Threat intelligence sharing is an important countermeasure against the increasing number of security threats to which companies and governments are exposed. Its objective is the cross-organizational exchange of information about actual and potential threats. In recent years, a heterogeneous market of threat intelligence sharing platforms (TISPs) has emerged. These platforms are inter-organizational systems that support collaborative collection, aggregation, analysis and dissemination of threat-related information. Organizations that consider using TISPs are often faced with the challenge of selecting suitable platforms. To facilitate the evaluation of TISPs, we present a framework for analyzing and comparing relevant TISPs. Our framework provides a set of 25 functional and non-functional criteria that support potential users in selecting suitable platforms. We demonstrate the applicability of our evaluation framework by assessing three platforms: MISP, OTX and ThreatQ. We describe common features and differences between the three platforms.

Digital transformation impacts longstanding business models and enables enterprises to create new ones. This transformation leads to increased competition that forces enterprises to compete, not only between companies but also between the entire supply chain and business networks. The emerging concept of digital business ecosystems (DBE) allows enterprises to concentrate on network co-creation and co-evolution of bundled services and products across enterprise boundaries. This exploratory study introduces a maturity model derived from existing DBEs. Based on employing a design science methodology, we reviewed 22 scientific publications, interviewed 28 senior experts from practice and derived a maturity model from the results. We applied the maturity model through an online survey to 29 DBEs from different industry sectors and compared it with 22 maturity assessment approaches from other domains. The maturity model enables researchers to compare and assess existing DBEs and helps practitioners to identify areas for improvement in the collaboration within DBEs.

The assessment of source code in university education is a central and important task for lecturers of programming courses. In doing so, educators are confronted with growing numbers of students having increasingly diverse prerequisites, a shortage of tutors, and highly dynamic learning objectives. To support lecturers in meeting these challenges, the use of automated programming assessment systems (APASs), facilitating formative assessments by providing timely, objective feedback, is a promising solution. Measuring the effectiveness and success of these platforms is crucial to understanding how such platforms should be designed, implemented, and used. However, research and practice lack a common understanding of aspects influencing the success of APASs. To address these issues, we have devised a success model for APASs based on established models from information systems as well as blended learning research and conducted an online survey with 414 students using the same APAS. In addition, we examined the role of mediators intervening between technology-, system- or self-related factors, respectively, and the users' satisfaction with APASs. Ultimately, our research has yielded a model of success comprising seven constructs influencing user satisfaction with an APAS.