Are Employees in Organizations with a Socially Oriented Mission Discouraged from Using Data-Driven Decision Models?

Organizations are increasingly emphasizing social missions beyond profits. In this study, we develop theory to suggest that this rising emphasis on social missions can make it more difficult to develop a data-driven culture by exacerbating employee algorithm aversion. In particular, for social decisions that affect the well-being of others (e.g., assessing loan applications), our theory suggests that emphasizing a social rather than profit-oriented mission will increase employees’ algorithm aversion by making them more averse to “reducing others to numbers.” To test this theory, we conduct a case-based experiment in which participants are randomly assigned to versions of the case that emphasize high-quality service as a means of either helping others (social-mission) or generating profits (profit mission). As expected, emphasizing the social rather than profit mission reduces participants’ reliance on advice from an algorithm but not their reliance on identical advice from a human expert. These findings contribute to our understanding of how social incentives change employee behavior and suggest that organizations who emphasize social missions may want to consider other controls to encourage data-driven decision-making.