Exploring the value of open data : A case study on Sweden

Abstract: The importance that governments put into open government data policies has increased over the last decade. However, a decreasing speed in this trend is potentially ongoing due to the objectives of these policies not being perceived as completed. Therefore, locating the impacts and measuring their relative value generation aids the understanding of how these objectives can succeed. This study examines the impacts of open government data in Sweden and their potential value generation, focusing on the financial ones. In this study, we developed a measurement model that comprehends six different impacts that generate a value. These impacts are innovation for established firms, innovative start-ups, innovation for public institutions, anti-corruption, and democracy/civil participation. The study has used 24 semi-structured interview findings to develop the model using the grounded theory method. The model was then subsequentially tested and validated by conducting a survey.  We used PLS-SEM as a method of analysis of the 69 responses on the survey from Swedish experts in the field. The results show a positive influence on the open government data financial value generation in the Swedish context, originating from data-driven innovation in established firms. Adding to this, positive impacts on the social value generated from open government data originate from innovative start-ups and product innovation in public institutions. The social value generated was also found to influence the financial value generation. Overall, the results also confirmed that the measurement model assessed is suited for evaluating the value generation of open government data. Thus, the study contributes to policies by visualizing the potential impacts and values that specific policy decisions may yield. Besides, the study contributes to theory thanks to developing a measurement model that could be applied to different contexts. Finally, a unique method that combines model development, context understanding, and model testing is used in the research. This method is considered a contribution due to its potential to be applied to future case study research.