2022, Hinkelmann, Knut

2022, Hinkelmann, Knut, Gerber, Aurona

2021, Heimsch, Fabian, Lüthi, Erhard, Gerber, Aurona, Hinkelmann, Knut

2020, Hinkelmann, Knut

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

2022, Hinkelmann, Knut

A company’s architecture can be represented by domain-specific models, which are defined by domain-specific modeling language. Since not all stakeholders are interested in the same models, dedicated views can be created to support navigation through the enterprise models. These views offer a snippet of the entire company and cover stakeholder-specific concerns. The relationships between the different views and models remain hidden and can be unveiled with much effort. The developed concept of the zoomability principle offers the ability to change the degree of detail using zoom in and out of the enterprise model. The different models and modeling languages used to express an enterprise are considered, and a form of navigation is established similar to an online map. The concept is based on two pillars,”Zoom Within” and”Zoom into Complements”. For this purpose, a metamodel was developed, which formalizes the elements used in the concept and their relationships. Developing the artifact, rules were defined that contribute to a generic approach allowing an application to another case. Furthermore, a prototype was developed, representing the zoomability principle and offering the possibility to perform zooming behavior. The artifact was evaluated through a demonstration. An additional prototype was created to demonstrate that the developed concept can be applied to a predefined set of situations.

2021, Wittmann, Xinhua, Lutfiju, Flutra, Gerber, Aurona, Hinkelmann, Knut

While interest in understanding the impact of Artificial Intelligence (AI) in the real world has been growing, there is limited research on what digital transformation means in the banking sector. The present paper aims to address this gap in the literature by means of a field study based on 11 interviews with wealth managers from across front, middle and back offices in a large Swiss bank. Our analyses suggest bank employees have relatively positive attitudes toward the adoption of new technologies. According to the research, the top three advantages for adopting AI in wealth management are: efficiency, enhanced clients’ experience and better customer insight. Yet, AI also brings new challenges to banking. Obstacles identified include process complexity, greater maintenance effort, and increased regulatory requirements. Still, AI is expected to change the banking model to an integrated, hybrid and leaner operation with digital processes that offer front-to-back solutions. With respect to the future of the bank workforce, hiring tech-savvy talent will be crucial. AI will be able to free bank employees from repetitive jobs for more interesting and creative tasks.

2021, Heimsch, Fabian, Lüthi, Erhard, Gerber, Aurona, Hinkelmann, Knut

In Switzerland, there is currently a major shortage of skilled workers in many companies and organisations. A particular bottleneck can be seen in the area of IT professions. The lack of qualified employees is a challenge for future education and training and intensifies the current competition for today's necessary and urgently sought talent in the IT sector. In this context, it will be crucial in the future how attractive and individualized compensation systems can be designed for potential employees. Needs-based compensation packages should help to attract and ultimately retain future IT professionals. The aim of this study is to measure the preferences of students of business informatics at the FHNW to analyse which elements of total rewards management are crucial for the choice of a future employer. The results will help companies optimise the total rewards system according to their needs or include those factors that can be expected to provide the best benefits for future employees. Thus, not only the total monetary value, but also the composition of financial and non-financial elements must be included in this overall consideration.The aim is to provide decision-makers in organisations with targeted information that will allow them to design optimal incentive packages to be an attractive employer for students of business informatics or potential employees in the informatics field.

2022, Hinkelmann, Knut

2021, Hinkelmann, Knut

Detection of check-worthy statements is a subtask in the fact-checking process, automation of which would decrease the time and burden required to fact-check a statement. This paper proposes an approach focused on the classification of statements into check-worthy and not check-worthy. For the current paper, a dataset is constructed by consulting different fact-checking organizations. It contains debates and speeches in the domain of politics. Thus, even the ability of check worthy approach is evaluated on this domain. It starts with extracting sentence-level and context features from the sentences, and classifying them based on these features. The feature set and context were chosen after several experiments, based on how well they differentiate check-worthy statements. The findings indicated that the context in the approach gives considerable contribution in the classification, while also using more general features to capture information from the sentences. The results were analyzed by examining all features used, assessing their contribution in classification, and how well the approach performs in speeches and debates separately to detect the check worthy statements to reduce the time and burden of fact checking process.

2021, Göldi, Susan, Kraft, Corin, Vitacco, Jacqueline, Gerber, Aurona, Hinkelmann, Knut

This article provides a brief overview on transformative trends in corporate communications based on a literature review. Furthermore, it presents a framework model on how to transform corporate communications in the digital age. The model is based on a grounded theory approach derived in a field study completed in 2015, which claims that more heterarchical structures in corporate communications are needed. In a subsequent project, the model is tested in an ongoing exploratory study. Based on the learnings from the two studies, we suggest a new model on how to organize corporate communications in the digital age. At the center of the new model are written and audio-visual content, created by associates in a collaborative process and supported by the organization.