Big Data, Proxies, Algorithmic Decision-Making and the Future of Management Theory

Abstract

The future of theory in the age of big data and algorithms is a frequent topic in management research. However, with corporate ownership of big data and data processing capabilities designed for profit generation increasing rapidly, we witness a shift from scientific to ‘corporate empiricism’. Building on this debate, our ‘Point’ essay argues that theorizing in management research is at risk now. Unlike the ‘Counterpoint’ article, which portrays a bright future for management theory given available technological opportunities, we are concerned about management researchers increasingly ‘borrowing’ data from the corporate realm (e.g., Google et al.) to build or test theory. Our objection is that this data borrowing can harm scientific theorizing due to how scaling effects, proxy measures and algorithmic decision-making performatively combine to undermine the scientific validity of theories. This undermining occurs through reducing scientific explanations, while technology shapes theory and reality in a profit-predicting rather than in a truth-seeking manner. Our essay has meta-theoretical implications for management theory per se, as well as for political debates concerning the jurisdiction and legitimacy of knowledge claims in management research. Practically, these implications connect to debates on scientific responsibilities of researchers.