Strategic redundancy in the use of big data: Evidence from a two-sided labor market

In this study, we examine how firms use the big data capabilities of third-party platforms to find transaction partners. Although use of the platform's big data capabilities creates value by lowering search costs, firms may capture little of this value if they become entirely dependent on the platform. We argue that firms invest in strategic redundancy, that is, they continue to rely partly on their internal screening capabilities to identify partners so as to maintain their bargaining power relative to the platform. We further predict that this reliance on internal screening is greater the lower the relative advantage of the platform's big data capabilities and the more salient the threat to the firm's bargaining power. We test these predictions in the context of an online labor platform, using a regression discontinuity design to examine the effect of the platform's recommendations on the firm's decision to hire an applicant. Consistent with our theory, we find that firms' use of the platform's recommendations is lower in later stages of the hiring process, in larger submarkets, and for firms with greater experience on the platform. Our study sheds new light on how firms make use of (third-party) big data techniques, showing that firms may strategically choose to limit such use in order to maintain independence.