Search

A widespread rhetoric suggests that market-like rules dominate employment relationships, and particularly compensation, but empirical evidence is inconclusive. This research examines organisations’ compensation policies in clusters of European capitalist economies to test such a hypothesis. Four fuzzy clusters emerged from data, namely, Standard, Internalised, Competitive and Incentive, which illustrates a division between organisation- and market-based models. Collective pay rules characterise organisation-based model, and this is the predominant model in all countries except for the liberal market economies. Firms from different models of capitalism rely on internal labour market pay rules, suggesting that the scope of the liberal market system is narrow. Differences within clusters of capitalist economies suggest a role for agency and hidden labour market specificities in each grouping. The similarities of pay policies open room to identifying capitalist economies differently.

This study illustrates the complexities involved in outsourcing domestic work to the market. It draws on an original dataset of paid domestic workers in Portugal to examine how specific tasks inter...

This paper examines online job advertisements to identify the type of skills and other attributes required for higher education graduates in European countries. The data were collected from European job websites in 2019 (n=1,752) for any country and occupation having a job offer requiring higher education. The empirical analysis starts with a fuzzy clustering to identify typical skill patterns required by employers. Six clusters emerge from the data; five can be labelled as adaptability skills, foreign languages, specific skills, work attributes, and managing skills. The remaining one is referred to as null cluster with no distinctive required skill. Subsequently, we examine the occupation and employment conditions associated with each fuzzy cluster. Despite the demand for graduates, the service and sales related occupations prevail in the null cluster. In other five well-defined clusters we find a mix of skills of some high-qualified occupations, and search for specific skills acquired through work experience.The findings raise the question about the assignment of graduates in less qualified occupations. info:eu-repo/semantics/publishedVersion

Increasing public transport use is recognized by many countries as crucial to the pursuit of a global strategy for environmental sustainability and improving urban mobility. Understanding what users value in a public transport service is essential to carry out this strategy. Using fuzzy clustering, we developed an index that measures individual user satisfaction with the public transport service in the metropolitan area of Lisbon and subsequently identified the possible determinants of satisfaction by means of a regression tree model. The results achieved unveil a hierarchical partition of the data, highlighting the diversified level of satisfaction among public transport users that is reflected in the distribution of the index. The managerial implications of the findings for the public transport service are addressed. info:eu-repo/semantics/publishedVersion

Firms respond differently to labour market regulations and develop an employment relationship accordingly. We use linked employer–employee data to examine the relationship between compensation poli...

We empirically illustrate how concepts and methods involved in a grade of membership (GoM) analysis can be used to sort individuals by competence. Our study relies on a data set compiled from the international survey on higher education graduates called REFLEX. We focus on the subset of data related to the perception of own competencies. It is first decomposed into fuzzy clusters that form a hierarchical fuzzy partition. Then, we calculate a scalar measure of competencies for each fuzzy cluster, and subsequently use the individual GoM scores to combine cluster-based competencies to position individuals on a scale from 0 to 1.

Measures of stock of skills alternative to human capital have raised fresh difficulties, especially in data managing. We propose to empirically compare the efficiency of a hierarchical cluster analysis and a fuzzy clustering in reducing discrete skill data. The outcomes of both methods are subsequently used to measure the impact of skills on earnings in addition to human capital. The proposed methodological comparison was made using an original dataset of retail bankers’ skills assessed by supervisors. Empirical evidence shows that the fuzzy approach is more efficient than the hierarchical clustering: the resulting clusters are fewer and easier to interpret. Furthermore, the earnings equation enriched with skill variables allowed us to correct the education premium, and provides information on monetary incentives related to individual skills. Our paper attempts to raise researchers’ and practitioners’ awareness of data reducing methods, and their implications for wage determinants. First published online:29 May 2015

The profit-oriented financial sector has grown in importance and influence, leading some authors to talk about a financialised economy. The question we raise in this paper is what is the role of non-profit oriented financial institutions and public programmes in the microfinance segment. We conclude that in this market there is a large diversity of institutions and non-for profit organisations have a significant role. Our analysis also shows that the diversity of institutional forms is important to foster market dimension, guarantee a good cover of the several vulnerable groups and a diversified offer of other services besides microcredit. Moreover, some specific institutions have an effect on the composition of the market in terms of personal and business loans, on loans terms, loans size, credit to targeted clients, and offer of other financial services. Moreover, we study how financial institutions cluster around some key variables. Finally, we fuzzy cluster microcredit national markets and describe how institutions types differ across the clusters.

The research on wage policies has been triggered by the interest in identifying whether labour market or institutional forces shape wage settings inside firms. This article draws on linked employer-employee data and uses a fuzzy c-means clustering analysis to identify the typical wage policies of medium and large firms in Portugal. Empirical evidence suggests firms are segmented into four clusters that can be labelled according to wage rules as regulated, asymmetric, hierarchical and discretionary. The first two clusters comprise low wage firms, and are highly responsive to market conditions. The firms belonging to the latter clusters take advantage of discretionary power to differentiate the workforce. Our findings therefore illustrate different dimensions of wage flexibility. Furthermore, we found that employment flexibility and wage adjustments can co-exist, and this affects female, young and blue-collar workers in particular.

WOS:000297169900021 (Nº de Acesso Web of Science) New approaches in economics of education consider the concept of competence to bringing in the multidimensional feature of labour force quality. Competence includes knowledge, skills, behaviours and attitudes. Each individual suits the combination of these elements to perform a task. Thus, different combinations expectedly lead to different task performance inside an occupation. In this paper, we focus on individual heterogeneity in homogeneous job requirements context. In sequel, we establish a theorem on unit simplex that potentially provides a ranking system by competence. The system is designed under a grade of membership framework, with a technique based on fuzzy sets theory. Under certain conditions, the referred theorem allows a mapping of individual multidimensional feature into the interval [0, 1]. So, the greater the value along this interval, the more competent the individual. An empirical study of a banking sector activity illustrates our research.