13.07.2022 | Vier Beiträge auf der AMCIS 2022

Die Professur für Anwendungssysteme und E-Business ist mit vier Beiträgen auf der Americas Conference on Information Systems 2022 (AMCIS 2022) vertreten:

Christian Finke präsentiert den Beitrag: "Using Distributed Ledger Technologies to Support Complex Supply Chains"

Abstract: The concept of blockchain, as part of distributed ledger technologies, has gained a lot of interest recently, especially in cryptocurrencies. With the addition of other technical capabilities, e.g., smart contracts and oracles, this interest has spread to other areas as well and affects a wide variety of business processes such as supply chain processes. However, in research, the wide variety of processes finds inadequate consideration to date. In this research paper, we provide an overview of the state of the art of distributed ledger technologies in supply chains and point out future research topics. Therefore, we conducted a structured literature review, systematized potential application areas in supply chain processes, and showed that research gaps exist. To address the research gaps, we derived open research questions, whereby conducting design studies to deal with the practical problems in the application areas plays a central role.

Philipp Hartmann präsentiert den Beitrag: "Trust, but Verify! - An Empirical Investigation of Students’ Initial Trust in AI-Based Essay Scoring"

Abstract: AI is becoming increasingly important in supporting education. Nowadays, AI-based systems can score essays in high-stakes exams not only by comparing words but also by evaluating content. However, for AI-based essay scoring systems to be used, they must be trusted. Based on a scenario-based experiment with 260 students at a German university, we were able to show that their initial trust in AI-based essay scoring systems is significantly lower than in human examiners. Human control of AI-scoring can partially reduce the negative effect. The perceived system characteristics and the personality traits of the students are important factors which positively influence trustworthiness and trust, respectively. Furthermore, we could show that the more complex the essay scoring is perceived, the less trustworthy the AI-based system is classified. No influence could be seen regarding the relevance of the scoring for the students, their AI-experience and technology affinity.

Abstract: The overall goal of this research study is to improve students’ modeling skills in large-scale educational settings by providing video-based case studies and introducing a formative peer feedback process to enable asynchronous, anonymous collaboration among the students. To this aim, we designed a learning concept and implemented an app that supports the provision of video-based case studies and the conduction of a double-blind peer feedback process. Our results from introducing the digital learning concept in an introductory course targeting information systems students indicate that the students’ motivation and reflection on the learning content could be fostered, and their modeling skills could be improved. Overall, we contribute with insights into how to conduct video-based case studies combined with peer feedback processes in information systems education.

Tobias Nießner präsentiert den Beitrag: "Influence of corporate industry affiliation in Financial Business Forecasting: A data analysis concerning competition"

Abstract: In recent years, we have seen a growing interest in the automated analysis of financial statements using AI methods. Starting from classical models motivated by financial ratios, the inclusion of additional data from financial statements, but also external data sources, plays an increasing role to improve the accuracy of existing models. We show that a closer look at the choice of location in terms of industry specifics and competition provide suitable information to optimize AI-based financial business forecasting to meet real-world requirements. Furthermore, we address the fact that competition as such has no impact on the length of reporting in financial statements with respect to their industries. This work contributes, first, by assessing the impact of competition on a company's annual financial statement, and second, by offering analysts a classification of the importance of data for forecasting.