FG ABWL, insbesondere Planung, Innovation und Gründung
Refine
Year of publication
Document Type
Way of publication
- Open Access (11)
Keywords
- M-shopping (6)
- Mobile shopping (5)
- Basel IV (4)
- Cluster analysis (3)
- Entrepreneurship (3)
- Germany (3)
- Mobile Shopping (3)
- Acceptance (2)
- Automobilindustrie (2)
- Basel III finalisation (2)
Institute
Research profile line
Evolution has enabled living organisms to respond to sensory input very fast in order to safeguard their chances of survival. This ability is largely based on the classification of perceptions into categories and their collective processing in associative structures. These associative structures, in turn, have a remarkable similarity to the biological neural networks which perform them. The author has chosen this natural way of thinking fast as a model for an innovative bionic approach to soft computing.
Still not a remedy for academics : the use of generative AI-powered tools in bibliometric analysis
(2025)
Artificial intelligence (AI) based tools hold great promise for automating time-consuming and labor-intensive tasks where humans are prone to making mistakes. So far, AI solutions are actively used in healthcare, IT, and large data processing. Yet, their ongoing adoption across all areas of everyday lives – by both professionals and individuals – raises ethical concerns, before all in education, where a risk of misjudgments or incorrect data manipulations remains high. However, the up-to-date literature barely addresses the problems of AI integration in real-world settings for academic and teaching purposes, focusing on generalized literature reviews. At the same time, some findings report the problem of large language models (LLM), which are known for persistent hallucinations. In this preliminary paper, we portrait the existing AI-powered platforms for bibliometric analysis – both traditional academic search engines with generative extensions (Scopus AI, WoS Research Assistant, etc.) and commonly used LLM chatbots. Our major outcome is that no one of the solutions on the market is able to substitute researchers in text-mining, but rather a combination of different tools may simplify the routine tasks. We also admit that more research is needed to compare existing tools in different settings, with different data sources and bibliometric analysis tasks, in order to develop evidence-based guidelines and pedagogical safeguards to support responsible integration of AI tools into scholarly and educational contexts.
In 2010, Germany adopted its first 10-year digital transformation strategy, Digital Agenda for Europe, in order to secure the provision of high-speed Internet connections for all its households and to promote entrepreneurship. However, the goals voiced in the first edition of the European broadband development plan (and, subsequently, in national plans) were rather ambitious, given the spatial varieties between different EU members, rural and more urbanized areas. That may explain why existing studies for European countries provide mixed outcomes, highlighting the positive role of broadband development, but arguing its limited effect for declining and rural areas. Our contribution to understanding the role of recent digital transformations is twofold. First, for German counties and independent states, we were able to support the view that better penetration of broadband contributes positively to the firm dynamics, both in rural and urbanized areas. Second, we admit that the digital infrastructure may not be sufficient by default, and individuals do need to possess the relevant-to-market skills so that the society may benefit from augmented broadband externalities. We suggest that further policies have to target on better complementarity between relevant skills and digital transformation and not just each component isolatedly.
The adoption of Capital Requirements Regulation (CRR) III in 2024 introduced a new regulatory architecture for credit valuation adjustment (CVA), requiring financial institutions to align capital buffers with evolving counterparty credit risk. This paper provides a comparative analysis of the standardised (SA-CVA), basic (BA-CVA) and simplified (SI-CVA) approaches, incorporating detailed numerical examples and explicit mapping to CRR III provisions. By tracing BA-CVA’s theoretical lineage to the Capital Asset Pricing Model (CAPM) and Modern Portfolio Theory (MPT), the study connects supervisory regulation with foundational financial theory. The findings highlight that while SA-CVA offers risk sensitivity and potential capital relief, BA-CVA and SI-CVA serve as accessible but conservative alternatives for less complex institutions. A dual-layered CVA strategy combining Pillar 1 minimums with internal Pillar 2 overlays is recommended to manage residual risks and wrong-way exposures effectively. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
This paper presents a framework to operationalize the multidimensional construct of a bank’s business model (BBM). We conceptualize the construct from a structural perspective, defining it as its balance sheet’s strategic composition and structure, encompassing asset allocation and funding sources. In contrast to prior research, our study describes the strategic decisions made by bank management as the starting point for the analysis, excluding the results of entrepreneurial activity from the construct’s conceptualization. We analyze balance sheet data for 163 European SSM banks and their subsidiaries—which we call SSM institutions—from 2014 to 2023, sourced from the S&P MI platform’s SNL Financial Institutions database. The study focuses on six balance sheet positions—three from the asset and three from the liability side—expressed as ratios to total assets. We apply a deep autoencoder-based clustering (DAC) model to operationalize the construct and compare the results with the k-means and k-medoids approach. Our empirical analyses identify four BBMs: diversified retail, non-diversified retail, wholesale, and investment-oriented banking. The DAC model leverages the nonlinear capabilities of deep learning, outperforming traditional clustering methods. This paper contributes to the literature on BBMs on a theoretical and technical level. Theoretically, a methodology for operationalizing the construct of a BBM is presented, which can be used to conduct cause-effect analyses. Technically, advanced clustering techniques, including deep learning models, are used to improve classification accuracy and provide new insights into the diversity of banks. The approach presented in this study offers valuable applications for both academics and practitioners in analyzing the impact of BBMs on other constructs, such as performance. Policymakers can leverage this framework to evaluate and guide the development of resilient business models.
More and more routine tasks are being handled with the help of computer technologies. Science is not neglected; for example, computational linguistics programs greatly simplify the analysis of scientific literature, although not without shortcomings. In this paper, we discuss some of the common challenges that arise when conducting literature analysis in KH Coder, a free distributed software offering analysis of text documents in multiple languages. The proposed solutions, in our opinion, will help researchers obtain more reliable and qualitative results depending on the objectives of the text-mining of relevant scientific literature.
Recent changes in information and communication technologies (ICT) have considerably changed the lives of millions of people and the economy around the world. On the one hand, a better broadband infrastructure improved the life quality of households and simplified their everyday routines. On the other hand, companies have benefited from increased employees’ productivity and the emergence of new business models that do not depend any more to a large extent on the location of the company. The latter circumstance was expected to be an additional motivating factor for small and medium-sized firms, as with the development of high-speed Internet, they could possibly successfully compete with market leaders; such goals, for example, were voiced in the Digital Agenda 2010 for Europe (European Commission, 2010).
Nevertheless, the academic literature lacks evidence linking the improvements of ICTs with ntrepreneurship (firm entries) and mostly reveals the state of the art for the developed countries, predominantly for the United States. This dissertation attempts, on the one hand, to cover the existing research gap for Germany as previous studies are based on outdated data from the DSL era, or refer to the firm productivity or economic performance. On the other hand, we try to investigate the experience of less developed countries and hence include two specific cases: one is Palestine (where the recent introduction of 3G connectivity boosted the business activity) and the second is Lithuania (an underperforming EU member with a complex historical background).
The main conclusion from this dissertation is that broadband, as a rule, has a statistically positive relation to the number of firm entries, which stays in line with recent studies. Whether the effect of high-speed connections is amplified thanks to other externalities, such as the presence of a highly qualified workforce (skill complementarity) or entrepreneurial training, remains beyond the scope of this work due to statistical data imperfections and is expected to be researched by the author in the future.
The ongoing digitalization had a global impact on economic patterns. With better broadband infrastructure, new businesses rely more on digital tools and technologies, are able to grow faster, and reach customers in remote markets. However, despite the growing importance of high-speed internet, there is a lack of research linking broadband provision to firm entries. This paper fills this gap by examining the relationship between the improvements in mobile internet speed and the firm entries in Lithuania over the 5-year time period from 2014 to 2019, the active phase of implementation of the Digital Agenda for Europe. As a result, we observed a negative and significant at 10% level relationship between changes in internet speed and business creation, which contradicts the recent findings in the existing literature.
Autonomes Fahren stellt einen Meilenstein in der Mobilität, seit der Erfindung des Personenkraftwagens, dar. Der Fortschritt in der Entwicklung des automatisierten Fahrens steigt stetig und vollautomatisiertes Fahren wird in naher Zukunft möglich sein. (Strijbosch 2018, S. 28-29) Da Vertrauen die Voraussetzung für die Technologieakzeptanz der Nutzer darstellt (Davis 1989, S. 985; Wu et al. 2011, S. 573), ist das Ziel der Studie, das Vertrauen in die Sicherheit von automatisierten Fahrzeugen des Level 1, dem assistierten Fahren und Level 3, dem hochautomatisierten Fahren (Society of Automotive Engineers 2022) zu untersuchen.
Dazu werden die beiden Hypothesen H1: Es besteht ein positiver Zusammenhang zwischen Vertrauen und Sicherheit und H2: Die deutsche Bevölkerung vertraut darauf, dass automatisiertes Fahren für den Fahrenden und seine Umwelt sicher ist, untersucht. Anhand der zielgerichteten Anpassung des Technology Acceptance Modells nach Mayer et al. (1995, S. 715) und den Erweiterungen von Lee und Kolodge (2020, S. 273) sowie Lewis und Marsh (2022, S. 37), werden sieben latente Variablen Funktionalität (F), Zuverlässigkeit (Z), Kontrolle (K), Vertrauen (V), Risiko (R), Sicherheitsempfinden (SE) und Nutzungsabsicht (N) mittels Strukturgleichungsmodell analysiert.
Wesentliche Ergebnisse der durchgeführten Untersuchungen sind, dass das Vorhandensein von Fahrerassistenzsystemen einen positiven Einfluss auf alle latenten Variablen, außer (R) hat, dass das Vertrauen in automatisiertes Fahren Level 1 größer ist, als jenes in Level 3 und dass eine Abhängigkeit von (V) gegenüber (Z), (R) und (SE) besteht. Beide Hypothesen konnten im Rahmen dieser Untersuchung bestätigt werden.
Basel IV und CRR 3
(2023)