Measuring the efficiency of U.S. pharmaceutical companies based on open innovation types

Abstract

The pharmaceutical industry, where research and development (R & D) efficiency is central to company survival, has recently faced significant challenges. To increase efficiency, companies must implement strategies such as open innovation (OI), wherein they sell their intellectual property, maximize their use of external resources, adjust their structures, and implement new business models. In this study, we divided 701 U.S. pharmaceutical companies according to their OI strategies to measure and compare their R & D efficiencies between 2001 and 2016. We analyzed the deal data of companies by first dividing them into four groups (inside-out, outside-in, coupled, and closed) to calculate R & D efficiency using stochastic and meta-frontier analyses. In the first group analysis, the coupled group shows high technical efficiency, but in an overall comparison, the inside-out group achieves the highest efficiency values. These values increased between 2005 and 2010, when the R & D crisis in the industry was great at its highest. We thus identified the characteristics of each group based on our results, and presented extensive analyses using a time-series comparison and enterprise-level analysis. We claim that pharmaceutical companies can still cope with the current R & D crisis by implementing different OI strategies.