Contributions published at Information Management (Gerhard Schwabe)

Only 50% of patients adhere to a prescribed therapy plan in developed countries, in less developed ones the percentage is even smaller (World Health Organization, 2003). One key point for the low adherence rate is a suboptimal healthcare-professional-to-patient communication, which itself originates from medical terminology (Härter et al., 2005). Furthermore, patients have a hard time remembering all therapy steps, because the information from the healthcare professional overload the short-term memory of the patient (Sandberg et al., 2008). These problems also exist in the widely used model of the “shared decision-making”. Consequently, this work tries to answer following research question. How can we support the shared decision-making in consultations with patients with adiposities via an application? To answer this question a prototype has been made in three iterations. This prototype was evaluated via consultations with healthcare professionals and patients. In this work, five design principles have been identified, which support the understanding of the patient about the therapy decisions. It was also found, how one can guarantee the usability and embedding in the consultation. But some healthcare professionals noted that they will decide about the usage of the application individually for each new patient. These results can be used as a guideline to create applications, which support shared decision-making in health-related consultations. This support should then increase the adherence of the patient to the therapy.

Conversational agents or digital assistants have continued gaining traction as an integral part of our personal and professional interactions. However, there is still room for improvement, particularly in professional advisory sessions or meetings. If banks manage to integrate conversational agents effectively into advisory sessions, they can attain new clients with a unique service experience and increase the perceived quality of the interaction. The University of Zurich's Information Management Research Group, in cooperation with external partners, has developed a prototype called Heinzelmännli to explore opportunities in this emerging field. The contribution of this thesis is twofold. Firstly, the effects the integration of a conversational agent has on interaction and communication are assessed based on experiments conducted in two Swiss banks. Secondly, based on the insights gathered, ThinkLets were developed to promote effective behaviors and limit destructive habits. Finally, the results are discussed in the context of conversational rights and interaction structure, as well as the perceived quality of service encounters. Also, suggestions are made on further improvements and developments of the conversational agent to support the points raised.

This thesis deals with the further development of the Reachability Trainer into the Reachability Trainer 3.0. It will be transformed into a conversational pedagogical agent that supports new employees of a public administration in telephone-based citizen service training during the onboarding process. Integrated into a social blended learning concept, the Reachability Trainer 3.0 offers six exercises with which the employees can train limitless how to act in different situations. The conversations between the employees and the Reachability Trainer 3.0 during the exercises take place at different degrees of structuring. For testing, two public administrations provide four groups of four to six people each. The groups work on different training programmes. Separated testing people from the public administrations perform the exercises too. Feedback is collected from all to answer which possibilities current technologies offer to develop such an agent, in which ways it can support new employees during onboarding and how it can be prevented from causing a feeling of being monitored by the Reachability Trainer.

This thesis examines the impact of Blockchain on the United Nations’ Sustainable Development Goals (SDGs). It includes two parts: Firstly, a comprehensive literature review is conducted to investigate published evidence of Blockchain as an enabler/inhibitor of the 169 targets stated in the SDGs. The study observed a positive impact of Blockchain on achieving targets in financial inclusion, supply chain management, fundraising, energy usage, environmental surveillance, health insurance and govern-ance. Increased energy consumption and money laundering due to cryptocurrencies are assessed as inhibitors. In the second part of the work, four fundraising platforms and four supply chain service providers are interviewed to examine practical evidence of Blockchain as an enabler/inhibitor for achieving the targets. A contribution to the targets’ achievement can be determined for all startups. However, it is observed that the Blockchain is only one piece of the puzzle, whereby the design of the business idea and the combination of additional technologies such as the Internet of Things (IoT) as a whole must be considered.

This thesis examines the public value creation in digital ecosystems. It, therefore, aims to elaborate on success factors that lead to successful public value creation in digital ecosystems. For this purpose, interviews were conducted with representatives of digital ecosystems as part of a multiple case study, which was then evaluated using qualitative analysis. Through the analysis combined with the literature review, a number of success factors were determined that positively influence the process of public value creation. In a second step, a fuzzy-set Qualitative Comparative Analysis (fsQCA) was performed, which compiles configuration paths from these success factors. The results of this configuration analysis suggest different configurations paths that show in which configurations the success factors lead to successful public value creation for platform owners and complementors.

This study analyzes the data collected within the ReAdvisor project at the Department of Informatics in collaboration with company re:spondelligent. Research work takes place from October 2021 to March 2022. The thesis gathers three types of data: videos, interviews and questionnaires, which are then analyzed qualitatively and quantitatively. The impact of the AI-human interaction on a socio-technical system is researched through: (a) analyzing changes in response authoring practices with the influence of the AI (through videos), (b) analyzing authors' perception of the AI on the intelligent co-writing (through interviews and questionnaires), and (c) researching what possible business models the modern machine learning tools enable. Results suggest that some of the introduced AI tools save time for students, but not for professionals. The AI tools regarded as most useful by both groups of authors are the response generator and the quality checker, in that order. All of the tools are reported to have room for improvement. Overall, the new system is perceived as a positive technological development which impacts the socio-technical system by enabling the collaboration between the AI and the humans. Lastly, the study develops a categorization of 11 AI-enabled business models and discusses strategic options to be used for enhancing re:spondelligent's business model.

Online peer-to-peer (P2P) sales of used and or high-value goods are gaining more and more relevance today. However, since potential buyers cannot physically examine product quality during online sales, information asymmetries and consequently uncertainty and mistrust that already exist in offline sales are exacerbated in online markets. Authenticated data platforms have been proposed to solve these problems by providing authenticated data about the negotiation object, integrating it into text-based channels secured by IT. Yet, we know little about the dynamics of online negotiations today and the impact of the introduction of authenticated data on online negotiation behaviors. We address this research gap based on two experimental studies along with the example of online used-car trade. We analyze users’ communicative and strategic actions in current P2P chat-based negotiations and examine how the introduction of authenticated data affects these behaviors using a conceptional model derived from literature. Our results show that authenticated data can promote less complex negotiation processes and more honest communication behavior between buyers and sellers. Further, the results indicate that chats with the availability of authenticated data can positively impact markets with information asymmetries. These insights provide valuable contributions for academics interested in the dynamics of online negotiations and the effects of authenticated data in text-based online negotiations. In addition, providers of trade platforms who aim to advance their P2P sales platforms benefit by achieving a competitive advantage and a higher number of customers.

In this master's thesis, the use of a digital twin for foreign students is examined in the context of a self-sovereign identity. Enabling international students to control their personal data and information in a transparent manner when dealing with public authorities. As such, this thesis explores how the creation of an SSI ecosystem in Switzerland could facilitate the process of issuing and signing of veri able credentials to foreign students. To achieve this the research follows a design science research approach to develop a technical prototype that aims to produce an SSI based wallet for foreign students. This will enable them to control and maintain their identities in a decentralized manner. The prototype was evaluated with various stakeholders representing relevant roles from a typical SSI ecosystem. This enabled to gather feedback from different perspectives from which design principles were formulated. As such, this research serves as a basis for further research in the area of self sovereign identity.

The Canton of Zurich would like to stimulate to adoption of blockchain projects in the public sector of Switzerland. Two methodologies have been developed to evaluate when the use of blockchain makes sense and which types to use. This paper aims to extend the reach of these methodologies by transforming them into a digital questionnaire. This was done by developing a methodology on how to transform the previous established research into the new format and by evaluating if this transformation was successful.

The digital twin technology has evolved tremendously in recent years, being applied in different industries, such as product life cycle management, manufacturing, waste management, smart cities, among others. A digital twin is a virtual replica of a physical entity comprised of three main components: the physical entity, its digital counterpart, and the environment in which they interact. The scope of this technology seems to have no limits, even being considered on humans. One of its most recent applications is towards citizens - the so-called "Citizen Twins". This thesis explores the application of the citizen twins' technology in Switzerland. To achieve this, academic help is required first to define and understand concepts of this technology. Likewise, this literature review defines a first list of needs and opportunities within the Swiss community in the social and technological fields. Then, interviews with Swiss citizens are carried out to validate these requirements, identify new ones, and create a first version of the citizen twins' prototype. Finally, this first version and its objectives are assessed through a focus group. Based on the collected results, the final prototype's version is generated, and the  findings from this solution and those of the literature are discussed. In this way, this research serves as a source for further study in the citizen twins' field.

The purpose of this thesis is the development of a process that compares manually and automatically generated financial advice protocols, created as part of the Heinzelmännli project. Common natural language processing techniques to measure textual similarity, such as semantic similarity, are not sufficient for the specific requirements in this context. Therefore, four additional similarity measures are developed to capture the similarity of two financial advice protocols as effectively as possible. The comparison process incorporates regulatory aspects as well as similarity measures that integrate the proposed transactions and information about the customers. The findings suggest that the Sentence-BERT language model in combination with the four custom similarity scores produces the most plausible results. In future work, the effectiveness of the comparison process must be explored by analyzing the automatically generated protocols, which have yet to be completed.

The growing amount of online reviews plays a significant role in a business' image and performance. Businesses in the hospitality industry often lack necessary resources to organize and manage online customer feedback and are therefore likely to search for alternative ways to handle this. AI-based technologies may offer valuable solutions. However , there is currently little research on if and how AI solutions may support the process of responding to online customer feedback in the hospitality industry. This paper presents and evaluates a concept for assisting customer feedback management with automatically generated responses to online reviews. Our solution contributes to ongoing investigations into text generation applications for supporting human authors and also proposes new approaches and potential business models for managing online customer feedback.

The emergence of blockchain projects enables new ways of collaboration between untrusted parties. Each of these projects, however , only exists because stakeholders of these projects find common ground. If this common ground is not found, blockchains are forked – organizationally and technically – which endangered major blockchain systems like Bitcoin or Ethereum. To assure the operation of such projects and, thus, to improve their governance, it is crucial to understand their stakeholders. This research conducted a literature review and a survey to (1) identify blockchain stakeholders and to (2) understand their interests as well as underlying motives for their interests. This research has two main contributions: a stakeholder map, which serves as a lens to study stakeholders of public blockchains, and exemplary insights from the application of this lens comprising of 74 survey responses. Consequently, this research provides a novel tool for stakeholder analysis in academia and practice to improve blockchain governance.

When major corporations build and manage own platforms, most of the conflicts are resolved internally. With the rise of blockchain systems, also blockchain- based platforms are increasingly tried out, which are governed in a decentralized fashion. But moving from hierarchical efficiency to a democratic inclusiveness, in which blockchain proponents believe, is difficult: the variety of included actors raise a variety of conflicts, when platform users become platform complementors or even owners. To manage these conflicts, it is neces- sary to analyze each actor in detail. This paper reflects on the developments within an ongoing enterprise blockchain consortium in a small European country in the automotive domain from a governance perspective. We portray the consortium’s stakeholder conflicts, pro- pose solutions for these conflicts and relate them to lit- erature on blockchain governance. Our findings contex- tualize several theoretical stances, emphasizing the im- portance of the organizational over the technological embedment in blockchain governance.

The electronic trade with used goods has been flourishing for many years and is constantly developing. Many private buyers and sellers find themselves able to offer used items or even purchase them below their new value through various market platforms (intermediaries). However, particular problems and challenges in the trade of used goods promote uncertainty and mistrust, especially high-involvement products. The seller of a used object usually has extensive knowledge about its previous use, hidden problems, and thus the current condition of the good. This information asymmetry is difficult to bridge, as the seller usually exploits the opportunity. Therefore, the buyer is dependent on the seller's willingness to release information, which may be incomplete and untrue, or suggest false facts. Especially in the online used-car market, which is the focus of this dissertation, these problems can be observed very distinctly. The seller of a used vehicle knows its history, previous treatment, and possible accidents and damages. At the same time, the buyer has to trust the seller's statements due to the lack of physical checkability. The resulting uncertainty about the seller and the quality of the vehicle results in distrust and a lower appreciation of the car. Akerlof described this in his popular work as the "Market for Lemons" (Akerlof 1970), in which even vehicles in good condition have no chance of being sold at an adequate price. The key to increase market transparency by reducing information asymmetry, and thus uncertainty and mistrust, is effective and efficient communication among market participants that supports and promotes the exchange of information. This exchange usually occurs during the negotiation phase between buyer and seller and strongly determines the negotiation outcome. The quantity and quality of communication can be enhanced by technical support. Authenticated data, technically immutable and credibly available in a market, has enormous potential here. This data allows the transfer of trust to some extent from the interpersonal level to technology (e.g., blockchain) and enables a better assessment of the actual state of the vehicle without physical inspection. Further, this data can be treated as an asset and be part of the trade in addition to the actual object of negotiation. However, how integration of such data from a data market into a platform can be done to increase the benefit of the participants and the platform has largely not been explored. This dissertation describes the research project conducted to design and develop features to support party communication and negotiation in the online used-car market to address the named challenges. In addition, a conceptual model of a future used-car market is developed that incorporates these features as well as other features from related research. The thesis is composed of four self-contained essays. The research content thereby builds on each other. It sheds light on the impact of blockchain-based authenticated data on the behavior of market participants in the online used-car market and the benefits that platforms experience by providing the data to all market participants. The underlying research follows the design science activities of the DSR cycle model (Hevner 2007; Briggs and Schwabe 2011): 1) discovering problems and opportunities, 2) designing and building artifacts and processes, and 3) validating artifacts and processes. The first two essays exploratively examined buyers’ and sellers’ expectations and preferences, and the disclosure and negotiation behavior with the availability of authenticated data. This exploration corresponds with the first DSR activity of discovering problems and opportunities. Essay 1 uses the results of an experiment using a market simulation game of the used-car market, the “car-market game”, to show the requirements of market participants to support their disclosing behavior during negotiation. Essay 2 complements this by examining, also through an experiment, what negotiation behavior participants exhibit currently and under the availability of authenticated data. The focus was on changes in patterns of negotiation procedures in terms of complexity and dishonest and deceptive behavior. The third essay incorporates the results of DSR activity two and three and elaborates on the design and development of new negotiation support elements, building on the findings and requirements of the first two essays. The elements were integrated into a text-based negotiation chat and evaluated to “authenticated data chat” in an experiment as a result of DSR activity three. The fourth essay shows how the used-car market can evolve while providing authenticated data to support market participants in their communication, information exchange, and trading of data about the vehicle and generate benefits for all market participants and competitive advantages for the platform operators. For this purpose, various artifact evaluations have also been conducted and summarized in related research performed by our research group. As the used-car market continuously evolves towards e-commerce, support for controlling sensitive information and negotiation between market participants becomes increasingly essential. There is extensive research in the negotiation literature, and textbased communication media such as instant messaging and chat have been extensively studied. But there is still a lack of insight into how dishonest behavior, mistrust, and uncertainty as a result of information imbalances in online negotiations can be reduced through the use of appropriate technology and design. In addition, platforms do not know exactly how they will need to evolve into a future used-car market in order to remain competitive in the long term. This dissertation contributes to fill these gaps.

Markets in which similar goods of different qualities are sold suffer from information asymmetries and their negative consequences. Dealers have established themselves, and mediate these markets through their use of quality signals. While these signals help to mitigate information asymmetries, these markets still function well below their optimum: a large share of goods sold are overpriced, and most of the benefits are reaped by intermediaries. In this paper we build on prior research that proposes the use of blockchain as an enabler for trusted, decentralized asset documentation. Applying a socio-technical lens, we describe how blockchain-enabled multi-party certification affords dealers the action potential to send signals that are more closely correlated to the unobservable quality of the underlying good (i.e., signals with a higher fit) than the signals they send today. We then both theorize and experimentally explore the market effects of the two types of signals. Using data from a laboratory market experiment with 210 participants, we find empirical evidence that multi-party certification affords dealers the action potential to send signals of significantly higher fit than those sent by intermediaries alone, leading to a reduction in information asymmetries, a more efficient allocation of goods, and an increase in market fairness.

This thesis takes dHealth Network as a case study and explores the blockchain platform’s token distribution and transaction visualization. To explore the application of blockchain network on health and medical domain, especially the data trading, the research pro- posed a price model to figure out the correlation between different data categories’ price indicators and related variables, i.e., patients’ willingness of trading data, the security level of data categories, and the information entropy of data categories. It turns out the first two variables have a more significant influence on the price indicators than the in- formation entropy of data categories. This paper suggests two methods to two methods are suggested to stimulate data and token transaction on the network.

A common goal can inspire companies and research institutions to embark on an adventure together despite competition. However, tensions arise soon after a project starts. While tensions are a focal part of innovative processes, research consortia need to pay close attention to them to avoid malicious developments. In this study, we investigate a research consortium consisting of industrial partners and research institutions. We identify the root cause of tensions and explore how Design Thinking artifacts can catalyze the positive energy of tensions while reducing negative impacts. We find that Design Thinking artifacts are pivotal in managing tensions and adapting their role depending on the context.

Conversational agents (CA) have drawn increasing interest from HCI research. They have become popular in different aspects of our lives, for example, in the form of chatbots as the primary point of contact when interacting with an insurance company online. Additionally, CA find their way into collaborative settings in education, at work, or financial advisory. Researchers and practitioners are searching for ways to enhance the customer's experience in service encounters by deploying CA. Since competence is an important treat of a financial advisor, they only accept CA in their interaction with clients if it does not harm their impression on the client. However, we do not know how the social presence of the CA affects this perceived competence. We explore this by evaluating three prototypes with different social presences. For this, we conducted a video-based online survey. In contrast to prior studies focusing on single human-computer interaction, our study explores CA in a dyadic setting of two humans and one CA. First, our results support the Computers-Are-Social-Actors paradigm as the CA with a strong social presence was perceived as more competent than the other two designs. Second, our data show a positive correlation between CA's and advisor's competence. This implies a positive impact of the CA on the service encounter as the CA and advisor can be seen as a competent team.