SI seminar with Aseem Kaul

Strategic redundancy in the use of third-party big data: Evidence from a two-sided labor matching platform. By: Moshe A. Barach (University of Minnesota), Aseem Kaul (University of Minnesota), Ming Leung (UC Irvine), Sibo Lu (Upwork.com) Seminar Speaker: Aseem Kaul (University of Minnesota)

Wednesday, June 12, 2019 - 13:00 to 14:15

In this study, we examine how firms use the big data capabilities of third-party platforms to find transaction partners. While 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 therefore argue that firms will invest in strategic redundancy, i.e., they will continue to partly rely on their internal capabilities to identify partners so as to maintain their bargaining power relative to the platform. We further predict that this reliance on internal capabilities will be greater, the lower the relative advantage of the platform, 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 research 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 sub-markets, and for firms with greater experience on the platform. Our study thus sheds new light on how firms make use of (third-party) big data techniques, emphasizing the strategic need to maintain independence as a barrier to big data adoption.

 

The seminar takes place in Kilen, room 2.53. The seminar is open to all. 
 

The page was last edited by: Department of Strategy and Innovation // 01/25/2024