Data sharing practice in Big Data ecosystems

Abstract

Big data has gained popularity in recent years both in industry and academia given actual and potential impact on contemporary business organizations. The combination of datasets, both internal and external to an organization, and the reuse of data for different purposes have been pointed to as the greatest value of big data (Davenport, 2013; Barton & Court, 2012). However, little is known (Thomas & Leiponen, 2016) about how firms, and particularly traditional industries, actually share data and which mechanisms they use to do so. While Open Innovation literature has already comprehensively captured the use of the various organizational modes through which external sources of knowledge are combined with internal developed knowledge (Chesbrough, 2003a, 2003b), they have not yet been applied to the understanding of data sharing practices in big data ecosystems and how industry characteristics affect the modes that companies use to share data in traditional industries. From a purposeful sampling of 102 real-life cases covering corporate early adopters of Big Data in eleven traditional sectors, this paper develops a conceptual framework of organizational modes implemented by traditional business in the big data ecosystem to extract business value from big data.