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While digitalization offers numerous new possibilities for value creation, managers have to overcome a number of threats and obstacles that it harbors. In this context, the concept of Corporate Digital Responsibility (CDR) is of increasing interest to practitioners. Drawing on the well-established paradigm of Corporate Social Responsibility, CDR comprises a set of principles designed to encourage the ethical and conscientious development, adoption, and utilization of digital technologies. This work aims at contributing to the evolving research base by empirically assessing consumer preferences and a consumer segmentation approach with regard to companies’ concrete CDR activities, thus supporting the operationalization of CDR. Hence, this work provides concrete guidance for firms’ CDR activities in practice. To this end, a series of Best–Worst Scaling and dual response studies with a representative sample of 663 German-speaking participants assesses consumers’ perspectives on firms’ concrete (possible) activities within several CDR dimensions. Both DURE studies reveal the potential halo effect of data privacy and security activities on the perception of the CDR engagement at large, suggesting a more holistic approach to digital responsibilities. Besides, the findings reveal that in case of CDR one size does not fit all. Especially in terms of informational approaches, consumer preferences are rather heterogeneous suggesting that consumer segmentation is beneficial for companies. Additionally, the high importance of price for the consumers’ evaluation shows that it can be useful to offer a slimmed-down version in terms of CDR activities for more price-conscious consumers.
A key technology driving the digital transformation of the economy is artificial intelligence (AI). It has gained a high degree of public attention with the initial release of the chatbot ChatGPT, which demonstrates the potential of generative AI (GAI) as a relatively new segment within AI. It is widely expected that GAI will shape the future of many industries and society in the coming years. This article provides a brief overview of the foundations of generative AI (“GAI”) including machine learning and what distinguishes it from other fields of AI. Furthermore, we look at important players in this emerging market, possible use cases and the expected economic potential as of today. It is apparent that, once again, a few US-based Big Tech firms are about to dominate this emerging technology and that the European tech sector is falling further behind. Finally, we conclude that the recently adopted Digital Markets Act (DMA) and the Digital Service Act (DSA) as well as the upcoming AI Act should be reviewed to ensure that the regulatory framework of European digital markets keeps up with the accelerated development of AI.