abstract
The increasing concentration of populations in urban areas in recent decades has strengthened the interest in – and the importance given to – these zones. Cities have become quite attractive from investors’ point of view because of the wide array of opportunities and growing need for investment in urban areas. Thus, city strategic planning quite often requires an understanding of the determinants that attract investment to urban zones. This study sought to identify the factors that strengthen urban investment based on the knowledge of a panel of experts. Fuzzy cognitive mapping techniques were applied to understand the concepts and decision criteria included in the decision-support model and their cause-and-effect relationships. The results provide insights into which determinants most strongly influence urban investment, namely, infrastructure, supporting services, and political-administrative factors. Diverse scenarios at the intra- and inter-cluster levels were created to clarify the impacts of variable changes on the model developed. The findings were validated by both the expert panel members and the vice-president of the Portuguese Association of Real Estate Developers and Investors. Advantages and limitations of the proposed framework are presented, as well as recommendations for future research.
Keyword : decision aid, (fuzzy) cognitive mapping, strategic planning, system dynamics, urban investment attractiveness, urban planning
How to Cite
Correia, J. S. R. ., Ferreira, F. A. F. ., Meidutė-Kavaliauskienė, I., Pereira, L. F. ., Zopounidis, C. ., & Correia, R. J. C. (2020). Factors influencing urban investment attractiveness: an FCM-SD approach. International Journal of Strategic Property Management, 24(4), 237-250. https://doi.org/10.3846/ijspm.2020.12384
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Bruneckienė, J., Zykienė, I., & Stankevičius, V. (2016). Critical analysis of city attractiveness factors in Lithuania–Poland cross-border regions: the viewpoints of businessmen and youth. Journal of Geography, Politics and Society, 6(2), 45–58.
Carayannis, E., Ferreira, F., Bento, P., Ferreira, J., Jalali, M., & Fernandes, B. (2019). Developing a socio-technical evaluation index for tourist destination competitiveness using cognitive mapping and MCDA. Technological Forecasting and Social Change, 131, 147–158. https://doi.org/10.1016/j.techfore.2018.01.015
Carley, K., & Palmquist, M. (1992). Extracting, representing, and analyzing mental models. Social Forces, 70(3), 601–636. https://doi.org/10.2307/2579746
Carvalho, J. (2013). On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in social sciences. Fuzzy Sets and Systems, 214, 6–19. https://doi.org/10.1016/j.fss.2011.12.009
Castanho, M., Ferreira, F., Carayannis, E., & Ferreira, J. (2019). SMART-C: developing a “smart city” assessment system using cognitive mapping and the Choquet integral. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2019.2909668
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De Noni, I., Orsi, L., & Zanderighi, L. (2014). Attributes of Milan influencing city brand attractiveness. Journal of Destination Marketing & Management, 3(4), 218–226. https://doi.org/10.1016/j.jdmm.2014.06.001
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Dobrovolskienė, N., Tamošiūnienė, R., Banaitis, A., Ferreira, F., Banaitienė, N., Taujanskaitė, K., & Meidutė-Kavaliauskienė, I. (2019). Developing a composite sustainability index for real estate projects using multiple criteria decision making. Operational Research, 19(3), 617–635. https://doi.org/10.1007/s12351-017-0365-y
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Estêvão, R., Ferreira, F., Rosa, A., Govindan, K., & MeidutėKavaliauskienė, I. (2019). A socio-technical approach to the assessment of sustainable tourism: adding value with a comprehensive process-oriented framework. https://doi.org/10.1016/j.jclepro.2019.06.318
Ezmale, S. (2012). Strategies for enhancing attractiveness of the cities in Latgale region. European Integration Studies, 6, 121–127. https://doi.org/10.5755/j01.eis.0.6.1601
Ezmale, S., & Litavniece, L. (2011). Spatial planning as a tool for improving attractiveness of the places: case of Latgale region. European Integration Studies, 5, 20–25.
https://doi.org/10.5755/j01.eis.0.5.1071
Faria, P., Ferreira, F., Jalali, M., Bento, P., & António, N. (2018). Combining cognitive mapping and MCDA for improving quality of life in urban areas. Cities, 78, 116–127. https://doi.org/10.1016/j.cities.2018.02.006
Fernandes, I., Ferreira, F., Bento, P., Jalali, M., & António, N. (2018). Assessing sustainable development in urban areas using cognitive mapping and MCDA. International Journal of Sustainable Development & World Ecology, 25(3), 216–226. https://doi.org/10.1080/13504509.2017.1358221
Ferreira, F. (2016). Are you pleased with your neighborhood? A fuzzy cognitive mapping-based approach for measuring residential neighborhood satisfaction in urban communities. International Journal of Strategic Property Management, 20(2), 130–141. https://doi.org/10.3846/1648715X.2015.1121169
Ferreira, F., Santos, S., Rodrigues, P., & Spahr, R. (2014). How to create indices for bank branch financial performance measurement using MCDA techniques: an illustrative example. Journal of Business Economics and Management, 15(4), 708–728. https://doi.org/10.3846/16111699.2012.701230
Ferreira, F., Spahr, R., Sunderman, M., & Jalali, M. (2018). A prioritisation index for blight intervention strategies in residential real estate. Journal of the Operational Research Society, 69(8), 1269–1285. https://doi.org/10.1080/01605682.2017.1390535
Fonseca, M., Ferreira, F., Fang, W., & Jalali, M. (2018). Classification and selection of tenants in residential real estate: a constructivist approach. International Journal of Strategic Property Management, 22(1), 1–11. https://doi.org/10.3846/ijspm.2018.317
Forrester, J. (1969). Urban dynamics. The MIT Press.
Gavrilova, T., Carlucci, D., & Schiuma, G. (2013). Art of visual thinking for smart business education. In Proceedings of the 8th International Forum on Knowledge Asset Dynamics (IFKAD-2013) (pp. 1754–1761), Zagreb, Croatia.
Georgiou, I. (2012). Messing about in transformations: structured systemic planning for systemic solutions to systemic problems. European Journal of Operational Research, 223(2), 392–406. https://doi.org/10.1016/j.ejor.2012.06.010
Grant, R. (2014). Contemporary Strategic Management. Wiley.
Hanafizadeh, P., & Aliehyaei, R. (2011). The application of fuzzy cognitive map in soft system methodology. Systemic Practice and Action Research, 24(4), 325–354. https://doi.org/10.1007/s11213-011-9190-z
Jiang, Y., & Shen, J. (2013). Weighting for what? A comparison of two weighting methods for measuring urban competitiveness. Habitat International, 38(2), 167–174. . https://doi.org/10.1016/j.habitatint.2012.06.003
Kang, I., Lee, S., & Choi, J. (2004). Using fuzzy cognitive map for the relationship management in airline service. Expert Systems with Applications, 26(4), 545–555. https://doi.org/10.1016/j.eswa.2003.10.012
Litavniece, L. (2012). The evaluation of a town’s attractiveness: a case study of Balvi city. In Proceedings of the 7th Annual International Scientific Conference “New Dimensions in the Development of Society” (pp. 170–179), Jelgava, Latvia.
Marques, S., Ferreira, F., Meidutė-Kavaliauskienė, I., & Banaitis, A. (2018). Classifying urban residential areas based on their exposure to crime: a constructivist approach. Sustainable Cities and Society, 39, 418–429. https://doi.org/10.1016/j.scs.2018.03.005
Martin, J., Bell, R., Farmer, E., & Henry, J. (2010). Strategic options development and analysis (SODA). In J. Rosenhead (Ed.), Rational analysis for a problematic world (pp. 21–70). Open University.
Miguel, B., Ferreira, F., Banaitis, A., Banaitienė, N., Meidutė-Kavaliauskienė, I., & Falcão, P. (2019). An expanded conceptualization of “smart” cities: adding value with fuzzy cognitive maps. E&M Economics and Management, 22(1), 4–21. https://doi.org/10.15240/tul/001/2019-1-001
Mingers, J., & Rosenhead, J. (2004). Problem structuring methods in action. European Journal of Operational Research, 152(3), 530–554. https://doi.org/10.1016/S0377-2217(03)00056-0
Ogata, K. (2004). System dynamics. Pearson Prentice Hall.
Oliveira, I., Carayannis, E., Ferreira, F., Jalali, M., Carlucci, D., & Ferreira, J. (2018). Constructing home safety indices for strategic planning in residential real estate: a socio-technical approach. Technological Forecasting and Social Change, 131, 67–77. https://doi.org/10.1016/j.techfore.2017.10.012
Papachristos, G. (2019). System dynamics modelling and simulation for sociotechnical transitions research. Environmental Innovation and Societal Transitions, 31, 248–261. https://doi.org/10.1016/j.eist.2018.10.001
Pires, A., Ferreira, F., Jalali, M., & Chang, H. (2018). Barriers to real estate investments for residential rental purposes: mapping out the problem. International Journal of Strategic Property Management, 22(3), 168–178. https://doi.org/10.3846/ijspm.2018.1541
Reis, I., Ferreira, F., Meidutė-Kavaliauskienė, I., Govindan, K., Fang, W., & Falcão, P. (2019). An evaluation thermometer for assessing city sustainability and livability. Sustainable Cities and Society, 47, 1–11. https://doi.org/10.1016/j.scs.2019.101449
Ribeiro, M., Ferreira, F., Jalali, M., & Meidutė-Kavaliauskienė, I. (2017). A fuzzy knowledge-based framework for risk assessment of residential real estate investments. Technological and Economic Development of Economy, 23(1), 140–156. https://doi.org/10.3846/20294913.2016.1212742
Richmond, B. (2001). An introduction to systems thinking. High Performance Systems.
Romão, J., Kourtit, K., Neuts, B., & Nijkamp, P. (2018). The smart city as a common place for tourists and residents: a structural analysis of the determinants of urban attractiveness. Cities, 78, 67–75. https://doi.org/10.1016/j.cities.2017.11.007
Sáez, L., & Periáñez, I. (2015). Benchmarking urban competitiveness in Europe to attract investment. Cities, 48, 76–85. https://doi.org/10.1016/j.cities.2015.06.002
Sáez, L., Periáñez, I., & Heras-Saizarbitoria, I. (2017). Measuring urban competitiveness: ranking European large urban zones. Journal of Place Management and Development, 10(5), 479–496. https://doi.org/10.1108/JPMD-07-2017-0066
Salmeron, J. (2012). Fuzzy cognitive maps for artificial emotions forecasting. Applied Soft Computing, 12(12), 3704-3710. https://doi.org/10.1016/j.asoc.2012.01.015
Saysel, A., Barlas, Y., & Yenigün, O. (2002). Environmental sustainability in an agricultural development project: a system dynamics approach. Journal of Environmental Management, 64(3), 247–260. https://doi.org/10.1006/jema.2001.0488
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