Measuring the quality of work: the case of the Italian social cooperatives

Proposal of a composite indicator of job quality based on a measure of weighted distances

“…In this case, job quality is measured by a unique indicator, based on the output, that is, the well-being of the worker at her/his job (Crandall 1976 ). The subjective quality of work has become a major subject of study and discussion in labour economics within a short time (Carpita and Golia 2012 ;Clark 2001Clark , 2005Gazioglu and Tansel 2006 ;Levy-Garboua et al 2007 ). On the other hand, job satisfaction has been shown to be an inadequate indicator of job quality.…”

“…Information on single individuals can be collected as a quantitative variable but also as a dichotomous or ordinal variable. While a considerable number techniques have been proposed for the aggregation of variables of the same nature in a CI (factor analysis for quantitative variables, e.g., in Susmilch and Johnsons ( 1975 ) or item response theory or rating scale models for ordinal variables, e.g., in Baker ( 1992 ) or Carpita and Golia ( 2012 ), respectively), less attention has been paid to the case of mixed data. The solutions that are often adopted are to either convert all of the variables to the same scale (such as dichotomous variables) or to quantify ordinal variables.…”

The GME estimator for the regression model with a composite indicator as explanatory variable

“…The dataset used derives from the I C S I 2007 (Indagine sulle Cooperative Sociali Italiane, 2007), a survey about social cooperatives sampled from the Istat-Census 2003 database of the Italian National Institute of Statistics, with paid workers that in 2007 answered the questionnaire designed by academic experts in economic and organisation fields with the aim to investigate the objective and subjective quality of work in the non-profit sector (Carpita and Golia 2012;Ciavolino and Nitti 2013). For this application we regress the Y = Wage Satisfaction, measured on a 7 points scale, on the composite indicator (ξ ), obtained as average of J = 4 items, measured through a 5 points Likert-type scale: X 1 = Responsibility; X 2 = Effort; X 3 = Stress; X 4 = Loyalty.…”

Treating ordinal data: a comparison between rating scale and structural equation models

“…The worker JS is often used as a proxy of the quality of work and represents one of its facets. It allows one to evaluate the subjective level of benefit gained from the working activity (Carpita and Golia 2012;Carpita and Vezzoli 2012). Fairness can be observed in relation to diverse aspects of work; here we consider the procedural fairness.…”

“…Fairness can be observed in relation to diverse aspects of work; here we consider the procedural fairness. It focuses on workers fairness judgments of the procedures used in determining outcomes (Carpita and Golia 2012). The original questionnaires were composed by 10 (JS) and 8 (PPF) items on a 10 points Likert scale, reported in Table 1.…”