Tesi etd-12232025-193442
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Tipo di tesi
Dottorato
Autore
SCROFANI, STEFANIA
URN
etd-12232025-193442
Titolo
Digital Transformation in Industry and Public Administration
Settore scientifico disciplinare
SECS-P/02
Corso di studi
Istituto di Economia - PHD IN ECONOMICS
Relatori
relatore Prof. MINA, ANDREA
Parole chiave
- Nessuna parola chiave trovata
Data inizio appello
05/06/2026;
Disponibilità
parziale
Riassunto analitico
This thesis provides a comprehensive analysis of the antecedents and consequences of digital transformation in both private and public sector organisations, analysing its drivers, implementation patterns, and economic consequences. Grounded in the economics of innovation and technology and innovation management literature, this dissertation employs micro-econometric methods to investigate how policy interventions shape technology adoption, how digitalisation influences labour productivity and organisational resilience to external shocks, and how leadership characteristics determine the pace of digital adoption in public administration.
The thesis is structured into three empirical chapters preceded by a brief introduction and with concluding remarks synthesizing the main findings and their implications.
Chapter 1 evaluates the 2017 Italian Industry 4.0 Plan, a horizontal fiscal policy designed to incentivise the adoption of Industry 4.0 technologies through tax credits and super-depreciation schemes. We develop an innovative identification strategy exploiting firms' financial statements to identify beneficiaries across Italian firms. Employing a difference-in-differences methodology, the analysis demonstrates that the fiscal incentives and subsequent adoption of Industry 4.0 technologies generate substantial gains in labour productivity. However, these effects exhibit considerable heterogeneity across firm size, industrial sectors, and types of incentives received. The findings reveal the limitations of neutral, horizontal policies in stimulating technology adoption among smaller and less dynamic firms, suggesting that more targeted interventions are necessary to accelerate digital transformation and sustain productivity growth.
Chapter 2 investigates whether prior adoption of digital technologies enhances firm resilience to exogenous shocks, using the COVID-19 pandemic as a natural experiment. Leveraging granular administrative data on technology adoption patterns, we assess the causal effect of pre-crisis digitalisation on firm performance during the pandemic using difference-in-differences combined with propensity score matching techniques. The results indicate that resilience benefits materialise primarily when firms adopt bundles of complementary technologies rather than isolated digital technologies. Furthermore, substantial sectoral heterogeneity emerges: manufacturing firms derive resilience predominantly from robotics, while service sector firms require integrated technological ecosystems centred on big data analytics. This chapter advances existing literature by explicitly incorporating technological complementarities and sectoral specificities into the analysis of resilience.
Chapter 3 extends the investigation to public sector organisations. Integrating Upper Echelons Theory with the Diffusion of Innovation framework, we examine how mayors' characteristics influence digital technology adoption in Italian municipalities. The analysis focuses on the adoption between 2012 and 2021 of the PagoPA platform, a milestone in the digital transformation of Italian Public Administration. The study reveals that mayors with digital skills acquired through prior professional experience significantly increase adoption likelihood. Additionally, homophily between mayors and Regions’ President promotes innovation, but only when moderated by municipal employees' human capital, thereby reconciling contradictory evidence on homophily's role in innovation adoption. Mayors’ tenure exhibits an inverted U-shaped relationship with adoption, reflecting the trade-off between accumulated experience and inertia.
In conclusion, this thesis underscores the multifaceted drivers of digital adoption, spanning policy design, technological complementarities, and leadership attributes, while revealing persistent heterogeneities. By integrating micro-econometric evidence with different theoretical backgrounds, it contributes to the debate on innovation diffusion and technology impact, while offering actionable insights for practitioners and policy-makers.
The thesis is structured into three empirical chapters preceded by a brief introduction and with concluding remarks synthesizing the main findings and their implications.
Chapter 1 evaluates the 2017 Italian Industry 4.0 Plan, a horizontal fiscal policy designed to incentivise the adoption of Industry 4.0 technologies through tax credits and super-depreciation schemes. We develop an innovative identification strategy exploiting firms' financial statements to identify beneficiaries across Italian firms. Employing a difference-in-differences methodology, the analysis demonstrates that the fiscal incentives and subsequent adoption of Industry 4.0 technologies generate substantial gains in labour productivity. However, these effects exhibit considerable heterogeneity across firm size, industrial sectors, and types of incentives received. The findings reveal the limitations of neutral, horizontal policies in stimulating technology adoption among smaller and less dynamic firms, suggesting that more targeted interventions are necessary to accelerate digital transformation and sustain productivity growth.
Chapter 2 investigates whether prior adoption of digital technologies enhances firm resilience to exogenous shocks, using the COVID-19 pandemic as a natural experiment. Leveraging granular administrative data on technology adoption patterns, we assess the causal effect of pre-crisis digitalisation on firm performance during the pandemic using difference-in-differences combined with propensity score matching techniques. The results indicate that resilience benefits materialise primarily when firms adopt bundles of complementary technologies rather than isolated digital technologies. Furthermore, substantial sectoral heterogeneity emerges: manufacturing firms derive resilience predominantly from robotics, while service sector firms require integrated technological ecosystems centred on big data analytics. This chapter advances existing literature by explicitly incorporating technological complementarities and sectoral specificities into the analysis of resilience.
Chapter 3 extends the investigation to public sector organisations. Integrating Upper Echelons Theory with the Diffusion of Innovation framework, we examine how mayors' characteristics influence digital technology adoption in Italian municipalities. The analysis focuses on the adoption between 2012 and 2021 of the PagoPA platform, a milestone in the digital transformation of Italian Public Administration. The study reveals that mayors with digital skills acquired through prior professional experience significantly increase adoption likelihood. Additionally, homophily between mayors and Regions’ President promotes innovation, but only when moderated by municipal employees' human capital, thereby reconciling contradictory evidence on homophily's role in innovation adoption. Mayors’ tenure exhibits an inverted U-shaped relationship with adoption, reflecting the trade-off between accumulated experience and inertia.
In conclusion, this thesis underscores the multifaceted drivers of digital adoption, spanning policy design, technological complementarities, and leadership attributes, while revealing persistent heterogeneities. By integrating micro-econometric evidence with different theoretical backgrounds, it contributes to the debate on innovation diffusion and technology impact, while offering actionable insights for practitioners and policy-makers.
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