TY - CHAP A1 - Batzel, Katharina A1 - Baum, Katharina T1 - Exploring information flow on twitter: social network analysis on gender-specific sedicine T2 - AMCIS Proceedings 2022 N2 - To date, sex and gender differences play only a minor role in medical research and practice, thereby putting individuals’ health at risk. Gender-specific medicine, or the practice of taking these differences into account when conducting research and treating patients so far is being discussed primarily by experts. With people increasingly using social media such as Twitter for sharing and searching for health-related information online, Twitter can potentially educate about gender-specific medicine. However, little is known about the information circulation and the structure of interactions on the Twitter network discussing this topic. Results of a network analysis show that the network exhibits a community-structure, with information exchange being limited and concentrated in silos. This indicates that there is untapped potential for acquiring new information by users through interacting with individuals outside their community. Public health officials may benefit from this insight and tailor online campaigns to enhance awareness on gender-specific medicine. Y1 - 2022 SN - 978-1-958200-00-1 IS - 1548 PB - AIS CY - Atlanta ER - TY - CHAP A1 - Rudian, Sylvio Leo A1 - Haase, Jennifer A1 - Pinkwart, Niels T1 - Predicting creativity in online courses T2 - 2022 International Conference on Advanced Learning Technologies (ICALT) N2 - Many prediction tasks can be done based on users’ trace data. This paper explores divergent and convergent thinking as person-related attributes and predicts them based on features gathered in an online course. We use the logfile data of a short Moodle course, combined with an image test (IMT), the Alternate Uses Task (AUT), the Remote Associates Test (RAT), and creative self-efficacy (CSE). Our results show that originality and elaboration metrics can be predicted with an accuracy of ~.7 in cross-validation, whereby predicting fluency and RAT scores perform worst. CSE items can be predicted with an accuracy of ~.45. The best performing model is a Random Forest Tree, where the features were reduced using a Linear Discriminant Analysis in advance. The promising results can help to adjust online courses to the learners’ needs based on their creative performances. KW - prediction KW - online course KW - trace data KW - creativity Y1 - 2022 SN - 978-1-6654-9519-6 SN - 978-1-6654-9520-2 U6 - https://doi.org/10.1109/ICALT55010.2022.00056 SP - 164 EP - 168 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Krause, Hannes-Vincent A1 - Baumann, Annika T1 - The devil in disguise BT - malicious envy’s impact on harmful interactions between social networking site users T2 - ICIS 2021: user behaviors, engagement, and consequences N2 - Envy constitutes a serious issue on Social Networking Sites (SNSs), as this painful emotion can severely diminish individuals' well-being. With prior research mainly focusing on the affective consequences of envy in the SNS context, its behavioral consequences remain puzzling. While negative interactions among SNS users are an alarming issue, it remains unclear to which extent the harmful emotion of malicious envy contributes to these toxic dynamics. This study constitutes a first step in understanding malicious envy’s causal impact on negative interactions within the SNS sphere. Within an online experiment, we experimentally induce malicious envy and measure its immediate impact on users’ negative behavior towards other users. Our findings show that malicious envy seems to be an essential factor fueling negativity among SNS users and further illustrate that this effect is especially pronounced when users are provided an objective factor to mask their envy and justify their norm-violating negative behavior. Y1 - 2021 UR - https://aisel.aisnet.org/icis2021/user_behaivors/user_behaivors/21 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Sultanow, Eldar A1 - Chircu, Alina A1 - Wüstemann, Stefanie A1 - Schwan, André A1 - Lehmann, Andreas A1 - Sept, André A1 - Szymaski, Oliver A1 - Venkatesan, Sripriya A1 - Ritterbusch, Georg David A1 - Teichmann, Malte Rolf T1 - Metaverse opportunities for the public sector T2 - International Conference on Information Systems 2022 : Special Interest Group on Big Data : Proceedings N2 - The metaverse is envisioned as a virtual shared space facilitated by emerging technologies such as virtual reality (VR), augmented reality (AR), the Internet of Things (IoT), 5G, artificial intelligence (AI), big data, spatial computing, and digital twins (Allam et al., 2022; Dwivedi et al., 2022; Ravenscraft, 2022; Wiles, 2022). While still a nascent concept, the metaverse has the potential to “transform the physical world, as well as transport or extend physical activities to a virtual world” (Wiles, 2022). Big data technologies will also be essential in managing the enormous amounts of data created in the metaverse (Sun et al., 2022). Metaverse technologies can offer the public sector a host of benefits, such as simplified information exchange, stronger communication with citizens, better access to public services, or benefiting from a new virtual economy. Implementations are underway in several cities around the world (Geraghty et al., 2022). In this paper, we analyze metaverse opportunities for the public sector and explore their application in the context of Germany’s Federal Employment Agency. Based on an analysis of academic literature and practical examples, we create a capability map for potential metaverse business capabilities for different areas of the public sector (broadly defined). These include education (virtual training and simulation, digital campuses that offer not just online instruction but a holistic university campus experience, etc.), tourism (virtual travel to remote locations and museums, virtual festival participation, etc.), health (employee training – as for emergency situations, virtual simulations for patient treatment – for example, for depression or anxiety, etc.), military (virtual training to experience operational scenarios without being exposed to a real-world threats, practice strategic decision-making, or gain technical knowledge for operating and repairing equipment, etc.), administrative services (document processing, virtual consultations for citizens, etc.), judiciary (AI decision-making aids, virtual proceedings, etc.), public safety (virtual training for procedural issues, special operations, or unusual situations, etc.), emergency management (training for natural disasters, etc.), and city planning (visualization of future development projects and interactive feedback, traffic management, attraction gamification, etc.), among others. We further identify several metaverse application areas for Germany's Federal Employment Agency. These applications can help it realize the goals of the German government for digital transformation that enables faster, more effective, and innovative government services. They include training of employees, training of customers, and career coaching for customers. These applications can be implemented using interactive learning games with AI agents, virtual representations of the organizational spaces, and avatars interacting with each other in these spaces. Metaverse applications will both use big data (to design the virtual environments) and generate big data (from virtual interactions). Issues related to data availability, quality, storage, processing (and related computing power requirements), interoperability, sharing, privacy and security will need to be addressed in these emerging metaverse applications (Sun et al., 2022). Special attention is needed to understand the potential for power inequities (wealth inequity, algorithmic bias, digital exclusion) due to technologies such as VR (Egliston & Carter, 2021), harmful surveillance practices (Bibri & Allam, 2022), and undesirable user behavior or negative psychological impacts (Dwivedi et al., 2022). The results of this exploratory study can inform public sector organizations of emerging metaverse opportunities and enable them to develop plans for action as more of the metaverse technologies become a reality. While the metaverse body of research is still small and research agendas are only now starting to emerge (Dwivedi et al., 2022), this study offers a building block for future development and analysis of metaverse applications. Y1 - 2022 UR - https://aisel.aisnet.org/sigbd2022/5/ PB - AIS CY - Atlanta ER - TY - CHAP A1 - Brandenburger, Bonny A1 - Teichmann, Malte T1 - Looking for participation BT - adapting participatory learning oriented-didactic design elements of FabLabs in learning factories T2 - 12th Conference on Learning Factories N2 - A stronger learner orientation through participatory learning increases learning motivation and results. But what does participatory learning mean? Where do learning factories and fabrication laboratories (FabLabs) stand in this context, and how can didactic implementation be improved in this respect? Using a newly developed analytical framework, which contains elements of the stage model of participation and general media didactics, we compare a FabLab and a learning factory example concerning the degree of participation. From this, we derive guidelines for designing participative teaching and learning processes in learning factories. We explain how FabLabs can be an inspiration for the didactic design of learning factories. KW - participatory learning KW - FabLabs KW - subject-oriented learning KW - analytical framework Y1 - 2022 UR - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4073886 SN - 1556-5068 SP - 1 EP - 6 PB - Social Science Electronic Publing CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Rieskamp, Jonas A1 - Mirbabaie, Milad A1 - Hofeditz, Lennart A1 - Vischedyk, Justin T1 - Conversational agents and their influence on the well-being of cliniciansclinicians T2 - ACIS 2023 proceedings N2 - An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors. KW - conversational agents KW - well-being KW - mental health KW - hospitals KW - clinicians Y1 - 2023 UR - https://aisel.aisnet.org/acis2023/66 PB - Australasian Association for Information Systems CY - Wellington ER - TY - CHAP A1 - Rojahn, Marcel A1 - Gronau, Norbert T1 - Digital platform concepts for manufacturing companies BT - a review T2 - 10th International Conference on Future Internet of Things and Cloud (FiCloud) N2 - Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms. Y1 - 2023 SN - 979-8-3503-1635-3 U6 - https://doi.org/10.1109/FiCloud58648.2023.00030 SP - 149 EP - 158 PB - IEEE CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Krause, Hannes-Vincent A1 - Große Deters, Fenne A1 - Baumann, Annika T1 - The envy spiral BT - unraveling the black box of social media positivityorganizations T2 - Proceedings of the 28th European Conference on Information Systems (ECIS) : ECIS 2020 Research-in-Progress Papers N2 - On Social Networking Sites (SNS) users disclose mostly positive and often self-enhancing information. Scholars refer to this phenomenon as the positivity bias in SNS communication (PBSC). However, while theoretical explanations for this phenomenon have been proposed, an empirical proof of these theorized mechanisms is still missing. The project presented in this Research-in-Progress paper aims at explaining the PBSC with the mechanism specified in the self-enhancement envy spiral. Specifically, we hypothesize that feelings of envy drive people to post positive and self-enhancing content on SNS. To test this hypothesis, we developed an experimental design allowing to examine the causal effect of envy on the positivity of users’ subsequently posted content. In a preliminary study, we tested our manipulation of envy and could show its effectiveness in inducing different levels of envy between our groups. Our project will help to broaden the understanding of the complex dynamics of SNS and the potentially adverse driving forces underlying them. Y1 - 2020 UR - https://aisel.aisnet.org/ecis2020_rip/68 SN - 978-1-7336325-1-5 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Vladova, Gergana A1 - Rüdian, Sylvio Leo T1 - From learners to educators BT - development of online courses by students for students T2 - The future of education N2 - The rapid growth of technology and its evolving potential to support the transformation of teaching and learning in post-secondary institutions is a major challenge to the basic understanding of both the university and the communities it serves. In higher education, the standard forms of learning and teaching are increasingly being challenged and a more comprehensive process of differentiation is taking place. Student-centered teaching methods are becoming increasingly important in course design and the role of the lecturer is changing from the knowledge mediator to moderator and learning companion. However, this is accelerating the need for strategically planned faculty support and a reassessment of the role of teaching and learning. Even though the benefits of experience-based learning approaches for the development of life skills are well known, most knowledge transfer is still realized through lectures in higher education. Teachers have the goal to design the curriculum, new assignments, and share insights into evolving pedagogy. Student engagement could be the most important factor in the learning success of university students, regardless of the university program or teaching format. Against this background, this article presents the development, application, and initial findings of an innovative learning concept. In this concept, students are allowed to deal with a scientific topic, but instead of a presentation and a written elaboration, their examination consists of developing an online course in terms of content, didactics, and concept to implement it in a learning environment, which is state of the art. The online courses include both self-created teaching material and interactive tasks. The courses are created to be available to other students as learning material after a review process and are thus incorporated into the curriculum. KW - future curriculum KW - digitalization KW - online courses KW - COVID-19 Y1 - 2020 UR - https://conference.pixel-online.net/files/foe/ed0010/FP/6824-CUD4792-FP-FOE10.pdf SN - 978-88-85813-87-8 U6 - https://doi.org/10.26352/E618_2384-9509 SN - 2420-9732 VL - 10 PB - Pixel CY - Florenz ER - TY - CHAP A1 - Vladova, Gergana A1 - Ullrich, André A1 - Sultanow, Eldar A1 - Tobolla, Marinho A1 - Sebrak, Sebastian A1 - Czarnecki, Christian A1 - Brockmann, Carsten ED - Klein, Maike ED - Krupka, Daniel ED - Winter, Cornelia ED - Wohlgemuth, Volker T1 - Visual analytics for knowledge management BT - advantages for organizations and interorganizational teams T2 - Informatik 2023 N2 - The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results. KW - knowledge management KW - visual analytics KW - knowledge transfer KW - teamwork KW - knowledge management system KW - tacit knowledge KW - explicit knowledge Y1 - 2023 SN - 978-3-88579-731-9 U6 - https://doi.org/10.18420/inf2023_187 SN - 1617-5468 SP - 1851 EP - 1870 PB - Gesellschaft für Informatik e.V. (GI) CY - Bonn ER -