Azkan, CanStrobel, GeroIggena, LennartGelhaar, JoshuaKreyenborg, Alexander2022-12-272022-12-272023-01-03978-0-9981331-6-4https://hdl.handle.net/10125/102740Data is nowadays considered as a key resource and represents the most valuable asset of our technology-driven world. However, the ability to use this resource in a value-adding way requires a holistic perspective. Small- and medium-sized enterprises in particular face major challenges in the innovation and development process. Despite preliminary research in the area of data-driven services (DDS), there is a lack of methodological analysis of the key barriers for SMEs in the context of DDS development. To address this shortcoming, we have developed an interpretive structural model based on a two-stage mixed-method approach by combining a structured literature review with practice-oriented focus group interviews to identify key barriers and their interdependencies and interactions. Our paper strengthens the knowledge of DDS development through a methodological barrier analysis and provides a guide for practitioners to eliminate the most relevant barriers to DSS development.10engAttribution-NonCommercial-NoDerivatives 4.0 InternationalData-driven Services in Manufacturing: Innovation, Engineering, Transformation, and Managementbarrier analysisdata-driven servicesinterpretive structural modellingmanufacturingsmall- and medium-sized enterprisestext10.24251/HICSS.2023.111