Automation technologies such as industrial robots, artificial intelligence, and big data analytics threaten to dislocate a large number of workers, given their ability to perform many work activities. This thesis aims to give a complete overview of the effects of automation on employment and consists of three papers. The first paper reviews prior studies investigating how automation technologies affect employment. Relevant publications are presented by distinguishing how the effects of automation technologies are estimated (i.e., estimation of the probability of automation or of the net impact on employment), the levels of analysis (i.e., global, international, continental, country, regional, labour market, industry, firm, occupational, worker, and work activities) and the type of automation technology (i.e., industrial robots, artificial intelligence, and big data analytics). Research gaps and future research agenda are identified. The second paper investigates how the institutional context in terms of gender equality (in general and in the education and work components) affects the risk of substitution faced by women, i.e., their risk of being replaced by automation technologies in performing work activities. The study shows that in institutional contexts where gender equality is high, women face a lower risk of substitution as women do not face stereotypes and structural barriers and can thus acquire the skills that cannot be automated by machines (i.e., perception and manipulation, creative intelligence, and social intelligence). The third paper analyses how the invention of automation technologies affects the labour demand of the innovative firm. It emerges that innovating in automation technologies increases firm employment, with the largest impact found for industrial robots and big data. Jointly innovating in the three automation technologies also increases firm employment. However, innovating in industrial robots decreases firm employment in SMEs, while innovating in industrial robots and in artificial intelligence decreases firm employment in young firms. This thesis enhances knowledge about automation by providing a review of previous studies, by developing a gender perspective on automation by taking into account the influence of the institutional context in terms of gender equality, and by focusing on firm level effects of automation technologies. Policy and managerial implications can be derived from this thesis as the results provide an insight into how automation technologies impact employment. Policy makers can be informed for the design of policies promoting the invention and adoption of automation technologies and removing gender barriers in education and in the labour market. Firms can evaluate the effects of automation technologies on their workforce and help workers in protecting against the risk of substitution. The necessary interventions at the national and firm level can be planned to reap the benefits of automation while safeguarding workers.

Automation and its impact on occupations and employment

Filippi, Emilia
2023

Abstract

Automation technologies such as industrial robots, artificial intelligence, and big data analytics threaten to dislocate a large number of workers, given their ability to perform many work activities. This thesis aims to give a complete overview of the effects of automation on employment and consists of three papers. The first paper reviews prior studies investigating how automation technologies affect employment. Relevant publications are presented by distinguishing how the effects of automation technologies are estimated (i.e., estimation of the probability of automation or of the net impact on employment), the levels of analysis (i.e., global, international, continental, country, regional, labour market, industry, firm, occupational, worker, and work activities) and the type of automation technology (i.e., industrial robots, artificial intelligence, and big data analytics). Research gaps and future research agenda are identified. The second paper investigates how the institutional context in terms of gender equality (in general and in the education and work components) affects the risk of substitution faced by women, i.e., their risk of being replaced by automation technologies in performing work activities. The study shows that in institutional contexts where gender equality is high, women face a lower risk of substitution as women do not face stereotypes and structural barriers and can thus acquire the skills that cannot be automated by machines (i.e., perception and manipulation, creative intelligence, and social intelligence). The third paper analyses how the invention of automation technologies affects the labour demand of the innovative firm. It emerges that innovating in automation technologies increases firm employment, with the largest impact found for industrial robots and big data. Jointly innovating in the three automation technologies also increases firm employment. However, innovating in industrial robots decreases firm employment in SMEs, while innovating in industrial robots and in artificial intelligence decreases firm employment in young firms. This thesis enhances knowledge about automation by providing a review of previous studies, by developing a gender perspective on automation by taking into account the influence of the institutional context in terms of gender equality, and by focusing on firm level effects of automation technologies. Policy and managerial implications can be derived from this thesis as the results provide an insight into how automation technologies impact employment. Policy makers can be informed for the design of policies promoting the invention and adoption of automation technologies and removing gender barriers in education and in the labour market. Firms can evaluate the effects of automation technologies on their workforce and help workers in protecting against the risk of substitution. The necessary interventions at the national and firm level can be planned to reap the benefits of automation while safeguarding workers.
16-mar-2023
Inglese
Trento, Sandro
Università degli studi di Trento
TRENTO
208
File in questo prodotto:
File Dimensione Formato  
Emilia Filippi - Ph.D. thesis.pdf

embargo fino al 16/03/2025

Dimensione 2.61 MB
Formato Adobe PDF
2.61 MB Adobe PDF

I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/60151
Il codice NBN di questa tesi è URN:NBN:IT:UNITN-60151