Do automation and AI impact on job reduction? A study on perceived risk of losing job among white-collars in the Italian manufacturing companies

Abstract

AbstractThe risk of losing one's job is surely among the most common risks, especially considering the progress of automation and artificial intelligence brought by the so-called fourth industrial revolution. Previous studies have focused on the measurement of the perception of this risk at large or the risk of losing job at blue-collars level, while this study, instead, aims at specifically focusing on the risk perceived by white-collar workers employed in Italian manufacturing companies. We investigated whether and to what extent the main job-related characteristics – age, education, department, position in the organization chart, and company size – can influence the perceived fear of losing one's job. We used an on-line questionnaire involving 302 white-collar respondents, modelling the predictors and the outcome using logistic regression. The findings show, in general, an optimistic point of view from the respondents and a statistically significant correlation between the kind of department, the kind of job and the size of the company and the perceived risk. The inquiry was also conducted through a qualitative analysis of the comments left by the respondents, uncovering traces of the phenomena that could have affected the optimistic and pessimistic points of view.Keywords: Automationartificial intelligenceindustry 4.0job lossWhite-Collars Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsAndrea ChiariniAndrea Chiarini is a Professor of Operations Management at University of Verona – Italy. He has been a consultant and trainer to a range of manufacturing and service firms on Lean Six Sigma, TQM and Industry 4.0. Along with other partners he set up in Italy a consulting firm dedicated to Lean Production, Six Sigma, IATF 16949, Industry 4.0 and Management Accounting. He has taught in post-Graduate courses and short courses for Executives. Senior Member of the American Society for Quality (ASQ), he serves as Associate Editor for the journal Business Strategy and the Environment, and he is in the editorial boards of Production Planning & Control, Journal of Manufacturing Technology Management, TQM Journal, and International Journal of Lean Six Sigma.Alberto GrandoAlberto Grando is a Professor of Operations Management at Bocconi University, Milan – Italy, where he teaches Operations Management, Sustainable Operations Management and Innovation and Technology Management. He is also Professor of Production & Supply Chain Management at the Operations and Technology Management Unit of SDA Bocconi School of Management. His research interests are operations performances measurement, supply chain management, logistics and production management.Sergio VenturiniSergio Venturini is an Associate Professor of Statistics in the Department of Economic and Social Sciences at the Università Cattolica del Sacro Cuore (Italy). His research interests include Bayesian data analysis methods, meta-analysis, and statistical computing. He co-authored many publications that have been published in different refereed international journals such as Annals of Applied Statistics, Bayesian Analysis and Journal of Statistical Software.Emanuele BorgonovoEmanuele Borgonovo is a Full Professor and Director of the Department of Decision Sciences at Bocconi University – Milan, Italy. Co-editor-in-Chief of the European Journal of Operational Research, President 2020–2022 of the Decision Analysis Society of INFORMS, member of the Scientific Committee of the Silvio Tronchetti Provera Foundation. PhD at the Massachusetts Institute of Technology. MSc in Nuclear Engineering with core in Mathematics and Physics from Politecnico di Milano, Italy. Recipient of several national and international awards, his research is at the basis of new methods for sensitivity analysis in fields ranging from Machine Learning to risk assessment.