Introducing digital technologies in the factory: determinants of blue-collar workers’ attitudes towards new robotic tools

Nora Hampel, Kai Sassenberg, Annika Scholl and Matthias Reichenbach

Behaviour and Information Technology, 2022, vol. 41, issue 14, 2973-2987

Abstract: In the context of blue-collar work, digital technologies and robotic systems are introduced at a rapid speed. However, employees are not always motivated to adopt such new technologies. Thus, it is essential to understand the drivers of employees’ attitudes towards new technology at work (e.g. their enthusiasm about new technology or their insecurity or resistance to change). The present study examines (actual and desired) work characteristics as a predictor of attitudes towards new technology in blue-collar work. Results from a correlational study among blue-collar workers (N = 127) showed that work characteristics among blue-collar workers could be divided into three dimensions, namely, work enrichment, work demands, and task identity. These correlated with attitudes towards a to-be-implemented new technology (here, robotic system): As expected, desired work demands correlated with greater technology enthusiasm, whereas a lack of actual work enrichment predicted technology-based job insecurity. Work characteristics were unrelated to user resistance to change. The findings suggest that how workers evaluate their current work, and how much they are (dis)satisfied with it, predicts attitudes towards new technology. This research adds to the knowledge about attitudes towards new technology in blue-collar work. Practical implications for the implementation of technologies in blue-collar work are discussed.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2021.1967448 (text/html)
Access to full text is restricted to subscribers.

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:taf:tbitxx:v:41:y:2022:i:14:p:2973-2987

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2021.1967448

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().