Corporate Hierarchy and Organizational Learning: Member Turnover, Code Change, and Innovation in the Multiunit Firm

Abstract

This study examines how recombinant innovation is affected by member turnover and organizational learning within a corporate hierarchy. Prior work has overlooked the role of organizational structure in organizational learning, focusing instead on the knowledge provided by individual new hires or on the disruption caused by individual departures. We address this gap by applying March’s [March JG (1991) Exploration and exploitation in organizational learning. Organ. Sci. 2(1):71–87.] mutual learning model to a corporate hierarchy. In doing so, we theorize how the contributions of corporate staff to socializing new employees and to learning from the organizational code may differ from those of the organization’s subunit members. Empirically, we examine the learning effects of aggregate corporate and subunit arrivals and departures on novel recombinant innovation by subunits. Using 24 years of Motorola company directories, we construct membership turnover measures for corporate and subunit employees and exploit patent data to capture recombinant innovation. Our results suggest that, whereas the influx of new ideas through arrivals may be critical, breaking the pattern of inertial behavior through departures is more important for recombinant innovation. Corporate departures matter most for recombinant innovation, a result that reflects not only corporate staff’s slower individual learning from the organizational code but also its ability to update that code more quickly. In supplementary analyses, we find different effects for technical and nontechnical staff and internal and external arrivals, as well as demonstrate the mutual learning mechanism using internal corporate documents to capture code change. Our study has strong implications for theories of organizational learning, strategic human capital, organization design, and innovation. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2022.1618 .