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Use of fuzzy cognitive maps to develop policy strategies for the optimization of municipal waste management: A case study of the land of fires (Italy)
Philosophy and History, KTH, School of Architecture and the Built Environment (ABE), Philosophy and History of Technology, History of Science, Technology and Environment. (Environmental Humanities Laboratory)ORCID iD: 0000-0001-9655-1533
2020 (English)In: Land use policy, ISSN 0264-8377, E-ISSN 1873-5754, Vol. 96Article in journal (Refereed) Published
Abstract [en]

This paper applies an analytical method for developing policy strategies to optimize municipal waste management systems (MWMSs) to the case of the Land of Fires (LoF). The LoF is an area of Italy’s Campania region that is characterized by a legacy of authoritarian environmental governance and the improper dumping and burning of waste. In this paper, we employ the fuzzy cognitive maps (FCM) method, which draws on a participatory approach. Specifically, the complexity of the investigated system was determined from the causal relations identified by relevant stakeholders and experts. The results show that the most effective policy strategies to improve the LoF MWMS, as identified by informants, include: fostering social innovation (e.g. communication and information campaigns); promoting technological innovation (e.g. material and process design); and supporting scientific and technological cooperation among actors. The overall diversity of the identified policy strategies suggests that policy makers must move beyond a simple “best option” approach, given the systemic complexity of the waste management sector.

Place, publisher, year, edition, pages
2020. Vol. 96
Keywords [en]
waste management, Land of Fires, Fuzzy cognitive maps, Policy strategies
National Category
Economic Geography
Research subject
Planning and Decision Analysis, Urban and Regional Studies; Planning and Decision Analysis, Strategies for sustainable development
Identifiers
URN: urn:nbn:se:kth:diva-273250DOI: 10.1016/j.landusepol.2020.104680Scopus ID: 2-s2.0-85084368032OAI: oai:DiVA.org:kth-273250DiVA, id: diva2:1429671
Funder
Swedish Research Council Formas, 2017-01962_3)
Note

QC 20200520

Available from: 2020-05-12 Created: 2020-05-12 Last updated: 2020-05-25Bibliographically approved

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