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Application and critical assessment of qualitative comparative analysis: determinants for the presence of service provision models for water supply and sanitation services in Brazil
Author(s) -
Nathalia Roland,
Sonaly Rezende,
Léo Heller
Publication year - 2018
Publication title -
water policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.488
H-Index - 56
eISSN - 1996-9759
pISSN - 1366-7017
DOI - 10.2166/wp.2018.164
Subject(s) - sanitation , qualitative comparative analysis , business , service (business) , water supply , population , state (computer science) , administration (probate law) , politics , service provider , process (computing) , public service , environmental planning , public administration , public economics , geography , economics , political science , marketing , engineering , computer science , environmental engineering , environmental health , medicine , algorithm , machine learning , law , operating system
The provision of water supply and sanitation services in Brazil is characterized by a diverse range of management models, public or private operators and various judicial-institutional arrangements. Using a quali-quantitative technique – qualitative comparative analysis (QCA) – this article presents an investigation of determining factors for the presence of different service provision models in Brazil, and discusses the application of said technique. In this study, four models were comparatively analyzed: direct municipal administration, indirect municipal administration, state utility company, and private enterprise (PRIV). Eight municipalities, with an urban population ranging from 10 to 20 thousand inhabitants, from Minas Gerais (a state in the Southeast region of Brazil) were selected for this study. The findings suggest that the decision-making process regarding a service provision model, in the cases studied, involves a combination of economic, political, social, institutional, and legal factors. The qualitative comparative analysis proved capable of compiling information for this analysis as it uncovered how determining factors are inter-related and allowed the predominant factors in each of the studied management models to be identified.

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