[{"publication_status":"published","jel":["J24","M54","L83","J28"],"citation":{"chicago":"Protte, Marius. “Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards,” 2026.","ieee":"M. Protte, “Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards.” 2026.","ama":"Protte M. Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards. Published online 2026.","apa":"Protte, M. (2026). <i>Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards</i>.","short":"M. Protte, (2026).","bibtex":"@article{Protte_2026, title={Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards}, author={Protte, Marius}, year={2026} }","mla":"Protte, Marius. <i>Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards</i>. 2026."},"year":"2026","date_created":"2026-04-27T12:05:47Z","author":[{"first_name":"Marius","orcid":"0000-0002-7529-1186","last_name":"Protte","id":"44549","full_name":"Protte, Marius"}],"date_updated":"2026-04-27T12:11:54Z","main_file_link":[{"url":"https://ssrn.com/abstract=6653658"}],"title":"Player-Perceived Workplace Quality and Team Performance: Evidence from NFLPA Report Cards","type":"preprint","status":"public","abstract":[{"text":"This paper examines whether player-reported workplace quality is associated with team success in the National Football League (NFL). Using panel data for all 32 NFL teams across four seasons (2022-2025), we test whether NFLPA report card rankings-player evaluations of facilities, travel, medical support, coaching, and organizational environment-are related to regular season win percentage. Fixed effects models controlling for player quality, roster composition, injuries, coaching tenure, and past performance reveal a statistically significant within-team association between better player-reported workplace conditions and higher win percentages. However, this relationship does not persist when workplace quality is lagged, suggesting that player evaluations may partly reflect current team performance rather than predict future outcomes. These findings indicate that player evaluations of workplace quality are closely aligned with team success, highlighting the role of perception and short-run performance dynamics in a high-skill labor market setting.","lang":"eng"}],"user_id":"44549","_id":"65499","language":[{"iso":"eng"}],"keyword":["NFL team performance","NFLPA report cards","player satisfaction","organizational environment","non-pecuniary compensation"]},{"title":"Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on Human Dishonesty","doi":"10.3389/frbhe.2025.1645749","main_file_link":[{"open_access":"1","url":"https://www.frontiersin.org/journals/behavioral-economics/articles/10.3389/frbhe.2025.1645749/full"}],"date_updated":"2025-09-29T09:31:38Z","oa":"1","volume":4,"date_created":"2025-09-18T07:52:40Z","author":[{"id":"44549","full_name":"Protte, Marius","last_name":"Protte","first_name":"Marius"},{"first_name":"Behnud Mir","full_name":"Djawadi, Behnud Mir","last_name":"Djawadi"}],"year":"2025","page":"1645749","intvolume":"         4","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>","short":"M. Protte, B.M. Djawadi, Frontiers in Behavioral Economics 4 (2025) 1645749.","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>.","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>","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>.","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>."},"keyword":["cheating","human-machine interaction","ambiguity","verification process","algorithm aversion","algorithm appreciation"],"language":[{"iso":"eng"}],"_id":"61339","user_id":"44549","status":"public","publication":"Frontiers in Behavioral Economics","type":"journal_article"},{"file_date_updated":"2023-10-23T10:35:22Z","_id":"48387","user_id":"44549","series_title":"Lecture Notes in Networks and Systems","department":[{"_id":"179"}],"status":"public","type":"book_chapter","conference":{"start_date":"2024-04-04","name":"Future of Information and Communication Conference (FICC)","location":"Berlin","end_date":"2024-04-05"},"doi":"https://doi.org/10.1007/978-3-031-53960-2_13","date_updated":"2024-12-09T11:46:02Z","author":[{"last_name":"Lebedeva","full_name":"Lebedeva, Anastasia","first_name":"Anastasia"},{"first_name":"Marius","last_name":"Protte","id":"44549","full_name":"Protte, Marius"},{"first_name":"Dirk","full_name":"van Straaten, Dirk","last_name":"van Straaten"},{"first_name":"René","id":"111","full_name":"Fahr, René","last_name":"Fahr"}],"volume":919,"citation":{"bibtex":"@inbook{Lebedeva_Protte_van Straaten_Fahr_2024, series={Lecture Notes in Networks and Systems}, title={Involvement of domain experts in the AI training does not affect adherence – An AutoML study}, volume={919}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-53960-2_13\">https://doi.org/10.1007/978-3-031-53960-2_13</a>}, booktitle={Advances in Information and Communication}, publisher={Springer, Cham}, author={Lebedeva, Anastasia and Protte, Marius and van Straaten, Dirk and Fahr, René}, year={2024}, pages={178–204}, collection={Lecture Notes in Networks and Systems} }","short":"A. Lebedeva, M. Protte, D. van Straaten, R. Fahr, in: Advances in Information and Communication, Springer, Cham, 2024, pp. 178–204.","mla":"Lebedeva, Anastasia, et al. “Involvement of Domain Experts in the AI Training Does Not Affect Adherence – An AutoML Study.” <i>Advances in Information and Communication</i>, vol. 919, Springer, Cham, 2024, pp. 178–204, doi:<a href=\"https://doi.org/10.1007/978-3-031-53960-2_13\">https://doi.org/10.1007/978-3-031-53960-2_13</a>.","apa":"Lebedeva, A., Protte, M., van Straaten, D., &#38; Fahr, R. (2024). Involvement of domain experts in the AI training does not affect adherence – An AutoML study. In <i>Advances in Information and Communication</i> (Vol. 919, pp. 178–204). Springer, Cham. <a href=\"https://doi.org/10.1007/978-3-031-53960-2_13\">https://doi.org/10.1007/978-3-031-53960-2_13</a>","ieee":"A. Lebedeva, M. Protte, D. van Straaten, and R. Fahr, “Involvement of domain experts in the AI training does not affect adherence – An AutoML study,” in <i>Advances in Information and Communication</i>, vol. 919, Springer, Cham, 2024, pp. 178–204.","chicago":"Lebedeva, Anastasia, Marius Protte, Dirk van Straaten, and René Fahr. “Involvement of Domain Experts in the AI Training Does Not Affect Adherence – An AutoML Study.” In <i>Advances in Information and Communication</i>, 919:178–204. Lecture Notes in Networks and Systems. Springer, Cham, 2024. <a href=\"https://doi.org/10.1007/978-3-031-53960-2_13\">https://doi.org/10.1007/978-3-031-53960-2_13</a>.","ama":"Lebedeva A, Protte M, van Straaten D, Fahr R. Involvement of domain experts in the AI training does not affect adherence – An AutoML study. In: <i>Advances in Information and Communication</i>. Vol 919. Lecture Notes in Networks and Systems. Springer, Cham; 2024:178–204. doi:<a href=\"https://doi.org/10.1007/978-3-031-53960-2_13\">https://doi.org/10.1007/978-3-031-53960-2_13</a>"},"intvolume":"       919","page":"178–204","has_accepted_license":"1","ddc":["000","600","330"],"language":[{"iso":"eng"}],"file":[{"date_created":"2023-10-23T10:35:22Z","creator":"mprotte","date_updated":"2023-10-23T10:35:22Z","access_level":"closed","file_name":"Lebedeva_Protte_vanStraaten_Fahr_2023_updated.pdf","file_id":"48388","file_size":767807,"content_type":"application/pdf","relation":"main_file","success":1}],"publication":"Advances in Information and Communication","title":"Involvement of domain experts in the AI training does not affect adherence – An AutoML study","publisher":"Springer, Cham","date_created":"2023-10-23T10:38:00Z","year":"2024"},{"title":"Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy","doi":"10.1109/MCS.2020.3019723","date_updated":"2023-10-23T10:38:19Z","publisher":"IEEE","author":[{"full_name":"Protte, Marius","id":"44549","last_name":"Protte","first_name":"Marius"},{"first_name":"René","full_name":"Fahr, René","id":"111","last_name":"Fahr"},{"first_name":"Daniel E.","last_name":"Quevedo","full_name":"Quevedo, Daniel E."}],"date_created":"2021-03-03T14:20:10Z","volume":40,"year":"2020","citation":{"ieee":"M. Protte, R. Fahr, and D. E. Quevedo, “Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy,” <i>IEEE Control Systems Magazine</i>, vol. 40, no. 6, pp. 57–76, 2020, doi: <a href=\"https://doi.org/10.1109/MCS.2020.3019723\">10.1109/MCS.2020.3019723</a>.","chicago":"Protte, Marius, René Fahr, and Daniel E. Quevedo. “Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy.” <i>IEEE Control Systems Magazine</i> 40, no. 6 (2020): 57–76. <a href=\"https://doi.org/10.1109/MCS.2020.3019723\">https://doi.org/10.1109/MCS.2020.3019723</a>.","ama":"Protte M, Fahr R, Quevedo DE. Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy. <i>IEEE Control Systems Magazine</i>. 2020;40(6):57-76. doi:<a href=\"https://doi.org/10.1109/MCS.2020.3019723\">10.1109/MCS.2020.3019723</a>","apa":"Protte, M., Fahr, R., &#38; Quevedo, D. E. (2020). Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy. <i>IEEE Control Systems Magazine</i>, <i>40</i>(6), 57–76. <a href=\"https://doi.org/10.1109/MCS.2020.3019723\">https://doi.org/10.1109/MCS.2020.3019723</a>","mla":"Protte, Marius, et al. “Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy.” <i>IEEE Control Systems Magazine</i>, vol. 40, no. 6, IEEE, 2020, pp. 57–76, doi:<a href=\"https://doi.org/10.1109/MCS.2020.3019723\">10.1109/MCS.2020.3019723</a>.","bibtex":"@article{Protte_Fahr_Quevedo_2020, title={Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy}, volume={40}, DOI={<a href=\"https://doi.org/10.1109/MCS.2020.3019723\">10.1109/MCS.2020.3019723</a>}, number={6}, journal={IEEE Control Systems Magazine}, publisher={IEEE}, author={Protte, Marius and Fahr, René and Quevedo, Daniel E.}, year={2020}, pages={57–76} }","short":"M. Protte, R. Fahr, D.E. Quevedo, IEEE Control Systems Magazine 40 (2020) 57–76."},"page":"57 - 76","intvolume":"        40","publication_status":"published","has_accepted_license":"1","issue":"6","ddc":["620","330"],"file_date_updated":"2021-03-03T14:21:50Z","language":[{"iso":"eng"}],"_id":"21369","user_id":"44549","department":[{"_id":"179"}],"abstract":[{"lang":"eng","text":"Successful design of human-in-the-loop control sys- tems requires appropriate models for human decision makers. Whilst most paradigms adopted in the control systems literature hide the (limited) decision capability of humans, in behavioral economics individual decision making and optimization processes are well-known to be affected by perceptual and behavioral biases. Our goal is to enrich control engineering with some insights from behavioral economics research through exposing such biases in control-relevant settings.\r\nThis paper addresses the following two key questions:\r\n1) How do behavioral biases affect decision making?\r\n2) What is the role played by feedback in human-in-the-loop control systems?\r\nOur experimental framework shows how individuals behave when faced with the task of piloting an UAV under risk and uncertainty, paralleling a real-world decision-making scenario. Our findings support the notion of humans in Cyberphysical Systems underlying behavioral biases regardless of – or even because of – receiving immediate outcome feedback. We observe substantial shares of drone controllers to act inefficiently through either flying excessively (overconfident) or overly conservatively (underconfident). Furthermore, we observe human-controllers to self-servingly misinterpret random sequences through being subject to a “hot hand fallacy”. We advise control engineers to mind the human component in order not to compromise technological accomplishments through human issues."}],"file":[{"content_type":"application/pdf","success":1,"relation":"main_file","date_updated":"2021-03-03T14:21:50Z","creator":"mprotte","date_created":"2021-03-03T14:21:50Z","file_size":1501292,"file_id":"21370","file_name":"Protte_Fahr_Quevedo.pdf","access_level":"closed"}],"status":"public","type":"journal_article","publication":"IEEE Control Systems Magazine"},{"_id":"21371","user_id":"44549","language":[{"iso":"eng"}],"type":"mastersthesis","status":"public","date_updated":"2022-01-06T06:54:57Z","author":[{"last_name":"Protte","full_name":"Protte, Marius","id":"44549","first_name":"Marius"}],"supervisor":[{"full_name":"Behnud Mir, Djawadi","last_name":"Behnud Mir","first_name":"Djawadi"},{"first_name":"Fahr","last_name":"René","full_name":"René, Fahr"}],"date_created":"2021-03-03T14:33:56Z","title":"The effect of organizational support on whistleblowing behavior - An experimental analysis","year":"2019","citation":{"apa":"Protte, M. (2019). <i>The effect of organizational support on whistleblowing behavior - An experimental analysis</i>.","mla":"Protte, Marius. <i>The Effect of Organizational Support on Whistleblowing Behavior - An Experimental Analysis</i>. 2019.","bibtex":"@book{Protte_2019, title={The effect of organizational support on whistleblowing behavior - An experimental analysis}, author={Protte, Marius}, year={2019} }","short":"M. Protte, The Effect of Organizational Support on Whistleblowing Behavior - An Experimental Analysis, 2019.","ieee":"M. Protte, <i>The effect of organizational support on whistleblowing behavior - An experimental analysis</i>. 2019.","chicago":"Protte, Marius. <i>The Effect of Organizational Support on Whistleblowing Behavior - An Experimental Analysis</i>, 2019.","ama":"Protte M. <i>The Effect of Organizational Support on Whistleblowing Behavior - An Experimental Analysis</i>.; 2019."}}]