Wirtschaft (MSB)
Filtern
Jahr
Publikationstyp
- Beitrag in einer Konferenzveröffentlichung (112) (entfernen)
Schlagworte
- Process-Driven Application (5)
- BPMN (4)
- Artificial Intelligence (2)
- Logistics (2)
- 3D printing (1)
- Activ Investor (1)
- Activist Investor (1)
- Analytics (1)
- Asset Stripping (1)
- Augmented Reality (1)
- BPM (1)
- Bildung (1)
- Business Process (1)
- Chatbot (1)
- Continuous Software Engineering (1)
- Control-Flow Graph Analysis (1)
- Corporate Raider (1)
- Cost drivers (1)
- Customer Journey Mapping (1)
- Customer Journey Mining (1)
- DSRP (1)
- Data Analytics (1)
- Data-Flow Anomalies (1)
- Design of Experiments (1)
- Digitalization (1)
- Dynamic Capabilities; continuous innovation generation; resource recombination (1)
- E-Assessment (1)
- Ecological sustainability (1)
- Economic value added (1)
- Feature-driven Development (1)
- Geld (1)
- Generative AI (1)
- Humanismus (1)
- ILIAS (1)
- Initial Public Offering (1)
- Large Language Model (1)
- Large Language Models (1)
- Life-cycle assessment (1)
- Literaturunterricht (1)
- Mapping (1)
- Mitschnitte von Vorlesungen (1)
- Model-Based Testing (1)
- No-Code (1)
- Online-Tests/Übungen (1)
- Packaging (1)
- Panopto (1)
- Prediction (1)
- Process Mining (1)
- Robotic Process Automation (1)
- Skills orientation (1)
- Software evolution (1)
- Static Analysis (1)
- Supply network mapping (1)
- Sustainable developement goals (1)
- Test migration (1)
- Value contribution (1)
- Wirtschaftskrise (1)
- active-based learning, problem-based learning, management education, community of practice, generic competences, transversal competences. (1)
- additive manufacturing (1)
- aesthetics of economics (1)
- bibliometric analysis (1)
- curriculum development (1)
- data management (1)
- digitalisation (1)
- ecosystem emergence (1)
- ecosystems (1)
- founding conditions (1)
- imprinting (1)
- internet of things (1)
- resilience (1)
- skills profiles (1)
- smart grid (1)
- study programme development, negotiation, change of perspective (1)
- supply chain (1)
- Ökonomik (1)
- Ökonomisches Wissen (1)
Fachbereich / Studiengang
The use of augmented reality (AR) in outbound logistics is associated with potentially strong stimuli for cost savings and throughput time. Nevertheless, the benefits of AR compared to conventional methods require a holistic analysis for investment decision making. Until now, research has only assessed case-study-related potentials and selected aspects of the technology. This paper answers the following research questions: How can the economic efficiency of AR in the packing process be quantified by utilizing a holistic model of value drivers? How can AR be technically implemented for packing processes in outbound logistics? What economic profit results from the use of AR technology in a case company’s packing process?
The presented model enables the investment decision to be supported based on economic value added (EVA), thereby providing an assessment of value drivers in packing systems. Cost drivers are identified on the basis of the Supply Chain Operations Reference (SCOR) process model. The technical and economic validation of the model was carried out by means of an empirical study: Expert interviews were conducted for validating the model elements. Data collection by a prototype at a mechanical-engineering company was used to calculate the value contribution. The mapping of cause-effect relationships within the framework of EVA driver trees has proven itself in both the expert interviews and the prototype validation. The field experiment at the case company demonstrated a positive value contribution of AR, in particular regarding employee productivity, length and variance of throughput time, quality aspects, volume utilization, and quantity of packing material used.
In-depth analysis of customer journeys to broaden the understanding of customer behaviors and expectations in order to improve the customer experience is considered highly relevant in modern business practices. Recent studies predominantly focus on retrospective analysis of customer data, whereas more forward-directed concepts, namely predictions, are rarely addressed. Additionally, the integration of robotic process automation (RPA) to potentially increase the efficiency of customer journey analysis is not discussed in the current field of research. To fill this research gap, this paper introduces “customer journey mining”. Process mining techniques are applied to leverage digital customer data for accurate prediction of customer movements through individual journeys, creating valuable insights for improving the customer experience. Striving for improved efficiency, the potential interplay of RPA and customer journey mining is examined accordingly. The research methodology followed is based on a design science research process. An initially defined customer journey mining artifact is operationalized through an illustrative case study. This operationalization is achieved by analyzing a log file of an online travel agency functioning as an orientation for researchers and practitioners while also evaluating the initially defined framework. The data is used to train seven distinct prediction models to forecast the touchpoint a customer is most likely to visit next. Gradient-boosted trees yield the highest prediction accuracy with 43.1%. The findings further indicate technical suitability for RPA implementation, while financial viability is unlikely.
AI-based chatbots as enabler for efficient external knowledge management in public administration
(2024)
This study addresses the pressing issue of staff shortages in German public administrations through the lens of digitalization, focusing on the potential of AI-based chatbots to solve this problem by replacing human labour. Employing a Design Science Research Process (DSRP) methodology, the research synthesizes theoretical foundations and regulatory frameworks to develop a robust chatbot concept. The artifact presented is a comprehensive architectural framework integrating user-centric design, linguistic processing, and regulatory compliance. The proposed artifact navigates complex federal structures and diverse IT infrastructures, promoting accessibility and inclusivity. Implications suggest enhanced efficiency and accessibility in public service delivery for potentially increasing citizen satisfaction and decreasing employee workload. The study underscores the importance of legal compliance and the evolving regulatory landscape in AI deployment. Future research will involve prototyping and evaluating the artifact's performance and applicability throughout the course of the DSRP, thus contributing to the advancement of digital transformation in public administrations.
Virtual reality (VR) is starting to realize some of its promise as a tool to improve training effectiveness. However, research on VR for training and development is limited. Existing theories and models relating to organizational training and learning are infrequently used in the VR literature. A greater understanding of why VR works in the training context would help training designers create effective programs that leverage this continuously developing technology. This paper provides a typology of VR technologies specifically relevant to HR and integrates HR training frameworks and theory into findings on VR training from these other literatures. We specifically focus on immersive VR technology and seek to better understand reasons for the effectiveness of VR technologies for both training and assessment. We review findings, integrate related streams of research, and offer guideposts for those contemplating VR implementation in four important areas: training reactions in a VR context, VR-specific learning outcomes, opportunities for assessment using VR, and the effect of VR on training transfer. We conclude the paper by identifying a VR-training agenda for HR researchers.