Factors influencing urban investment attractiveness: an FCM-SD approach

    Joana S. R. Correia Affiliation
    ; Fernando A. F. Ferreira Affiliation
    ; Ieva Meidutė-Kavaliauskienė   Affiliation
    ; Leandro F. Pereira Affiliation
    ; Constantin Zopounidis   Affiliation
    ; Ricardo J. C. Correia Affiliation


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.
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May 25, 2020
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Ackermann, F., & Eden, C. (2001). SODA – Journey making and mapping in practice. In J. Rosenhead, & J. Mingers (Eds.), Rational analysis for a problematic world revisited: problem structuring methods for complexity, uncertainty and conflict (pp. 43–60). John Wiley & Sons.

Amrollahi, A., & Rowlands, B. (2018). OSPM: a design methodology for open strategic planning. Information & Management, 55(6), 667–685.

Armstrong, J. (1982). The value of formal planning for strategic decisions: review of empirical research. Strategic Management Journal, 3(3), 197–211.

Barney, J. (2002). Gaining and sustaining competitive advantage. Prentice Hall.

Bell, S., & Morse, S. (2013). Groups and facilitators within problem structuring processes. Journal of the Operational Research Society, 64(7), 959–972.

Belton, V., & Stewart, T. (2002). Multiple criteria decision analysis: an integrated approach. Kluwer Academic Publishers.

Brito, V., Ferreira, F., Pérez-Gladish, B., Govindan, K., & MeidutėKavaliauskienė, I. (2019). Developing a green city assessment system using cognitive maps and the Choquet integral. Journal of Cleaner Production, 218, 486–497.

Bruneckiene, J., Cincikaite, R., & Kilijoniene, A. (2012). The specifics of measurement the urban competitiveness at the national and international level. Engineering Economics, 23(3), 256–270.

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.

Carley, K., & Palmquist, M. (1992). Extracting, representing, and analyzing mental models. Social Forces, 70(3), 601–636.

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.

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.

Castellacci, F. (2018). Co-evolutionary growth: a system dynamics model. Economic Modelling, 70(C), 272–287.

Chen, Y., & Jeng, B. (2002). Yet another representation for system dynamics models, and its advantages. In Proceedings of the 20th International Conference of the System Dynamics Society (pp. 1–27), Palermo, Italy.

De Noni, I., Orsi, L., & Zanderighi, L. (2014). Attributes of Milan influencing city brand attractiveness. Journal of Destination Marketing & Management, 3(4), 218–226.

Ding, C., & Lai, S. (2012). Challenges in urban management. Journal of Urban Management, 1(2), 1–2.

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.

Eden, C., & Ackermann, F. (2001). SODA – the principles. In J. Rosenhead, & J. Mingers (Eds.), Rational analysis for a problematic world revisited: problem structuring methods for complexity, uncertainty, and conflict (pp. 21–41). John Wiley & Sons.

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.

Ezmale, S. (2012). Strategies for enhancing attractiveness of the cities in Latgale region. European Integration Studies, 6, 121–127.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Jiang, Y., & Shen, J. (2013). Weighting for what? A comparison of two weighting methods for measuring urban competitiveness. Habitat International, 38(2), 167–174. .

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.

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.

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.

Mingers, J., & Rosenhead, J. (2004). Problem structuring methods in action. European Journal of Operational Research, 152(3), 530–554.

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.

Papachristos, G. (2019). System dynamics modelling and simulation for sociotechnical transitions research. Environmental Innovation and Societal Transitions, 31, 248–261.

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.

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.

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.

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.

Sáez, L., & Periáñez, I. (2015). Benchmarking urban competitiveness in Europe to attract investment. Cities, 48, 76–85.

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.

Salmeron, J. (2012). Fuzzy cognitive maps for artificial emotions forecasting. Applied Soft Computing, 12(12), 3704-3710.

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.

Sedarati, P., Santos, S., & Pintassilgo, P. (2019). System dynamics in tourism planning and development. Tourism Planning & Development, 16(3), 256–280.

Serrano, F. (2003). City competitiveness and attractiveness: a new approach to evaluate economic development in Mexican cities (Doctoral dissertation). University of Glasgow.

Shepherd, S. (2014). A review of system dynamics models applied in transportation. Transportmetrica B: Transport Dynamics, 2(2), 83–105.

Singhal, S., McGreal, S., & Berry, J. (2013). An evaluative model for city competitiveness: application to UK cities. Land Use Policy, 30(1), 214–222.

Snieška, V., & Zykienė, I. (2015). City attractiveness for investment: characteristics and underlying factors. Procedia-Social and Behavioral Sciences, 213, 48–54.

Stach, W., Kurgan, L., Pedrycz, W., & Reformat, M. (2005). Genetic learning of fuzzy cognitive maps. Fuzzy Sets and Systems, 153(3), 371–401.

Sterman, J. (2000). Business dynamics: systems thinking and modeling for a complex world. Irwin/McGraw-Hill.

Tan, Y., Jiao, L., Shuai, C., & Shen, L. (2018). A system dynamics model for simulating urban sustainability performance: a China case study. Journal of Cleaner Production, 199, 1107–1115.

Thaller, C., Niemann, F., Dahmen, B., Clausen, U., Leerkamp, B. (2017). Describing and explaining urban freight transport by system dynamics. Transportation Research Procedia, 25, 1075–1094.

Wiranatha, A., & Smith, P. (2000). A conceptual framework for a dynamic model for regional planning: towards sustainable development for Bali, Indonesia. In Proceedings of the 1st International Conference on Systems Thinking in Management (pp. 649–654), Geelong, Australia.

Yaman, D., & Polat, S. (2009). A fuzzy cognitive map approach for effect-based operations: an illustrative case. Information Sciences, 179(4), 382–403.

Zomorodian, M., Lai, S., Homayounfar, M., Ibrahim, S., Fatemi, S., & El-Shafie, A. (2018). The state-of-the-art system dynamics application in integrated water resources modeling. Journal of Environmental Management, 227, 294–304.