nep-cbe New Economics Papers
on Cognitive and Behavioural Economics
Issue of 2023‒07‒24
six papers chosen by
Marco Novarese
Università degli Studi del Piemonte Orientale

  1. Virtue Signals By Deivis Angeli; Matt Lowe; The Village Team; Matthew Lowe
  2. Testing for Manipulation: Experimental Evidence on Dark Patterns By Bogliacino, Francesco; Leonardo, Pejsachowicz; Liva, Giovanni; Lupiáñez-Villanueva, Francisco
  3. Loss Aversion, Risk Aversion, and the Shape of the Probability Weighting Function By Matthew D. Rablen
  4. Replication Report on Altmann et al. (2022) By Bachler, Sebastian; Erhart, Andrea; Holzknecht, Armando
  5. Transparent app design reduces excessive usage time and increases willingness to pay compared to common behavioral design - A framed field experiment By Timko, Christina; Adena, Maja
  6. Less is More Expensive: The Cognitive Cost of Bulk Buying and the Effect of Regulating the Display of Unit Prices By Bauner, Christoph; Hossain, Mallick

  1. By: Deivis Angeli; Matt Lowe; The Village Team; Matthew Lowe
    Abstract: We study whether tweets about racial justice predict the offline behaviors of nearly 20, 000 US academics. In an audit study, academics that tweet about racial justice discriminate more in favor of minority students than academics that do not tweet about racial justice. Racial justice tweets are more predictive of race-related political tweets than political contributions, suggesting that visibility increases informativeness. In contrast, the informativeness of tweets is lower during periods of high social pressure to tweet about racial justice. Finally, most graduate students mispredict informativeness, more often underestimating than overestimating, reducing the welfare benefits of social media.
    Keywords: virtue signals, social signalling , discrimination, audit experiment, political behavior
    JEL: C93 D91 I23 J15 J71 D83
    Date: 2022
  2. By: Bogliacino, Francesco (Universidad Nacional de Colombia); Leonardo, Pejsachowicz; Liva, Giovanni; Lupiáñez-Villanueva, Francisco
    Abstract: Several countries and supranational authorities are debating whether to regulate or ban dark patterns, deceptive users’ interfaces. A key empirical component to this debate is how to assess manipulation. In this study, we develop a transaction test which measure to what extent the dark patterns lead to decisions inconsistent with elicited preferences. We conducted a large preregistered online study (N=7430) with a representative population of six countries to identify both the effect of dark patterns on consumers’ choice consistency and the potential counteracting effects of protective measures. Our treatments include three dark patterns - hiding information on the product, toying-with-emotions, and the use of psychological profiling to personalize the display for the consumer – and two versions of a protective measure that discloses information and requires subject to confirm the selection. Participants are assigned to either a motivated delay or incentive compatible time pressure environment, allowing to identify the impact of treatments on consumers paying enough attention and on situationally vulnerable consumer. Dark patterns do manipulate consumers, showing remarkable effects on both average and vulnerable consumers. The cool down intervention has a null effect. We stress test the transaction test in a controlled experiment, where the preference elicitation is incentive compatible, we collect repeated measurement of choices among lotteries and we manipulate the extent of the mistake. In this additional experiment, the TWE treatment resulted in greater inconsistency compared to the control group, particularly in lotteries where the point of indifference was less likely to be located at the boundaries of the MPL grid. While subjects learned to be consistent through multiple rounds of choice and with decision problems further from their area of indifference, the learning effect is less pronounced under the TWE treatment.
    Date: 2023–06–29
  3. By: Matthew D. Rablen
    Abstract: Loss aversion, risk aversion, and the probability weighting function (PWF) are three central concepts in explaining decisionmaking under risk. I examine interlinkages between these concepts in a model of decisionmaking that allows for loss averse/tolerant stochastic reference dependence and optimism/pessimism over probability distributions. I give a preference interpretation to commonly observed shapes of PWF and to risk aversion. In particular, I establish a connection between loss aversion and both risk aversion and the inverse-S PWF: loss aversion is a necessary condition to observe each of these phenomena. The results extend to distinct PWFs in the gain and loss domains, as under prospect theory.
    Keywords: probability weighting, rank dependent expected utility, loss aversion, risk aversion, reference dependence, optimism, pessimism, prospect theory
    JEL: D91 D81 D01
    Date: 2023
  4. By: Bachler, Sebastian; Erhart, Andrea; Holzknecht, Armando
    Abstract: In the paper of, Altmann et al. (2022) the authors investigate whether positive effects which are due to behavioral policy interventions in policytargeted domains come along with negative effects in policy non-targeted domains. Using lab and online experiments where subjects have to solve one policy-focused decision task and one non-focused background task, the authors show that increasing incentives or steering attention to the former led to higher attention spans, lower default adherence rates, and a higher choice quality in the decision task. However, because of steering participants focus to the decision task, lower choice quality and lower attention spans in the background task emerged as a consequence, which was particularly pronounced among individuals with lower cognitive capabilities and complex decision tasks. Essentially, the authors also describe that the negative effects in the background tasks offset the positive effects in the decision task, ultimately yielding a net-zero effect overall. Therefore, the authors emphasize policymakers to also consider the potential negative cognitive spillovers in order to not overestimate the benefits of behavioral policy interventions. All the results the authors in the main text report are significant on 5% and 1% significance levels. All findings presented in the main text of the paper can be replicated using the original Stata code and verified thoroughly using R. Additionally, we performed two robustness tests to ensure the reliability of the paper’s main results, and they remained consistent. Hence, the reported findings in the paper appear to be robust.
    Date: 2023
  5. By: Timko, Christina; Adena, Maja
    Abstract: Smartphone app designers often use behavioral design to influence users, increase sales, and boost advertising revenue. Behavioral design relies on elements ranging from app appearance to black-box algorithms and personalization. It commonly exploits behavioral biases, such as the lack of self-control. Consumers are seldom aware of such design and usually have no control over it. Aiming to protect consumers, the recently enacted European Digital Services Act requires app design to be more transparent and adjustable. In a framed field experiment, we document that behavioral design increases app usage time, especially in the case of vulnerable users. An app version that adds transparency and offers protection features helps to overcome temptation. The higher willingness to pay for the transparent version shows that the positive effects of app transparency and increased consumer protection might not only materialize on the demand side but may also challenge current practices on the supply side.
    Keywords: smartphone app, filtering algorithm, transparency, consumer protection, field experiment
    JEL: C93 O33 D83 L86 M38 D18
    Date: 2023
  6. By: Bauner, Christoph; Hossain, Mallick
    Keywords: Consumer/Household Economics, Institutional and Behavioral Economics, Marketing
    Date: 2023

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