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- Fachgruppe Betriebswirtschaftslehre (347) (remove)
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.
Enhancing higher entrepreneurship education: insights from practitioners for curriculum improvement
(2024)
Curricula for higher entrepreneurship education should meet the requirements of both a solid theoretical foundation and a practical orientation. When these curricula are designed by education specialists, entrepreneurs are usually not consulted. To explore practitioners’ curricular recommendations, we conducted 73 semi-structured interviews with entrepreneurs with at least five years of professional experience. We collected 49 items for teaching and learning objectives, 37 for contents, 28 for teaching methods, and 17 for assessment methods. The respondents are convinced that students should acquire solid knowledge in business and management, legal issues, and entrepreneurship. For the latter, only some core aspects are provided. The entrepreneurs put greater emphasis on entrepreneurial skills and attitudes and consider experiential learning designs as most suitable, both in the secure setting of the classroom and in real life. The findings can help reflect on current entrepreneurship curriculum designs.
Invisible iterations: how formal and informal organization shape knowledge networks for coordination
(2024)
This study takes a network approach to investigate coordination among knowledge workers as grounded in both formal and informal organization. We first derive hypotheses regarding patterns of knowledge-sharing relationships by which workers pass on and exchange tacit and codified knowledge within and across organizational hierarchies to address the challenges that underpin contemporary knowledge work. We use survey data and apply exponential random graph models to test our hypotheses. We then extend the quantitative network analysis with insights from qualitative interviews and demonstrate that the identified knowledge-sharing patterns are the micro-foundational traces of collective coordination resulting from two underlying coordination mechanisms which we label ‘invisible iterations’ and ‘bringing in the big guns’. These mechanisms and, by extension, the associated knowledge-sharing patterns enable knowledge workers to perform in a setting that is characterized by complexity, uncertainty and ambiguity. Our research contributes to theory on the interplay between formal and informal organization for coordination by showing how self-directed, informal action is supported by the formal organizational hierarchy. In doing so, it also extends understanding of the role that hierarchy plays for knowledge-intensive work. Finally, it establishes the collective need to coordinate work as a previously overlooked driver of knowledge network relationships and network patterns. © 2024 The Authors. Journal of Management Studies published by Society for the Advancement of Management Studies and John Wiley & Sons Ltd.
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.
The devil in disguise
(2021)
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.
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.
Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively.
Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
Die Herstellung von Produkten bindet Energie sowie auch materielle Ressourcen. Viel zu langsam entwickeln sich sowohl das Bewusstsein der Konsumenten sowie der Produzenten als auch gesetzgebende Aktivitäten, um zu einem nachhaltigen Umgang mit den zur Verfügung stehenden Ressourcen zu gelangen. In diesem Beitrag wird ein lokaler Remanufacturing-Ansatz vorgestellt, der es ermöglicht, den Ressourcenverbrauch zu reduzieren, lokale Unternehmen zu fördern und effiziente Lösungen für die regionale Wieder- und Weiterverwendung von Gütern anzubieten.
Strategic social media use positively influences organizational goals such as the long-term accrual of social capital, and thus social media information governance has become an increasingly important organizational objective. It is particularly important for humanitarian nongovernmental organizations (HNGOs), whose work relies on accurate and timely information regarding socially altruistic behavior (donations, volunteerism, etc.). Despite the potential of social media for increasing social capital, tensions in governing social media information across an organization's different operational levels (regional, intermediate, and national) pose a difficult challenge. Prominent governance frameworks offer little guidance, as their focus on control and incremental policymaking is largely incompatible with the processes, roles, standards, and metrics needed for managing self-governing social media. This study offers a notion of dynamic and co-evolutionary process management of multi-level organizations as a means of conceptualizing social media information governance for the accrual of organizational social capital. Based on interviews with members of HNGOs, this study reveals tensions that emerge within eight focus areas of accruing social capital in multi-level organizations, explains how dynamic process management can ease those tensions, and proposes corresponding strategy recommendations.
Since the beginning of the recent global refugee crisis, researchers have been tackling many of its associated aspects, investigating how we can help to alleviate this crisis, in particular, using ICTs capabilities. In our research, we investigated the use of ICT solutions by refugees to foster the social inclusion process in the host community. To tackle this topic, we conducted thirteen interviews with Syrian refugees in Germany. Our findings reveal different ICT usages by refugees and how these contribute to feeling empowered. Moreover, we show the sources of empowerment for refugees that are gained by ICT use. Finally, we identified the two types of social inclusion benefits that were derived from empowerment sources. Our results provide practical implications to different stakeholders and decision-makers on how ICT usage can empower refugees, which can foster the social inclusion of refugees, and what should be considered to support them in their integration effort.
With the surging reliance on videoconferencing tools, users may find themselves staring at their reflections for hours a day. We refer to this phenomenon as self-referential information (SRI) consumption and examine its consequences and the mechanism behind them. Building on self-awareness research and the strength model of self-control, we argue that SRI consumption heightens the state of self-awareness and thereby depletes participants’ mental resources, eventually undermining virtual meeting (VM) outcomes. Our findings from a European employee sample revealed contrary effects of SRI consumption across speaker vs listener roles. Engagement with self-view is positively associated with self-awareness, which, in turn, is negatively related to satisfaction with VM process, perceived productivity, and enjoyment. Looking at the self while listening to others exhibits adverse direct and indirect (via self-awareness) effects on VM outcomes. However, looking at the self when speaking exhibits positive direct effects on satisfaction with VM process and enjoyment.
#Gesellschaftslehre 7/8
(2022)
#Gesellschaftslehre 9/10
(2023)
Factory Innovation Award
(2023)
Einmal mehr brachte die Hannover Messe die Spitzen der Industrie zusammen, um die wegweisenden Innovationen des Jahres mit dem begehrten Factory Innovation Award 2023 zu ehren. Dieser renommierte Preis, der erstmals auf der Industrial Transformation Stage verliehen wurde, markierte den Höhepunkt einer spannungsgeladenen Veranstaltung.
Selbstbestimmtes Lernen mit Onlinekursen findet zunehmend mehr Akzeptanz in unserer Gesellschaft. Lernende können mithilfe von Onlinekursen selbst festlegen, was sie wann lernen und Kurse können durch vielfältige Adaptionen an den Lernfortschritt der Nutzer angepasst und individualisiert werden. Auf der einen Seite ist eine große Zielgruppe für diese Lernangebote vorhanden. Auf der anderen Seite sind die Erstellung von Onlinekursen, ihre Bereitstellung, Wartung und Betreuung kostenintensiv, wodurch hochwertige Angebote häufig kostenpflichtig angeboten werden müssen, um als Anbieter zumindest kostenneutral agieren zu können. In diesem Beitrag erörtern und diskutieren wir ein offenes, nachhaltiges datengetriebenes zweiseitiges Geschäftsmodell zur Verwertung geprüfter Onlinekurse und deren kostenfreie Bereitstellung für jeden Lernenden. Kern des Geschäftsmodells ist die Nutzung der dabei entstehenden Verhaltensdaten, die daraus mögliche Ableitung von Persönlichkeitsmerkmalen und Interessen und deren Nutzung im kommerziellen Kontext. Dies ist eine bei der Websuche bereits weitläufig akzeptierte Methode, welche nun auf den Lernkontext übertragen wird. Welche Möglichkeiten, Herausforderungen, aber auch Barrieren überwunden werden müssen, damit das Geschäftsmodell nachhaltig und ethisch vertretbar funktioniert, werden zwei unabhängige, jedoch synergetisch verbundene Geschäftsmodelle vorgestellt und diskutiert. Zusätzlich wurde die Akzeptanz und Erwartung der Zielgruppe für das vorgestellte Geschäftsmodell untersucht, um notwendige Kernressourcen für die Praxis abzuleiten. Die Ergebnisse der Untersuchung zeigen, dass das Geschäftsmodell von den Nutzer*innen grundlegend akzeptiert wird. 10 % der Befragten würden es bevorzugen, mit virtuellen Assistenten – anstelle mit Tutor*innen zu lernen. Zudem ist der Großteil der Nutzer*innen sich nicht darüber bewusst, dass Persönlichkeitsmerkmale anhand des Nutzerverhaltens abgeleitet werden können.
Band 5/6
(2020)
Zum Schuljahr 2020/21 trat in Nordrhein-Westfalen ein neuer Kernlehrplan für die Realschule, Gesamtschule und Sekundarschule in Kraft. Dafür haben wir gemeinsam mit Fachkräften aus dem Bundesland die #-Schulbuchreihen entwickelt.
In #Politik Wirtschaft – Nordrhein-Westfalen platzieren wir die Inhalte der Lehrpläne Politik und Wirtschaft sinnvoll kombiniert, sodass Sie Ihren Unterricht der Fächer mit einem Buch ganz individuell organisieren können.
Wir bieten Ihnen innovative und aktuelle Produkte für einen modernen Politik- und Wirtschaftsunterricht. Neben dem neuen Lehrplan sind die Vorgaben des Medienkompetenzrahmens und die besonderen Herausforderungen heterogener Lerngruppen berücksichtigt.
Die Konzeption bietet einerseits die Möglichkeit, die problemorientiert und schülernah aufbereiteten Inhalte entlang von Doppelseiten zu bearbeiten, die sich am didaktischen Aufbau von Unterrichtsstunden orientieren. Gleichzeitig gibt es in der Rubrik „Gemeinsam aktiv“ konkrete Vorschläge, größere Einheiten durch selbstgesteuertes Lernen projektartig in Gruppen zu erschließen. Dadurch können Sie Ihren Unterricht einfach und schnell besonders vielfältig und spannend gestalten.
Ein besonderes Kennzeichen der Reihe ist die Orientierung an der Lebenswelt der Schülerinnen und Schüler. Durch Fallbeispiele werden sie direkt angesprochen. Eine kreative Vielfalt aus Bild-, Grafik- und Textmaterial, aktivierende Aufgaben, Methoden-und Grundwissenseiten und ein Kompetenzcheck zum Abschluss der Großkapitel vervollständigen das Angebot.
Zu jeder Unterrichtseinheit wird passgenau zum Schulbuch unterschiedliches Differenzierungsmaterial (Texte in einfacher Sprache, Vorstrukturierung von Aufgaben u.v.m) erstellt. Dieses steht Ihnen in unserem digitalen Lehrermaterial click & teach zur Verfügung und kann von Ihnen nach individuellen Bedürfnissen für einzelne digitale Schulbücher freigeschaltet werden.
Looking for participation
(2022)
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.
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.
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.
The business problem of having inefficient processes, imprecise process analyses and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS) and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes.
Widespread on social networking sites (SNSs), envy has been linked to an array of detrimental outcomes for users’ well-being. While envy has been considered a status-related emotion and is likely to be experienced in response to perceiving another’s higher status, there is a lack of research exploring how status perceptions influence the emergence of envy on SNSs. This is important because SNSs typically quantify social interactions and reach with metrics that indicate users’ relative rank and status in the network. To understand how status perceptions impact SNS users, we introduce a new form of metric-based digital status rooted in SNS metrics that are available and visible on a platform. Drawing on social comparison theory and status literature, we conducted an online experiment to investigate how different forms of status contribute to the proliferation of envy on SNSs. Our findings shed light on how metric-based digital status influences feelings of envy on SNSs. Specifically, we could show that metric-based digital status impacts envy through increasing perceptions of others’ socioeconomic and sociometric statuses. Our study contributes to the growing discourse on the negative outcomes associated with SNS use and its consequences for users and society.
The envy spiral
(2020)
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.
Enhancing economic efficiency in modular production systems through deep reinforcement learning
(2024)
In times of increasingly complex production processes and volatile customer demands, the production adaptability is crucial for a company's profitability and competitiveness. The ability to cope with rapidly changing customer requirements and unexpected internal and external events guarantees robust and efficient production processes, requiring a dedicated control concept at the shop floor level. Yet in today's practice, conventional control approaches remain in use, which may not keep up with the dynamic behaviour due to their scenario-specific and rigid properties. To address this challenge, deep learning methods were increasingly deployed due to their optimization and scalability properties. However, these approaches were often tested in specific operational applications and focused on technical performance indicators such as order tardiness or total throughput. In this paper, we propose a deep reinforcement learning based production control to optimize combined techno-financial performance measures. Based on pre-defined manufacturing modules that are supplied and operated by multiple agents, positive effects were observed in terms of increased revenue and reduced penalties due to lower throughput times and fewer delayed products. The combined modular and multi-staged approach as well as the distributed decision-making further leverage scalability and transferability to other scenarios.
One for all, all for one
(2022)
We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.
As the complexity of learning task requirements, computer infrastruc- tures and knowledge acquisition for artificial neuronal networks (ANN) is in- creasing, it is challenging to talk about ANN without creating misunderstandings. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information and knowledge on the base of an integration with knowledge- intensive business process models and a process-oriented knowledge manage- ment are attractive. With the aim of making the design of learning tasks express- ible by models, this paper proposes a graphical modeling language called Neu- ronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaptation exemplifies its use as a first demonstration.
It’s personal
(2021)
The new technologies of the Fourth Industrial Revolution (4IR) are disrupting traditional models of work and learning. While the impact of digitalization on education was already a point of serious deliberation, the COVID-19 pandemic has expedited ongoing transitions. With 90% of the world’s student population having been impacted by national lockdowns—online learning has gone from being a luxury to a necessity, in a context where around 3.6 billion people are offline. As the impacts of the 4IR unfold alongside the current crisis, it is not enough for future policy pathways to prioritize educational attainment in the traditional sense; it is essential to reimagine education itself as well as its delivery entirely. Future policy narratives will need to evaluate the very process of learning and identify the ways in which technology can help reduce existing disparities and enhance digital access, literacy and fluency in a scalable manner. In this context, this chapter analyses the status quo of online learning in India and Germany. Drawing on the experiences of these two economies with distinct trajectories of digitalization, the chapter explores how new technologies intersect with traditional education and local sociocultural conditions. Further, the limitations and opportunities presented by dominant ed-tech models is critically analyzed against the ongoing COVID-19 pandemic.
Viktimologie als die Erforschung von Kriminalitätsopfern war lange Zeit auf „street crimes“ fokussiert. Inzwischen gibt es Opfertypologien und -betrachtungen für eine Vielzahl weiterer Delikte – jedoch bleibt der Fokus nach wie vor auf menschlichen Opfern. Gerade mit Blick auf neue digitale Angriffsformen werden Unternehmen allerdings als Opfer immer interessanter und – unter dem Stichwort Cybersecurity – stellen als Forschungsobjekt verstärkt neue Anforderungen. Diese Entwicklung läuft weitgehend unabhängig von der Viktimologie; Bezüge zur klassischen Opferforschung werden kaum hergestellt. Dieses Kapitel widmet sich dieser Lücke, indem es existierende Forschungsansätze zu Unternehmen als Opfer von Cybercrime anhand viktimologischer Schemata und Fragestellungen einordnet. Weiterhin wird mit dem Verständnis von Unternehmen und Individuen als Systeme eine Vorgehensweise skizziert, um bestehende Ansätze aus der Viktimologie auf die Betrachtung von Unternehmen als Opfer anzupassen und zu übertragen.
We and AI
(2021)
From learners to educators
(2020)
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.
This study is dedicated to the interdependencies between digital sovereignty and sustainable digitalization, which need to be explicitly linked to an increasing degree in political discourse, academia, and societal debates. Digital skills are the prerequisites for shaping digitalization in the interest of society and sustainable development.
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.
Assistenzsysteme finden im Kontext der digitalen Transformation immer mehr Einsatz. Sie können Beschäftigte in industriellen Produktionsprozessen sowohl in der Anlern- als auch in der aktiven Arbeitsphase unterstützen. Kompetenzen können so arbeitsplatz- und prozessnah sowie bedarfsorientiert aufgebaut werden. In diesem Beitrag wird der aktuelle Forschungsstand zu den Einsatzmöglichkeiten dieser Assistenzsysteme diskutiert und mit Beispielen illustriert. Es werden unter anderem auch Herausforderungen für den Einsatz aufgezeigt. Am Ende des Beitrags werden Potenziale für die zukünftige Nutzung von AS in industriellen Lernprozessen und für die Forschung identifiziert.
Intrinsic motivation is widely considered essential to creativity because it facilitates more divergent thinking during problem solving. However, we argue that intrinsic motivation has been theorized too heavily as a unitary construct, overlooking various internal factors of a task that can shape the baseline level of intrinsic motivation people have for working on the task. Drawing on theories of cognitive styles, we develop a new scale that measures individual preferences for three different creative thinking styles that we call divergent thinking, bricoleurgent thinking, and emergent thinking. Through a multi-study approach consisting of exploratory factor analysis, confirmatory factor analysis, and convergent validity, we provide psychometric evidence showing that people can have distinct preferences for each cognitive process when generating ideas. Furthermore, when validating this scale through an experiment, we find that each style becomes more dominant in predicting overall enjoyment, engagement, and creativity based on different underlying structures of a task. Therefore, this paper makes both theoretical and empirical contributions to literature by unpacking intrinsic motivation, showing how the alignment between different creative thinking styles and task can be essential to predicting intrinsic motivation, thus reversing the direction of causality between the motivational and cognitive components of creativity typically assumed in literature.
Der Einsatz Künstlicher Intelligenz (KI) wird zunehmend relevant – sowohl in Berufen mit formalisierbaren Aufgaben als auch in Berufsfeldern, für deren Aufgaben Erfahrungswissen notwendig ist und situationsabhängig Entscheidungen getroffen werden, die mit folgenschweren Konsequenzen verbunden sein können. Um das Potenzial der Zusammenarbeit zwischen Mensch und KI auszuschöpfen, muss sich der Mensch entsprechend wappnen. Somit verändern sich die Kompetenzanforderungen an Mitarbeiter:innen auf allen Ebenen und an ihre Führungskräfte. Relevante Konzepte des lebenslangen Lernens und der betrieblichen Weiterbildung gewinnen durch den Einfluss der Technologie auch unter teilweise veränderten Lernbedingungen vermehrt an Bedeutung. Neben neuen technischen und Fachkompetenzen, sind für die Nutzung von und die Zusammenarbeit mit der neuen Technologie weitere Kompetenzen notwendig, um z. B. einschätzen zu können, wann die Arbeit der Maschine ethisch vertretbar, effektiv, verantwortungsvoll, fair, transparent und nachvollziehbar ist. Auch neue Tätigkeitsprofile entstehen und die beruflichen Rollen verändern sich entsprechend. Neben den Anforderungen, die die KI an Bildung und Kompetenzentwicklung stellt, wird sie weiterhin zunehmend zur Gestaltung von Lernumgebungen und für den Kompetenzaufbau im Beruf eingesetzt. Sie ist somit nicht nur der Auslöser von Veränderungen, sondern auch das Instrument, welches genutzt wird, um die Lehre zu unterstützen und individueller, abwechslungsreicher sowie zeit- und ortunabhängiger zu gestalten. Im Beitrag werden Chancen und Herausforderungen durch den Einsatz von KI für zwei Dimensionen diskutiert: die Transformationsprozesse in der Berufswelt und die Gestaltung von Lernprozessen.
Damit die EU ihre ambitionierten Klimaschutzziele erreichen kann, werden die Preise für Treibhausgasemissionen in den nächsten Jahren spürbar steigen. Das hat ökonomische Auswirkungen für die EU-Mitgliedsländer, aber auch den Rest der Welt. Einzelne Sektoren und auch Volkswirtschaften werden davon unterschiedlich stark getroffen.
Worth the pain?
(2021)
How do exporting firms react to sanctions? Specifically, which firms are willing — or capable — to serve the market of a sanctioned country? We investigate this question for four sanctions episodes using monthly data on the universe of French exporting firms. We draw on recent econometric advances in the estimation of dynamic fixed effects binary choice models. We find that the introduction of new sanctions in Iran and Russia significantly lowered firm-level probabilities of serving these sanctioned markets, while the (temporary) lifting of the U.S. sanctions on Cuba and the removal of sanctions against Myanmar had no or only small trade-inducing effects, respectively. Additionally, the impact of sanctions is very heterogeneous along firm dimensions and by case particularities. Firms that depend more on trade finance instruments are more strongly affected, while prior experience in the sanctioned country considerably softens the blow of sanctions, and firms can be partly immune to the sanctions effect if they are specialized in serving “crisis countries”. Finally, we find suggestive evidence for sanctions avoidance by exporting indirectly via neighboring countries.
Purpose
The purpose of this paper is to investigate how learning solely via an assistance system influences work performance compared with learning with a combination of an assistance system and additional training. While the training literature has widely emphasised the positive role of on-the-job training, particularly for groups that are often underrepresented in formalised learning situations, organisational studies have stressed the risks that emerge when holistic process knowledge is lacking and how this negatively affects work performance. This study aims at testing these negative effects within an experimental design.
Design/methodology/approach
This paper uses a laboratory experimental design to investigate how assistance-system-guided learning influences the individuals’ work performance and work satisfaction compared with assistance-system-guided learning combined with theoretical learning of holistic process knowledge. Subjects were divided into two groups and assigned to two different settings. In the first setting, the participants used the assistance systems as an orientation and support tool right at the beginning and learned the production steps exclusively in this way. In the second setting, subjects received an additional 10-min introduction (treatment) at the beginning of the experiment, including detailed information regarding the entire work process.
Findings
This study provides evidence that learners provided with prior process knowledge achieve a better understanding of the work process leading to higher levels of productivity, quality and work satisfaction. At the same time, the authors found evidence for differences among workers’ ability to process and apply this additional information. Subjects with lower productivity levels faced more difficulties processing and applying additional process information.
Research limitations/implications
Methodologically, this study goes beyond existing research on assistance systems by using a laboratory experimental design. Though the external validity of this method is limited by the artificial setting, it is a solid way of studying the impact of different usages of digital assistance systems in terms of training. Further research is required, however, including laboratory experiments with larger case numbers, company-level case studies and analyses of survey data, to further confirm the external validity of the findings of this study for the workplace.
Practical implications
This study provides some first evidence that holistic process knowledge, even in low-skill tasks, has an added value for the production process. This study contributes to firms' training policies by exploring new, digitalised ways of guided on-the-job training and demonstrates possible training benefits for people with lower levels of (initial) abilities and motivation.
Social implications
This study indicates the advantage for companies and societies to invest in additional skills and training and points at the limitations of assistance systems. This paper also contributes to training policies by exploring new, digitalised ways of guided on-the-job training and demonstrates possible training benefits for people with lower levels of (initial) abilities and motivation.
Originality/value
This study extends existing research on digital assistance systems by investigating their role in job-related-training. This paper contributes to labour sociology and organisational research by confirming the importance of holistic process knowledge as opposed to a solely task-oriented digital introduction.
We welcome you to the 53rd Hawaii International Conference on System Sciences (HICSS) conference. After joining with Intentional Forgetting Minitrack last year, this is the fourth year of the Organizational Learning Minitrack. We add Unlearning, and Intentional Forgetting to proudly bring you the latest research focused on organizational learning issues within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack.
We welcome you to the 54th Hawaii International Conference on System Sciences (HICSS-54) conference. This is the fifth year for the Organizational Learning Minitrack which has had the usual growing pains: two years ago, we added the topic of Unlearning and joined with the Intentional Forgetting Minitrack - as these topics are all organizationally-based knowledge management issues. We proudly bring you the latest research focused on the methods to develop and maintain organizational learning within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational
learning in this Minitrack.
Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect.
New technological applications such as Augmented Reality or Massive Open Online Courses (MOOCs) lead to alternative ways of learning. In order to be able to use this to its potential, the promotion of digital competencies “Digital Competence is the set of knowledge, skills, attitudes, abilities, strategies, and awareness that are required when using ICT and digital media to perform tasks; solve problems; communicate; manage information; collaborate; create and share content; and build knowledge effectively, efficiently, appropriately, critically, creatively, autonomously, flexibly, ethically, reflectively for work, le sure, participation, learning, and socialising.” (Ferrari, 2012). and a corresponding amount of practical "learning-by-doing" effects is required (cf. Ecker/Campbell 2019, p. 154). For this purpose, spaces and framework conditions must be created for application-based learning, which is also increasingly required by the employment market. In this context, we take a closer look at a new emerging subculture in university infrastructure called Maker Movement (MM). Our research work aims at investigating the pedagogical potential of particularly university-integrated makerspaces (MS) to enhance experiential learning with digital tools. To decode the innovative potential, we collected qualitative data from nine in-depth, semi-structured interviews with lab managers and researchers at European MS in six different countries.
Research into the effects of social media on well-being often distinguishes “active” and “passive” use, with passive use supposedly more harmful to well-being (i.e., the passive use hypothesis). Recently, several studies and reviews have begun to question this hypothesis and its conceptual basis, the active/passive dichotomy. As this dichotomy has become a staple of social media research but evidence challenging its validity is mounting, a comprehensive debate on its pros, cons, and potential future is needed. This adversarial review brings together two voices – one more supportive, and the other more critical – toward the active/passive model. In constructive dialogue, we summarize and contrast our two opposing positions: The first position argues that the active/passive dichotomy is a useful framework because it adequately describes how and why passive use is (more) harmful for well-being. The second position challenges the validity of the dichotomy and the passive use hypothesis specifically. Arguments are presented alongside (a) the empirical basis, (b) conceptualization, and (c) operationalization of active and passive use, with particular focus on the passive use hypothesis. Rather than offering a conciliatory summary of the status quo, the goal of this review is to carve out key points of friction in the literature on the effects of social media through fruitful debate. We summarize our main agreements and unresolved disagreements on the merits and shortcomings of the active/passive dichotomy. In doing so, this review paves the way for researchers to decide whether and how they want to continue applying this lens in their future work.