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Tax evasion is an economic crime that nearly all world countries suffer from. Its consequences are countless, including poor public spending on infrastructure projects and social welfare programs, low economic growth and development, institutional mistrust and fiscal deficits. For developing countries in particular, targeting development programs and infrastructural investments requires an efficient tax collection policy to generate sufficient funds for such purposes. This makes the tax evasion problem a critical one and countering it extremely policy relevant. Based on evidence that shows how the understanding of taxpayers' behavior is an essential factor in fighting evasion, this paper aims to test different factors that might incentivize citizens using a behavioral and experimental approach, in non-Western educated industrialized rich democracies (non-WEIRD) countries, to comply more.

This paper uses a survey experiment to examine the impact of different behavioral primes on tax compliance behavior. Specifically, it observes subjects' compliance behavior in two contexts: voice and empathy. A total of 273 students from a big public university in Egypt were randomly selected to participate in this study.

In the “Voice” treatment, the explanatory variable (VOICE) was found statistically significant, thus confirming the hypothesis that democracy, through having a voice in the decision-making process, affects compliance positively. As for the “Empathy” treatment, the explanatory variable (EMPATHY) was also found significant. This confirms the second hypothesis that triggering feelings of empathy, through highlighting the good cause behind public spending that uses taxpayers' money, affects compliance behavior positively.

Despite the fact that the experimental methodology is a methodology with high internal validity, examining the impact of a specific intervention on behavior, a replication of the experiment in other contexts might be useful in increasing the external validity of the findings. Specifically, conducting this experiment on a nonstudent sample might lead to even more powerful results by increasing the ecological validity of the results.

This study advocates a more behaviorally informed public policy. Specifically, Egyptian policymakers are recommended to adopt behavioral nudges as a complement to existing policies. The authors believe the findings, if confirmed by repeated experiments (lab, lab-in-the-field and rational choice theories on both student and non-student samples) in a number of Arab countries, might also help in offering cost-effective nudges for the Arab world policymakers, where culture and the political context are to a great extent similar.

The findings of the study have a number of social implications. Higher tax compliance will enable higher levels of public spending on a number of social targets such as education, health and welfare programs.

While the study builds on recent research examining how to incentivize tax compliance, it simultaneously seeks to make three contributions. First, the study design aims to apply recent advances in behavioral sciences (impact of voice and empathy) in a policy area that has not seen much use of such interventions in the Egyptian context (i.e. tax compliance). Second, the study is policy relevant in the sense that it aims to increase the effectiveness of existing government policies by complementing them with behavioral primes. Third, there is nearly no literature found applying this topic in a non-WEIRD country such as Egypt.

The creation and dissemination of fake news can have severe consequences for a company’s brand. Researchers, policymakers and practitioners are eagerly searching for solutions to get us out of the “fake news crisis”. Here, one approach is to use automated tools, such as artificial intelligence (AI) algorithms, to support managers in identifying fake news. The study in this paper demonstrates how AI with its ability to analyze vast amounts of unstructured data, can help us tell apart fake and real news content. Using an AI application, this study examines if and how the emotional appeal, i.e., sentiment valence and strength of specific emotions, in fake news content differs from that in real news content. This is important to understand, as messages with a strong emotional appeal can influence how content is consumed, processed and shared by consumers.

The study analyzes a data set of 150 real and fake news articles using an AI application, to test for differences in the emotional appeal in the titles and the text body between fake news and real news content.

The results suggest that titles are a strong differentiator on emotions between fake and real news and that fake news titles are substantially more negative than real news titles. In addition, the results reveal that the text body of fake news is substantially higher in displaying specific negative emotions, such as disgust and anger, and lower in displaying positive emotions, such as joy.

This is the first empirical study that examines the emotional appeal of fake and real news content with respect to the prevalence and strength of specific emotion dimensions, thus adding to the literature on fake news identification and marketing communications. In addition, this paper provides marketing communications professionals with a practical approach to identify fake news using AI.