Understanding the drivers of Urban Development Agreements with the rough set approach and robust decision rules

• Oppio, Alessandra ^[1] ; Dell’Ovo, Marta ^[1] ; Torrieri, Francesca ^[2] ; Miebs, Grzegorz ^[3] ; Kadziński, Miłosz ^[3]
  1. [1] Polytechnic University of Milan

     Polytechnic University of Milan

     Milán, Italia

     
  2. [2] University of Naples Federico II

     University of Naples Federico II

     Nápoles, Italia

     
  3. [3] Institute of Computing Science, Poznan University of Technology, Poznań, Poland

  Mostrar afiliaciones +
• Localización: Land use policy: The International Journal Covering All Aspects of Land Use, ISSN 0264-8377, ISSN-e 1873-5754, Nº. 96, 2020
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • The rise of neoliberalism in the context of urban development has encouraged cooperation between public and private parties. This cooperation is structured by contracts, generally called Urban Development Agreements (UDAs). Being part of the urban regeneration strategies, UDAs aim at achieving durable improvements of abandoned areas, namely brownfields, according to the sustainability principles. Thus, within the negotiation between private developers and public administrations, multiple and conflicting instances have to be faced case by case. Despite the uniqueness of each UDA, it is possible to define a set of pertinent characteristics that play a crucial role in determining the fairness and appropriateness of the public-private partnership. Given this context, we propose a novel variant of the Dominance Rough Set Approach (DRSA) for i) exploring the relationship between condition attributes or criteria and effects of urban development processes and for ii) supporting negotiations according to the detection of a set of relevant features. Specifically, DRSA is applied on a sample of UDAs recently concluded in the Lombardy Region (Northern Italy), and then tested on a sample of other UDAs under the negotiation phase. The analysis involves five dimensions represented by attributes and criteria related to urban, institutional, negotiation, development and economic contexts. The inferred decision rules provide useful knowledge for supporting complex decision processes such as the allocation of costs and benefits within UDAs.