| Abstrakt: |
Introduction: An open data-based business needs business models and a shared environment called an ecosystem. This research aimed to provide a framework for managing a businessoriented open data ecosystem. Methodology: The research used a qualitative grounded theory method. Data were gathered using deep semi-structured interviews. The research population consisted of 15 experts of macro-data, open innovations and data management domains. Hence, purposive sampling was used to select the interviewees. Data were analyzed using open, axial and selective coding stages. Findings: The findings of the proposed model included the sections of causal conditions, strategies, intervening conditions, infrastructure conditions and their outcomes. Causal conditions were embedded in factors such as data-oriented approach, program-oriented approach, use-anduser-oriented approach, Network and ecosystem approach and open innovation approach. Intervening conditions were value-based mechanisms based on the open data and customers. The contextual conditions included several categories such as business contextualization, legal requirements, institutional requirements, technical requirements, operational-process requirements and cultural-social requirements. Strategies such as business, relationship profit, and innovation process management should be employed to manage the open data ecosystem. The outcome of open data ecosystem management included value proposition, cost structure and revenue stream, skill capability, organizational capability and information technology capability. Conclusion: The framework proposed in this study helps data-based businesses identify key components of open data ecosystem management and focuses on the capacity of open data ecosystem value creation to develop innovative information flows. [ABSTRACT FROM AUTHOR] |
