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Modelling The Urban Sustainable Development By Using Fuzzy Sets

Author

Listed:
  • Daniela Hincu

    (Academy of Economic Studies, Piata Romana 6, Bucharest, Romania)

Abstract

The sustainable urban development is a subject of interest for regional policy makers and it needs appropriate assessment based on futile instruments for research, and for practical reasonsl (planning and decision making). Even if the sustainability’s attainment is a research topic field for academia and urban planners and managers and, as well, an ambitious goal for any resource administrator, yet there is no precise way of defining and measuring it. The sustainability of the urban development policy implies multiple and diversified aspects from rational exploitation of the local resources and well-structured workforce to environmental issues, endowment of modern urban facilities and infrastructure elements. As the urban sustainability is measured using a multitude of basic indicators, needing proper information to make long term management decision and planning, the subject is treated with fuzzy setsseen as an appropriate manner to deal with ambiguity, subjectivity and imprecision in the human reasoning when processing large volumes of data, eventually unstructured and complex. The paper proposed a modeling approach based on fuzzy sets inspired by the SAFE (Sustainability Assessment by Fuzzy Evaluation), a model which provides a mechanism for measuring development sustainability. The papers intends presenting a quantitative methodology in assessing the potential sustainability of urban development (in terms of adequacy) by pointing the failures in pursuing trends that are associated to a robust growth in the urban areas. The advantages of such approach are derived from taking into account the multi-criteria and uncertainty facets of the phenomenon; also, having in mind that the sustainability remains a non-straight-cut concept, being vaguely defined it implies a non-deterministic character by using the fuzzy set logic. The proposed model is designed to assess the divergence from desired trajectories, the weak point in reaching indicators’ target (as they are commonly regardedd as appropriate in what is understood as a good practices), it may then be addressed for policy makers in indicating some action measures in urban administration as they intendenly strive towards increasingly sustainable development on the long term.

Suggested Citation

  • Daniela Hincu, 2011. "Modelling The Urban Sustainable Development By Using Fuzzy Sets," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 6(2), pages 88-103, May.
    • Handle: RePEc:rom:terumm:v:6:y:2011:i:2:p:88-103
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    References listed on IDEAS

    as
    1. Lazim ABDULLAH & Nurhanadia WAHAB, 2010. "A Fuzzy Decision Making Approach In Evaluating Ferry Service Quality," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 2(1), pages 94-107, March.
    2. Nijkamp, Peter & Vreeker, Ron, 2000. "Sustainability assessment of development scenarios: methodology and application to Thailand," Ecological Economics, Elsevier, vol. 33(1), pages 7-27, April.
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    More about this item

    Keywords

    sustainability; urban management; indicators; fuzzy approach.;
    All these keywords.

    JEL classification:

    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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