@article{65182, abstract = {{The aggregation of rating metrics in reputation systems is crucial for mitigating information overload by condensing customer rating distributions into singular valence scores. While platforms typically employ technical aggregation functions, such as the arithmetic mean to capture product quality, it remains unclear whether these functions align with customers' innate aggregation patterns. To address this knowledge gap, we designed a controlled economic decision experiment to elicit customers' aggregation principles by analyzing their product ranking decisions and contrasting these with various reference functions. Our findings indicate that, on average, customers aggregate rating information in accordance with the arithmetic mean. However, a granular analysis at the individual level reveals significant heterogeneity in aggregation behavior, with a substantial cluster exhibiting binary patterns that focus equally on negative (1-2 star) and positive (4-5 star) ratings. Additional clusters concentrate on negative feedback, particularly 1-star ratings or 1-2 star ratings collectively. Notably, these inherent aggregation patterns exhibit stability across variations in numerical information presentation and are not significantly influenced by individual characteristics, such as online shopping experience, risk attitudes, or demographics. These findings suggest that while the arithmetic mean captures average consumer behavior, platforms could benefit from offering customizable aggregation options to better cater to diverse user preferences for processing rating distributions. By doing so, platforms can enhance the effectiveness of their reputation systems and improve the overall quality of decision-making for consumers.}}, author = {{van Straaten, Dirk and Mir Djawadi, Behnud and Melnikov, Vitalik and Hüllermeier, Eyke and Fahr, René}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment}}}, doi = {{http://dx.doi.org/10.2139/ssrn.6201258}}, year = {{2026}}, } @article{65181, abstract = {{In many Western societies, mass immigration has been one of the most divisive policy issues in recent years. Seemingly moderate inflows of migrants can have substantial demographic consequences in the long run, due to (1) higher fertility of the migrant population, (2) its younger age distribution, and (3) the possibility of family reunification. Yet, demography hardly appears in the policy debate, even in media outlets that are critical of mass immigration. This may indicate that the mechanics of population dynamics are not widely understood. We design a laboratory experiment in which we confront subjects with 30 different migration scenarios. Subjects have to decide when to stop a given inflow of migrants to achieve a target share of migrants after 60 years. In line with all our pre-registered hypotheses, in scenarios that contain elements of usual mass immigration the growth of the migrant population is systematically underestimated. This bias is even stronger in scenarios that closely resemble the German situation since the opening of the borders during the 2015 refugee crisis.}}, author = {{Abbink, Klaus and Mir Djawadi, Behnud}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Migration and Long-Term Demographic Change: Can We Control the Numbers?}}}, doi = {{http://dx.doi.org/10.2139/ssrn.6343618}}, year = {{2026}}, } @article{63910, author = {{Mir Djawadi, Behnud}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Dishonesty of Parents and Children – Evidence from a Field Experiment}}}, doi = {{http://dx.doi.org/10.2139/ssrn.6121987}}, year = {{2026}}, } @article{63909, abstract = {{IntroductionHuman-machine interactions become increasingly pervasive in daily life and professional contexts, motivating research to examine how human behavior changes when individuals interact with machines rather than other humans. While most of the existing literature focused on human-machine interactions with algorithmic systems in advisory roles, research on human behavior in monitoring or verification processes that are conducted by automated systems remains largely absent. This is surprising given the growing implementation of algorithmic systems in institutions, particularly in tax enforcement and financial regulation, to help monitor and identify misreports, or in online labor platforms widely implementing algorithmic control to ensure that workers deliver high service quality. Our study examines how human dishonesty changes when verification of statements that may be untrue is performed by machines vs. humans, and how ambiguity in the verification process influences dishonest behavior.MethodWe design an incentivized laboratory experiment using a modified die-roll paradigm where participants privately observe a random draw and report the result, with higher reported numbers yielding greater monetary rewards. A probabilistic verification process introduces risk of identifying a lie and punishment, with treatments varying by verification entity (human vs. machine) and degree of ambiguity in the verification process (transparent vs. ambiguous).ResultsOur results show that under transparent verification rules, cheating magnitude does not significantly differ between human and machine auditors. However, under ambiguous conditions, cheating magnitude is significantly higher when machines verify participants' reports, reducing the prevalence of partial cheating while leading to behavioral polarization manifested as either complete honesty or maximal overreporting. The same applies when comparing reports to a machine entity under ambiguous and transparent verification rules.DiscussionThese findings emphasize the behavioral implications of algorithmic opacity in verification contexts. While machines can serve as effective auditors under transparent conditions, their black box nature combined with ambiguous verification processes may unintentionally incentivize more severe dishonesty. These insights have practical implications for designing automated oversight systems in tax audits, compliance, and workplace monitoring.}}, author = {{Protte, Marius and Mir Djawadi, Behnud}}, issn = {{2813-5296}}, journal = {{Frontiers in Behavioral Economics}}, publisher = {{Frontiers Media SA}}, title = {{{Human vs. algorithmic auditors: the impact of entity type and ambiguity on human dishonesty}}}, doi = {{10.3389/frbhe.2025.1645749}}, volume = {{4}}, year = {{2025}}, } @article{63908, author = {{Mir Djawadi, Behnud and Plaß, Sabrina and Loer, Sabrina}}, issn = {{0014-2921}}, journal = {{European Economic Review}}, publisher = {{Elsevier BV}}, title = {{{“I don’t believe that you believe what I believe”: an experiment on misperceptions of social norms and whistleblowing}}}, doi = {{10.1016/j.euroecorev.2025.105189}}, volume = {{180}}, year = {{2025}}, } @article{63911, author = {{Mir Djawadi, Behnud and Plaß, Sabrina and Loer, Sabrina}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Social Information Interventions under Competing Norms: Evidence from a Whistleblowing Experiment}}}, doi = {{http://dx.doi.org/10.2139/ssrn.5345248}}, year = {{2025}}, } @article{63912, author = {{Mir Djawadi, Behnud and Wester, Lisa}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Social Interaction and Feedback-Giving Behavior in the Sharing Economy - An Experimental Analysis}}}, doi = {{https://dx.doi.org/10.2139/ssrn.5345248}}, year = {{2025}}, } @techreport{59520, abstract = {{Normative expectations – beliefs about what others perceive as appropriate – have been shown to influence behavioural choices across various domains. We examine this concept in the context of whistleblowing, where potential whistleblowers face two competing norms: promoting fairness by reporting wrongdoing versus maintaining loyalty to peers by staying silent. We investigate how normative expectations about these two mutually exclusive actions affect reporting decisions. Specifically, we test whether providing information on the majority beliefs about either the appropriateness of whistleblowing, or of staying silent, or about both behaviours together, differentially affects the whistleblowing decision. Using an incentivized experiment with UK employees on Prolific, our study yields four key findings: First, employees are more likely to report misconduct when they believe that the majority considers whistleblowing to be appropriate. Second, they are less likely to blow the whistle when they believe staying silent is deemed appropriate. Third, this effect prevails for a particularly important subgroup: among employees who believe that the majority supports whistleblowing, the reporting probability increases substantially when they simultaneously expect that staying silent is deemed inappropriate. Fourth, providing information about both normative dimensions combined or only about the inappropriateness of staying silent significantly increases whistleblowing compared to the (no information) baseline and to information about whistleblowing appropriateness alone. These findings demonstrate the importance of normative expectations about both behavioural options for accurately predicting whistleblowing behaviour, and that social information interventions are most effective when they target behaviours where appropriateness beliefs about conflicting options are dispersed. }}, author = {{Mir Djawadi, Behnud and Plaß, Sabrina and Loer, Sabrina}}, keywords = {{Whistleblowing, Normative Expectations, Social Information Intervention, Social Norms, Economic Experiment}}, title = {{{Multiple Normative Expectations and Interventions -Experimental Evidence on Whistleblowing Behaviour}}}, year = {{2024}}, } @techreport{59521, abstract = {{Social norms fundamentally shape economic decision-making, yet individuals often systematically misperceive what others think and do, potentially leading to suboptimal social outcomes. We examine how such misperceptions affect behaviour and whether correcting them can induce a behavioural change, using whistleblowing as an application. Through survey data and an incentivized laboratory experiment, we demonstrate that while a majority of individuals (>75%) privately support whistleblowing, almost half (45.92%) misperceive the majority’s view. Both personal normative beliefs and normative expectations strongly predict whistleblowing behaviour. Their alignment is particularly noteworthy: individuals who personally support whistleblowing are more likely to report misconduct when they believe others share their views. A social information intervention revealing the true distribution of peer support affects subgroups differently: while it increases whistleblowing behaviour among individuals who already personally favour reporting misconduct, there is no effect among those who are personally resistant to it. Still, given the relatively low cost of such social information interventions, they offer an economically viable means of achieving behavioural change in at least some of the targeted individuals. }}, author = {{Mir Djawadi, Behnud and Plaß, Sabrina and Loer, Sabrina}}, keywords = {{Social Norms, Normative Expectations, Personal Normative Belief, Misperceptions, Whistleblowing}}, title = {{{“I don’t believe that you believe what I believe”: an experiment on misperceptions of social norms and whistleblowing}}}, year = {{2024}}, } @inbook{45880, author = {{Elrich, Alina and Kaimann, Daniel and Fahr, René and Kundisch, Dennis and Mir Djawadi, Behnud and Müller, Michelle and Poniatowski, Martin and Schäfers, Sabrina and Frick, Bernd}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{45--64}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Empirical Analysis in Markets for OTF Services}}}, doi = {{10.5281/zenodo.8068430}}, volume = {{412}}, year = {{2023}}, } @inbook{46088, author = {{Mir Djawadi, Behnud and Plaß, Sabrina and Schäfers, Sabrina}}, booktitle = {{Organizational Wrongdoing as the “Foundational” Grand Challenge: Consequences and Impact}}, editor = {{Gabbioneta, Claudia and Clemente, Marco and Greenwood, Royston}}, isbn = {{9781837532834}}, issn = {{0733-558X}}, pages = {{73--100}}, publisher = {{Emerald Publishing Limited}}, title = {{{Peers: Powerful or Negligible? A Systematic Review on Peer Factors and Internal Whistleblowing}}}, doi = {{10.1108/s0733-558x20230000085005}}, volume = {{85}}, year = {{2023}}, } @techreport{45616, abstract = {{Aggregation metrics in reputation systems are important for overcoming information overload. When using these metrics, technical aggregation functions such as the arithmetic mean are implemented to measure the valence of product ratings. However, it is unclear whether the implemented aggregation functions match the inherent aggregation patterns of customers. In our experiment, we elicit customers' aggregation heuristics and contrast these with reference functions. Our findings indicate that, overall, the arithmetic mean performs best in comparison with other aggregation functions. However, our analysis on an individual level reveals heterogeneous aggregation patterns. Major clusters exhibit a binary bias (i.e., an over-weighting of moderate ratings and under-weighting of extreme ratings) in combination with the arithmetic mean. Minor clusters focus on 1-star ratings or negative (i.e., 1-star and 2-star) ratings. Thereby, inherent aggregation patterns are neither affected by variation of provided information nor by individual characteristics such as experience, risk attitudes, or demographics.}}, author = {{van Straaten, Dirk and Melnikov, Vitalik and Hüllermeier, Eyke and Mir Djawadi, Behnud and Fahr, René}}, title = {{{Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes}}}, volume = {{72}}, year = {{2021}}, } @article{80, abstract = {{Models on network formation have often been extended to include the potential of network disruption in recent years. Whereas the theoretical research on network formation under the threat of disruption has thus gained prominence, hardly any experimental research exists so far. In this paper, we therefore experimentally study the emergence of networks including the aspect of a known external threat by relating theoretical predictions by Dzuibiński and Goyal (2013) to actual observed behaviour. We deal with the question if subjects in the role of a strategic Designer are able to form safe networks for least costs while facing a strategic Adversary who is going to attack their networks. Varying the costs for protecting nodes, we designed and tested two treatments with different predictions for the equilibrium network and investigated whether one of the least cost equilibrium networks was more likely to be reached. Furthermore, the influence of the subjects’ farsightedness on their decision-making process was elicited and analysed. We find that while subjects are able to build safe networks in both treatments, equilibrium networks are only built in one of the two treatments. In the other treatment, predominantly safe networks are built but they are not for least costs. Additionally, we find that farsightedness –as measured in our experiment– has no influence on whether subjects are able to build safe or least cost equilibrium networks. Two robustness settings with a reduced external threat or more liberties to modify the initial networks qualitatively confirm our results. Overall, in this experiment observed behaviour is only partially in line with the theoretical predictions by Dzuibiński and Goyal (2013).}}, author = {{Endres, Angelika Elfriede and Recker, Sonja and Mir Djawadi, Behnud and Hoyer, Britta}}, journal = {{Journal of Economic Behavior and Organization }}, pages = {{708--734}}, title = {{{Network Formation and Disruption - An Experiment: Are equilibrium networks too complex?}}}, doi = {{10.1016/j.jebo.2018.11.004}}, volume = {{157}}, year = {{2019}}, } @article{63913, author = {{Mir Djawadi, Behnud and Nieken, Petra}}, issn = {{1556-5068}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Labor Market Chances of Whistleblowers - Potential Drivers of Discrimination}}}, doi = {{10.2139/ssrn.3481126}}, year = {{2019}}, } @article{5330, abstract = {{In Internet transactions, customers and service providers often interact once and anonymously. To prevent deceptive behavior a reputation system is particularly important to reduce information asymmetries about the quality of the offered product or service. In this study we examine the effectiveness of a reputation system to reduce information asymmetries when customers may make mistakes in judging the provided service quality. In our model, a service provider makes strategic quality choices and short-lived customers are asked to evaluate the observed quality by providing ratings to a reputation system. The customer is not able to always evaluate the service quality correctly and possibly submits an erroneous rating according to a predefined probability. Considering reputation profiles of the last three sales, within the theoretical model we derive that the service provider’s dichotomous quality decisions are independent of the reputation profile and depend only on the probabilities of receiving positive and negative ratings when providing low or high quality. Thus, a service provider optimally either maintains a good reputation or completely refrains from any reputation building process. However, when mapping our theoretical model to an experimental design we find that a significant share of subjects in the role of the service provider deviates from optimal behavior and chooses actions which are conditional on the current reputation profile. With respect to these individual quality choices we see that subjects use milking strategies which means that they exploit a good reputation. In particular, if the sales price is high, low quality is delivered until the price drops below a certain threshold, and then high quality is chosen until the price increases again.}}, author = {{Mir Djawadi, Behnud and Fahr, Rene and Haake, Claus-Jochen and Recker, Sonja}}, issn = {{1932-6203}}, journal = {{PLoS ONE}}, number = {{11}}, publisher = {{Public Library of Science}}, title = {{{Maintaining vs. Milking Good Reputation when Customer Feedback is Inaccurate}}}, doi = {{10.1371/journal.pone.0207172}}, volume = {{13}}, year = {{2018}}, } @techreport{1057, author = {{Sürücü, Oktay and Mir Djawadi, Behnud and Brangewitz, Sonja}}, publisher = {{Universität Paderborn}}, title = {{{Asymmetric Dominance Effect with Multiple Decoys for Low- and High-Variance Lotteries}}}, year = {{2017}}, } @techreport{63915, author = {{Bartuli, Jenny and Mir Djawadi, Behnud and René, Fahr}}, title = {{{Business Ethics in Organizations: An Experimental Examination of Whistleblowing and Personality}}}, volume = {{No. 10190}}, year = {{2016}}, } @article{63914, author = {{Mir Djawadi, Behnud and Fahr, René and Turk, Florian}}, issn = {{1556-5068}}, journal = {{SSRN Electronic Journal}}, publisher = {{Elsevier BV}}, title = {{{Tailored Financial Incentives to Fight Medical Non-Persistence in Therapeutic Treatment: A Behavioral Economic Engineering Approach}}}, doi = {{10.2139/ssrn.2713058}}, year = {{2016}}, } @article{228, abstract = {{We investigate the pervasiveness of lying in professional contexts such as insurance fraud, tax evasion and untrue job applications. We argue that lying in professional contexts share three characterizing features: (1) the gain from the dishonest behavior is uncertain, (2) the harm that lying may cause to the other party is only indirect and (3) lies are more indirect lies by action or written statements. Conducted as a field experiment with a heterogenous group of participants during a University ‘‘Open House Day’’, our ‘‘gumball-machineexperiment’’ provides field evidence on how preferences for lying are shaped in situations typically found in professional contexts which we consider to be particularly prone to lying behavior compared to other contexts. As a key innovation, our experimental design allows measuring exact levels of cheating behavior under anonymous conditions. We find clean evidence that cheating is prevalent across all sub groups and that more than 32% of the population cheats for their own gain. However, an analysis of the cheating rates with respect to highest educational degree and professional status reveals that students cheat more than non-students. This finding warrants a careful interpretation of generalizing laboratory findings with student subjects about the prevalence of cheating in the population.}}, author = {{Fahr, Rene and Mir Djawadi, Behnud}}, journal = {{Journal of Economic Psychology}}, pages = {{48--59}}, publisher = {{Elsevier}}, title = {{{“…and they are really lying”: Clean Evidence on the Pervasiveness of Cheating in Professional Contexts from a Field Experiment.}}}, doi = {{10.1016/j.joep.2015.03.002}}, year = {{2015}}, } @article{444, abstract = {{BackgroundMedical nonpersistence is a worldwide problem of striking magnitude. Although many fields of studies including epidemiology, sociology, and psychology try to identify determinants for medical nonpersistence, comprehensive research to explain medical nonpersistence from an economics perspective is rather scarce.ObjectivesThe aim of the study was to develop a conceptual framework that augments standard economic choice theory with psychological concepts of behavioral economics to understand how patients’ preferences for discontinuing with therapy arise over the course of the medical treatment. The availability of such a framework allows the targeted design of mechanisms for intervention strategies.MethodsOur conceptual framework models the patient as an active economic agent who evaluates the benefits and costs for continuing with therapy. We argue that a combination of loss aversion and mental accounting operations explains why patients discontinue with therapy at a specific point in time. We designed a randomized laboratory economic experiment with a student subject pool to investigate the behavioral predictions.ResultsSubjects continue with therapy as long as experienced utility losses have to be compensated. As soon as previous losses are evened out, subjects perceive the marginal benefit of persistence lower than in the beginning of the treatment. Consequently, subjects start to discontinue with therapy.ConclusionsOur results highlight that concepts of behavioral economics capture the dynamic structure of medical nonpersistence better than does standard economic choice theory. We recommend that behavioral economics should be a mandatory part of the development of possible intervention strategies aimed at improving patients’ compliance and persistence behavior.}}, author = {{Mir Djawadi, Behnud and Fahr, Rene and Turk, Florian}}, journal = {{Value in Health}}, number = {{8}}, pages = {{814--822}}, publisher = {{Elsevier}}, title = {{{Conceptual Model and Economic Experiments to Explain Nonpersistence and Enable Mechanism Designs Fosterin Behavioral Change}}}, doi = {{10.1016/j.jval.2014.08.2669}}, year = {{2014}}, }