Investigating a typology of trust orientations towards national and European institutions: A person-centered approach

There is a growing recognition that trust attitudes towards national and European institutions are systematically related. Despite substantial research interest, the exact nature of this relationship remains unclear. We argue that a person-centered approach with its focus on identifying groups of individuals with similar attitudinal profiles provides a valuable complement to the currently standard variable-oriented approach in addressing this challenge. To illustrate, we examine the extent to which a prior typology of diffuse support for the European Union (EU) would emerge from a multilevel latent class analysis of the Eurobarometer data (2014). Our results provide support for the investigated typology by identifying four distinct trust profiles at the individual level that coalesce into separate latent clusters at the country level. Our findings underscore the value of a person-centered approach for the study of EU support.     

Labour market mobility and workers' skills in a comparative perspective: exploring the role of unemployment insurance benefits

This article argues that there might be important efficiency gains for countries to provide generous unemployment insurance benefits. Firstly, generous unemployment benefits might reduce the risks, real or perceived, associated with labour market transitions such as changing employer and/or career. Secondly, such benefits might increase workers' skills levels, both by functioning as a form of insurance for workers' investments in skills that are not easily transferable between employers and by facilitating the accumulation of skills that are developed through experience with different employers. These arguments are supported by empirical data, covering 14 countries, from the Eurobarometer survey.     

Rising Preferred Retirement Age in Europe: Are Europe’s Future Pensioners Adapting to Pension System Reforms?

This study investigates whether older workers have adapted their preferred retirement age to the pension reforms aimed at extending working life. Based on data from Eurobarometer and the European Social Survey in 12 European countries, the analysis shows that future pensioners have indeed increased their preferred retirement age and adjusted to the new credo of late retirement. However, the strength of the increase was found to vary between different groups of older workers: It is much stronger for the higher-educated than for the lower-educated. This finding supports recent concerns regarding the reemergence of social inequality in the retirement process.     

Bayesian networks of customer satisfaction survey data

A Bayesian network (BN) is a probabilistic graphical model that represents a set of variables and their probabilistic dependencies. Formally, BNs are directed acyclic graphs whose nodes represent variables, and whose arcs encode the conditional dependencies among the variables. Nodes can represent any kind of variable, be it a measured parameter, a latent variable, or a hypothesis. They are not restricted to represent random variables, which form the “Bayesian” aspect of a BN. Efficient algorithms exist that perform inference and learning in BNs. BNs that model sequences of variables are called dynamic BNs. In this context, [A. Harel, R. Kenett, and F. Ruggeri, Modeling web usability diagnostics on the basis of usage statistics, in Statistical Methods in eCommerce Research, W. Jank and G. Shmueli, eds., Wiley, 2008] provide a comparison between Markov Chains and BNs in the analysis of web usability from e-commerce data. A comparison of regression models, structural equation models, and BNs is presented in Anderson et al. [R.D. Anderson, R.D. Mackoy, V.B. Thompson, and G. Harrell, A bayesian network estimation of the service–profit Chain for transport service satisfaction, Decision Sciences 35(4), (2004), pp. 665–689]. In this article we apply BNs to the analysis of customer satisfaction surveys and demonstrate the potential of the approach. In particular, BNs offer advantages in implementing models of cause and effect over other statistical techniques designed primarily for testing hypotheses. Other advantages include the ability to conduct probabilistic inference for prediction and diagnostic purposes with an output that can be intuitively understood by managers.