Presenting an Open Government Data driven Innovation Model using Grounded Theory

Government data collected from public funds and contains valuable data, if opened, can be usable in various areas, can stimulate innovation. It is necessary to investigate contexts and factors affecting the Open Government Data driven Innovation (OGDI). The main question of research is: How does open government data lead to the creation of innovation? So that, trying to answer six sub-questions consisting: causal conditions, background conditions, intervening conditions, main phenomenon, strategies, and consequences about OGDI. This research, according to mixed method (qualitative-quantitative), first used the grounded theory based on Strauss-Corbin method; then due to qualitative analysis of data obtained from interviews, three-stage coding was used; next a quantitatively evaluated done by using Shannon's entropy method. Based on data sufficiency principle, up to theoretical saturation stage, 11 semi-structured interactive interviews with experts were done. Due to results obtained from interviews, 6 main categories according to the sub-questions of the research, and 20 sub-categories containing 95 concepts were extracted. Attention requirements per each main categories, subcategories and concepts were suggested for future research. Proposed theoretical model shows that, at first step, if "setting of supporting laws for OGDI", and "the demands of external stakeholders" (causal conditions) are done correctly; and at second step if simultaneously "market development and investment in OGDI" (context conditions), "drafting the data governance document" (main phenomenon), and "utilizing the capacity of the private sector in form of PPP"(intervention condition), executed correctly; also in third step, by using all types of innovation (strategy), it will achieve consequences such as transparency in the organization, solving "stagnation of private businesses" and "unemployment in society" problems.