Social Nudges as Mitigators in Privacy Choice Environments

In light of prominent data leaks and a surge of civilian surveillance systems, information service providers are confronted with an increased level of skepticism towards their privacy practices. The predicament is that not only do providers rely on users' information to optimize their services, users also risk losing the benefits of increasingly personalized services. Research on information privacy has paid great attention to explaining and predicting factors of privacy-related outcomes. On a macro level, researchers have come up with a plethora of models that are focused on deliberate and rational decision-making. In contrast, non-rational decision-making within privacy choice environments (i.e., presentation of privacy-related choices to users) has to date only been sparsely investigated. A more holistic approach to privacy-related outcomes is provided by the Person-Technology fit model. This model describes a relationship between an individual and a technology, which, when it is out of equilibrium, causes stress for the individual. Research on technology-induced stress has discovered that it affects both general stress (e.g., psychological strain) and situational stress outcomes (e.g., behavioral reactions). In this regard, research has explicated intrusive technology features (i.e., features that acquire information from and provide information to the user) as the most salient drivers of stress caused by privacy invasions for users of digital services. However, previous contributions have focused on psychological antecedents of privacy invasions, neglecting how firms may design and enhance privacy choice environments to alleviate privacy-related stress. Likewise, existing literature lacks to address how service providers can combine different technology features in the design of their services to reduce privacy-related stress. Hence, digital nudging, which refers to the practice of influencing user behavior in digital choice environments by leveraging the effect of cognitive biases and decision heuristics in user interface design, holds promising potential for service providers to overcome the detrimental effects of privacy-related stress. Specifically, research has found evidence that social nudges, defined as nudges based on social influences (i.e., unwritten social laws), can guide users to better decisions in choice environments. However, social nudging has been ignored in the context of privacy-related decision making. This thesis draws on four studies that were conducted to investigate how intrusive technology features affect privacy-related outcomes, and how to utilize social nudges as mitigating technology features in privacy choice environments. The first study describes a laboratory experiment and a subsequent field experiment, which investigated how the intrusive effects of unintentional voice activations of smart home assistants drive user strain and interpersonal conflicts through privacy invasions, while the study demonstrates how anthropomorphic design features alleviate user strain. The second study elaborates upon the intrusive effect of push- based information delivery on users’ geographical location information disclosure through privacy concerns, which can be attenuated by signals of social proof in mobile app stores. Finally, for the third study, we cooperated with the German startup Partner der Wissenschaft UG to investigate how low message interactivity affects users’ information disclosure in a chatbot conversation, which we enhanced by employing platform self-disclosure nudges. In sum, this thesis highlights the importance of understanding the technology-stressor-strain causal relationship for information services by providing significant contributions: First, the findings extend previous research on technology-induced stress by illuminating specific design mechanisms for digital services. In this regard, the studies demonstrate how intrusive technology features drive privacy-related stressors and ultimately cause users to disengage with the respective information services. Thereby, we address the calls for particular and context- related intrusive technology features with applicable design recommendations from Ayyagari, Grover, and Purvis (2011) and Speier, Vessey, and Valacich (2003). Second, this thesis expands the Person-Technology model by a new layer of technology features that help to mitigate and overcome users’ privacy-related stress. More specifically, this study illuminates how social nudges can be utilized as mitigating strategies for technology-induced stress and hereby effectuate better privacy-related outcomes. In this regard, this thesis addresses the calls for research from Kretzer and Maedche (2018) and Mirsch, Lehrer, and Jung (2017) on specific and context-related digital nudges with applicable design recommendations by putting together a catalog of social nudges for privacy choice environments