The effect of individual and task characteristics on decision aid reliance
Abstract
This research explores reliance behaviours of decision-makers using a decision aid. Objective and subjective task characteristics in the form of task complexity and task difficulty, respectively, are examined, along with the effect of the individual characteristic of expertise. A total of 130 subjects (65 novices and 65 experienced practitioners) completed a lab experiment using a decision aid (Insolve-DG) to help them make decisions for two insolvency tasks with differing levels of complexity. The research finds that the objective task characteristic (task complexity) and individual characteristic (expertise) both affect reliance behaviours; however, their effects are fully mediated by the subjective task characteristic (task difficulty). Expertise and task complexity are both associated with the degree of task difficulty experienced by an individual user: increasing task complexity increases task difficulty, and increasing expertise reduces task difficulty. Task difficulty and task complexity are established as different constructs; and importantly it is task difficulty, not task complexity, that ultimately affects reliance.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The complexity of a task can elevate its perceived difficulty, potentially resulting in greater reliance on AI systems.
“This is further backed by [100] indicating that the complexity of a task can elevate its perceived difculty, potentially resulting in greater reliance on AI systems.”
From Dealing with Uncertainty: Understanding the Impact of Prognostic Versus Diagnostic Tasks on Trust and Reliance in Human-AI Decision Making (2024) · cites this paper as [100]
Greater user reliance on decision aids occurs when a task is more difficult.
“This hypothesis is informed by previous work that showed greater user reliance on decision aids when a task is more difficult [7,57].”
From Understanding User Reliance on AI in Assisted Decision-Making (2022) · cites this paper as [57]
Prior work [57] also showed that the higher the level of expertise the participant has in the task, the smaller the effect of task difficulty on user reliance.
“The prior work also showed the higher the level of expertise the participant has in the task, the smaller the effect of task difficulty on user reliance.”
From Understanding User Reliance on AI in Assisted Decision-Making (2022) · cites this paper as [57]
Prior work [57] showed that increase in task complexity and difficulty heightens reliance.
“This finding contradicts the results from prior work [57], which showed that increase in task complexity and difficulty heightens reliance.”
From Understanding User Reliance on AI in Assisted Decision-Making (2022) · cites this paper as [57]
Cites
Preacher, K. J., & Hayes, A. F. (2008) · Behavior Research Methods · doi:10.3758/brm.40.3.879 · Cited by 34,117 · see citing works
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709 · see citing works
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006 · see citing works
Chase, W. G., & Simon, H. A. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90004-2 · Cited by 4,479 · see citing works
(1991) · Choice Reviews Online · doi:10.5860/choice.28-5376 · Cited by 4,217 · see citing works
Mathieson, K. (1991) · Information Systems Research · doi:10.1287/isre.2.3.173 · Cited by 4,216 · see citing works
EXPERT AND EXCEPTIONAL PERFORMANCE: Evidence of Maximal Adaptation to Task Constraints
Ericsson, K. A., & Lehmann, A. C. (1996) · Annual Review of Psychology · doi:10.1146/annurev.psych.47.1.273 · Cited by 2,139 · see citing works
The robust beauty of improper linear models in decision making.
Dawes, R. M. (1979) · American Psychologist · doi:10.1037/0003-066x.34.7.571 · Cited by 1,970 · see citing works
(1991) · Cited by 1,767 · see citing works
Bhattacherjee, A., & Premkumar, G. (2004) · MIS Quarterly · doi:10.2307/25148634 · Cited by 1,764 · see citing works
Measuring and Assessing Organizations.
Price, J. L., de Ven, A. H. V., & Ferry, D. L. (1981) · Administrative Science Quarterly · doi:10.2307/2392488 · Cited by 1,642 · see citing works
Task Complexity: A Review and Analysis
Campbell, D. J. (1988) · The Academy of Management Review · doi:10.5465/amr.1988.4306775 · Cited by 1,634 · see citing works
Order effects in belief updating: The belief-adjustment model
Hogarth, R. M., & Einhorn, H. J. (1992) · Cognitive Psychology · doi:10.1016/0010-0285(92)90002-j · Cited by 1,596 · see citing works
Task complexity: Definition of the construct
Wood, R. E. (1986) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(86)90044-0 · Cited by 1,393 · see citing works
Surpassing Ourselves: An Inquiry into the Nature and Implications of Expertise
Bereiter, C., & Scardamalia, M. (1993) · Medical Entomology and Zoology · Cited by 1,366 · see citing works
Venkatesh, V., Thong, J. Y. L., Chan, F. K. Y., Hu, P. J.-H., & Brown, S. A. (2011) · Information Systems Journal · doi:10.1111/j.1365-2575.2011.00373.x · Cited by 852 · see citing works
Johnson, E. J., & Payne, J. W. (1985) · Management Science · doi:10.1287/mnsc.31.4.395 · Cited by 839 · see citing works
Vinkhuyzen, R. E., Verschure, P. F. M. J., & Newell, A. (1994) · The American Journal of Psychology · doi:10.2307/1422886 · Cited by 831 · see citing works
Behavioral research in accounting
Section, O. (1989) · Medical Entomology and Zoology · Cited by 747 · see citing works
A Task Contingent Model of Work-Unit Structure
de Ven, A. H. V., & Delbecq, A. L. (1974) · Administrative Science Quarterly · doi:10.2307/2393888 · Cited by 352 · see citing works
Evaluating the Impact of DSS, Cognitive Effort, and Incentives on Strategy Selection
Todd, P., & Benbasat, I. (1999) · Information Systems Research · doi:10.1287/isre.10.4.356 · Cited by 312 · see citing works
Effects of Objective and Subjective Task Complexity on Performance
Maynard, D. C., & Hakel, M. D. (1997) · Human Performance · doi:10.1207/s15327043hup1004_1 · Cited by 249 · see citing works
Effects of justification and a mechanical aid on judgment performance
Ashton, R. H. (1992) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(92)90040-e · Cited by 245 · see citing works
Decision Support Systems: Directed and Nondirected Change
Silver, M. S. (1990) · Information Systems Research · doi:10.1287/isre.1.1.47 · Cited by 212 · see citing works
Feedback Specificity, Exploration, and Learning.
Goodman, J. S., Wood, R. E., & Hendrickx, M. (2004) · Journal of Applied Psychology · doi:10.1037/0021-9010.89.2.248 · Cited by 201 · see citing works
Predicting the continued use of Internet-based learning technologies: the role of habit
Limayem, M., & Cheung, C. M. K. (2011) · Behaviour & Information Technology · doi:10.1080/0144929x.2010.490956 · Cited by 191 · see citing works
Arnol'd, �. �., Clark, Collier, P. A., Leech, & Sutton, S. G. (2006) · MIS Quarterly · doi:10.2307/25148718 · Cited by 166 · see citing works
Bolt, M. A., Killough, L. N., & Koh, H. C. (2001) · Decision Sciences · doi:10.1111/j.1540-5915.2001.tb00951.x · Cited by 158 · see citing works
Impact of intelligent decision aids on expert and novice decision‐makers’ judgments
Arnold, V., Collier, P. A., Leech, S. A., & Sutton, S. G. (2004) · Accounting and Finance · doi:10.1111/j.1467-629x.2004.00099.x · Cited by 126 · see citing works
Mackay, J. M., & Elam, J. J. (1992) · Information Systems Research · doi:10.1287/isre.3.2.150 · Cited by 118 · see citing works
Parkes, A. (2012) · Decision Support Systems · doi:10.1016/j.dss.2012.10.025 · Cited by 110 · see citing works
Self-citationArnold, V., Collier, P. A., Leech, S. A., et al. (2000) · Accounting and Finance · doi:10.1111/1467-629x.00039 · Cited by 87 · see citing works
Information systems and performance: the role of technology, the task and the individual
Bravo, E., Santana, M., & Rodón, J. (2014) · Behaviour and Information Technology · doi:10.1080/0144929x.2014.934287 · Cited by 51 · see citing works
Kaplan, S. E., Reneau, J. H., & Whitecotton, S. M. (2001) · Journal of Behavioral Decision Making · doi:10.1002/1099-0771(200101)14:1 · Cited by 49 · see citing works
Determinants of reliance: An empirical test of the theory of technology dominance
Hampton, C. (2005) · International Journal of Accounting Information Systems · doi:10.1016/j.accinf.2005.10.001 · Cited by 48 · see citing works
Chan, S. H., Song, Q., & Yao, L. J. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.04.059 · Cited by 43 · see citing works
Explanation provision and use in an intelligent decision aid
Arnold, V., Clark, N., Collier, P. A., et al. (2004) · Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management · doi:10.1002/isaf.222 · Cited by 41 · see citing works
The effect of task complexity and expert system type on the acquisition of procedural knowledge
Mascha, M. F. (2001) · International Journal of Accounting Information Systems · doi:10.1016/s1467-0895(01)00016-1 · Cited by 36 · see citing works
Anderson, J., Jennings, M. M., Kaplan, S. E., & Reckers, P. M. J. (1995) · Journal of Accounting and Public Policy · doi:10.1016/0278-4254(94)00021-r · Cited by 36 · see citing works
Mascha, M. F., & Smedley, G. (2007) · International Journal of Accounting Information Systems · doi:10.1016/j.accinf.2007.03.001 · Cited by 35 · see citing works
Sonderegger, A., Sauer, J., & Eichenberger, J. (2013) · Behaviour and Information Technology · doi:10.1080/0144929x.2013.853835 · Cited by 34 · see citing works
A validated expert system for decision making in corporate recovery
Collier, P. A., Leech, S. A., & Clark, N. (1999) · Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management · doi:10.1002/(sici)1099-1174(199906)8:2 · Cited by 25 · see citing works
A generalized model of decision-making processes for companies in financial distress
Leech, S. A., Clark, N., & Collier, P. A. (1999) · Accounting Forum · doi:10.1111/1467-6303.00009 · Cited by 20 · see citing works
Information Systems Foundations: Theory, Representation and Reality
Hart, D., & Gregor, S. D. (2007) · ANU Press eBooks · doi:10.22459/isftrr.11.2007 · Cited by 20 · see citing works
Advances in Accounting Behavioral Research
Arnold, V. (2008) · Advances in accounting behavioral research · doi:10.1016/s1475-1488(2008)11 · Cited by 16 · see citing works
A Model of Audit Judgment: Cognition in a Professional Context
Anderson, U. L., Koonce, L. L., & Marchant, G. (1991) · Recent research in psychology · doi:10.1007/978-1-4612-3190-5_3 · Cited by 7 · see citing works
King, V. A. (1989) · Medical Entomology and Zoology · Cited by 5 · see citing works
Performance with information technology : individual fit and reliance on decision support systems
Davern, M. J. (1999) · Medical Entomology and Zoology · Cited by 4 · see citing works
Advances in Accounting Behavioural Research
(2014) · Advances in accounting behavioral research · doi:10.1108/aabr · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Understanding User Reliance on AI in Assisted Decision-Making
Cao, S., & Huang, C.-M. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555572 · Cited by 71 · see citing works
How Time Pressure in Different Phases of Decision-Making Influences Human-AI Collaboration
Cao, S., Gomez, C., & Huang, C.-M. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3610068 · Cited by 48 · see citing works
Salimzadeh, S., He, G., & Gadiraju, U. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641905 · Cited by 41 · see citing works
“This is further backed by [100] indicating that the complexity of a task can elevate its perceived difculty, potentially resulting in greater reliance on AI systems.”
BackgroundResultZhang, Z. T., Buchner, F., Liu, Y., & Butz, A. (2024) · Proceedings of Mensch und Computer 2024 · doi:10.1145/3670653.3670660 · Cited by 6 · see citing works
Raees, M., Khan, V.-J., Lykourentzou, I., & Papangelis, K. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791467 · Cited by 5 · see citing works
- Authors
- Parkes, A.
- Affiliations
- The University of Melbourne (AU)
- Corresponding author
- Parkes, Alison
- ORCID
- Parkes, Alison
- Venue
- Behaviour & Information Technology
- Publisher
- Informa UK Limited
- Published
- 2016-08-22
- Volume
- 36
- Issue
- 2
- Pages
- 165-177
- ISSN
- 0144-929X (ISSN-L)
- 1362-3001
- OpenAlex
- W2513928524
- Cited by
- 26
- References
- 49
- Citations by year
- 2026: 5 · 2025: 2 · 2024: 6 · 2023: 4 · 2022: 3 · 2021: 2 · 2020: 3 · 2019: 1
- FWCI
- 0.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Behaviour and Information Technology (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Decision Support System Applications
- Keywords
- decision support system, task complexity, task difficulty, expertise, mediation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
