LAUSR

Abstract Big Data is one of the most debated topics, as its implications for innovation management and entrepreneurship development are attracting interest from researchers and practitioners. Despite the increasing interest on this topic, a relevant research question remains unsolved: what are the conditions required for the effective management of Big Data? Adopting the interpretative lens provided by Systems Thinking and Service Logic, a set of hypotheses are defined and tested through the Partial Least Squares (PLS), with reference to the 50 Big Data companies for 2017 as identified by Big Data Quarterly. The results show that several elements such as company's investment in innovation and technology and specialization of human resource positively impact on Big Data Companies' Return on Investment (ROI). Results and discussions herein enrich previous managerial debate about the domain of Big Data highlighting ‘tangible’ elements on which act for improving innovation management approaches for companies.