Making Digital File Management Successful: A Grounded Model of DFM Adoption in the Public Sector

File management is crucial for the viability of public sector authorities. The success of digital file management (DFM) is influenced by employees\u27 IT adoption. There is a gap in research on employee perceptions of IT adoption in public sector authorities in the European Union (EU). For this reason, this study examines the adoption of the DFM system ‘E File Bund’ (GER: E-Akte Bund), based on a critical case selection of German federal authorities in the EU, and aims to identify the characteristics that determine the adoption of DFM in the public sector from employees\u27 perspective. Fifteen semi structured interviews with users and experts from German federal authorities are conducted and analyzed using the Grounded Theory Methodology (GTM). The primary contribution is a grounded model of the phenomenon DFM adoption. The results provide valuable insights for authorities, practitioners and researchers to enhance DFM adoption and contribute to the digital transformation of the public sector

AI in Government: A Study on Explainability of High-Risk AI-Systems in Law Enforcement & Police Service

Law enforcement and police service are, related to the proposed AI Act of the European Commission, part of the high-risk area of artificial intelligence (AI). As such, in the area of digital government and high-risk AI systems exists a particular responsibility for ensuring ethical and social aspects with AI usage. The AI Act also imposes explainability requirements on AI, which could be met by the usage of explainable AI (XAI). The literature has not yet addressed the characteristics of the high-risk area law enforcement and police service in relation to compliance with explainability requirements. We conducted 11 expert interviews and used the grounded theory method to develop a grounded model of the phenomenon AI explainability requirements compliance in the context of law enforcement and police service. We discuss how the model and the results can be useful to authorities, governments, practitioners and researchers alike

Success of Digital Identity Infrastructure: A Grounded Model of eID Evolution Success

Digital identities (eID) are one of the crucial building blocks of a digital infrastructure. There are major differences between countries of the European Union when it comes to the success of digital identity infrastructure, yet, we lack insights into the conditions for successful digital identity infrastructure evolution (eID evolution success). Taking the outset in a digital infrastructure perspective, we conducted 18 expert interviews in the context of the European Union with the focal case of the eID infrastructure in Germany. We used the grounded theory method to develop a model of eID evolution success. We discuss how the model can be useful to governments, practitioners and researchers alike

Work System Quality Assessment: A TIHPS Grounded Measurement Model

Work systems are natural units of analysis for thinking about systems in organizational settings. Literature has not yet considered work systems from a quality perspective, whereby quality can be approached through various perspectives (e.g. user- or value-oriented perspective). This paper aims to combine work system theory with a context-independent quality assessment instrument, in order to make the quality of work systems measurable and to better solve problems that arise in work systems (e.g. IT skill shortage). For this purpose, a literature review, seven qualitative expert interviews and a quantitative empirical validation with a total of 155 IT professionals were conducted. As a result, a measurement model to assess work system quality is developed. The results show significant correlations with work output satisfaction, employer attractiveness, high quality emphasis of organizations and concepts of ideal employers, as well as valuable insights regarding multiple factors that capture work system quality

Artificial Intelligence Explainability Requirements of the AI Act and Metrics for Measuring Compliance

Explainability in artificial intelligence (AI) is crucial for ensuring transparency, accountability, and risk mitigation, thereby addressing digital responsibility, social, ethical and ecological aspects of information system usage. AI will be regulated in the European Union (EU) through the AI Act. This regulation introduces requirements for explainable AI (XAI). This paper examines which requirements for XAI are regulated and which metrics could be used for measuring compliance. For this purpose, legal texts from the European Parliament and Council were analyzed in order to ascertain XAI requirements. Additionally, XAI taxonomies and metrics were collected. The results reveal, that the AI Act provides abstract regulations for explainability, making it challenging to define specific metrics for achieving explainability. As a solution, we propose a socio-technical metric classification for measuring compliance. Further studies should analyze forthcoming explainability requirements to make AI verifiable and minimize risks arising from AI

The TIHP Framework – An Instrument for Measuring Quality of Hybrid Services

Although services are often provided as hybrids containing digital (e.g., online-registration) and physical (e.g., on-site appointment) service components, we lack appropriate instruments that could measure the quality of hybrid services across different types of organizations. Building on prior literature in service quality measurement, we develop and validate an instrument to measure service recipient’s perceptions of quality in hybrid services that can be used by organizations in the public and private sector. The key contribution of this paper is the Technology, Information, Human, Process framework (TIHP), a measurement instrument with four quality dimensions and 28 quality attributes. Our empirical validation with answers from 121 service recipients supports the psychometric validity of this instrument. We discuss how the TIHP framework can be useful to governments, practitioners, and researchers alike

Exploring the role of the various methionine residues in the Escherichia coli CusB adapter protein.

The dissemination of resistant pathogenic microbes has become one of the most challenging problems that modern medicine has faced. Developing novel drugs based on new molecular targets that previously were not targeted, is therefore the highest priority in antibiotics research. One approach that has been recently suggested is to inhibit copper transporters in prokaryotic systems. Copper is required for many biological pathways, but sometimes it can harm the cell. Pathogenic systems have a highly sophisticated copper-regulation network; therefore, a better understanding of how this network operates at the molecular level should assist in developing the next generation of antibiotics. The CusB protein is part of the CusCBA periplasmic Cu(I) efflux system in Gram-negative bacteria, and was recently reported to play a key role in the functioning of the whole CusCBA system, in which conformational changes as well as the assembly/disassembly process control the opening of the transporter. More knowledge of the underlying mechanism is needed to attain a full understanding of CusB functioning, which is associated with targeting specific and crucial residues in CusB. Here, we combine in-vitro structural measurements, which use EPR spectroscopy and UV-Vis measurements, with cell experiments to explore the role of the various methionine residues in CusB. We targeted two methionine residues (M227 and M241) that are essential for the proper functioning of CusB