Excessive Relatedness is as Difficult as Unrelated Diversification: Evidence from Private Equity Platforms
By Prothit Sen, Sai Jakkaraju, Vivek Tandon
Citation
Sen, Prothit., Jakkaraju, Sai., Tandon, Vivek. (2025). Excessive Relatedness is as Difficult as Unrelated Diversification: Evidence from Private Equity Platforms .
Copyright
2025
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Abstract
This study examines corporate portfolio implementation in private equity (PE) "buy-and-build" platforms by distinguishing resource similarity and complementarity. While RBV links relatedness to performance, it conflates these dimensions, overlooking their distinct managerial demands. Integrating the attention-based view (ABV) with RBV, we explore how similarity and complementarity create attention trade-offs that complicate portfolio development. Using novel PE-specific measures—financial correlations for similarity and input-output interdependencies for complementarity—we analyze a proprietary dataset of PE platforms. Results show that platforms prioritizing either dimension implement faster than unrelated portfolios, but extreme relatedness increases implementation time, aligning with ABV predictions. Mechanism tests highlight external stimuli: cost pressures (e.g., high taxes) drive similarity-based scale expansion, while revenue opportunities (e.g., GenAI boom) propel complementarity-driven scope strategies, especially in digital sectors. This study advances corporate portfolio theory by addressing measurement challenges and highlighting trade-offs between scale and scope synergies in inorganic portfolio development.

Prothit Sen is an Assistant Professor of Strategy at the Indian School of Business (ISB). His research interests primarily include business model innovations and the impact of such innovations on corporate strategy decisions such as strategic alliances and private equity portfolio strategies. In terms of research methodology, Professor Sen performs empirical analyses over secondary data by using a combination of predictive models that use machine learning algorithms and classical econometric techniques for making causal inferences regarding the phenomena of his interest.

Prior to completing his PhD, Professor Sen worked for several years as a consultant at Bain & Company in Gurgaon, India. His advisory experience in India spanned across manufacturing, automotive, IT services, and private equity sectors.

Prothit Sen
Prothit Sen