Despite the large number of contributions on happiness at work, accurate measures are still missing. In this realm, our study investigates the influence of happiness drivers in the workplace, considering the core elements related to both hedonia and eudaimonia, on the most commonly used outcome variable in the management literature that analyses happiness, i.e., the sum of positive feelings. We first explored the drivers of happiness using categorical PCA to find the latent dimensions able to summarize original variability. Then, we analyzed their configuration within a binary regression framework to identify their relative contribution in predicting the probability of employee happiness.

Measuring happiness at work with categorical Principal Component Analysis / Kocollari, Ulpiana; Cavicchioli, Maddalena; Demaria, Fabio. - (2022), pp. 1143-1148. ((Intervento presentato al convegno SIS 2022 - 51th Scientific Meeting of the Italian Statistical Society tenutosi a Caserta, Italy nel 22-24 giugno 2022.

Measuring happiness at work with categorical Principal Component Analysis

kocollari ulpiana;cavicchioli maddalena;demaria fabio
2022

Abstract

Despite the large number of contributions on happiness at work, accurate measures are still missing. In this realm, our study investigates the influence of happiness drivers in the workplace, considering the core elements related to both hedonia and eudaimonia, on the most commonly used outcome variable in the management literature that analyses happiness, i.e., the sum of positive feelings. We first explored the drivers of happiness using categorical PCA to find the latent dimensions able to summarize original variability. Then, we analyzed their configuration within a binary regression framework to identify their relative contribution in predicting the probability of employee happiness.
SIS 2022 - 51th Scientific Meeting of the Italian Statistical Society
Caserta, Italy
22-24 giugno 2022
1143
1148
Kocollari, Ulpiana; Cavicchioli, Maddalena; Demaria, Fabio
Measuring happiness at work with categorical Principal Component Analysis / Kocollari, Ulpiana; Cavicchioli, Maddalena; Demaria, Fabio. - (2022), pp. 1143-1148. ((Intervento presentato al convegno SIS 2022 - 51th Scientific Meeting of the Italian Statistical Society tenutosi a Caserta, Italy nel 22-24 giugno 2022.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1280738
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