Rurality and Competitiveness. Some Observations on the Local Area

Balestrieri, Mara

doi:10.1177/0973005214546599

Cited by 7 publications

(4 citation statements)

References 29 publications

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“…Therefore, this section focuses on regional-level and territorial-level competitiveness. In this respect, the strategy of considering competitiveness at the regional level as a starting point for the municipal context was also used in other studies -for instance, by Kurek et al (2020) and Balestrieri (2014) -in which the authors analysed municipal competitiveness in relation to two specific cases, namely the impact of geothermal resources on municipal competitiveness in Poland and the linkage between competitiveness and rurality, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Competitiveness: A Composite Indicator for Italian Municipalities

2022

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This study measures territorial competitiveness at the municipal level in Italy, by proposing a robust composite indicator based on variables not yet used in the literature. The underlying theoretical framework is identified based on the literature on regional competitiveness. The proposed indicator consists of the following seven dimensions of competitiveness: Education, Job, Economic Wellbeing, Territory and Environment, Entrepreneurship, Innovation, and Infrastructures and Mobility. Data are retrieved mainly from administrative sources, for 2014 and 2015. In the building process, three aggregation methods are compared: a compensatory method, the arithmetic mean, and two partially compensatory methods, the geometric mean and the Adjusted Mazziotta-Pareto Index (AMPI). The arithmetic mean turns out to be the most robust method among the three considered, but the AMPI is the most robust method among the two partially compensatory methods. All the methods considered agree in identifying Innovation and Entrepreneurship as the most influential pillars in 2014 and 2015, respectively. The detailed geographical focus provides specific insights into territorial competitiveness in Italy. It emerges a rather heterogeneous picture of municipal competitiveness within the Italian regions. Highly competitive municipalities are present in every region, though with different concentration levels.

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Section: Literature Reviewmentioning

confidence: 99%

Measuring Competitiveness: A Composite Indicator for Italian Municipalities

2022

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“…Kırsallık sosyal, ekonomik, kültürel ve politik yönlerden özellikle de kırsal alanların geleceği açısından büyük önem taşımaktadır (Avrupa Komisyon Raporu;. Ekonomik faaliyetlerin ve nüfusun kentsel alanlara göçü, tarım sektörünün öneminin kaybolması, kırsal alanlardaki çevresel baskıların ve kırsal toplulukların sürdürülebilirliği konusundaki endişelerin artması sonucunda kırsal alanların değişen doğasını tanımlama ve izleme ihtiyacı (Balestrieri, 2014;Harrington ve O'Donoghue; acil ve daha da önemli bir hale gelmiştir. Yanı sıra kaynak dağılımını optimize etmeye, alanlar arasındaki eşitsizlik konusundaki boşluğu kapatmaya ve en az avantajlı nüfuslar için yaşam standartlarını yükseltmeye yönelik (Ocaña-Riola ve Sánchez-Cantalejo; 2005) politika ve kararlar açısından da kırsalın tanımı önem taşımaktadır.…”

Section: Kuramsal çErçeveunclassified

“…Yoğun nüfuslu bir bölgeye ait olmayan, her biri 100 kişi/km 2 'den fazla nüfus yoğunluğuna sahip belediye grupları 'orta yoğunluklu bölgeler' olup; bölgenin toplam nüfusu en az 50.000 kişi veya yoğun nüfuslu bir bölgeye bitişik olmalıdır. 'Düşük nüfuslu bölgeler': yoğun nüfuslu veya orta dereceli olarak sınıflandırılmayan belediye gruplarıdır (Boscacci vd., 1999;EUROSTAT, 2010;Balestrieri, 2014).…”

Section: Kuramsal çErçeveunclassified

Kırsallığın Seçilmiş Sosyo-demografik Değişkenler Yardımıyla Kümelenmesi ve Zamana Bağlı Değişimi

özlü¹

2020

Planning

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Rural areas, which have social, economic, physical and cultural differences, have a multi-component structure. This multi-component structure is of great importance for the future and sustainability of settlements.The acceptance that rural areas should be determined by one-dimensional criteria such as population density or agriculture forms the basis of the generally accepted regional classification efforts with a deductive approach. Contrary to transnational comparisons where population density criteria is key variable, methodologies that would allow temporal and contextual national/regional analyses and findings that would serve as input to future policies are required. After discussing the limitations created by univariate classifications, it was aimed to classify the rural areas of Turkey with the help of selected sociodemographic variables in addition to the population density. Considering the heterogeneous structure of the rural context and the purpose of measuring the time-dependent change of rural life with socio-demographic data as well as the population criteria of the study, a multivariate process was followed at the NUTS-3 level. The dataset was obtained from Turkey Statistical Institute data and Two-Step clustering was used. As a result of the study, the change of rural conditions of the provinces in the similar and different clusters, which are discussed in the socio-demographic title, based on time and causality were discussed comparatively. The results will be useful and guiding for statistical regions and sub-regions as input to the planning decision on similarities and differences and in the production of socio-demographic policies.

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“…The other conceptualization of rural communities is geographical (territorial & spatial). In this approach, although demographic features such as population density, size, and spatial ranges play an essential role in defining rural communities, it seems that the population density is an inadequate or, at least, partial indicator for defining the rural communities (Balestrieri 2014).…”

Section: Introductionmentioning

confidence: 99%