Current Projects

Why do people reject free beneficial offers?

with Caroline Goukens and Vicki G. Morwitz

In this project, we employ online experiments to investigate whether and why people reject free offers. Previous research has revealed that people tend to overestimate the benefits of zero-price products and that such offers lead to positive emotional responses (Shampanier et al. 2007). Others have shown that these positive responses are also triggered by pseudo-free offers, i.e., zero-price goods that involve non-monetary costs (Dallas and Morwitz 2018).

In a series of experiments (N=2,442), we have shown that free offers may also lead to negative responses and be rejected. Importantly, in contrast to previous studies, in our experiments we offer products that are truly profitable to participants, i.e., they will help them earn more money. Nevertheless, comparing various framings we consistently find a high share of individuals (ca. 30-60%) rejecting a product offered to them for free. Our initial results suggest that free offers may trigger suspiciousness and, thus, make people forgo even a truly free and profitable deal. In future experiments, we plan to test interventions that will help mitigate this effect.

Non-monetary costs of free and paid digital products. An empirical analysis.

In this project, I compare free and paid digital goods and services to find out whether they differ with respect to potential non-monetary and deferred costs imposed on the users. Specifically, I investigate samples of digital goods and services in three categories — online news services, and navigation and personal finance mobile applications. For each product or service in the sample I collect, code and analyze the following information: (1) types of personal data gathered, (2) privacy-relevant permissions requested, (3) presence of ads and newsletters, (4) presence and type of a license to user-generated content, (5) the content of provisions on data protection and sharing, (6) the content of warranty and liability disclaimers, (7) the content of provisions on modification of terms and services, dispute resolution and termination.

Judges and machines: how do ‘predictive justice’ tools affect judicial decision-making?

with Matthias van der Haegen

In this project, we study the influence of predictive justice on judicial decision-making in a highly realistic experimental setting. Predictive justice has risen to prominence over the past years, as the legal industry discovers the potential of machine learning within the legal domain. Predictive justice holds many advantages: it may increase efficiency, accuracy and consistency of judicial decisions. In order to make sure that these advantages are indeed achieved an no negative side effects occur that would compromise the requirements of a fair trial, we need to ascertain how these tools affect judges’ decision making.

In the experiment, judges will decide upon a fictitious landlord-tenant dispute under the assumption they are judges in a fictitious country. Relevant material such as legal provisions, precedents and doctrine will be provided, but some participants will also find an A.I-generated prediction on the probability of a landlord being liable in a given case. In our experiment, we will measure the influence of this prediction on the final decision and the decision-making process. We are currently piloting our experimental design with law students. As the next step, we plan to run the study with judges of one of the Dutch District Courts.

The impact of preferential selection on group decision-making

with Angela Dorrough, Andreas Gloeckner, and Madeline Heilman

In addition to securing gender equality, legislators claim that preferential selection will also have positive effects on corporate performance by, for example, increasing the quality of group decision-making. Previous research on preferential selection has primarily focused on individual task performance whereas the evidence on the effects on group behaviors is scarce. We plan to investigate whether preferential selection of women has an effect on the quality of group decision-making in male-dominated domains and shed light on the underlying mechanisms. Specifically, we will focus on the evaluation of men’s and women’s performance in a group task and the group members’ willingness to interact with each other after the introduction of preferential treatment.