Quaderni IRCrES 25 – Capitolo 6
Capitolo 6
Verso strumenti decisionali per l’equilibrio vita‑lavoro dei lavoratori maturi: un modello integrato basato su reti neurali artificiali*
Towards decision-making tools for the work-life balance of mature workers: an integrated model based on artificial neural networks
Donatella Bramanti(a), Luisa Errichiello(b), Greta Falavigna(c), Sara Nanetti(a)
(a) Università Cattolica del Sacro Cuore, Dipartimento di Sociologia, Largo A. Gemelli 1, 20123, Milano, Italia.
(b) CNR-ISMed,Consiglio Nazionale delle Ricerche – Istituto di Studi sul Mediterraneo, via Cardinale Guglielmo
Sanfelice, 8, 80134 Napoli, Italia
(c) CNR-IRCrES, Consiglio Nazionale delle Ricerche – Istituto di Ricerca sulla Crescita Economica Sostenibile, strada
delle Cacce 73, 10135 Torino, Italia
corresponding authors: donatella.bramanti@unicatt.it; luisa.errichiello@cnr.it; greta.falavigna@cnr.it; sara.nanetti@unicatt.it
Abstract
In recent decades, population ageing has become a defining shift across Europe, forcing a rethink of welfare and pension systems at both national and EU levels. While data unequivocally document the trend, public perception lags. Many resist its practical consequence – the postponement of retirement – which keeps people in the labour market longer. Ageing also intersects with health and care dynamics. Longer life does not always mean healthier later life; functional decline increases vulnerability and care needs. At the same time, older people face rising family responsibilities, from grandchild care to support for very old parents, intensifying their social and domestic workload. These pressures make it crucial to improve older workers’ work-life balance (WLB) and to understand how WLB shapes retirement timing. Yet research often treats these domains separately and seldom yields actionable tools. We propose an integrated evidence-to-design approach that links WLB determinants with retirement push/pull dynamics among Italian seniors. Using an original 2024-2025 survey of Italian workers aged 55+, measuring working conditions, WLB, retirement intentions, and bonding/bridging social capital, we: (i) quantify the determinants of WLB and the push/pull factors influencing retirement; (ii) develop a pilot AI module that profiles WLB-dissatisfaction classes and ranks class-specific drivers; and (iii) outline a web-based tool that translates evidence into class-specific policy portfolios. Findings indicate that policy should shift from one-size-fits-all to targeted bundles. The proposed tool helps managers and policymakers both raise older workers’ satisfaction and allocate resources efficiently. Next steps include embedding retirement push/pull directly into a multi-task ANN, expanding stratification by industry and region, and performing external and temporal validation.
Keywords: older workers; work-life balance, retirement push/pull factors; social capital; artificial neural networks; policy design.
DOI: 10.23760/2499-6661.2026.25_06
ISBN: 978-88-98193-40-0
ISSN (online): 2499-6661
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How to Cite
Bramanti, D., Errichiello, L., Falavigna, G., & Nanetti, S. (2026). Verso strumenti decisionali per l’equilibrio vita‑lavoro dei lavoratori maturi: un modello integrato basato su reti neurali artificiali. In D’Ascenzio, A., Errichiello, L., Falavigna, G., & Lamonica, V. (cur.). Mercato del lavoro e relazioni sociali dopo i 50. Riflessioni e politiche per il benessere in una società che invecchia (pp. 127-141). Quaderni
IRCrES 25. CNR-IRCrES. http://dx.doi.org/10.23760/2499-6661.2026.25_06
* Questo lavoro è stato realizzato nell’ambito del progetto finanziato da Next Generation EU – “Age-It – Ageing well in an ageing society” (PE0000015), CUP B83C22004880006 – Piano Nazionale di Ripresa e Resilienza (PNRR) – PE8 – Missione 4, Componente 2, Investimento 1.3. Le opinioni espresse sono esclusivamente degli autori e non riflettono necessariamente quelle dell’Unione Europea o della Commissione Europea. Né l’Unione Europea né la Commissione Europea possono essere ritenute responsabili dei contenuti qui riportati.