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841. Coevolution of Job Automation Risk and Workplace Governance

Working Paper n.841 - Settembre 2020

Filippo Belloc

DEPS, USiena

Gabriel Burdin

University of Leeds and IZA

Luca Cattani

University of Bologna

William Ellis

Indipendent Researcher

Fabio Landini

University of Parma

Abstract

In current debates about job automation, technology adoption is framed as a politics-neutral decision driven by the search for technical efficiency. Discussions about the nature of job design (i.e. the content and distribution of tasks within firms) and its associated automation risk are usually devoid of institutional context. However, job design may be affected by the way firms are governed. A critical feature of workplace governance is the extent to which decision making is shared by capital owners and workers via institutionalized forms of employee representation (ER). In this paper, we propose an evolutionary model to study the complementary fit and endogenous dynamics of job design and workplace governance. We show that two technological-political conventions are likely to emerge: in one of them workplace governance is based on ER and job designs have low automation risk; in the other, ER is absent and workers are involved in automation-prone production tasks. We explore the validity of the theory by using data from a large sample of European workers including detailed information on occupations, task environment, working conditions as well as presence of ER. Results are consistent with the theory: automation risk is negatively associated with the presence of ER. Our analysis can be useful to rationalize the historical experience of Nordic countries, where simultaneous experimentation with codetermination rights and job enrichment programs (supplemented by nationwide institutional reforms) seem to have had enduring consequences in the way these countries confront technological challenges. Policy debates about automation should avoid technological determinism and devote more attention to socio-institutional factors shaping the future of work.
 
Keywords
Automation, Job Design, Employee Representation, Evolutionary Game.
Jel Codes
J24, J51, O33