User-generated online comments and posts increasingly contain abusive content that needs moderation from an ethical but also legislative perspective. The amount of comments and the need for moderation in our digital world often overpower the capacity of manual moderation. To remedy this, platforms often adopt semi-automated moderation systems. However, because such systems are typically black boxes, user trust in and acceptance of the system is not easily achieved, as black box systems can be perceived as nontransparent and moderating user comments is easily associated with censorship. Therefore, we investigate the relationship of system transparency through explanations, user trust and system acceptance with an online experiment. Our results show that the transparency of an automatic online comment moderation system is a prerequisite for user trust in the system. However, the objective transparency of the moderation system does not influence the user's acceptance.

Decision makers in organisations are often overtaxed by huge amounts of information in daily business processes. As a potential support strategy, this study examined ‘directed forgetting’ (Bjork, 1970) in a simulated sales planning scenario. We assumed that the availability of a computer-based decision support system (DSS) triggers the forgetting of decision-related background information. Such directed forgetting should not only release memory capacities for additional tasks but also enhance decision quality and decrease strain of decision makers. Assumptions were tested in an experimental study with N = 90 participants. Consistent with our assumptions, results revealed a higher recall of decision-unrelated information, higher decision quality and higher well-being when participants could use a DSS as compared to two Control conditions without a DSS. Moreover, directed forgetting effects were qualified by participants’ trust in the DSS. This study provides the first evidence for directed forgetting effects cued by information systems in a business context. Practitioner summary: Information overload is an increasing challenge in modern business organisations. Extending findings from basic memory research, this study shows that availability of a computer-based decision support system triggers forgetting of decision-related background information, which in turn increases users’ mental resources for additional tasks, decision quality, and well-being.

A unified framework outlining the procedures and methods necessary to adhere to data management standards is essential for effective Data Governance. Data Governance Frameworks serve as a guide to secure and trustworthy data exchange between different (legal) entities. Their specific implications differ based on the field they are incorporated in. Thus, to extract their full potential, they need to be suitably designed. However, there is a lack of knowledge in the literature concerning the assets and components of Data Governance Frameworks tailored for data intermediaries, including Data Trusts. Moreover, there is a limited understanding of what crucial components the frameworks consist of and how they can be managed to maximize frameworks’ performance. The level of effectiveness of such frameworks needs to be measured by analyzing the performance of certain assets. These relations between the components and the assets are yet to be thoroughly explored and precisely defined. Establishing a strong link between the components and assets gives an overview to practitioners on how the intended assets can be fulfilled properly with the corresponding component. Therefore, practitioners can tackle the respective management components to achieve the intended trustworthiness in the data trust ecosystem. This study conducts a systematic analysis of existing Data Governance Frameworks, identifying the crucial assets as well as components, and provides a mapping between them. The findings set a base that enables the development of a comprehensive Data Governance Framework tailored specifically for Data Trusts.