[{"status":"public","type":"journal_article","publication":"Frontiers in Behavioral Economics","keyword":["cheating","human-machine interaction","ambiguity","verification process","algorithm aversion","algorithm appreciation"],"language":[{"iso":"eng"}],"_id":"61339","user_id":"44549","year":"2025","citation":{"apa":"Protte, M., &#38; Djawadi, B. M. (2025). Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty. <i>Frontiers in Behavioral Economics</i>, <i>4</i>, 1645749. <a href=\"https://doi.org/10.3389/frbhe.2025.1645749\">https://doi.org/10.3389/frbhe.2025.1645749</a>","bibtex":"@article{Protte_Djawadi_2025, title={Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty}, volume={4}, DOI={<a href=\"https://doi.org/10.3389/frbhe.2025.1645749\">10.3389/frbhe.2025.1645749</a>}, journal={Frontiers in Behavioral Economics}, author={Protte, Marius and Djawadi, Behnud Mir}, year={2025}, pages={1645749} }","mla":"Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty.” <i>Frontiers in Behavioral Economics</i>, vol. 4, 2025, p. 1645749, doi:<a href=\"https://doi.org/10.3389/frbhe.2025.1645749\">10.3389/frbhe.2025.1645749</a>.","short":"M. Protte, B.M. Djawadi, Frontiers in Behavioral Economics 4 (2025) 1645749.","ama":"Protte M, Djawadi BM. Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty. <i>Frontiers in Behavioral Economics</i>. 2025;4:1645749. doi:<a href=\"https://doi.org/10.3389/frbhe.2025.1645749\">10.3389/frbhe.2025.1645749</a>","ieee":"M. Protte and B. M. Djawadi, “Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty,” <i>Frontiers in Behavioral Economics</i>, vol. 4, p. 1645749, 2025, doi: <a href=\"https://doi.org/10.3389/frbhe.2025.1645749\">10.3389/frbhe.2025.1645749</a>.","chicago":"Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty.” <i>Frontiers in Behavioral Economics</i> 4 (2025): 1645749. <a href=\"https://doi.org/10.3389/frbhe.2025.1645749\">https://doi.org/10.3389/frbhe.2025.1645749</a>."},"page":"1645749","intvolume":"         4","title":"Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty","main_file_link":[{"open_access":"1","url":"https://www.frontiersin.org/journals/behavioral-economics/articles/10.3389/frbhe.2025.1645749/full"}],"doi":"10.3389/frbhe.2025.1645749","date_updated":"2025-09-29T09:31:38Z","oa":"1","date_created":"2025-09-18T07:52:40Z","author":[{"first_name":"Marius","full_name":"Protte, Marius","id":"44549","last_name":"Protte"},{"last_name":"Djawadi","full_name":"Djawadi, Behnud Mir","first_name":"Behnud Mir"}],"volume":4},{"language":[{"iso":"eng"}],"keyword":["Algorithm aversion","Time series","Decision making","Advice taking","Forecasting"],"user_id":"51271","department":[{"_id":"196"}],"_id":"37312","status":"public","abstract":[{"lang":"eng","text":"Optimal decision making requires appropriate evaluation of advice. Recent literature reports that algorithm aversion reduces the effectiveness of predictive algorithms. However, it remains unclear how people recover from bad advice given by an otherwise good advisor. Previous work has focused on algorithm aversion at a single time point. We extend this work by examining successive decisions in a time series forecasting task using an online between-subjects experiment (N = 87). Our empirical results do not confirm algorithm aversion immediately after bad advice. The estimated effect suggests an increasing algorithm appreciation over time. Our work extends the current knowledge on algorithm aversion with insights into how weight on advice is adjusted over consecutive tasks. Since most forecasting tasks are not one-off decisions, this also has implications for practitioners."}],"type":"conference","publication":"Hawaii International Conference on System Sciences","main_file_link":[{"open_access":"1","url":"https://scholarspace.manoa.hawaii.edu/items/62b58ddc-895c-48c3-8194-522a1758a26f"}],"conference":{"name":"Hawaii International Conference on System Sciences"},"title":"Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time","date_created":"2023-01-18T10:53:51Z","author":[{"full_name":"Leffrang, Dirk","id":"51271","orcid":"0000-0001-9004-2391","last_name":"Leffrang","first_name":"Dirk"},{"full_name":"Bösch, Kevin","last_name":"Bösch","first_name":"Kevin"},{"last_name":"Müller","full_name":"Müller, Oliver","id":"72849","first_name":"Oliver"}],"date_updated":"2024-01-10T09:52:59Z","oa":"1","citation":{"short":"D. Leffrang, K. Bösch, O. Müller, in: Hawaii International Conference on System Sciences, 2023.","bibtex":"@inproceedings{Leffrang_Bösch_Müller_2023, title={Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time}, booktitle={Hawaii International Conference on System Sciences}, author={Leffrang, Dirk and Bösch, Kevin and Müller, Oliver}, year={2023} }","mla":"Leffrang, Dirk, et al. “Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time.” <i>Hawaii International Conference on System Sciences</i>, 2023.","apa":"Leffrang, D., Bösch, K., &#38; Müller, O. (2023). Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time. <i>Hawaii International Conference on System Sciences</i>. Hawaii International Conference on System Sciences.","ama":"Leffrang D, Bösch K, Müller O. Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time. In: <i>Hawaii International Conference on System Sciences</i>. ; 2023.","chicago":"Leffrang, Dirk, Kevin Bösch, and Oliver Müller. “Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time.” In <i>Hawaii International Conference on System Sciences</i>, 2023.","ieee":"D. Leffrang, K. Bösch, and O. Müller, “Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time,” presented at the Hawaii International Conference on System Sciences, 2023."},"year":"2023"},{"user_id":"51271","department":[{"_id":"196"}],"_id":"50118","language":[{"iso":"eng"}],"keyword":["Algorithm aversion","Data","Decision-making","Advice-taking","Human-Computer Interaction"],"type":"conference","publication":"Wirtschaftsinformatik Conference","status":"public","abstract":[{"lang":"eng","text":"Despite the widespread use of machine learning algorithms, their effectiveness is limited by a phenomenon known as algorithm aversion. Recent research concluded that unobserved variables can cause algorithm aversion. However, the impact of an unobserved variable on algorithm aversion remains unclear. Previous studies focused on situations where humans had more variables available than algorithms. We extend this research by conducting an online experiment with 94 participants, systematically varying the number of observable variables to the advisor and the advisor type. Surprisingly, our results did not confirm that an unobserved variable had a negative effect on advice-taking. Instead, we found a positive impact in an algorithm appreciation scenario. This study provides new insights into the paradoxical behavior in which people weigh advice more despite having fewer variables, as they correct for the advisor's errors. Practitioners should consider this behavior when designing algorithms and account for user correction behavior."}],"date_created":"2024-01-03T09:50:06Z","author":[{"full_name":"Leffrang, Dirk","id":"51271","orcid":"0000-0001-9004-2391","last_name":"Leffrang","first_name":"Dirk"}],"date_updated":"2024-01-10T09:53:24Z","main_file_link":[{"url":"https://aisel.aisnet.org/wi2023/19 "}],"conference":{"name":"Wirtschaftsinformatik","location":"Paderborn"},"title":"The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization","issue":"19","citation":{"mla":"Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” <i>Wirtschaftsinformatik Conference</i>, no. 19, 2023.","bibtex":"@inproceedings{Leffrang_2023, title={The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization}, number={19}, booktitle={Wirtschaftsinformatik Conference}, author={Leffrang, Dirk}, year={2023} }","short":"D. Leffrang, in: Wirtschaftsinformatik Conference, 2023.","apa":"Leffrang, D. (2023). The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. <i>Wirtschaftsinformatik Conference</i>, <i>19</i>.","chicago":"Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” In <i>Wirtschaftsinformatik Conference</i>, 2023.","ieee":"D. Leffrang, “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization,” in <i>Wirtschaftsinformatik Conference</i>, Paderborn, 2023, no. 19.","ama":"Leffrang D. The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. In: <i>Wirtschaftsinformatik Conference</i>. ; 2023."},"year":"2023"}]