New political objectives, emerging regulatory regimes for the digital sphere, and higher penalties for violations have intensified the pressure to develop lawful IT artefacts. As the adaptation of existing IT artefacts to new regulations can be expensive and arduous, a more attractive approach would be to design IT artefacts lawfully from the beginning. A major challenge is that the law is generally technology-neutral, and lawful design requires legal expertise throughout the development, which is costly and time consuming due to communication challenges between legal experts and developers. One possible approach to proactively consider IT regulations in the systems development is design patterns that convey legal design knowledge and support developers in determining the appropriate design options. Consequently, we develop a framework for lawful design patterns and demonstrate their feasibility and advantages using the example of developing AI-based assistants and the regulation of the General Data Protection Regulation (GDPR). Using the design pattern framework, we develop design patterns for lawful AI-based assistants and evaluate them using (a) an experimental approach to show the usefulness of the patterns for developers and (b) rely on a legal simulation study to holistically evaluate how design patterns contribute to lawful IT.

This paper employs a longitudinal perspective to examine continued system use (CSU) by individuals in utilitarian, volitional contexts when alternative systems are present . We focus on two key behavioural antecedents of CSU – habit and continuance intention – and theorise how the relationships between CSU and these antecedents evolve over time. In addition, we hypothesise how the interaction effect of habit and intention on CSU evolves temporally. Our theorising differs from extant literature in two important respects: 1) In contrast to the widespread acceptance of the diminishing effect of continuance intention on CSU in the information systems (IS) literature, we hypothesise that in our context, its impact increases with time; and 2) In contrast to the negative moderation effect of habit on the relationship between intention and CSU proposed in the literature, we posit a positive interaction effect. We collect longitudinal survey data on the use of a higher education IS from students in a European university. Our results suggest that the impact of continuance intention on CSU as well as the interaction effect between habit and intention are increasing over time. We further introduce a methodological innovation – the permutation approach to conduct the multi-group analysis with repeated measures – to the literature.

The adoption of innovative technologies confronts IT-Service-Management (ITSM) with an increasing volume and variety of requests. Artificial intelligence (AI) possesses the potential to augment customer service employees. However, the training data for AI systems are annotated by domain experts with little interest in labeling correctly due to their limited perceived value. Ultimately, insufficient labeled data leads to diminishing returns in AI performance. Following a design science research approach, we provide a novel human-in-the-loop (HIL) design for ITSM support ticket recommendations by incorporating a value co-creation perspective. The design incentivizes ITSM agents to provide labels during their everyday ticket-handling procedures. We develop a functional prototype based on 17,120 support tickets provided by a pilot partner as an instantiation and evaluate the design through accuracy metrics and user evaluations. Our evaluation revealed that recommendations after label improvement showed increased user ratings, and users are willing to contribute their domain knowledge. The improved labels can be utilized to continuously enhance the AI system as rewards showed increasing growth with decreasing marginal returns. Overall, our results emphasize agents' need for value-in-use by providing better results if they improve the labeling of support tickets pre-labeled by AI. Thus, we provide prescriptive knowledge of a novel HIL design that enables efficient and interactive labeling in the context of diverse applications of reinforcement learning systems.

IT carve-out projects are complex and cost-intensive components of M&A transactions. Existing research sheds little light on the determinants of IT carve-out project complexity and/or its effects on divestor performance. Instead, research has focused on the post-acquisition IT integration project and acquirer performance. This paper presents the first divestor-centric model of IT transactions from the divestor to the acquirer when a Business Unit in a Multi-Business Organization (MBO) is carved out and integrated into another MBO. The model explains how divestor business and IT alignment pre-conditions contribute to increased IT carve-out project complexity. Such complexity increases IT carve-out project time to physical IT separation and creates IT stranded assets, which decrease post-divestment business, IT alignment and divestor performance. The current recommended strategy of adopting transitional service agreements (TSAs) to handle IT carve-out complexity is compared with two new proactive strategies derived from the model. TSA-based strategies restrict the divestor from both decommissioning IT stranded assets and reconfiguring its IT assets to support its new post-divestment business strategy. The two new strategies address IT carve-out complexity without incurring the negative effects from adopting TSAs.

1. With thousands of peer-reviewed publications and thousands of applications in education, industry, and government, gamification has taken the world by storm. But this explosion of gamification i...

Technology acceptance research has shown that trust is an important factor fostering use of information systems (IS). As a result, numerous IS researchers have studied factors that build trust in I...

This research-in-progress paper presents a research project that aims at developing, piloting and evaluating a crowdfunding platform to support financing for start-ups emerging from university. Currently, universities' own financial resources to support setting up businesses from universities are limited. Universities' business foundation consultancy can often only intermediate between entrepreneurs on the one side and restricted funding programs or few investors on the other side. A crowdfunding platform enables many individuals of the (university) crowd to support promising business ideas with little investments cumulating to a greater sum in total. Thus, it has the potential to extend universities' opportunities to support entrepreneurs. In addition, tasks like idea communication, idea evaluation and investment decisions can be outsourced to the crowd. The idea, research setting, first results and a future outlook of this research project are discussed in this paper.