Employment Quality: Are There Differences by Types of Contract?

Muñoz, José María Arranz; García‐Serrano, Carlos; Hernanz, Virginia

doi:10.1007/s11205-017-1586-4

Cited by 23 publications

(25 citation statements)

References 27 publications

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“…In this context, researchers have used composite indicators not only to represent urban inequality [4,5], but also to represent its different dimensions. For example, it is possible to indicate socioeconomic [6,27,28], neighborhood [7,29], and household inequalities [8,30], among others [31,32]. The present research focuses both on the general representation of urban inequality and on its dimensions.…”

Section: Urban Inequalitymentioning

confidence: 99%

“…This limitation means that intra-urban inequality composite indicators constructed from methods based on aggregation and weighting (e.g., see [4,5]) do not capture the effects among the underlying dimensions of the inequality. Such methods do not allow for consideration of the influence that indicators have on each other, such as socioeconomic [6], neighborhood [7], and household [8] inequalities.…”

Section: Introductionmentioning

confidence: 99%

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Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator

et al. 2020

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Composite indicators are almost always determined by methods that aggregate a reasonable number of manifest variables that can be weighted—or not—as new synthesis variables. A problem arises when these aggregations and weightings do not capture the possible effects that the various underlying dimensions of the phenomenon have on each other, and consequently distort the assessment of intra-urban inequality. In this paper, we explore the direct and indirect effects that the different underlying dimensions of intra-urban inequality have on indicators that represent this phenomenon. Structural equation modeling was used to build a composite indicator that captures the direct and indirect effects of the underlying dimensions of intra-urban inequality. From this modeling that combines confirmatory factor analysis with a system of simultaneous equations, the intra-urban inequality of the urban conurbation of Maringá–Sarandi–Paiçandu, Brazil was measured. The model comprises first- and second-order structures. The first-order structure is composed of non-observed variables that represent three underlying dimensions of intra-urban inequality. The second-order structure is the intra-urban inequality composite indicator that synthesizes the non-observed variables of the first-order structure. The model aims at demonstrating how to perform a theorized measurement of urban inequality so that it makes it possible to identify which dimensions most influence the others, as well as which dimensions are more relevant to this purpose.

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Section: Urban Inequalitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator

et al. 2020

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“…The most recent papers (i.e. Arranz et al, 2018;Warren & Lyonette, 2018) are published in these two journals.…”

Section: Resultsmentioning

confidence: 99%

Composite Indicators to Measure Quality of Working Life in Europe: A Systematic Review

et al. 2021

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In the last two decades, Quality of Working Life (QWL) has become a core element of the European social model and the European Employment Strategy. “More and better jobs” is a strategic goal promoted within Europe for emphasising the attention in QWL. However, there is a large debate in the literature on the definition of QWL, its dimensions, and consequently on the methods to use for its measurement. To the best of our knowledge, the systematic reviews currently available in the literature on QWL measurement in European organisations investigate only a particular industry and/or working population. Moreover, they do not focus specifically on composite indicators, although they appear promising in facilitating QWL understanding and comparisons for supporting decision-makers and policy makers. To overcome these gaps, we conducted a systematic review to identify composite indicators for measuring QWL in European organisations. The review returned 19 studies that are analysed based on a set of factors related to QWL locutions, index name, geographical area, industry or population, level of analysis, dimensions, type of data, inputs, outputs, and test and/or validation. The results highlight a significant heterogeneity among the indicators, confirming the lack of an agreed upon QWL composite indicator for Europe. Such heterogeneity concerns also QWL dimensions. A critical comparison of the different composite indicators is provided, along with a unifying proposal of QWL macro-dimensions. Several gaps in the literature are pointed out suggesting directions for future research.

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“…Yet, although these three dimensions have represented the basic core of precariousness dimensions, more recent research has focused on new dimensions of precarious employment. Thus, as a matter of example, Evans and Gibb (2009), McKay et al (2012), OECD (2015, and Arranz et al (2018) open the range of factors to other characteristics of employment (related, among others, to the excessive prolongation of the working day, hazardous work, at night or on weekends, the absence of training received in the company, the relationship with the controls or the flexibility, and ability to predict schedules) showing, in short, the lack of consensus in the literature about what characteristics make up a precarious job.…”

Section: General Literaturementioning

confidence: 99%

“…In particular, they examine how precarious employment is affected by new forms of contracts derived from the flexibilization under legislative changes (Tangian, 2008;Burroni and Keune, 2011;OECD, 2015); the generalization of subcontracting and outsourcing (Perulli, 2003;Evans and Gibb, 2009); and the effect of economic crises through increased unemployment (Kretsos, 2010). In a similar vein, they analyse the effect of belonging to specific groups such as young people (Bradley and van Hoof, 2005;Kretsos, 2010); women (Fudge and Owens, 2006;Bradley and Healy, 2008;Sheen, 2010); workers hired through temporary employment agencies (Elcioglu, 2010;Arranz et al, 2018); older workers (D'Amours, 2010); immigrants (Bhalla and McCorick, 2009;Porthé et al, 2010); or employees in certain sectors (Perulli, 2003;Ross, 2009). International comparisons of employment precariousness are, on the other hand, rather scarce.…”

Section: General Literaturementioning

confidence: 99%

Multidimensional measurement of precarious employment using hedonic weights: Evidence from Spain

Pérez

Alaiz

Simón

2020

Journal of Business Research

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This article examines employment precariousness in Spain based on multidimensional precarious measures in the framework of the counting approach proposed by Foster (2007 and. The methodological novelty of our approach consists of the use of hedonic weights derived from the subjective evaluation of the determinants of job satisfaction by employees for the selection and the quantification of the influence of the dimensions of jobs that make up multidimensional precariousness indices from the perspective of low-quality jobs. The evidence obtained confirms that the precariousness of the employment created in Spain intensified significantly in the aftermath of the economic crisis and intense labour reforms. Moreover, it suggests that although the temporary nature of employment is the most salient component of employment precariousness from a multidimensional perspective, a broad set of job attributes negatively associated with job satisfaction should be considered in the multidimensional measurement of employment precariousness.

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Employment Quality: Are There Differences by Types of Contract?

Cited by 23 publications

References 27 publications

Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator

Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator

Composite Indicators to Measure Quality of Working Life in Europe: A Systematic Review

Multidimensional measurement of precarious employment using hedonic weights: Evidence from Spain

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