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Nudging the Use of Facemasks

An Empirical Study on the Effects of Social Norms, Disclosure and Warnings in Germany

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Business Administration>Management




Term Paper: The concept of nudge The concept of nudge is a special way of influencing behavior in the field of behavioral economics. By definition, boost is “any aspect of the choice architecture that changes people’s behavior in a predictable way, without prohibiting any choice or significantly changing their economic incentives” (Thaler & Sunstein, 2008, p. 6). The selection framework represents the environment in which individuals make decisions (Thaler & Sunstein, 2008, p. 3). As described by Thaler and Sunstein, since the origin of the concept, the government has a legitimate interest in implementing push strategies to shape citizen behavior (2008, p. 13). Boosters have a wide range of applications, from warning smokers (Jolls, 2015, p. 1412) to using social norms to save energy (Allcott, 2011, p. 1082). Since nudge is a relatively new field of research, its effectiveness and which nudge is effective are not completely clear. The latest research by D'Adda et al. (2017, p. 10) and Esposito et al. (2017, p. 11) Indicates that nudges have limited influence on people's behavior, or the unintentional influence of nudges (see et al., 2013, p. 580). Sunstein (2017, p. 5) even described “some pushes are ineffective or counterproductive” based on type or situation. In order to classify boosts and check the effectiveness of different boosting interventions, Hummel and Maedche (2019, p. 3) conducted a systematic review of empirical research. They divided boosts into ten categories and classified them according to their effects. Ranked. Default rules, warnings, and triggering implementation intentions show the highest effect size (Hummel & Maedche, 2019, p. 20). Sunstein (2017, p. 5) agrees with these findings and believes that default rules are the most promising type of promotion. Although Thaler and Sunstein (2008, p. 8) describe nudges in the context of improving people's lives, critics have raised concerns that nudges are not an appropriate policy tool. Rizzo and Whitman (2008, p. 908) warned that this may lead the government to accept more external control. Further research claims that it takes advantage of the imperfections of human beings, and nudges itself to patronize people who are too stupid to decide for themselves (Goodwin, 2012, p. 86; Salinger and White, 2011, p. 928) ). This study aims to investigate whether nudges can significantly increase the likelihood of wearing a mask when not required by law. Three different nudge treatments are used to influence the behavior of participants: social norms, warnings, and information disclosure. In addition, the control group without any intervention was used to measure and compare treatment effects. 2. In the first step of the method, individual behaviors were observed in the town centers of the three largest cities in North Rhine-Westphalia: Cologne, Düssel-dorf and Dortmund (North Rhine-Westphalia) State Government Office IT.NRW, 2020). The goal is to identify and classify voluntary masks based on specific circumstances. Three hours of observation resulted in 94 missed opportunities to wear masks voluntarily. Examples include using crowded sidewalks or standing in front of frequently visited stores without a mask. The results were used to develop a questionnaire containing 12 items that describe the situation even if the law does not require a valid reason to wear a mask (see Appendix A: Online Survey). Participants used a seven-point Likert scale from 0 (unlikely) to 6 (very likely) to assess the likelihood of wearing a mask in these situations. A total of 140 participants between the ages of 17 and 59 participated in the online survey. They were randomly assigned to one of the treatment groups or the control group. Each of the four groups consisted of 35 participants. The average age of all groups was 25.2 years (SD = 3.5), and 59.8% of participants were women. High school and college students accounted for the majority of the sample (7.6%; 43.3%). All participants live in North Rhine-Westphalia, Germany. For each of the three nudging treatments, a prompt composed of pictures and text related to COVID-19 was created (see Appendix B: nudging intervention). To ensure that participants perceive the prompt, they must answer the questions related to the prompt before they can access the survey. It is designed as a cover story based on I am not a robot verification code. 3. Results The average probability of wearing masks in different groups was calculated. The control group (CG) had the lowest average score (M = 3.93, SD = 1.33). The warning group (WG) and the disclosure group (DG) have similar average values ​​(M = 4.43, SD = .55; M = 4.49, SD = .87), while the social norm group (SG) shows the highest average rating ( M = 4.86, standard deviation = 1.41). A one-way analysis of variance (ANO-VA) has been calculated to test for differences between groups. Levene's test of questionnaire scores is significant. Therefore, no homogeneity assumption was given (F (3, 136) = 23.161, p = .000), and Welch-ANOVA was calculated to account for unequal variances between groups. The results of the analysis of variance showed that there were significant differences between the groups (F (3, 50.54) = 2.065, p = .017). Dunnet-T3 corrected post-hoc tests showed significant average differences between CG and SG (p = .000) and between SG and WG (p = .011). In addition, SG is significantly different from DG (p = .009). Read Less