https://arvinfomedia.com/myjournals/index.php/GIJGS/issue/feed 2026-10-05T06:32:35+00:00 Open Journal Systems <p><strong>Global Impact Journal: Geographical Studies</strong> is a peer-reviewed journal dedicated to publishing high-quality original research articles, comprehensive reviews, and selected high-impact reprints in the areas of geography. The journal provides a platform for rigorous, innovative, and interdisciplinary research that advances theoretical understanding, informs practice, and addresses contemporary local, regional, and global geographical challenges.</p> <p>Published half-yearly, the journal is available in both print and electronic formats, ensuring wide accessibility to the research community.</p> https://arvinfomedia.com/myjournals/index.php/GIJGS/article/view/461 2026-10-05T06:29:28+00:00 Martina D’Amario paolo.postiglione@unich.it Alfredo Cartone paolo.postiglione@unich.it Paolo Postiglione paolo.postiglione@unich.it

<p>This study introduces a novel methodology in which a composite indicator derived using the Entropy Weight Method is decomposed into a location-specific component and a spatial component. Although EWM is widely recognized for its robustness in constructing data-driven composite indicators, standard applications typically overlook spatial information. To address this limitation, we combine EWM with spatial filtering techniques to disentangle location-specific effects from spatial spillovers, thereby improving the ability of the composite indicator to capture regional dynamics. This decomposition makes it possible to assess the relative contribution of local characteristics and spillover effects to the overall magnitude of the indicator in each region. In addition, we propose a random permutation test to evaluate the statistical significance of the spatial component. The methodology is applied to the construction of a composite indicator for education and training across 107 Italian provinces, using data from the Benessere Equo e Sostenibile (BES) dataset. The results show that the proposed approach provides policy-relevant insights that support targeted interventions and efficient resource allocation.</p>

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