Effort as investment in healthcare dialogue-based agents: On the role of means-goal configurations

The recent pandemic and resultant increase in clinical caseload have brought dialogue-based agents (DBAs) to the forefront of attention in the healthcare industry. The ability of these agents to accomplish a variety of sequential and related tasks within a single application software has made them more effortful and complex. While effort requirements and complexity of information systems are generally considered negative attributes, the potential effect of user effort investment on user perceptions and decisions is less investigated. Within the framework of goal systems theory, this study explores how perceived effort could be appropriated to enhance users' positive perceptions and willingness to accept healthcare DBAs outputs. We find evidence for the positive role both in the perceived effort before and after the actual use of healthcare DBAs as well as in user goal magnitude and means-goal configuration on perceptions of usefulness and probability of considering outputs. •Perceived effort is treated as a distinct variable from perceived complexity.•User perceived effort indirectly boosts users' positive perception of healthcare DBAs.•“Counterfinality” is introduced as a mechanism to explain users' adoption of healthcare DBAs.•Users' goal magnitude plays a significant role in the adoption of healthcare DBA.