Adapting to the Agricultural Labor Market Shaped by Robotization

Vasso Marinoudi, Lefteris Benos, Carolina Camacho Villa, Maria Lampridi, Dimitrios Kateris (), Remigio Berruto, Simon Pearson, Claus Grøn Sørensen and Dionysis Bochtis
Additional contact information
Vasso Marinoudi: Lincoln Institute for Agri-Food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK
Lefteris Benos: Institute for Bio-Economy and Agri-Technology (IBO), Centre of Research and Technology-Hellas (CERTH), 57001 Thessaloniki, Greece
Carolina Camacho Villa: Lincoln Institute for Agri-Food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK
Maria Lampridi: farmB Digital Agriculture S.A., Dekatis Evdomis (17th) Noemvriou 79, 55534 Thessaloniki, Greece
Dimitrios Kateris: Institute for Bio-Economy and Agri-Technology (IBO), Centre of Research and Technology-Hellas (CERTH), 57001 Thessaloniki, Greece
Remigio Berruto: Interuniversity Department of Regional and Urban Studies and Planning, Viale Matttioli 39, 10125 Torino, Italy
Simon Pearson: Lincoln Institute for Agri-Food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK
Claus Grøn Sørensen: Department of Electrical and Computer Engineering, Aarhus University, DK-8000 Aarhus, Denmark
Dionysis Bochtis: farmB Digital Agriculture S.A., Dekatis Evdomis (17th) Noemvriou 79, 55534 Thessaloniki, Greece

Sustainability, 2024, vol. 16, issue 16, 1-20

Abstract: Agriculture is being transformed through automation and robotics to improve efficiency and reduce production costs. However, this transformation poses risks of job loss, particularly for low-skilled workers, as automation decreases the need for human labor. To adapt, the workforce must acquire new qualifications to collaborate with automated systems or shift to roles that leverage their unique human abilities. In this study, 15 agricultural occupations were methodically mapped in a cognitive/manual versus routine/non-routine two-dimensional space. Subsequently, each occupation’s susceptibility to robotization was assessed based on the readiness level of existing technologies that can automate specific tasks and the relative importance of these tasks in the occupation’s execution. The qualifications required for occupations less impacted by robotization were summarized, detailing the specific knowledge, skills, and work styles required to effectively integrate the emerging technologies. It was deduced that occupations involving primary manual routine tasks exhibited the highest susceptibility rate, whereas occupations with non-routine tasks showed lower susceptibility. To thrive in this evolving landscape, a strategic combination of STEM (science, technology, engineering, and mathematics) skills with essential management, soft skills, and interdisciplinary competences is imperative. Finally, this research stresses the importance of strategic preparation by policymakers and educational systems to cultivate key competencies, including digital literacy, that foster resilience, inclusivity, and sustainability in the sector.

Keywords: Occupational Information Network (O*NET) system; process automation; technological substitution/complementarity; agricultural workforce capacity-building (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/16/7061/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/16/7061/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:16:p:7061-:d:1458241

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().