{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:43:55Z","timestamp":1760237035677,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,2,18]],"date-time":"2020-02-18T00:00:00Z","timestamp":1581984000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>This study analyses the most appropriate methodology to make similarity classifications among the cities of the Algarve (Portugal) according to 105 sustainability indicators monitored with the Observatory of Sustainability of the Algarve Region for Tourism (OBSERVE). The methodology used to establish the similarities was the cluster analysis with 4 different approaches which reduced the dimensions of the data set: total approach, pillar approach, subject area approach, and indicator approach. By combining the approaches, a total of 620 different cluster analyses were performed. The results reflected that the data analysis approaches with less dimensions were those that performed the best groups among cities. In this sense, the approaches with a high number of indicators (e.g., the total or the pillar approach) were characterised by misclassifying cities in more than 30% of the indicators. Thus, the most acceptable cluster analysis approach was that with a low number of indicators. Through this approach, it was possible to make correct groups of the sustainability level of the cities of the Algarve. These results provided an appropriate methodology for the decision-making regarding the sustainability of a region and could be extrapolated to other regions to assess sustainability or environmental indicators.<\/jats:p>","DOI":"10.3390\/su12041536","type":"journal-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T10:49:16Z","timestamp":1582282156000},"page":"1536","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Challenge for Planning by Using Cluster Methodology: The Case Study of the Algarve Region"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0716-8589","authenticated-orcid":false,"given":"David","family":"Bienvenido-Huertas","sequence":"first","affiliation":[{"name":"Department of Building Construction II, University of Seville, Av. Reina Mercedes 4A, 41012 Seville, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2056-6453","authenticated-orcid":false,"given":"F\u00e1tima","family":"Farinha","sequence":"additional","affiliation":[{"name":"University of Algarve, Institute of Engineering, Campus da Penha, 8005-139 Faro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3042-0802","authenticated-orcid":false,"given":"Miguel Jos\u00e9","family":"Oliveira","sequence":"additional","affiliation":[{"name":"University of Algarve, Institute of Engineering, Campus da Penha, 8005-139 Faro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0037-2798","authenticated-orcid":false,"given":"Elisa M. J.","family":"Silva","sequence":"additional","affiliation":[{"name":"University of Algarve, Institute of Engineering, Campus da Penha, 8005-139 Faro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7753-3767","authenticated-orcid":false,"given":"Rui","family":"Lan\u00e7a","sequence":"additional","affiliation":[{"name":"University of Algarve, Institute of Engineering, Campus da Penha, 8005-139 Faro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1016\/j.scs.2018.10.009","article-title":"The Lisbon ranking for smart sustainable cities in Europe","volume":"44","author":"Akande","year":"2019","journal-title":"Sustain. 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