Abstract
A richer approach to studying Decision Support System (DSS) interactions is required to understand and predict the nature of actual use in the workplace. We used questionnaire and interview techniques to examine workers’ experiences relating to DSS use in naturalistic settings. We aimed to: 1) Reveal what workers perceive to be the most important factors when deciding whether to accept support from a DSS and 2) Elicit patterns that emerge from DSS users’ recounted experiences using the systems, which may impact their future use. Current and prospective DSS users (N = 93) from numerous industries responded to a questionnaire relating to the factors they perceive to influence their use of DSSs. Subsequently, a retrospective interview protocol was employed to investigate the experiences of a subset of DSS users (N = 10). The questionnaire results underscore a range of factors considered to be very important to the acceptance of DSSs (i.e. decision quality; decision importance; decision risk; historical accuracy; decision accountability; and system comprehension). Further, a series of interconnected themes relating to workers’ use of DSSs were identified from the interview transcripts using thematic analysis. We discuss how these issues may impact workers’ intentions to use DSSs in the workplace, and advocate for the use of naturalistic decision-making techniques to study technology acceptance.
Original language | English |
---|---|
Pages (from-to) | 332-350 |
Number of pages | 19 |
Journal | Journal of Cognitive Engineering and Decision Making |
Volume | 17 |
Issue number | 4 |
Early online date | 7 Aug 2023 |
DOIs | |
Publication status | Published - Dec 2023 |
Bibliographical note
Copyright Human Factors and Ergonomics Society 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- decision support system
- naturalistic decision-making
- technology acceptance
- critical decision method