Filtern
Volltext vorhanden
- nein (60) (entfernen)
Erscheinungsjahr
Dokumenttyp
Schlagworte
- Digitale Plattformen (5)
- Industry 4.0 (5)
- Digital platforms (4)
- E-Mail Tracking (4)
- ERP (4)
- Industrie 4.0 (4)
- digital platforms (4)
- Analytics (3)
- Internet of Things (3)
- Maschinen- und Anlagenbau (3)
- Privacy (3)
- enterprise systems (3)
- production control (3)
- systematic literature review (3)
- COVID-19 (2)
- Chrome (2)
- ERP system (2)
- Firefox (2)
- KMU (2)
- Machine learning (2)
- Machinery and plant engineering (2)
- Platform Innovation (2)
- browser platforms (2)
- deep reinforcement learning (2)
- digital learning (2)
- enteprise-level (2)
- enterprise system (2)
- information systems research (2)
- machine learning (2)
- platform innovation (2)
- production planning (2)
- requirements (2)
- Adaptivität (1)
- Altsyteme (1)
- Analytic Infrastructures (1)
- Anti-Tracking Infrastructure (1)
- Anwendungszentrum Industrie 4.0 (1)
- Application success (1)
- Architecture concepts (1)
- Architekturkonzept (1)
- Automatisierung (1)
- Blockchain (1)
- Boundary resources (1)
- Browser Platform (1)
- Browser Platforms (1)
- CPS (1)
- Case Study (1)
- Cloud (1)
- Consensus algorithms (1)
- Coring (1)
- Countermeasures (1)
- Creative process (1)
- Cross-System (1)
- Customer satisfaction (1)
- Cyber-Phsysische Systeme (1)
- Cyber-Physical Manufacturing Systems (1)
- Cyber-physical systems (1)
- Data Privacy (1)
- Data privacy (1)
- Decentral Decision Making (1)
- Digital Marketplaces (1)
- Digital Platforms (1)
- Discontinued Features (1)
- Email tracking (1)
- Enterprise Resource Planning (1)
- Enterprise System (1)
- Enterprise-grade (1)
- Feature Removal (1)
- Federal states (1)
- Geschäftsmodell (1)
- Geschäftsmodelle (1)
- Government as a platform (1)
- IIoT (1)
- Individualization (1)
- Industrial Analytics (1)
- Information Security and Privacy (1)
- Integration (1)
- Internet of things (1)
- Invidiuallösungen (1)
- KVP (1)
- Kaizen (1)
- Kunststoffindustrie (1)
- Lean Core (1)
- Lernfabrik (1)
- Lernszenario (1)
- Machine Learning (1)
- Measuring Efficient Task Processing (1)
- Mobile IIoT-Technologie (1)
- Mobile Software Ecosystems (1)
- Mobile device platforms (1)
- Modeling (1)
- Mozilla Firefox (1)
- Newsletter (1)
- Online Dating (1)
- Online Marketing (1)
- Online behavior (1)
- Personalization (1)
- Platform Coring (1)
- Platform delivery strategies (1)
- Platform economy (1)
- Platform types (1)
- Plattform Ökosystem (1)
- Plattform-Bereitstellungsstrategien (1)
- Plattformtypen (1)
- Pockets of creativity (1)
- Potenziale (1)
- Problems (1)
- Process Mining (1)
- Production (1)
- Prozessintegration (1)
- Public sector (1)
- Public service platforms (1)
- Qualität (1)
- RFID (1)
- RPA (1)
- Requirements (1)
- Research Agenda (1)
- Robotic Process Automation (1)
- SME (1)
- Security (1)
- Self-esteem (1)
- Simulation (1)
- Software Platforms (1)
- Software Prototype (1)
- Spielifizierung (1)
- Strategie (1)
- Sustainability (1)
- Systematic literature revieew (1)
- Systematisches Vorgehen (1)
- Systemauswahl (1)
- TAM (1)
- Task realization strategies (1)
- Three-tier Architecture (1)
- Tinder (1)
- Verbesserungen (1)
- Verbesserungsprozess (1)
- application center Industrie 4.0 (1)
- automation (1)
- business process platform (1)
- complementary market entry (1)
- coring (1)
- creative process (1)
- cyber-physical production systems (1)
- cyber-physical systems (1)
- data analytics (1)
- data requirements (1)
- data security (1)
- database (1)
- deep learning (1)
- digital learning factory (1)
- digital marketplaces (1)
- discipline differences (1)
- e-learning (1)
- eference Architecture Model (1)
- enterprise architecture (1)
- enterprise ecosystems: the integrated enterprise (1)
- evaluation (1)
- federal states (1)
- future (1)
- geographical distribution (1)
- government as a platform (1)
- higher education (1)
- hybrid simulation (1)
- information flow control (1)
- information gateway (1)
- is governance (1)
- it/business alignment (1)
- learning scenario (1)
- levels of information systems research (process, enterprise-, ecosystem- & industry-level) (1)
- literature review (1)
- manufacturing processes (1)
- manufacturing systems (1)
- mobile IIoT-technologies (1)
- mobile software ecosystems (1)
- modeling (1)
- modular production (1)
- multi-agent system (1)
- multi-objective optimisation (1)
- neural networks (1)
- organizational level (1)
- plastics industry (1)
- platform acceptance (1)
- platform coring (1)
- platform economy (1)
- platform ecosystem (1)
- platform-based business models (1)
- plattformbasierte Geschäftsmodelle (1)
- pockets of creativity (1)
- potentials (1)
- privacy (1)
- problems (1)
- process integration (1)
- production engineering computing (1)
- production networks (1)
- production planning and control (1)
- public sector (1)
- public service platforms (1)
- reinforcement learning (1)
- simulation (1)
- software platforms (1)
- software selection (1)
- subject differences (1)
- task realization strategies (1)
- taxonomy (1)
- technology acceptance (1)
- technology-mediated teaching (1)
- third-party developer (1)
- university teaching (1)
- virtual learning (1)
- web-tracking (1)
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.
Obwohl Handelsplattformen zunehmend an Bedeutung gewinnen, besteht im deutschsprachigen Raum ein Mangel an umfassenden Marktübersichten. Dadurch fehlt es Verkäufern, potenziellen Plattformbetreibern und Kunden an einer soliden Grundlage für fundierte Entscheidungen. Das ändern wir mit folgendem Beitrag. Erfahren Sie hier das Wichtigste über den rasant wachsenden Markt der Handelsplattformen.
Die Digitalisierung des deutschen Mittelstandes schreitet weiterhin schleppend voran. So verfügt zwar ein wachsender Teil dieser Unternehmen über vereinzelte Informations- und Kommunikationssysteme, die zielführende Vernetzung und Integration dieser Systeme stellt jedoch weiterhin eine große Aufgabe dar [1]. Besonders vor dem Hintergrund wachsender Bedürfnisse für Informationen und Transparenz sehen sich Unternehmen zunehmend mit der analyseorientierten Nutzbarmachung der Unternehmensdaten konfrontiert [2].
While Information Systems (IS) Research on the individual and workgroup level of analysis is omnipresent, research on the enterprise-level IS is less frequent. Even though research on Enterprise Systems and their management is established in academic associations and conference programs, enterprise-level phenomena are underrepresented. This minitrack provides a forum to integrate existing research streams that traditionally needed to be attached to other topics (such as IS management or IS governance). The minitrack received broad attention. The three selected papers address different facets of the future role of enterprise-wide IS including aspects such as carbonization, ecosystem integration, and technology-organization fit.
While Information Systems Research exists at the individual and workgroup levels, research on IS at the enterprise level is less common. The potential synergies between the study of enterprise systems (ES) and related fields have been underexplored and often treated as separate entities. The ongoing challenge is to seamlessly integrate technological advances and align business processes across organizations. While systems integration within an organization is common, changes occur when industry and ecosystem perspectives come into play. The four selected papers address different facets of the future role of enterprise ecosystems, including implementation challenges, ecosystem boundaries, and B2B platform specifics.
Enterprise solutions, specifically enterprise systems, have allowed companies to integrate enterprises’ operations throughout. The integration scope of enterprise solutions has increasingly widened, now often covering customer activities, activities along supply chains, and platform ecosystems. IS research has contributed a wide range of explanatory and design knowledge dealing with this class of IS. During the last two decades, many technological as well as managerial/organizational innovations extended the affordances of enterprise solutions—but this broader scope also challenges traditional approaches to their analysis and design. This position paper presents an enterprise-level (i.e., cross-solution) perspective on IS, discusses the challenges of complexity and coordination for IS design and management, presents selected enterprise-level insights for IS coordination and governance, and explores avenues towards a more comprehensive body of knowledge on this important level of analysis.
Enterprise Resource Planning (ERP) systems are critical to the success of enterprises, facilitating business operations through standardized digital processes. However, existing ERP systems are unsuitable for startups and small and medium-sized enterprises that grow quickly and require adaptable solutions with low barriers to entry. Drawing upon 15 explorative interviews with industry experts, we examine the challenges of current ERP systems using the task technology fit theory across companies of varying sizes. We describe high entry barriers, high costs of implementing implicit processes, and insufficient interoperability of already employed tools. We present a vision of a future business process platform based on three enablers: Business processes as first-class entities, semantic data and processes, and cloud-native elasticity and high availability. We discuss how these enablers address current ERP systems' challenges and how they may be used for research on the next generation of business software for tomorrow's enterprises.
Modern browsers are digital software platforms, as they allow third parties to extend functionality by providing extensions. In a highly competitive environment, differentiation through provided functionality is a key factor for browser platforms. As the development of browsers progress, new functions are constantly being released. Browsers could thus enter complementary markets by adding functionality previously provided by third-party extensions, which is referred to as ‘platform coring’. Previous studies have missed the perspective of the parties involved. To address this gap, we conducted interviews with third-party and core developers in the security and privacy domain from Firefox and Chrome. This study provides three contributions. First, insights into stakeholder-specific issues concerning coring. Second, measures to prevent coring. Third, strategical guidance for developers and owners. Third-party vendors experienced and core developers confirmed that coring occurs on browser platforms. While developers with extrinsic motivations assess coring negatively, developers with intrinsic motivations perceive coring positively.
Software platforms regularly introduce new features to remain competitive. While platform innovation is considered to be a critical success factor, adding certain features could hurt the ecosystem. If platform owners provide functionality that was previously provided by a contributor, the owners enter complementary product spaces. Complementary market entry frequently occurs on software platforms and is a major concern for third-party developers.
Divergent findings on the impact of complementary market entry call for the consideration of additional factors. As prior research neglected the third-party perspective, this contribution aims to address this gap. We explore the use of measures to prevent complementary market entry using a survey approach on browser platforms. The research model is tested with 655 responses among developer from Mozilla Firefox and Google Chrome. To explain countermeasures employment, developer’s attitude and perceived likelihood are important. The results reveal that developers employ countermeasures if complementary market entry is assessed negatively and perceived as likely for their extension. Differences among browser platforms concerning complementary market entry are identified. Product spaces of extensions being available on multiple platforms are less likely to be entered and more heavily protected. Implications for research and stakeholders, i.e. platform owners and contributors are discussed.