We introduce novel metrics to evaluate production process heterogeneity using both machine learning (ML) and traditional kernels. ML kernels, particularly through economically motivated transfer learning models, enhance M&A forecasting accuracy. A wider gap in firms' production processes predicts fewer M&As, lower success rates, reduced returns, diminished post-M&A growth, and increased divestiture. Dynamic learning among repeat acquirors mitigates adverse effects of production process dissimilarity on post-M&A growth. The adoption of Right-to-Work laws, reducing employees' bargaining power, significantly alleviates detrimental effects of heterogeneous production processes. Our findings underscore the pivotal role of technology heterogeneity in shaping integration synergy and firm boundary decisions.

I document novel evidence of a substitutionary relationship in supply chain innovation: When R&D becomes relatively cheaper upstream through state tax credits, customers strategically reduce innovative investment while their suppliers increase it. Suppliers produce no additional patents from the increased R&D; instead, customers accrue more patents in their suppliers’ technological domains. These patents are more exploratory and garner more citations. As mechanisms through which upstream R&D can translate to downstream patents, formal alliances and collaborative patenting arrangements become more frequent. Collectively, findings indicate firms can outsource innovative expenditures upstream, while still reaping the innovative outputs, blurring traditional firm boundaries.

We document a large and rising intangible investment gap between small and large U.S. firms. Smaller firms invest disproportionately in intangible capital, despite facing tighter financing constraints, and this gap has tripled since the 1980s alongside a pronounced increase in intangible investment volatility. We develop a dynamic industry-equilibrium model in which firms invest in both physical and intangible capital under financial frictions. Intangible investment is subject to idiosyncratic quality shocks and can be partially financed internally through equity-based compensation. These features generate an option like payoff to intangible investment: downside risk is limited by exit, while upside gains scale with realized quality. This mechanism makes intangible capital particularly attractive for small firms with high exit risk. Our analysis reveals that the joint increase in intangible investment volatility and the decline in financing frictions for intangible capital account for approximately 60% of the post-2000 gap in intangible-to-physical capital ratios between small and large firms over the 2001–2023 period.