Emergence of technostress among employees working with physical robots
Lampi, A., Salo, M., Venermo, K., & Pirkkalainen, H. (2023). Emergence of technostress among employees working with physical robots. In ECIS 2023 : Proceedings of the 31st European Conference on Information Systems, Kristiansand, Norway, June 11.-16.6.2023 (Article 395). Association for Information Systems. https://aisel.aisnet.org/ecis2023_rp/395
Date
2023Discipline
TietojärjestelmätiedeValue Creation for Cyber-Physical Systems and ServicesInformation Systems ScienceValue Creation for Cyber-Physical Systems and ServicesCopyright
© Association for Information Systems
Despite the growing body of literature on technostress, there is limited knowledge about the emergence of technostress among people working with physical robots. In this paper, we aim to address this research gap by exploring how technostress emerges among employees working with physical robots. The study was based on qualitative online questionnaire responses from 197 present or previous users of robots at work. Based on our data, we identified several robot-related environmental conditions that contributed to perceived work-related stress. Our findings reveal that the emergence of technostress among employees working with physical robots has distinct characteristics and that the technostressors identified in previous studies are insufficient for explaining stress in this context. Therefore, our study extends the technostress literature and provides insights into employees’ experiences in organizations that use physical robots.
Publisher
Association for Information SystemsConference
European Conference on Information SystemsIs part of publication
ECIS 2023 : Proceedings of the 31st European Conference on Information Systems, Kristiansand, Norway, June 11.-16.6.2023ISSN Search the Publication Forum
2184-1934Keywords
Original source
https://aisel.aisnet.org/ecis2023_rp/395Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/183210549
Metadata
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Related funder(s)
Academy of FinlandFunding program(s)
Academy Research Fellow, AoF
Additional information about funding
This research has been funded by the Emil Aaltonen Foundation and the Academy of Finland (341359).License
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