Platformised digital agriculture and technostress: implications for psychosocial occupational safety and health

D. Manzoni and M. Černič Istenič*

The Research Centre of the Slovenian Academy of Sciences and Arts, Sociomedical Institute, Novi trg 2, SI-1000 Ljubljana, Slovenia
*Correspondence: majda.cernic-istenic@zrc-sazu.si

Abstract:

Digitalisation in agriculture is increasingly structured through platformisation: daily work is mediated by interconnected sensors, dashboards, notification pipelines, and vendor-governed service ecosystems. While automation and data-driven management can reduce physical workload and enable more flexible work organisation, platform-mediated arrangements may also increase psychosocial occupational safety and health (OSH) risks by reshaping temporality, interpretive responsibility, predictability, and practical agency. This article aims to explain how platform-mediated arrangements in digital agriculture generate technostress-related psychosocial OSH demands and to identify design and governance levers that may mitigate these risks in welfare- and time-critical settings. The study presents a theory-guided integrative review (narrative synthesis) using empirical ‘evidence anchors’; it is not a meta-analysis and does not provide pooled effect estimates, prevalence measures, or sector-wide quantitative inference. From a prior systematic review corpus, eleven scholarly sources (2004–2023) – primarily on automatic milking systems and related monitoring infrastructures – were selected and synthesised to identify recurring sociotechnical arrangements. The analysis yields a platform-architecture model linking work reorganisation to technostress appraisals clustered around four patterns: (1) availability pressures under always-on monitoring, (2) interpretive burden under opaque outputs and epistemic asymmetry, (3) constrained agency under proprietary service and update pathways, and (4) intensified self-evaluation under metricised dashboards. Framing technostress as an upstream outcome of platform-mediated work organisation clarifies why psychosocial OSH cannot be addressed through individual adaptation alone: risk depends on how platform design and governance allocate urgency, distribute uncertainty, and shape access to expertise, support, and repair. The article therefore proposes contestability – users’ capacity to inspect, adjust, and stabilise platform mechanisms – as a practical mitigation principle for OSH-sensitive digitalisation.

Key words:

automatic milking systems, digital agriculture, monitoring infrastructures, platformisation, psychosocial OSH, technostress

Studies of Operating Parameters in Milking Robots With Selectively Guided Cow Traffic

A. Laurs and J. Priekulis

Institute of Agricultural Engineering, Latvia University of Agriculture,
J. Cakstes bulv. 5, Jelgava, LV-3001, Latvia;
e-mail: armins.laurs@promedia.lv; Juris.Priekulis@ llu.lv

Abstract:

Milking robots have been launched on Latvian dairy farms only recently. As the technology differs essentially from that of traditional milking, with the introduction of new technology a range of questions has arisen that have not been topical before. For instance, there has been uncertainty about determining the optimal size of the group of milk cows for robots as well as about planning the robot location and the waiting box.

On installing robots in reconstructed barns, it came out that it was not possible to stick to the designs offered by the companies, and after milking the cows were not sent to the barns but back to the waiting box. As a result, the milked cows had a chance to visit the robots repeatedly. Therefore, a question arose – how much does the repeated visiting of robots influence the effective load.

Moreover, there has been uncertainty about the correct location for the robot in relation to the waiting box using several robots. It was observed that usually in such a case one robot is visited more than the other.

The present research tries to answer these recurring questions. The research results showed that the optimal size of the group of cows served by one robot depends on the average milking time and the time necessary for washing the milk line. If the cows return to the waiting box after milking, the effective load of the robot decreases. The location of the robot in the waiting box in relation to the entrance gate essentially influences the number of visiting one or the other robot per day.

Key words: