Big data is an emerging field that combines expertise across a range of domains, including software development, data management and statistics. However, it has been shown that big data projects suffer because they often operate at a low level of process maturity. To help address this gap, the Diffusion of Innovation Theory is used as a theoretical lens to identify factors that might drive an organization to try and improve their process maturity. Specifically, thirteen acceptance factors for teams to use (or not use) a Big Data CMM are identified. These results suggest that a positive perception exists with respect to relative advantage, compatibility and observability factors, and a negative perception exists with respect to perceived complexity. While more work is required to refine the list of factors, this insight can help guide the improvement of big data team processes.
Saltz, Jeffrey, (2017). "ACCEPTANCE FACTORS FOR USING A BIG DATA CAPABILITY AND MATURITY MODEL". In Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal, June 5-10, 2017 (pp. 2602-2612). ISBN 978-0-9915567-0-0 Research-in-Progress Papers.