Contributions published at Information Management (Gerhard Schwabe)

Community-based healthcare is a promising approach to tackling workforce shortage in healthcare, especially in low- and middle-income countries. Community health workers (CHWs) are lay cadres that bridge healthcare disparities by living in the community where they should provide basic health services, mainly through education. However, high attrition rates and underperformance of these health workers limit the scope of such programs. In addition, mobile health is not the hoped-for silver bullet to solve the two challenges. This paper examines two pilot projects using mobile health for non-communicable disease care from an empowerment perspective. We propose design knowledge of mobile health for the structural empowerment of CHWs. Furthermore, we evaluate their psychological empowerment by analyzing mobile health's intended and unintended consequences. Finally, our study demonstrates how the empowerment of CHWs could help overcome the persisting challenges and lead to a sustainable and resilient health system.

Adherence to therapy is a significant issue when treating patients who suffer from adiposity. To improve therapy success, modern technology can be used to assist in increasing patients' adherence to therapy. One such technology is the Digital Companion application, which includes a mobile app for patients to track their therapy progress and a web interface for doctors to access further analytics on their patients' ongoing therapy outcomes. This bachelor thesis investigates how we can contribute to the Digital Companion application by developing a Natural Language Processing engine that analyzes the journal entries written by patients in the Digital Companion mobile application. The analysis we provide consists of a topic-based sentiment analysis-oriented algorithm. Through this approach, our aim is to identify which aspects of the therapy are going well for the patient and which are not. This may not always be apparent to the doctor due to their limited time and resources when preparing for a specific patient's consultation and their lack of oversight of what occurs between consultations. With our proposed model, we achieved better precision and recall scores than other industry-leading models when evaluating the patients' data, demonstrating the effectiveness of our approach for the task at hand.

The importance of fairness in algorithmic decisions and artificial intelligence has grown continuously over the last years and the research on it has expanded to include the study of fairness perception. At the same time, the influence of cultural background on perception of fairness in algorithmic decisions remains largely unexplored in the do¬mains of cross-cultural fairness studies and fairness in artificial intelligence. The purpose of this thesis is to conduct a 3 (country, independent) x 2 (scenario, independent) x 3 (strategy, dependent) factorial design preliminary experiment to find out whether the perception of fairness in contexts of algorithmic decisions differs across cultures. To assess this, a survey was developed, detailing the use of an algorithm for decision making in a school admission and in a loan approval scenario, and how the employment of different fairness notions (independence, separation, and sufficiency) would influence those decisions. The survey was distributed online to 300 participants, 100 each per country (Germany, South Africa, and the United States of America), who were asked to rank the three fairness notions from fairest to least fair per scenario. The resulting data was analysed based on mean rank per strategy and rank frequency. Statistical tests employed to prove significance were not applicable to the data type at hand – neither ordinal, nor ranked. For further analysis, the 3 x 2 x 3 matrix was extended by the independent variables gender, age, and openness towards AI. The more independent variables were introduced to make specific statements, the more diverse the observed tendencies were. Nevertheless, results show a clear overall preference for one strategy as the fairest: separation. Except for scenario 1 in South Africa, where independence was ranked as fairest. The required insights on fairness perception in South African culture to explain this divergent tendency are not present in current literature on cross-cultural fairness.

Chronic diseases are a worldwide problem. However, many cases could be prevented or treated by lifestyle changes. The use of mobile health technologies like health apps offers new opportunities to support treatments. This thesis examines how the journal of such a health app affects the patient-doctor collaboration. The patients and doctors make treatment agreements about the behavior of patients in the phase between consultations. The patients have the agreements stored on the health app and can make notes about their execution. The doctors can review the notes in the journal before the consultation. They then discuss the journal with the patient in the consultation. In this thesis the interviews conducted after the follow-up consultation are analyzed. The patients report predominantly positive effects on the patient-doctor collaboration. For example, patients report that the journal had positive effects on the patient-doctor relationship and that they could collaboratively create a treatment plan that they believe to be sustainable. They also report that the doctor’s influence affected the motivation of the patients positively through the journal in the phase in between consultations. The insights about the importance of the patient-doctor relationship were used to extend an existing theoretical model.

Recent regulatory changes have enabled NCAA student-athletes to proft from their name, image, and likeness (NIL), departing from previous policies requiring those athletes to maintain their amateur status. However, despite the changes, it is unlikely that all the approximately 500,000 NCAA student-athletes will proft from NIL contracts. Within this context, we study how to design a fair and inclusive solution that may help all student-athletes se- cure NIL fnancial resources. Following a design science approach, we defne design requirements after interviewing student-athletes. Subsequently, we derive three design principles: inclusiveness, fairness, and transparency. Thereafter, we suggest a blockchain-based artifact that satisfes all design principles. Our idea lies in designing collectibles as non-fungible tokens (NFTs) that pay diferent roy- alties whenever a transaction (purchase or exchange) happens in diferent markets (primary or secondary). Finally, we evaluate our solution by discussing its features with current student-athletes.

Online reviews have become a ubiquitous source of information for consumers, and response authors play a critical role in addressing customer feedback. However, the vast amount and complexity of online reviews pose a significant challenge for those who respond to them. By implementing artificial intelligence (AI), the possibility of enhancing both the efficiency and quality of online review responses arises. In this thesis, it is examined how the use of various degrees of AI assistance affects the performance of response authors across a variety of efficiency and quality metrics. In order to address this question, a survey was conducted to gather data on the perceived quality of review responses composed by novice and professional authors in four distinct settings: without any AI support (B setting), with partial AI support (I setting), with AI-powered response generator support (G setting), and with fully automated AI-generated responses (G-AI setting). In addition, data on the efficiency of the response authors was recorded during writing sessions in each setting. The results show that the use of AI significantly improves the efficiency of response authors. In particular, the G setting greatly reduced the writing time for both professional and novice authors. Furthermore, the use of GPT-3, an advanced AI language model, resulted in significantly higher quality responses than those which a competing AI system and most of the other work configurations were able to produce. Based on these findings, a work configuration is proposed which combines the strengths of AI systems with human authors to optimize the online review response process. This proposed configuration aims to maximize efficiency and response quality while minimizing the workload on human authors. In conclusion, this thesis provides valuable insights into the potential of AI support to enhance the performance of response authors in the context of online reviews. The proposed optimal work configuration provides a practical solution for businesses and individuals looking to optimize their response authoring process.

Digital agents are considered a general-purpose technology. They spread quickly in private and organizational contexts, including education. Yet, research lacks a conceptual framing to describe interaction with such agents in a holistic manner. While focusing on the interaction with a pedagogical agent, that is, a digital agent capable of natural-language interaction with a learner, we propose a model of learning activity based on activity theory. We use this model and a review of prior research on digital agents in education to analyze how various characteristics of the activity, including features of a pedagogical agent or learner, influence learning outcomes. The analysis leads to identification of information systems research directions and guidance for developers of pedagogical agents and digital agents in general. We conclude by extending the activity theory-based model beyond the context of education and show how it helps designers and researchers ask the right questions when creating a digital agent.

Trust is a crucial component for successful transactions regardless of whether they are executed in physical or virtual spaces. Blockchain technology is often discussed in the context of trust and referred to as a trust-free, trustless, or trustworthy technology. However, the question of how the trustworthiness of blockchain platforms should be demonstrated and proven to end users still remains open. While there may be some genuine trust in the blockchain technology itself, on an application level trust in an IT artifact needs to be established. In this article, we examine how trust-supporting design elements may be implemented to foster an end user's trust in a blockchain platform. We follow the design science paradigm and suggest a practically useful set of design elements that can help designers of blockchain platforms to build more trustworthy systems.

Workplace learning is often used to train employees systematically. New in this context is workplace learning with the help of a pedagogical agent (PA). Following Actions Design Research (ADR), this paper describes organizational training for telephone service using such PA. To develop the training, existing employee telephone service problems were analyzed, and the content of the learning program was determined based on this analysis. Subsequently, a PA was developed, implemented, and used in three municipalities. The evaluation of the learning outcome shows promising results but also yields some challenges: even though the employees improved in various aspects of the learning, they also developed a perception of surveillance. This research concludes with the formulation of design principles and suggestions for the organizational embedding of a PA in a workplace setting.

To address global problems, intergovernmental collaboration is needed. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts of data to perform well. However, data sharing between governments is limited. A possible solution is federated learning (FL), a decentralised AI method created to utilise personal information on edge devices. Instead of sharing data, governments can build their own models and just share the model parameters with a centralised server aggregating all parameters, resulting in a superior overall model. By conducting a structured literature review, we show how major intergovernmental data sharing challenges like disincentives, legal and ethical issues as well as technical constraints can be solved through FL. Enhanced AI while maintaining privacy through FL thus allows governments to collaboratively address global problems, which will positively impact governments and citizens.

Governments across the globe are facing pressure to increase the speed of their digital transformation to meet the needs of the digital society while fulfilling their primary task of delivering public value. While researchers agree on the importance of the public sector for public value creation, recently, more and more studies have recognized the criticality of collaboration between the public and private sectors for successful public value creation. In our research, we conduct a qualitative survey. We examine the idea of collaboration between the public and the private sectors in more detail and add the citizens' perspective. We highlight the need for joint forces for optimal public value creation, identify ways to achieve this, and determine what digital technologies can support this process.

In diesem Artikel wird das Ergebnis einer Studie aufgearbeitet, die ergab, dass Behörden trotz ihrer Bemühungen, bürgerfreundlicher zu werden, ihre Ziele nicht erreichen können, solange sie auf Effizienz und Rechtskonformität konzentriert bleiben. Denn dadurch erkennen sie die Transparenzprobleme, mit denen die Einwohnerinnen und Einwohner heute konfrontiert sind, nicht. Diese sind u.a. Informations-, Geschäftsprozess-, Kosten-, Gesetzesintransparenz etc. Der Artikel benennt diese, um die Grundlage für deren Bewältigung zu legen und eine klare Strategie zu ermöglichen, die den Zweck und den Umfang einer Dienstleistung verdeutlicht und ein Datenintegrationskonzept, das über alle Dienstleistungskanäle reicht, ermöglicht.

The process of answering reviews on an online review platform is vital for restaurants and hotels to manage customer relations. The hospitality industry can outsource this process to specific providers. The company this thesis is based on uses an Algorithmic Management approach to manage the review-responding process conducted by the authors. The study aims to discuss the potential and enhance Algorithmic Management processes in the field of online Customer Feedback Management. The research is split into three parts, a prerequisite analysis of the previous implementation, an implementation phase, and an evaluation of the implementation. In the prerequisite analysis, the first iteration of the Algorithmic Matching and Algorithmic Control process was evaluated with interviews, a survey, and videos. For the matching of reviews to authors, the efficiency improved by 38.44%, and a shift in administrator roles was observed. Consequently, administrators started to rely on assisting tools to control the author’s responses. In the implementation phase, an interview with the administrator was conducted, and code analysis was performed to define the requirements. The implementation, on the one hand, advanced the review-author matching algorithm. On the other hand, created the Performance Score and, thus, a measure for Algorithmic Control. The evaluation of the implementation bases the findings on interviews with the administrator, videos, and sample records of author-admin responses. The evaluation revealed a further improvement of efficiency by 23.71%. Additionally, the Performance Score has a correlation coefficient of 0.8849 compared to the administrator’s defined experience score, showing an accurate mental model mapping. To conclude, the research shows the potential of Algorithmic Management in online Customer Feedback Management, with an increase in efficiency, a reduction in bias, and increasing the transparency of the Algorithmic Matching and Algorithmic Control processes.

This research paper uses two experiments to show the impact of semi-autonomous to autonomous drones in firefighting operations. It evaluates the possible applications using two workshops with experienced professional firefighters. These workshops reveal a variety of possible uses in different major missions. The need for deployment seems to be particularly high for fire and natural hazards. Based on this, deployment scenarios for two experiments were created. They are intended to show a future in which drone systems take on independent missions and actively and independently support the emergency services in their work. The tasks carried out by the drones illustrate the organizational consequences in the immediate vicinity of the operational command, as well as the technical challenges posed to such systems. Based on surveys before and after the experiments, a high willingness of the firefighters to collaborate with this system results. Especially in the so-called chaos phase, the drones are decision support devices on the one hand, and on the other hand they can autonomously perform standardized tasks. Ultimately, this leads to rapid, safe and efficient incident management. This work opens up space for valuable collaboration between drones and firefighters, while illustrating challenges and limitations of such systems.

The government as a Platform (GaaP) concept is gaining popularity in recent years. However, only a few examples of its implementation exist and have been described in the academic literature. In part, this is because GaaP is a challenging research subject due to the lack of conceptual definition as well as its intertwined nature with digital technologies, institutions, and multiple actors involved. This thesis aims to investigate whether the GaaP approach could be applied to the digital systems of the Canton of Zurich in the context of the Ukrainian refugee crisis. Using the design science research methodology, a high-level architecture of a public service platform based on Gaap principles and practices is proposed. Through in-depth qualitative interviews with representatives from 13 organizations involved in the crisis, key challenges and existing digital solutions in the Canton of Zurich are identified. Following TOGAF's architecture development method, business architecture in a form of a refugee journey and an information system architecture of the proposed solution is presented. The solution is demonstrated and evaluated by stakeholders. Based on the results, evidence is presented that the current situation could be enhanced with the use of GaaP principles and recommendations for further research are given. Keywords: Digital Platforms, Government as a Platform, Public Sector, Digital Platforms for Crisis Management.

The goal of this thesis is to analyze what the potential applications for human-drone collaboration in public entities are, which organizational and procedural consequences the police force is faced with in order to integrate autonomous drones and what challenges arise during a police operation with autonomous drone support. Literature research and interviews with test subjects and police representatives resulted in potential use cases such as assisting the police during police operations, arriving first at a crime scene and providing visual information, helping fire fighters find the source of a fire, enabling rescue teams locate missing people, and many more. Consequences for the police force are the implementation of novel technology, training officers to use it efficiently and having to maintain reputation. Managing communication is the most dominant challenge for the police when operating with an autonomous drone.

Non-communicable diseases (NCDs) are the leading cause of global deaths and an increasing economic burden. Adherence to treatment among NCD patients is generally low due to the demanding treatment plans (i.e., lifestyle changes). Persuasive systems are a promising approach to complement traditional NCD care to support patients in behavior change and increase long-term adherence. However, we ask ourselves: To what extent does current persuasive systems research address the need for continuous, comprehensive, and adaptive NCD care? And where are the blind spots that need to be addressed by developers and researchers of more comprehensive persuasive systems? To answer these questions, we analyzed 57 articles on persuasive systems for NCD care in a systematic literature review. Our results show clear gaps in research and design of persuasive systems. We conceptualize comprehensive persuasive systems in the Fogg-PDSA matrix combining social (e.g., medical professionals) and technical aspects (i.e., persuasive applications) of persuasion.

Software projects rely on what we call project archetypes, i.e., pre-existing mental images of how projects work. They guide distribution of responsibilities, planning, or expectations. However, with the technological progress, project archetypes may become outdated, ineffective, or counterproductive by impeding more adequate approaches. Understanding archetypes of software development projects is core to leverage their potential. The development of applications using machine learning and artificial intelligence provides a context in which existing archetypes might outdate and need to be questioned, adapted, or replaced. We analyzed 36 interviews from 21 projects between IBM Watson and client companies and identified four project archetypes members initially used to understand the projects. We then derive a new project archetype, cognitive computing project, from the interviews. It can inform future development projects based on AI-development platforms. Project leaders should proactively manage project archetypes while researchers should investigate what guides initial understandings of software projects.

More and more large technology companies have developed their conversational agents and made them more popular as they advanced. The advancements are far from over and there are many improvements to be made. The Information Management Research Group of the University of Zurich has developed its own conversational agent with multiple external partners. The project is called Heinzelmännli and the prototype in this thesis is called Mo. Mo is used specifically in financial consultations. Trust is a large proponent of financial services which is why it is important to explore the impact of Mo on the trust in those services. This thesis explores the trust relations and the impact on trust Mo has in those financial consultations, but also the optimal autonomy of Mo regarding trust. Experiments were conducted in two Swiss banks where insights were gathered. Through those insights, results are observed and discussed in this thesis to answer questions regarding the impact on trust, as well as the autonomy of Mo.

In recent years, the research field of conversational agents has made more and more progress. We have now reached a point where conversational agents are so advanced that they can be used in financial advisory encounters to support advisors in their work. The research project around the conversational agent Heinzelmännli has the goal of doing just that, but it has not been evaluated yet, what influence Heinzelmännli has on conversational efficiency and effectiveness. This is precisely where this work closes an important research gap. First, efficiency and effectiveness factors were defined, which can be used to measure conversational efficiency and effectiveness. Then, these factors were used to measure the conversational efficiency and effectiveness of traditional financial advisory encounters (without Heinzelmännli), financial advisory encounters with an optimal version of Heinzelmännli, and financial advisory encounters with a non-optimal version of Heinzelmännli. Finally, the data from these three settings were compared. This thesis concludes that a differentiated picture emerges concerning conversational efficiency and effectiveness: While the settings with the different versions of Heinzelmännli seem less efficient than the traditional setting when looking at the factors, Heinzelmännli seems to promote conversational effectiveness because the common understanding among the participants seems to increase. These observations are stronger for the non-optimal setting than for the optimal one. This means that although the non-optimal setting is less efficient than the optimal one, it increases conversational effectiveness more. From the results, it can be interpreted that it is important to minimise the error rate and processing time of input for digital agents and that it is important to allow clients and advisors to share knowledge by using the artefacts.