Persuasiveness of expert systems

Dijkstra, Jaap J.; Liebrand, Wim B. G.; Timminga, Ellen

doi:10.1080/014492998119526

Cited by 161Human-Automation Interaction and SafetyUsability and User Interface DesignPsychology of Social Influence

Persuasiveness of expert systems

Open access

Dijkstra, Jaap J., Liebrand, Wim B. G., Timminga, Ellen·1998·Behaviour & Information Technology

DOI 10.1080/014492998119526

Open this paper in CoChat — free account Open PDF

Abstract

Expert system advice is not always evaluated by examining its contents. Users can be persuaded by expert system advice because they have certain beliefs about advice given by a computer. The experiment in this paper shows that subjects (n = 84) thought that, given the same argumentation, expert systems are more objective and rational than human advisers. Furthermore, subjects thought a problem was easier when advice on it was said to be given by an expert system while the advice was shown in production rule style. Such beliefs can influence expert system use.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1080/014492998119526

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

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?

Reported behaviors include both a skepticism or distrust of algorithmic advice (algorithmic aversion) and more willingness to adhere to algorithmic advice over human advice (algorithmic appreciation).
“Reported behaviors include both a skepticism or distrust of algorithmic advice (algorithmic aversion)12–14 and more willingness to adhere to algorithmic advice over human advice (algorithmic appreciation)15,16.”
From Do as AI say: susceptibility in deployment of clinical decision-aids (2021) · cites this paper as [16]
The cited paper bears on the algorithmic-appreciation part of the sentence, not the separately cited aversion part. Its Results (§3.1, page unavailable) and Conclusions (§4, page unavailable) say that subjects rated expert-system advice as more objective and rational than human advice, but did not show greater compliance with it; the small compliance effect varied by case. Thus it does not support greater willingness to adhere to algorithmic advice over human advice. (LLM, conf=0.87)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · 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
The Elaboration Likelihood Model of Persuasion
Petty, R. E., & Cacioppo, J. T. (1986) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(08)60214-2 · Cited by 8,822 · see citing works
“The Need for Cognition.”
Cacioppo, J. T., & Petty, R. E. (1982) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.42.1.116 · Cited by 5,359 · see citing works
Communication and Persuasion: Central and Peripheral Routes to Attitude Change
Marquart, F., & Naderer, B. (2015) · Springer eBooks · doi:10.1007/978-3-658-09923-7_20 · Cited by 5,007 · see citing works
User acceptance of information technology: system characteristics, user perceptions and behavioral impacts
Davis, F. D. (1993) · International Journal of Man-Machine Studies · doi:10.1006/imms.1993.1022 · Cited by 4,754 · see citing works
The Efficient Assessment of Need for Cognition
Cacioppo, J. T., Petty, R. E., & Feng Kao, C. (1984) · Journal of Personality Assessment · doi:10.1207/s15327752jpa4803_13 · Cited by 2,913 · see citing works
The measurement of user information satisfaction
Ives, B., Olson, M. H., & Baroudi, J. J. (1983) · Communications of the ACM · doi:10.1145/358413.358430 · Cited by 1,830 · see citing works
Persuasion theory and research
O’Keefe, D. J. (1990) · Cited by 1,555 · see citing works
Explaining the Role of User Participation in Information System Use
Hartwick, J., & Barki, H. (1994) · Management Science · doi:10.1287/mnsc.40.4.440 · Cited by 1,540 · see citing works
Measuring User Participation, User Involvement, and User Attitude
Barki, H., & Hartwick, J. (1994) · MIS Quarterly · doi:10.2307/249610 · Cited by 898 · see citing works
An empirical study of the impact of user involvement on system usage and information satisfaction
Baroudi, J. J., Olson, M. H., & Ives, B. (1986) · Communications of the ACM · doi:10.1145/5666.5669 · Cited by 894 · see citing works
A Theoretical Assessment of the User-Satisfaction Construct in Information Systems Research
Melone, N. P. (1990) · Management Science · doi:10.1287/mnsc.36.1.76 · Cited by 705 · see citing works
Early Diagnosis of MIS Implementation Failure: Promising Results and Unanswered Questions
Ginzberg, M. J. (1981) · Management Science · doi:10.1287/mnsc.27.4.459 · Cited by 631 · see citing works
Rethinking the Concept of User Involvement
Barki, H., & Hartwick, J. (1989) · MIS Quarterly · doi:10.2307/248700 · Cited by 613 · see citing works
Alternative Measures of System Effectiveness: Associations and Implications
Srinivasan, A. (1985) · MIS Quarterly · doi:10.2307/248951 · Cited by 537 · see citing works
Usefulness and ease of use: field study evidence regarding task considerations
Keil, M., Beranek, P. M., & Konsynski, B. R. (1995) · Decision Support Systems · doi:10.1016/0167-9236(94)e0032-m · Cited by 430 · see citing works
User acceptance of microcomputer technology: An empirical test
Igbaria, M. (1993) · Omega · doi:10.1016/0305-0483(93)90040-r · Cited by 419 · see citing works
The Use of Information in Decision Making: An Experimental Investigation of the Impact of Computer-Based Decision Aids
Todd, P., & Benbasat, I. (1992) · MIS Quarterly · doi:10.2307/249534 · Cited by 390 · see citing works
The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology
Igbaria, M., Schiffman, S. J., & Wieckowski, T. J. (1994) · Behaviour and Information Technology · doi:10.1080/01449299408914616 · Cited by 373 · see citing works
Some Cautions on the Measurement of User Information Satisfaction*
Galletta, D. F., & Lederer, A. L. (1989) · Decision Sciences · doi:10.1111/j.1540-5915.1989.tb01558.x · Cited by 348 · see citing works
Source Attributions and Persuasion: Perceived Honesty as a Determinant of Message Scrutiny
Priester, J. R., & Petty, R. E. (1995) · Personality and Social Psychology Bulletin · doi:10.1177/0146167295216010 · Cited by 347 · see citing works
The Impact of Explanation Facilities on User Acceptance of Expert Systems Advice
Ye, L. R., & Johnson, P. E. (1995) · MIS Quarterly · doi:10.2307/249686 · Cited by 290 · see citing works
Is user satisfaction a valid measure of system effectiveness?
Gatian, A. W. (1994) · Information & Management · doi:10.1016/0378-7206(94)90036-1 · Cited by 272 · see citing works
Understanding Social Psychology
Jacobs, H., Worchel, S., Cooper, J., & Goethals, G. R. (1989) · Teaching Sociology · doi:10.2307/1317953 · Cited by 228 · see citing works
AN EMPIRICAL ASSESSMENT OF COMPUTER‐ASSISTED DECISION ANALYSIS*
Aldag, R. J., & Power, D. (1986) · Decision Sciences · doi:10.1111/j.1540-5915.1986.tb00243.x · Cited by 198 · see citing works
Correlates of user satisfaction with end user computing
Igbaria, M., & Nachman, S. A. (1990) · Information & Management · doi:10.1016/0378-7206(90)90017-c · Cited by 179 · see citing works
The Influence of Decision Aids on Choice Strategies: An Experimental Analysis of the Role of Cognitive Effort
Todd, P., & Benbasat, I. (1994) · Organizational Behavior and Human Decision Processes · doi:10.1006/obhd.1994.1074 · Cited by 170 · see citing works
Determining information system usage: Some issues and examples
Szajna, B. (1993) · Information & Management · doi:10.1016/0378-7206(93)90037-t · Cited by 105 · see citing works
User information satisfaction: IS implementability and effectiveness
Iivari, J., & Ervasti, I. (1994) · Information & Management · doi:10.1016/0378-7206(94)90049-3 · Cited by 94 · see citing works
Computer-Assisted Decision Making: Performance, Beliefs, and the Illusion of Control
Kottemann, J. E., Davis, F. D., & Remus, W. (1994) · Organizational Behavior and Human Decision Processes · doi:10.1006/obhd.1994.1002 · Cited by 91 · see citing works
Discretionary use of personal computers by knowledge workers: testing of a social psychology theoretical model
PARE, G., & ELAM, J. J. (1995) · Behaviour & Information Technology · doi:10.1080/01449299508914635 · Cited by 84 · see citing works
Alternating Least Squares Algorithms for Simultaneous Components Analysis with Equal Component Weight Matrices in Two or More Populations
Kiers, H. A. L., & ten Berge, J. M. F. (1989) · Psychometrika · doi:10.1007/bf02294629 · Cited by 83 · see citing works
The influence of decision aids on choice strategies under conditions of high cognitive load
Todd, P., & Benbasat, I. (1994) · IEEE Transactions on Systems Man and Cybernetics · doi:10.1109/21.286376 · Cited by 67 · see citing works
Harmful effects of seemingly helpful information on forecasts of stock earnings
Davis, F. D., Lohse, G. L., & Kottemann, J. E. (1994) · Journal of Economic Psychology · doi:10.1016/0167-4870(94)90003-5 · Cited by 64 · see citing works
Experience with a structure, process and outcome framework for evaluating an information system
Cornford, T., Doukidis, G., & Forster, D. (1994) · Omega · doi:10.1016/0305-0483(94)90030-2 · Cited by 60 · see citing works
Evidence and principles of functional and dysfunctional DSS
Kottemann, J. E., & Remus, W. (1987) · Omega · doi:10.1016/0305-0483(87)90028-4 · Cited by 26 · see citing works
Using human factor guidelines for developing expert systems
Suh, C., & Suh, E. (1993) · Expert Systems · doi:10.1111/j.1468-0394.1993.tb00091.x · Cited by 16 · see citing works
Man-Made Minds: The Promise of Artificial Intelligence
Waldrop, M. M. (1987) · Cited by 13 · see citing works
User responsibility and exception handling in decision support systems
Chen, Z. (1992) · Decision Support Systems · doi:10.1016/0167-9236(92)90045-q · Cited by 12 · see citing works
Individual differences in the performance and use of an expert system
Will, R. P. (1992) · International Journal of Man-Machine Studies · doi:10.1016/0020-7373(92)90084-x · Cited by 8 · see citing works
A model for justification production by expert planning systems
Bridges, S. M. (1995) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1995.1062 · Cited by 4 · see citing works

Flagged first, then by citations

1 of the 43 references couldn’t be matched to a known paper.

Research works printed but not linked: 6

[7]7. BODEN, M. 1990, Artificial intelligence and images of man, in R. Ennals and J. Gardin (eds), Interpretation in the Humanities: Perspectives from Artificial Intelligence (Cam- bridge: Cambridge University Press), 10-21.
[17]17. DIJKSTRA, J. J. 1995, The influence of an expert system on the user's view: How to fool a lawyer. New Review of Applied Expert Systems, 1, 123 -138.
[22]22. HOLLNAGEL, E. 1989, The reliability of expert systems-an inquiry of the background, in E. Hollnagel (ed.), The Reliability of Expert Systems (Sussex: Ellis Horwood), 14 - 32.
[41]41. ROBEY, D. 1979, User attitude and management information system use. Academy of Management Journal, 22, 527-538.
[50]50. WOGNUM, P. M. 1990, Explanation of Automated Reasoning: How and Why?, Ph.D. dissertation, University of Twente.
[51]51. WORCHEL, S., COOPER, J. and GOETHALS, G. R. 1988, Under- standing Social Psychology (Chicago: Dorsey Press).

Sorted by citations

Algorithm appreciation: People prefer algorithmic to human judgment
Logg, J. M., Minson, J. A., & Moore, D. A. (2019) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2018.12.005 · Cited by 2,061 · see citing works
The role of trust in automation reliance
Dzindolet, M. T., Peterson, S. A., Pomranky, R. A., Pierce, L. G., & Beck, H. P. (2003) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(03)00038-7 · Cited by 1,276 · see citing works
In AI we trust? Perceptions about automated decision-making by artificial intelligence
Araujo, T., Helberger, N., Kruikemeier, S., & de Vreese, C. H. (2020) · AI & SOCIETY · doi:10.1007/s00146-019-00931-w · Cited by 1,038 · see citing works
Untitled work
(2002) · Cited by 770 · see citing works
Manipulating and Measuring Model Interpretability
Poursabzi-Sangdeh, F., Goldstein, D. G., Hofman, J. M., Wortman Vaughan, J. W., & Wallach, H. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445315 · Cited by 728 · see citing works
Almost human: Anthropomorphism increases trust resilience in cognitive agents.
de Visser, E. J., Monfort, S. S., McKendrick, R., Smith, M. A. B., McKnight, P. E., Krueger, F., & Parasuraman, R. (2016) · Journal of Experimental Psychology: Applied · doi:10.1037/xap0000092 · Cited by 614 · see citing works
Similarities and differences between human–human and human–automation trust: an integrative review
Madhavan, P., & Wiegmann, D. A. (2007) · Theoretical Issues in Ergonomics Science · doi:10.1080/14639220500337708 · Cited by 577 · see citing works
What influences algorithmic decision-making? A systematic literature review on algorithm aversion
Mahmud, H., Islam, A. K. M. N., Ahmed, S. I., & Smolander, K. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121390 · Cited by 601 · see citing works
Do as AI say: susceptibility in deployment of clinical decision-aids
Gaube, S., Suresh, H., Raue, M., Merritt, A., Berkowitz, S. J., Lermer, E., Coughlin, J. F., Guttag, J. V., Colak, E., & Ghassemi, M. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00385-9 · Cited by 543 · see citing works
In bot we trust: A new methodology of chatbot performance measures
Przegalińska, A., Ciechanowski, L., Stróż, A., Gloor, P. A., & Mazurek, G. (2019) · Business Horizons · doi:10.1016/j.bushor.2019.08.005 · Cited by 355 · see citing works
Credibility: A multidisciplinary framework
Rieh, S. Y., & Danielson, D. R. (2007) · Annual Review of Information Science and Technology · doi:10.1002/aris.2007.1440410114 · Cited by 336 · see citing works
Understanding algorithm aversion: When is advice from automation discounted?
Prahl, A., & Van Swol, L. (2017) · Journal of Forecasting · doi:10.1002/for.2464 · Cited by 308 · see citing works
My Friends, Editors, Algorithms, and I
Thurman, N. J., Moeller, J., Helberger, N., & Trilling, D. (2018) · Digital Journalism · doi:10.1080/21670811.2018.1493936 · Cited by 249 · see citing works
Watch Me Improve—Algorithm Aversion and Demonstrating the Ability to Learn
Berger, B., Adam, M., Rühr, A., & Benlian, A. (2020) · Business & Information Systems Engineering · doi:10.1007/s12599-020-00678-5 · Cited by 184 · see citing works
Towards Deeper Understanding of Persuasion in Software and Information Systems
B, H. O.-K. A., & Harjumaa, M. (2008) · ACHI ... the ... International Conference on Advances in Computer-Human Interactions · doi:10.1109/achi.2008.31 · Cited by 179 · see citing works
Managerial overreliance on AI-augmented decision-making processes: How the use of AI-based advisory systems shapes choice behavior in R&D investment decisions
Keding, C., & Meissner, P. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120970 · Cited by 168 · see citing works
How to overcome algorithm aversion: Learning from mistakes
Reich, T., Kaju, A., & Maglio, S. J. (2022) · Journal of Consumer Psychology · doi:10.1002/jcpy.1313 · Cited by 139 · see citing works
Human–Human Reliance in the Context of Automation
Lyons, J. B., & Stokes, C. K. (2012) · Hum. Factors · doi:10.1177/0018720811427034 · Cited by 158 · see citing works
Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making
Inkpen, K., Chappidi, S., Mallari, K., Nushi, B., Ramesh, D., Michelucci, P., Mandava, V., Vepřek, L. H., & Quinn, G. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3534561 · Cited by 132 · see citing works
The 3 C's of anthropomorphism: Connection, comprehension, and competition
Yang, L. W., Aggarwal, P., & McGill, A. L. (2019) · Consumer Psychology Review · doi:10.1002/arcp.1054 · Cited by 130 · see citing works
Who is the fairest of them all? Public attitudes and expectations regarding automated decision-making
Helberger, N., Araujo, T., & de Vreese, C. H. (2020) · Computer law & security review · doi:10.1016/j.clsr.2020.105456 · Cited by 121 · see citing works
We and it: an interdisciplinary review of the experimental evidence on how humans interact with machines
Chugunova, M., & Sele, D. (2022) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2022.101897 · Cited by 118 · see citing works
Who is the Expert? Reconciling Algorithm Aversion and Algorithm Appreciation in AI-Supported Decision Making
Hou, Y. T.-Y., & Jung, M. F. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479864 · Cited by 108 · see citing works
The World is not Enough: Trust in Cognitive Agents
de Visser, E. J., Krueger, F. W., McKnight, P. E., Scheid, S., Smith, M. A. B., Chalk, S., & Parasuraman, R. (2012) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181312561062 · Cited by 107 · see citing works
How should intelligent agents apologize to restore trust? Interaction effects between anthropomorphism and apology attribution on trust repair
Kim, T., & Song, H. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101595 · Cited by 101 · see citing works
“I Am Here to Assist You Today”: The Role of Entity, Interactivity and Experiential Perceptions in Chatbot Persuasion
Ischen, C., Araujo, T., van Noort, G., Voorveld, H. A. M., & Smit, E. G. (2020) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2020.1834297 · Cited by 105 · see citing works
AI in the hands of imperfect users
Kostick, K. M., & Gerke, S. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00737-z · Cited by 109 · see citing works
The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: Evidence from Field Experiments
Bai, B., Dai, H., Zhang, D., Zhang, F., & Hu, H. (2020) · Manufacturing & Service Operations Management · doi:10.1287/msom.2022.1120 · Cited by 98 · see citing works
Anthropomorphizing information to enhance trust in autonomous vehicles
Niu, D., Terken, J., & Eggen, B. (2018) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.20745 · Cited by 90 · see citing works
A Parsimonious Language Model of Social Media Credibility Across Disparate Events
Mitra, T., Wright, G. P., & Gilbert, É. (2017) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2998181.2998351 · Cited by 80 · see citing works
Learning From the Slips of Others: Neural Correlates of Trust in Automated Agents
de Visser, E. J., Beatty, P. J., Estepp, J. R., Kohn, S., Abubshait, A., Fedota, J. R., & McDonald, C. G. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00309 · Cited by 73 · see citing works
Investigating Differences in Crowdsourced News Credibility Assessment
Bhuiyan, M. M., Zhang, A. X., Sehat, C. M., & Mitra, T. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3415164 · Cited by 75 · see citing works
Job candidates’ reactions to AI-enabled job application processes
van Esch, P., Black, J. S., & Arli, D. (2021) · AI and Ethics · doi:10.1007/s43681-020-00025-0 · Cited by 72 · see citing works
Motivating, Influencing, and Persuading Users
Fogg, B. J., Danielson, D. R., & Cuellar, G. (2007) · Human factors and ergonomics · doi:10.1201/9781410615862.ch7 · Cited by 71 · see citing works
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Balagopalan, A., Zhang, H., Hamidieh, K., Hartvigsen, T., Rudzicz, F., & Ghassemi, M. (2022) · Conference on Fairness, Accountability and Transparency · doi:10.1145/3531146.3533179 · Cited by 115 · see citing works
More Human-Likeness, More Trust?: The Effect of Anthropomorphism on Self-Reported and Behavioral Trust in Continued and Interdependent Human-Agent Cooperation
Kulms, P., & Kopp, S. (2019) · Proceedings of Mensch und Computer 2019 · doi:10.1145/3340764.3340793 · Cited by 68 · see citing works
Should I Trust the Artificial Intelligence to Recruit? Recruiters’ Perceptions and Behavior When Faced With Algorithm-Based Recommendation Systems During Resume Screening
Lacroux, A., & Martin-Lacroux, C. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.895997 · Cited by 67 · see citing works
Believing in Analytics: Managers’ Adherence to Price Recommendations from a DSS
Caro, F., & Cuenca, A. S. D. T. (2023) · Manufacturing & Service Operations Management · doi:10.1287/msom.2022.1166 · Cited by 66 · see citing works
What type of algorithm is perceived as fairer and more acceptable? A comparative analysis of rule-driven versus data-driven algorithmic decision-making in public affairs
Wang, G., Guo, Y., Zhang, W., Xie, S., & Chen, Q. (2023) · Government Information Quarterly · doi:10.1016/j.giq.2023.101803 · Cited by 71 · see citing works
Trust criteria for artificial intelligence in health: normative and epistemic considerations
Kostick, K. M., Lang, B. H., Smith, J. N., Hurley, M. E., & Blumenthal‐Barby, J. (2023) · Journal of Medical Ethics · doi:10.1136/jme-2023-109338 · Cited by 68 · see citing works
When do consumers prefer AI-enabled customer service? The interaction effect of brand personality and service provision type on brand attitudes and purchase intentions
Yang, C., & Hu, J. (2021) · Journal of Brand Management · doi:10.1057/s41262-021-00261-7 · Cited by 62 · see citing works
Under Pressure: Examining Social Conformity With Computer and Robot Groups
Hertz, N., & Wiese, E. (2018) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720818788473 · Cited by 53 · see citing works
Effect of Human-AI Interaction on Detection of Malignant Lung Nodules on Chest Radiographs
Lee, J. H., Hong, H., Nam, G., Hwang, E. J., & Park, C. M. (2023) · Radiology · doi:10.1148/radiol.222976 · Cited by 52 · see citing works
Can AI Enhance People’s Support for Online Moderation and Their Openness to Dissimilar Political Views?
Wojcieszak, M., Thakur, A., Gonçalves, J. F. F., Casas, A., Menchen-Trevino, E., & Boon, M. (2021) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmab006 · Cited by 52 · see citing works
Impact of Algorithmic Decision Making on Human Behavior: Evidence from Ultimatum Bargaining
Erlei, A., Nekdem, F., Meub, L., Anand, A., & Gadiraju, U. (2020) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v8i1.7462 · Cited by 50 · see citing works
Creating More Credible and Persuasive Recommender Systems: The Influence of Source Characteristics on Recommender System Evaluations
Yoo, K., & Ulrike Gretzel, B. (2010) · Springer eBooks · doi:10.1007/978-0-387-85820-3_14 · Cited by 49 · see citing works
Multi-Chatbot or Single-Chatbot? The Effects of M-Commerce Chatbot Interface on Source Credibility, Social Presence, Trust, and Purchase Intention
Tan, S.-M., & Liew, T. W. (2022) · Human Behavior and Emerging Technologies · doi:10.1155/2022/2501538 · Cited by 54 · see citing works
Algorithm aversion in delegated investing
Germann, M., & Merkle, C. (2022) · Journal of Business Economics · doi:10.1007/s11573-022-01121-9 · Cited by 48 · see citing works
Expert Systems for Forecasting
Collopy, F., Adya, M. P., & Armstrong, J. S. (2001) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-0-306-47630-3_14 · Cited by 43 · see citing works
Challenging presumed technological superiority when working with (artificial) colleagues
Rieger, T., Roesler, E., & Manzey, D. (2022) · Scientific Reports · doi:10.1038/s41598-022-07808-x · Cited by 39 · see citing works
Using generative AI as decision-support tools: unraveling users’ trust and AI appreciation
Huynh, M.-T. (2024) · Journal of Decision System · doi:10.1080/12460125.2024.2428166 · Cited by 46 · see citing works
Behavior change support systems: the next frontier for web science
B, H. O.-K. A. (2010) · Cited by 40 · see citing works
Social Recommender Systems
Rafaeli, S., Dan-Gur, Y., & Barak, M. (2005) · International Journal of Distance Education Technologies · doi:10.4018/jdet.2005040103 · Cited by 39 · see citing works
Justice, trust, and moral judgements when personnel selection is supported by algorithms
Feldkamp, T., Langer, M., Wies, L., & König, C. J. (2023) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2023.2169140 · Cited by 41 · see citing works
Human Versus Machine: Contingency Factors of Anthropomorphism as a Trust-Inducing Design Strategy for Conversational Agents
Seeger, A.-M., & Heinzl, A. (2017) · Lecture notes in information systems and organisation · doi:10.1007/978-3-319-67431-5_15 · Cited by 34 · see citing works
Psychologically targeted persuasive advertising and product information in e-commerce
Saari, T., Ravaja, N., Laarni, J., Turpeinen, M., & Kallinen, K. (2004) · International Conference on Electronic Commerce · doi:10.1145/1052220.1052252 · Cited by 31 · see citing works
We and It: An Interdisciplinary Review of the Experimental Evidence on Human-Machine InteractionPreprint
Chugunova, M., & Sele, D. (2020) · SSRN Electronic Journal · doi:10.3929/ethz-b-000442053 · Cited by 30 · see citing works
Task-specific algorithm advice acceptance: A review and directions for future research
Kaufmann, E., Chacon, A., Kausel, E. E., Herrera, N., & Reyes, T. H. (2023) · Data and Information Management · doi:10.1016/j.dim.2023.100040 · Cited by 28 · see citing works
The (Im)perfect Automation Schema: Who Is Trusted More, Automated or Human Decision Support?
Rieger, T., Kugler, L. M., Manzey, D., & Roesler, E. (2023) · Hum. Factors · doi:10.1177/00187208231197347 · Cited by 24 · see citing works
“I Believe AI Can Learn from the Error. Or Can It Not?”: The Effects of Implicit Theories on Trust Repair of the Intelligent Agent
Kim, T., & Song, H. (2022) · International Journal of Social Robotics · doi:10.1007/s12369-022-00951-5 · Cited by 26 · see citing works
The Effect of past Algorithmic Performance and Decision Significance on Algorithmic Advice Acceptance
Saragih, M., & Morrison, B. W. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1990518 · Cited by 25 · see citing works
Embodied Digital Technologies: First Insights in the Social and Legal Perception of Robots and Users of Prostheses
Mandl, S., Bretschneider, M., Meyer, S., Gesmann-Nuissl, D., Asbrock, F., Meyer, B. M., & Strobel, A. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.787970 · Cited by 25 · see citing works
Two distinct and separable processes underlie individual differences in algorithm adherence: Differences in predictions and differences in trust thresholds
Fenneman, A., Sickmann, J., Pitz, T., & Sanfey, A. G. (2021) · PLoS ONE · doi:10.1371/journal.pone.0247084 · Cited by 27 · see citing works
FACTORS THAT AFFECT TRUST AND RELIANCE ON AN AUTOMATED AID
Sánchez, J. (2006) · UPT. Syiah Kuala University Library (Syiah Kuala University) · Cited by 24 · see citing works
Trusted Autonomy Under Uncertainty
Smithson, M. J. (2018) · Studies in systems, decision and control · doi:10.1007/978-3-319-64816-3_10 · Cited by 23 · see citing works
Unmanned aerial systems (UAS) operators’ accuracy and confidence of decisions: Professional pilots or video game players?
Wheatcroft, J. M., Jump, M., Breckell, A. L., & Adams-White, J. E. (2017) · Cogent Psychology · doi:10.1080/23311908.2017.1327628 · Cited by 22 · see citing works
The Effect of Advice Valence on the Perceived Credibility of Data Analytics
Chen, C. X., Hudgins, R., & Wright, W. F. (2021) · Journal of Management Accounting Research · doi:10.2308/jmar-2020-015 · Cited by 21 · see citing works
Human preferences toward algorithmic advice in a word association task
Bogert, E., Lauharatanahirun, N., & Schecter, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-18638-2 · Cited by 23 · see citing works
Algorithmic Decisions, Desire for Control, and the Preference for Human Review over Algorithmic Review
Lyons, H., Miller, T., & Velloso, E. (2023) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3593013.3594041 · Cited by 21 · see citing works
Persuasion: An Analysis and Common Frame of Reference for IS Research
Slattery, P., Vidgen, R. T., & Finnegan, P. (2020) · Communications of the Association for Information Systems · doi:10.17705/1cais.04603 · Cited by 19 · see citing works
The social consequences of Machine Allocation Behavior: Fairness, interpersonal perceptions and performance
Claure, H., Kim, S., Kizilcec, R. F., & Jung, M. F. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107628 · Cited by 21 · see citing works
The nature, dimensionality, and effects of perceptions of community governance
Kayhan, V. O. (2014) · Information & Management · doi:10.1016/j.im.2014.10.004 · Cited by 19 · see citing works
Perceptions of AI engaging in human expression
Bower, A. H., & Steyvers, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-00426-z · Cited by 18 · see citing works
Mixing It Up: How Mixed Groups of Humans and Machines Modulate Conformity
Hertz, N., Shaw, T. H., de Visser, E. J., & Wiese, E. (2019) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343419869465 · Cited by 17 · see citing works
Calibrating workers’ trust in intelligent automated systems
Lucas, G., Becerik-Gerber, B., & Roll, S. C. (2024) · Patterns · doi:10.1016/j.patter.2024.101045 · Cited by 23 · see citing works
Human-algorithm interaction: Algorithmic pricing in hybrid laboratory markets
Normann, H., & Sternberg, M. (2022) · European Economic Review · doi:10.1016/j.euroecorev.2022.104347 · Cited by 17 · see citing works
Adaptive Automation: Building Flexibility into Human-Machine Systems☆
Dzindolet, M. T., Beck, H. P., & PIERCE, L. (2005) · Advances in human performance and cognitive engineering research · doi:10.1016/s1479-3601(05)06007-8 · Cited by 15 · see citing works
My Health Advisor is a Robot: Understanding Intentions to Adopt a Robotic Health Advisor
Kim, J., Merrill, K., Xu, K., & Collins, C. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2239559 · Cited by 14 · see citing works
Trust in self-driving vehicles is lower than in human drivers when both drive almost perfectly
Yokoi, R. (2024) · Transportation Research Part F: Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.03.019 · Cited by 10 · see citing works
Mega-influencer follower effect: the mediating role of sense of control in brand attitudes, purchase intentions and engagement
Dong, X., Zhou, R., & Liao, J. (2024) · European Journal of Marketing · doi:10.1108/ejm-04-2023-0278 · Cited by 13 · see citing works
An experimental machine learning study investigating the decision-making process of students and qualified radiographers when interpreting radiographic images
Rainey, C., Villikudathil, A. T., McConnell, J., Hughes, C., Bond, R., & McFadden, S. L. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000229 · Cited by 13 · see citing works
How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making?
Narayanan, S., Yu, G., Ho, C.-J., & Yin, M. (2023) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3600211.3604709 · Cited by 12 · see citing works
Fact Checking Chatbot: A Misinformation Intervention for Instant Messaging Apps and an Analysis of Trust in the Fact Checkers
Lim, G., & Perrault, S. T. (2023) · Mobile communication in Asia · doi:10.1007/978-94-024-2225-2_11 · Cited by 12 · see citing works
AI or human: How the type of information to be disclosed alters customer service agent preferences
Dai, X., Zhang, L., Huang, Z., & Wang, L. (2025) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2025.104621 · Cited by 11 · see citing works
Gain-loss separability in human- but not computer-based changes of mind
Lin, Y., Xu, P., Fan, J., Gu, R., & Luo, Y. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107712 · Cited by 13 · see citing works
User Perceptions of News Recommender Systems and Trust in Media Outlets: A Five-Country Study
Blassnig, S., Mitova, E., Strikovic, E., Urman, A., de Vreese, C. H., Hannák, A., & Esser, F. (2024) · Journalism Studies · doi:10.1080/1461670x.2024.2364628 · Cited by 11 · see citing works
Exploring Localized Usability Implementation in mHealth App Design for Healthcare Practitioners in the Global South Context: A Case Study
Acharya, K. R. (2022) · Technical Communication: Journal of the Society for Technical Communication · doi:10.55177/tc885177 · Cited by 10 · see citing works
Ruled by robots: preference for algorithmic decision makers and perceptions of their choices
Chugunova, M., & Luhan, W. J. (2024) · Public Choice · doi:10.1007/s11127-024-01178-w · Cited by 12 · see citing works
Improving Human Deception Detection Using Algorithmic Feedback
Serra-García, M., & Uri Gneezy, B. (2025) · Management Science · doi:10.1287/mnsc.2023.02792 · Cited by 11 · see citing works
An expert system for the quantification of fault rates in construction fall accidents
Birgönül, M. T., Dikmen, İ., Budayan, C., & Demirel, T. (2015) · International Journal of Occupational Safety and Ergonomics · doi:10.1080/10803548.2015.1123516 · Cited by 10 · see citing works
Manipulation and the Ai Act: Large Language Model Chatbots and the Danger of MirrorsPreprint
Krook, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4719835 · Cited by 10 · see citing works
Unveiling coping mechanisms in marketplace discrimination: The allure of artificial intelligence recommendations
Talebi, A., Mukherjee, S., Gera, N., Kaur, K., & Das, G. (2025) · Journal of Product Innovation Management · doi:10.1111/jpim.12774 · Cited by 9 · see citing works
Beyond Algorithm Aversion in Human-Machine Decision-Making
Burton, J. W., Stein, M., & Jensen, T. B. (2023) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-031-30085-1_1 · Cited by 9 · see citing works
Emotional expressions facilitate human–human trust when using automation in high-risk situations
Feng, J., Sanchez, J., Sall, R. J., Lyons, J. B., & Nam, C. S. (2019) · Military Psychology · doi:10.1080/08995605.2019.1630227 · Cited by 9 · see citing works
Big Data and Trust in Public Policy Automation
Waggoner, P., Kennedy, R., Le, H., & Shiran, M. (2019) · Statistics Politics and Policy · doi:10.1515/spp-2019-0005 · Cited by 9 · see citing works
Personal Remote Assistance in Ambient Assisted Living—Experimental Research of Elderly People’s Trust and Their Intention to Use
Steinke, F., Ingenhoff, A., & Fritsch, T. (2014) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2014.903789 · Cited by 9 · see citing works
Five principles for the intelligent use of AI in medical imaging
Colak, E., Moreland, R., & Ghassemi, M. (2021) · Intensive Care Medicine · doi:10.1007/s00134-020-06316-8 · Cited by 9 · see citing works
Human-Algorithm Interaction: Algorithmic Pricing in Hybrid Laboratory MarketsPreprint
Normann, H., & Sternberg, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4087304 · Cited by 9 · see citing works
Chatbots in education: Outperforming students but perceived as less trustworthy
Laun, M., Puderbach, L., Hirt, K., Wyss, E., Friemert, D., Hartmann, U., & Wolff, F. (2025) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2025.102373 · Cited by 9 · see citing works
Algorithms in selection decisions: Effective, but unappreciated
Rabinovitch, H., Budescu, D. V., & Bereby‐Meyer, Y. (2024) · Journal of Behavioral Decision Making · doi:10.1002/bdm.2368 · Cited by 8 · see citing works

On the use of computerised decision aids: an investigation into the expert system as persuasive communicator
Dijkstra, J. J. (2006) · Cited by 3 · see citing works
Self-citation
User agreement with incorrect expert system advice
Dijkstra, J. J. (1999) · Behaviour and Information Technology · doi:10.1080/014492999118832 · Cited by 124 · see citing works
Self-citation
Persuasive expert systems: the influence of confidence and discrepancy
Jiang, J. J., Klein, G. L., & Vedder, R. G. (2000) · Computers in Human Behavior · doi:10.1016/s0747-5632(00)00014-5 · Cited by 28 · see citing works
Expert systems as decision aids : issues and strategies
Liang, T. (1987) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 26 · see citing works
An empirical investigation of the effect of variations in expert system explanation presentation on users' acquisition of expertise and perceptions of the system
Everett, A. M. (1994) · Lincoln (University of Nebraska) · Cited by 9 · see citing works

Authors: Dijkstra, J. J., Liebrand, W. B. G., & Timminga, E.
Affiliations: University of Groningen (NL)
Venue: Behaviour & Information Technology
Publisher: Informa UK Limited
Published: 1998-01
Volume: 17
Issue: 3
Pages: 155-163
ISSN: 0144-929X (ISSN-L)
1362-3001
DOI: 10.1080/014492998119526
OpenAlex: W1984763500
Cited by: 161
References: 43
Citations by year: 2026: 12 · 2025: 13 · 2024: 16 · 2023: 19 · 2022: 21 · 2021: 18 · 2020: 11 · 2019: 8 · 2018: 7 · 2017: 4 · 2016: 2 · 2015: 2 · 2014: 2 · 2013: 1 · 2012: 2
FWCI: 2.08
Type: journal article
Language: en
Open access: green
research.rug.nl
Licence: other-oa
Locations: Behaviour and Information Technology (publishedVersion)
University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
Topics: Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
Social Sciences › Sociology and Political Science › Psychology of Social Influence
Keywords: expert systems, persuasiveness, user beliefs, perceived objectivity, production rules

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

Persuasiveness of expert systems

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Self-check

Cites

Cited by

Related

Record

About these checks