Presenting an Open Data Ecosystem Management Framework from a Business Perspective with a Grounded Theory Approach

An open data-based business needs business models and a shared environment called an ecosystem. This research aims to provide a framework for managing a business-oriented open data ecosystem.

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.

The findings of the proposed model include the sections of causal conditions, strategies, intervening conditions, infrastructure conditions, and their outcomes. Causal conditions are embedded in factors such as Data-oriented approach, Program-oriented approach, Use- and User-oriented approach, Network and ecosystem approach, and open innovations approach. Intervening conditions are value-based mechanisms based on open data and customers. The Contextual conditions include several categories such as business contextualization, legal requirement, institutional requirement, technical requirement, operational-process requirement, and cultural-social requirement. Strategies such as business, relationship profit, and innovation process management must be employed to manage the open data ecosystem. The outcomes of open data ecosystem management will include value proposition, cost structure and revenue stream, skill capability, organizational capability, and information technology capability.

The framework proposed in this study helps data-based businesses to identify key components of open data ecosystem management and focuses on the capacity of open data ecosystem value creation to develop innovative information flows.