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

Abstract

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.

Urban-Rural Dichotomy of Quality of Life

“…There are many QOL measurements at the global level, as well as at the level of European countries, drawing data from Eurostat, European Social Survey, and the European Values Study [1][2][3]. Our own measurements are published by the OECD or The Economist Intelligence Unit.…”

“…The OECD [14] has changed its approach in view of the large differences in the population criterion necessary for classifying a municipality as urban. It proposed a population density criterion of 150 inhabitants per km 2 . It divided the regions into three categories:…”

Calidad del empleo creado en las cooperativas y sociedades laborales en la recuperación económica 2013-2016. Análisis del caso de España

“…La calidad laboral no sólo presenta la dificultad de la especificación de las dimensiones o áreas que comprende dicho concepto, sino que también se enfrenta a un segundo nivel de conceptualización y delimitación dentro de cada dimensión. En este sentido, en el caso de la dimensión socioeconómica, tampoco existe una única delimitación de los aspectos a incluir, si bien hay coincidencia en diferentes investigaciones empíricas al incluir variables relativas al salario y otras retribuciones, al tipo de jornada laboral, a la duración de los contratos, aspectos relacionados con la conciliación o con la formación y cualificación (una revisión sistemática de esta literatura se encuentra en Stepana et al, 2021). Los indicadores estadísticos asociados a las áreas incluidas en el indicador de calidad vienen determinados por la disponibilidad dentro de las fuentes de información utilizadas en cada propuesta.…”

“…Con respecto a la primera etapa, el marco teórico desarrollado (Santero-Sánchez et al, 2015, Muñoz de Bustillo et al, 2011, Stepana et al, 2021 sienta las bases conceptuales para la inclusión de los indicadores individuales, cuya selección final también está determinada por la disponibilidad de información estadística, detallada en el siguiente apartado (base de datos). La normalización incluye todas las conversiones requeridas no sólo para homogeneizar las unidades de medida, sino también para asegurar que los valores de los indicadores individuales no se compensan entre ellos.…”

COINr: An R package for developing composite indicators

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Composite indicators (CIs) are aggregations of indicators that aim to measure complex, multidimensional and typically socio-economic concepts such as sustainable development (Conceição, 2020), innovation (Dutta et al, 2020), globalisation (William Becker et al, 2021), gender equality (Equal Measures 2030, and many more. CIs are very widely used in policymaking, by international organisations, and they are equally well-covered in academic literature (El Gibari et al, 2019;David Lindén et al, 2021;Stefana et al, 2021). They are often used to rank and benchmark countries or regions to help direct policy making, but are also frequently used for advocacy (Cobham et al, 2015).The COINr package, introduced in this article, aims to provide a harmonised development environment for composite indicators that includes all common operations from indicator selection, data treatment and imputation up to aggregation, presentation of results and sensitivity analysis.

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