The effects of user assistance systems on user perception and behavior

The rapid development of information technology (IT) is changing how people approach and interact with IT systems (Maedche et al. 2016). IT systems can increasingly support people in performing ever more complex tasks (Vtyurina and Fourney 2018). However, people's cognitive abilities have not evolved as quickly as technology (Maedche et al. 2016). Thus, different external factors (e.g., complexity or uncertainty) and internal conditions (e.g., cognitive load or stress) reduce decision quality (Acciarini et al. 2021; Caputo 2013; Hilbert 2012). User-assistance systems (UASs) can help to compensate for human weaknesses and cope with new challenges. UASs aim to improve the user's cognition and capabilities, benefiting individuals, organizations, and society. To achieve this goal, UASs collect, prepare, aggregate, analyze information, and communicate results according to user preferences (Maedche et al. 2019). This support can relieve users and improve the quality of decision-making. Using UASs offers many benefits but requires successful interaction between the user and the UAS. However, this interaction introduces social and technical challenges, such as loss of control or reduced explainability, which can affect user trust and willingness to use the UAS (Maedche et al. 2019). To realize the benefits, UASs must be developed based on an understanding and incorporation of users' needs. Users and UASs are part of a socio-technical system to complete a specific task (Maedche et al. 2019). To create a benefit from the interaction, it is necessary to understand the interaction within the socio-technical system, i.e., the interaction between the user, UAS, and task, and to align the different components. For this reason, this dissertation aims to extend the existing knowledge on UAS design by better understanding the effects and mechanisms during the interaction between UASs and users in different application contexts. Therefore, theory and findings from different disciplines are combined and new theoretical knowledge is derived. In addition, data is collected and analyzed to validate the new theoretical knowledge empirically. The findings can be used to reduce adaptation barriers and realize a positive outcome. Overall this dissertation addresses the four classes of UASs presented by Maedche et al. (2016): basic UASs, interactive UASs, intelligent UASs, and anticipating UASs. First, this dissertation contributes to understanding how users interact with basic UASs. Basic UASs do not process contextual information and interact little with the user (Maedche et al. 2016). This behavior makes basic UASs suitable for application contexts, such as social media, where little interaction is desired. Social media is primarily used for entertainment and focuses on content consumption (Moravec et al. 2018). As a result, social media has become an essential source of news but also a target for fake news, with negative consequences for individuals and society (Clarke et al. 2021; Laato et al. 2020). Thus, this thesis presents two approaches to how basic UASs can be used to reduce the negative influence of fake news. Firstly, basic UASs can provide interventions by warning users of questionable content and providing verified information but the order in which the intervention elements are displayed influences the fake news perception. The intervention elements should be displayed after the fake news story to achieve an efficient intervention. Secondly, basic UASs can provide social norms to motivate users to report fake news and thereby stop the spread of fake news. However, social norms should be used carefully, as they can backfire and reduce the willingness to report fake news. Second, this dissertation contributes to understanding how users interact with interactive UASs. Interactive UASs incorporate limited information from the application context but focus on close interaction with the user to achieve a specific goal or behavior (Maedche et al. 2016). Typical goals include more physical activity, a healthier diet, and less tobacco and alcohol consumption to prevent disease and premature death (World Health Organization 2020). To increase goal achievement, previous researchers often utilize digital human representations (DHRs) such as avatars and embodied agents to form a socio-technical relationship between the user and the interactive UAS (Kim and Sundar 2012a; Pfeuffer et al. 2019). However, understanding how the design features of an interactive UAS affect the interaction with the user is crucial, as each design feature has a distinct impact on the user's perception. Based on existing knowledge, this thesis highlights the most widely used design features and analyzes their effects on behavior. The findings reveal important implications for future interactive UAS design. Third, this dissertation contributes to understanding how users interact with intelligent UASs. Intelligent UASs prioritize processing user and contextual information to adapt to the user's needs rather than focusing on an intensive interaction with the user (Maedche et al. 2016). Thus, intelligent UASs with emotional intelligence can provide people with task-oriented and emotional support, making them ideal for situations where interpersonal relationships are neglected, such as crowd working. Crowd workers frequently work independently without any significant interactions with other people (Jäger et al. 2019). In crowd work environments, traditional leader-employee relationships are usually not established, which can have a negative impact on employee motivation and performance (Cavazotte et al. 2012). Thus, this thesis examines the impact of an intelligent UAS with leadership and emotional capabilities on employee performance and enjoyment. The leadership capabilities of the intelligent UAS lead to an increase in enjoyment but a decrease in performance. The emotional capabilities of the intelligent UAS reduce the stimulating effect of leadership characteristics. Fourth, this dissertation contributes to understanding how users interact with anticipating UASs. Anticipating UASs are intelligent and interactive, providing users with task-related and emotional stimuli (Maedche et al. 2016). They also have advanced communication interfaces and can adapt to current situations and predict future events (Knote et al. 2018). Because of these advanced capabilities anticipating UASs enable collaborative work settings and often use anthropomorphic design cues to make the interaction more intuitive and comfortable (André et al. 2019). However, these anthropomorphic design cues can also raise expectations too high, leading to disappointment and rejection if they are not met (Bartneck et al. 2009; Mori 1970). To create a successful collaborative relationship between anticipating UASs and users, it is important to understand the impact of anthropomorphic design cues on the interaction and decision-making processes. This dissertation presents a theoretical model that explains the interaction between anthropomorphic anticipating UASs and users and an experimental procedure for empirical evaluation. The experiment design lays the groundwork for empirically testing the theoretical model in future research. To sum up, this dissertation contributes to information systems knowledge by improving understanding of the interaction between UASs and users in different application contexts. It develops new theoretical knowledge based on previous research and empirically evaluates user behavior to explain and predict it. In addition, this dissertation generates new knowledge by prototypically developing UASs and provides new insights for different classes of UASs. These insights can be used by researchers and practitioners to design more user-centric UASs and realize their potential benefits

Digital Human Representations for Health Behavior Change: A Structured Literature Review

Organizations have increasingly begun using digital human representations (DHRs), such as avatars and embodied agents, to deliver health behavior change interventions (BCIs) that target modifiable risk factors in the smoking, nutrition, alcohol overconsumption, and physical inactivity (SNAP) domain. We conducted a structured literature review of 60 papers from the computing, health, and psychology literatures to investigate how DHRs’ social design affects whether BCIs succeed. Specifically, we analyzed how differences in social cues that DHRs use affect user psychology and how this can support or hinder different intervention functions. Building on established frameworks from the human-computer interaction and BCI literatures, we structure extant knowledge that can guide efforts to design future DHR-delivered BCIs. We conclude that we need more field studies to better understand the temporal dynamics and the mid-term and long-term effects of DHR social design on user perception and intervention outcomes

The insurance effect of renewable distributed energy resources against uncertain electricity price developments

To combat climate change, many countries all around the world currently foster the development of renewable energy sources (RES). However, in contrast to traditional energy systems that relied on few central power plants, RES are typically highly decentral and spread all over a country. Against this backdrop, the promotion of a decentralization of the energy system by fostering a regional balance of energy demand and supply with a corresponding increase in energy democracy is seen as a promising approach. However, energy democracy driven by an increasing involvement of consumers requires adequate investments of consumers in their own local RES in order to become active players, usually called prosumers. Risk associated with uncertain long-term electricity price developments is generally seen as a barrier to investments. In contrast, we describe that an investment in distributed energy resources (DERs) may actually serve as a consumer's insurance against price risk. Our results set out that the consideration of risk-aversion may actually positively shift an investment decision in renewable DERs. This is due to the prosumer becoming more self-sufficient and less dependent on uncertain price developments. To analyze such an insurance effect, we create a formal decision model considering the prosumer's risk-aversion and derive the prosumer's optimal investment in renewable DERs. However, our results also indicate that under some circumstances the insurance effect disappears: When a prosumer turns into a predominant producer, the prosumer is again exposed to risk in terms of uncertain revenues. Ultimately, our work highlights the importance of a consideration of the insurance effect when assessing an investment in renewable DERs

The insurance effect of renewable distributed energy resources against uncertain electricity price developments

To combat climate change, many countries all around the world currently foster the development of renewable energy sources (RES). However, in contrast to traditional energy systems that relied on few central power plants, RES are typically highly decentral and spread all over a country. Against this backdrop, the promotion of a decentralization of the energy system by fostering a regional balance of energy demand and supply with a corresponding increase in energy democracy is seen as a promising approach. However, energy democracy driven by an increasing involvement of consumers requires adequate investments of consumers in their own local RES in order to become active players, usually called prosumers. Risk associated with uncertain long-term electricity price developments is generally seen as a barrier to investments. In contrast, we describe that an investment in distributed energy resources (DERs) may actually serve as a consumer's insurance against price risk. Our results set out that the consideration of risk-aversion may actually positively shift an investment decision in renewable DERs. This is due to the prosumer becoming more self-sufficient and less dependent on uncertain price developments. To analyze such an insurance effect, we create a formal decision model considering the prosumer's risk-aversion and derive the prosumer's optimal investment in renewable DERs. However, our results also indicate that under some circumstances the insurance effect disappears: When a prosumer turns into a predominant producer, the prosumer is again exposed to risk in terms of uncertain revenues. Ultimately, our work highlights the importance of a consideration of the insurance effect when assessing an investment in renewable DERs

Never trust, always verify: a multivocal literature review on current knowledge and research gaps of zero-trust

In response to weaknesses of current network security solutions, the zero-trust model follows the idea that no network – whether internal or external – is trustworthy. The concept of zero-trust is enjoying increasing attention in both research and practice due to its promise to fulfil complex new network security requirements. Despite zero-trust's advantages over traditional solutions, it has not yet succeeded in replacing existing approaches. Uncertainty remains regarding the concept's distinct benefits and drawbacks for organisations and individuals, which hinders a holistic understanding of zero-trust and wide-spread adoption. Research can make valuable contributions to the field by systematically providing new insights into zero-trust. To support researchers in this endeavour, we aim to consolidate the current state of the knowledge about zero-trust and to identify gaps in the literature. Thus, we conduct a multivocal literature review, analysing both academic and practice-oriented publications. We develop a research framework for zero-trust to structure the identified literature and to highlight future research avenues. Our results show that the academic literature has focused mainly on the architecture and performance improvements of zero-trust. In contrast, the practice-oriented literature has focused on organisational advantages of zero-trust and on potential migration strategies. However, economic analyses and user-related studies have been neglected by both academia and practice. Future research may rely on our findings to advance the field in meaningful ways.</p