06. May 2020 : Two Papers accepted at ECIS 2020 in Marrakesh, Morocco (Virtual Conference)
We are proud to announce that the paper "The Humans Behind Artificial Intelligence – An Operationalisation of AI Competencies" by Eduard Anton, Alina Behne and Frank Teuteberg as well as the paper "Understanding the Role of Predictive and Prescriptive Analytics in Healthcare: A Multi-Stakeholder Approach" by Thuy Duong Oesterreich, Christian Fitte, Alina Behne and Frank Teuteberg have been accepted for publication at the Twenty-Eighth European Conference on Information Systems (ECIS 2020).
ECIS 2020 will be organised this year as a virtual conference from 15-17 June. The ECIS conference has a “B” ranking according to the VHB Jourqual 3 ranking and an "A" ranking according to the WKWI journal and conference ranking.
The Humans Behind Artificial Intelligence – An Operationalisation of AI Competencies
Despite the importance of artificial intelligence (AI) proficiency as a determinant for AI adoption, there remains a lack of empirical research studying competencies needed to leverage AI effectively. This paper addresses this research gap with a mixed methods approach. First, we conduct a qualitative content analysis of the practical and scientific literature to derive and structure the existing body of knowledge. We subsequently perform a quantitative content analysis of 9,247 job advertisements. We merge the results using a triangulation approach and a) present a comprehensive overview of key technical and managerial competencies essential for implementing and utilising AI on an individual level, b) highlight the demand for AI-related competencies in the three occupational fields Data Sci-ence and Engineering, Software Engineering and Development, and Business Development and Sales, and c) underline the need to adapt workforce competencies to a labour market transformation induced by AI.
Understanding the Role of Predictive and Prescriptive Analytics in Healthcare: A Multi-Stakeholder Approach
The volume, velocity and variety of data is continuously rising. While many industry sectors are already applying big data analytics for various purposes, the use of big data in healthcare remains limited. A major reason for this development lies in the fragmented structure and conflicts of interests among the various stakeholders in the sector. To date, there is a lack of a comprehensive study that integrates insights from both practical and academic literature with expert knowledge to create a holistic picture of the main use cases, challenges and benefits of predictive and prescriptive analytics (PPA) in healthcare. To fill this gap, we investigated the role of PPA in healthcare from different stakeholder perspectives. We conducted a systematic literature review and applied content analysis to identify the main patterns extracted from the literature. The findings were triangulated with insights gained from 9 interviews with healthcare experts. Overall, we identified 8 use case clusters, 18 key benefits and 10 key challenges for the stakeholders involved. Furthermore, the role of PPA in healthcare is discussed from different stakeholders’ perspectives. Our findings reveal that the stakeholders pursue contrasting interests, which require legal regulation such that PPA can diffuse on a wider scale.