Capability as Projection of an Append-Only Organizational Log: An Event-Sourced Substrate Theory of Organizational Capability and Transfer Failure

This paper specifies an event-sourced substrate beneath organizational capability rather than treating capability as a stored stock of resources or routines. Capabilities are computed from the cumulative trace of what a firm has actually done, evaluated at the moment a strategic question is asked. The paper specifies three formal objects: a partially ordered log of immutable events, a projection operator that reads the log under a query and a render time, and a compatibility function that scores log-merge events such as acquisitions. Four propositions follow: clean log merges preserve projection continuity; snapshot imports without the underlying log diverge within three years; writedown magnitude in failed M&A is jointly determined by raw log incompatibility and acquirer integration-policy choice; imitators who observe only the projection cannot replicate capability responses to novel queries. The framework is illustrated by three honestly coded process-traced cases – Disney’s 2006 acquisition of Pixar, Microsoft’s 2014 acquisition of Nokia’s handset assets, and persistent imitation failure of the Toyota Production System – under a single-coder pass of a pre-registered protocol. A worked Monte Carlo simulation reproduces the predicted comparative statics. The substrate-projection distinction reframes the long-running tautology critique of dynamic capabilities as a category error and generates falsifiable predictions about transfer failure. Includes zharnikov-2026al-capability-as-projection.yaml (Paper Spec v0.1.0) – a machine-readable specification of the paper's claims, assumptions, and dependencies. The paper's full machine-first bundle (the SPINE claim/dependency graph and the ONTOLOGY term module) lives in the public repository; see https://github.com/spectralbranding/paper-spec for the standard. This PDF is generated programmatically from that machine-first source under a research-as-repository model.