Smart Working: Bayesian Insights and Beyond.

Purpose – This research investigates how smart working contributes to sustainable development and organisational resilience, aligning with select United Nations Sustainable Development Goals. Design/methodology/approach – Drawing on 964 respondents from small and medium-sized Italian enterprises, this study employs Bayesian Structural Equation Modeling to examine the interconnections between smart working, organisational resilience, employee well-being, and sustainability outcomes. Findings – The results show a strong positive relationship between organisational resilience and the adoption of smart working. Implementing smart working enhances employee work-life balance and productivity, lowers commuting costs, and reduces resource consumption, contributing to economic and environmental sustainability. Research limitations/implications – The generalisability of this study is constrained by its Italian sample and cross-sectional methodology. Future research should address these limitations by examining long-term environmental effects, comparing hybrid and fully remote models, and extending analyses to diverse industries and international landscapes. Originality/value – Using Bayesian Structural Equation Modelling, this study reveals the importance of robust digital infrastructure, agile management, and supportive policymaking in maximising the sustainability and resilience benefits of remote work contributing to key Sustainable Development Goals.