Advancing M&A Research with a Novel Dataset on Post-Acquisition Integration: Performance and Innovation Implications

Post-acquisition integration is the process of aligning operations, structures, and routines between the acquiring and target firms after an M&A deal is closed. While integration can unlock synergies and long-term value, it can also disrupt established practices and create internal resistance. Although post-acquisition integration has been the object of many studies in corporate strategy (e.g., Barkema & Schijven, 2008; Graebner et al., 2017; Larsson & Finkelstein, 1999; Zaheer et al., 2013), data availability and measurement challenges have hindered empirical analysis both on the role of post-acquisition integration in shaping the outcomes of M&A activities (e.g., performance, innovation output) and on the key drivers that lead to the decision to integrate a target firm (e.g., quality or business of the target firm). Studies based on surveys-based measures offer rich but small-scale insights that are subject to generalizability issues. Studies focusing on media-based proxies offer a more scalable measure of post-acquisition integration, but they typically rely on blurred signals of integration occurrence. Overall, the academic community still lacks a comprehensive dataset that can measure post-acquisition integration on a large scale. Thus, this study aims to develop an open-access dataset to measure post-acquisition integration, revisit one of the core findings in M&A research (i.e., the influence of post-acquisition integration on acquisition performance), and explore post-acquisition integration's role on firms’ innovation capacity.

Subproject #1 primarily aims to develop an open-access dataset of post-acquisition integration by leveraging two existing datasets: SDC Platinum and the National Establishment Time Series (NETS). To do so, it will track structural changes in the acquiring and target firms—such as closing or relocating facilities, reassigning workforces, and restructuring revenue flows—before and after the deal closing. The expected outcome is a dataset of measures of post-acquisition integration covering nearly 190,000 deals in the US from 1989 to the present, representing ~65% of all deals included in the SDC database during the examination period.

Subproject #2 utilizes the resulting dataset to revisit one of the core debates in M&A research: Does higher integration necessarily lead to better acquisition performance, or does it destroy value? Under what boundary conditions? Prior studies report mixed findings, highlighting both the benefits of synergy and the potential erosion of routines and key personnel. This subproject will test, on a large scale, whether integration is beneficial on average and under what conditions it is more beneficial—such as organizational similarity or prior M&A experience.

Subproject #3 narrows the analyses to the pharmaceutical sector (included in the database of Subproject #1) and explores another key question in M&A research (Paruchuri et al., 2006; Puranam et al., 2006; Valentini, 2012)-i.e., how integration practices influence firms’ innovation capacity. The pharmaceutical sector is an ideal setting to explore the connection between M&A and innovation due to the prominent role of M&A activities in an industry that is heavily dependent on innovation (e.g., pipeline management). By linking the new integration metrics with drug development data, this subproject aims to assess whether specific integration strategies improve R&D outcomes, accelerate clinical trials, raise approval success rates, or stifle promising projects through overly aggressive restructuring.