To Reduce Bias, You Must Identify It First! Towards Automated Gender Bias Detection

Stereotypical gender representation in textbooks influences the personal and professional development of children. For example, if women do not pursue a STEM career because of gender stereotypes, this is not only an individual problem but also negative for society in general. It is hence crucial that textbooks do not convey gender stereotypes but are gender-balanced. Currently, textbook analysis is predominantly conducted manually, if at all. However, this is time-consuming and consequently cost-intensive. Therefore, as part of a design science research project, we developed a gender language analyzer. Our initial prototype is already capable of automatically analyzing textbooks and recommending suggestions regarding gender-balancing. We will further improve our prototype in the next design science research cycle (e.g., by integrating self-learning techniques). With this tool, publishers will be able to automatically analyze textbooks to reduce gender bias. Moreover, we provide the scientific community with design knowledge regarding automated identification of gender bias

FeelFit – Design and Evaluation of a Conversational Agent to Enhance Health Awareness

In the course of digitalisation, healthcare systems are undergoing a major transformation. The generation and processing of health-related data are intended to improve health concerns. However, individual health awareness remains inadequate. To counteract this problem, issues in the fields of health awareness, wearable health monitoring systems, conversational agents, and user interface design were identified. Meta-requirements were derived from these issues and then converted into design principles. We developed the FeelFit conversational agent under consideration of those design principles. FeelFit measures vital parameters with various wearable sensors and presents them, enriched with personalised health information, to the user in the form of a conversation via individually configurable input and output devices. The conversational agent was evaluated by two experiments with 90 participants and a workshop. The results confirm a positive usability and task fulfilment of our conversational agent. Compared to known applications, the participants highlighted the more natural interaction and seamless integration of various sensors as strengths of FeelFit

Beyond the Rating Matrix: Debiasing Implicit Feedback Loops in Collaborative Filtering

Implicit feedback collaborative filtering recommender systems suffer from exposure bias that corrupts performance and creates filter bubbles and echo chambers. Our study aims to provide a practical method that does not inherit any exposure bias from the data given the information about the user, the choice, and the choice set associated with each observation. We validated the model’s functionality and capability to reduce bias and compared it to baseline mitigation strategies by simulation. Our model inherited little to no bias, while the other approaches failed to mitigate all bias. To the best of our knowledge, we are first to identify a feasible approach to tackle exposure bias in recommender systems that does not require arbitrary parameter choices or large model extensions. With our findings, we encourage the recommender systems community to move away from rating-matrix-based towards discrete-choice-based models

Digital Transformation in Automotive: Drivers of Effective Sales Behaviors During Servitization at a German Car Manufacturer

Manufacturers deem servitization a competitive remedy, facing heightened customer expectations and competition amidst their digital transformation. Servitization refers to a shift from offering products to offering digital product-service systems. Although previous research inquired about traditional service operations, research into the servitization’s digital nature remains nascent and insights addressing the behavioral changes associated with such transformations are lacking. This paper presents an ongoing case study at a German car manufacturer, sharing insights into which organizational and individual factors drive salespeople’s behaviors during servitization based on twelve interviews and eleven workshops. The analysis suggests that usage clarity is key to mediating behaviors. Organizational factors driving behaviors include information dissemination, service orientation, and formalization. Individual factors driving behaviors include technology affinity and involvement. The paper contributes to understanding salespeople’s behavioral changes during introduction of digital product-service systems. Recommendations on designing personnel training programs to improve the marketing of digital product-service systems are derived

Die Auswirkungen der Blockchain Technologie auf Geschäftsmodellinnovation

Fueled by the success of cryptocurrencies such as Bitcoin, blockchain technology has emerged as an interesting and promising technological solution in a variety of industries. However, it remains unclear to what extent blockchain technology possesses the potential to transform existing business models or to enable new business models. So far, scientific studies have been predominantly technologically driven; the economic viability, e.g., in the form of innovative, sustainable business models, as well as the acceptance of blockchain technology have not been sufficiently investigated. This dissertation addresses this research gap and focuses on three domains: The financial sector, the temporary employment industry, and the healthcare sector. To investigate the impact of blockchain technology on business model innovation as well as its impact on existing business models, quantitative and qualitative methods are applied in the form of a mixed-method approach. Within this approach, (acceptance) models, tools, methods, and prototypes are developed. Moreover, recommendations for decision makers are elaborated and central economic, ecological, political, legal, social, and ethical challenges and opportunities of blockchain technology for business models and business model innovations are identified and discussed. The results of this dissertation support economic and political decision makers as well as researchers in the fields of blockchain technology and business model innovation

Towards a Business Model Taxonomy of Startups in the Finance Sector using Blockchain

In recent years, the blockchain technology has aroused growing interest in science and practice. Particularly the financial sector has high expectations of this technology, as is evidenced by numerous established start-ups and large amounts of venture ca

Learnings from the design and acceptance of the German COVID-19 tracing app for IS-driven crisis management: a design science research

Abstract Background This article investigates the research problem of digital solutions to overcome the pandemic, more closely examining the limited effectiveness and scope of the governmental COVID-19 tracing apps, using the German COVID-19 tracing app (Corona-Warn-App) as an example. A well-designed and effective instrument in the technological toolbox is of utmost importance to overcome the pandemic. Method A multi-methodological design science research approach was applied. In three development and evaluation cycles, we presented, prototyped, and tested user-centered ideas of functional and design improvement. The applied procedure contains (1) a survey featuring 1993 participants from Germany for evaluating the current app, (2) a gathering of recommendations from epidemiologists and from a focus group discussion with IT and health experts identifying relevant functional requirements, and (3) an online survey combined with testing our prototype with 53 participants to evaluate the enhanced tracing app. Results This contribution presents 14 identified issues of the German COVID-19 tracing app, six meta-requirements, and three design principles for COVID-19 tracing apps and future pandemic apps (e.g., more user involvement and transparency). Using an interactive prototype, this study presents an extended pandemic app, containing 13 potential front-end (i.e., information on the regional infection situation, education and health literacy, crowd and event notification) and six potential back-end functional requirements (i.e., ongoing modification of risk score calculation, indoor versus outdoor). In addition, a user story approach for the COVID-19 tracing app was derived from the findings, supporting a holistic development approach. Conclusion Throughout this study, practical relevant findings can be directly transferred to the German and other international COVID-19 tracing applications. Moreover, we apply our findings to crisis management theory—particularly pandemic-related apps—and derive interdisciplinary learnings. It might be recommendable for the involved decision-makers and stakeholders to forego classic application management and switch to using an agile setup, which allows for a more flexible reaction to upcoming changes. It is even more important for governments to have a well-established, flexible, design-oriented process for creating and adapting technology to handle a crisis, as this pandemic will not be the last one

Exploring User Acceptance Determinants of COVID-19-Tracing Apps to Manage the Pandemic

International audienceTracing infectious individuals and clusters is a major tactic for mitigating the pandemic. This paper explores the factors impacting the intentions and actual use of COVID-19 contact tracing apps based on a technology acceptance model. A partial least squares structural equation model has been applied to understand determinants for the usage of tracing apps based on a large sample (N = 2,398) from more than 30 countries (mainly from Germany and USA). Further, the paper presents a classification of COVID-19 apps and users. Through that, the study provides insights for technologists and designers of tracing apps as well as policy makers and practitioners to work toward enhancing user acceptance. Moreover, the results are abstracted to general social participation with apps in order to manage future strategies. The theoretical contribution of this work includes the results of our acceptance model and a classification of COVID-19 tracing and tracking apps