Organizational Selection of Innovation

Summary

A formal Organization Science model of portfolio selection that compares delegation against several explicit aggregation rules and finds that aggregating multiple agents' impressions beats delegation in most settings, that delegation wins only when the organization actually employs the relevant experts and can route projects to them, and - the key result - that letting agents rank projects often outperforms averaging their scores or counting approval votes, especially under tight budgets when few alternatives can be selected from many. This is the management-venue antecedent that most directly prefigures the ISR paper's aggregation-rule dimension, and it gives the paper a ready-made rule set (ranking, averaging, approval voting, delegation) with theoretical predictions to test against LLM agents. Outside the window but absent from the knowledge base and hard to justify omitting from an ISR framing built on organizational design.

Contribution

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Method

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Relevance to RISE

Surfaced by the 2026-09-07 literature sweep as a high-priority candidate for the Architecture as Epistemology (ISR) paper (angle: organization theory applied to AI agents). Verified against: Verified via Semantic Scholar Graph API record for DOI 10.1287/orsc.2023.17357 on 2026-09-07: full abstract read, 2 authors, Organization Science, publication date 2024-05-16, arXiv preprint 2405.09843. INFORMS publisher page returns HTTP 403 to automated fetching.

Critique / open questions

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Key quotes

Budgetary constraints force organizations to pursue only a subset of possible innovation projects. (abstract)

Identifying which subset is most promising is an error-prone exercise, and involving multiple decision makers may be prudent. (abstract)