The current refugees’ crisis is undermining the main government coalitions of many countries in the European Union (EU), and tolerant attitudes and open admission policies toward immigrants seem to be part of the recent past history. The dilemma is gaining a lot of media attention as the public and political debate on migration is now playing an important role in all the European elections. Thus, the aim of this paper twofold. First, an analytical tool is developed to measure two synthetic indicators: (1) the citizens’ openness towards immigration for 23 countries—18 EU Countries, plus Iceland, Israel, Norway, Switzerland, and Russia—included in the 2016 European Social Survey; and (2) the citizens’ openness towards immigrants and refugees for 22 countries (same set without Hungary). And second, the effects of political orientation of citizens over the last synthetic indicator (immigrants and refugees) are studied. The approach of Data Envelopment Analysis (DEA) will be adopted here, with the purpose of identifying which countries are more, or less, open to the phenomenon of immigration and refugees. The results show that the Nordic countries and leftist are those which show more openness to immigration and refugees.

The study analyzes national identity using the International Social Survey Program (ISSP) database for the waves of 2003 and 2013. First, the Exploratory Factor Analysis (EFA) and the Multigroup Confirmatory Factor Analysis (MGCFA) are used to find the dimensions of the items included in the national identity module. Second, the civic and ethnic dimensions are analyzed through both a fuzzy clustering analysis and an extended apostle model to classify citizens’ national identity as the following: (1) post nationalists; (2) ethnic oriented; (3) civic-oriented; (4) credentialists. Third, the fuzzy eco-extended apostle model is applied to analyze 16 different national identity categories, for which the four pure mentioned categories are further studied. Fourth, the effects of some social characteristics, such as country-year, political orientation-year, and age-year, on the respective pure national Identity categories are studied using two distinct approaches, namely, contingency tables and conditional probability ratios. Results show that citizens tend to be more pure-credentialist than any other category and that social characteristics play a determinant role in explaining each category of citizens’ national identity.

Many immigrants have risked their lives searching for a better future by crossing the Mediterranean Sea or the Atlantic Ocean. The Canary Islands became the centre of another emerging humanitarian and human rights crisis at Europe’s frontier in 2020. The study aims to analyse whether attitudes towards immigrants are affected by territories close to these humanitarian crises. To this end, the study is based on previous studies using a Fuzzy-Hybrid TOPSIS method to analyse attitudes toward immigrants. The synthetic indicator will be built upon a set of eight indicators that proxy the ethnic, economic, cultural, and religious threats experienced by the citizens. The International Social Survey Program (ISSP) dataset for the year 2013 for six countries, namely Belgium, Germany, Spain, France, United Kingdom, and Portugal, will be used. Results show that the attitude toward immigrants is affected by the territorial dimension as classified by the nomenclature of territorial units for statistics at NUTS2 and NUTS3 levels, and that attitudes are very different between those of some of the archipelagos and islands considered in the study. In particular, our results point out a sort of duality between the Balearic Islands—the most open territory toward immigrants, and Corse—the least open territory toward immigrants.

The public and political debate about immigration now play a big role in all European elections, and there is a trend increasing an anti-immigrant sentiment that receives important media attention. This work, based on the European Social Survey (ESS) round 9 data for 27 European countries, contributes to such debate by introducing a new method in the field, a Fuzzy-Hybrid Approach (FHA), that complements other methodological methods that have been used to measure citizens’ attitudes towards immigrants. The novel approach in the field provides a synthetic indicator that measures openness towards immigrants (OTISI). Then, we analyse the relationship that exists between some specific sociodemographic variables and the new index. Results show that country, political orientation, age, religion, economic situation, gender, birthplace, employment, education, universalism, and conformity are key drivers that explain different attitudes towards immigrants. Our findings concur with other previous studies showing that the results are robust and that the method can be applied in future social science studies.

The study aims to analyze the determinants for being an immigrant in Cuenca (Ecuador). Our analysis is based on the answers given to a scale formed by 30 items included in a questionnaire administered to a representative sample of 369 immigrants. A fuzzy hybrid multi-criteria decision-making method, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), is used to analyze whether immigrants are more or less exigent regarding the items included in the scale to reside in Cuenca. Then, a fuzzy clustering method is applied to analyze the differences observed in the main determinants observed over a number of traits according to their similarities to three obtained profiles: (1) extreme exigent immigrants; (2) extreme unneedful immigrants; and (3) intermediate exigent immigrants. Results show that items such as access to internet and benefits for retirees were highly valued by some immigrants. In addition, the authors found that information channels, reasons for immigrating, house location, main transport mode, income and main income source are the main determinants that differentiate whether the immigrants in Cuenca (Ecuador) are more or less demanding with respect to the exigency scale developed in the study. The main contributions to the body of knowledge, the policy implications and lines for future research are finally discussed.

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National identity studies diverge on several issues, such as the number of factors and their respective items’ adscription. Multi-Group Confirmatory Factor Analysis (MGCFA) is the standard method applied to cross-national datasets. Differences between groups can be the result of measurement artefacts. We argue that these problems can be better addressed by an alternative approach that builds a synthetic indicator named Relative National Identity Synthetic Indicator (RNISI), based on a Fuzzy Hybrid Analysis (FHA). The study aims to shed some light on the study of the latent variable national identity by comparing two methodologies: the classic method most often used (MGCFA) and the Fuzzy-Hybrid Approach, which, to our knowledge, has not been previously applied. This empirical study was based on a dataset from across ten countries using two waves (2003 and 2013) of the International Social Survey Programme (ISSP). The FHA results were compared with those obtained by two MGCFA models in which national identity was built as a second-order construct that depends on the ethnic, ancestry and civic first-order latent variables. The comparison lets us conclude that FHA can be considered a valid tool to measure the national identity by groups, and to provide additional information in form of elasticity figures. These figures can be employed to analyse the indicator’s sensitivity by group and for each of the items included in the national identity construct.

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