Network-Dependent Allocation (NDL)
NDL — Condition where valuation depends on network relationships and representation quality.
Description
Network-dependent allocation occurs when asset valuation depends on network relationships within consideration infrastructure. When ranking and valuation become network-dependent on representation quality, allocative outcomes shift in ways traditional metrics cannot capture.
Related Concepts
Related Research
Inferential Monopoly Theory
This working paper introduces inferential monopoly theory as a distinct analytical category for market concentration in AI-mediated markets. Classical monopoly theory examines market power through control over production, distribution, pricing, or market share. This paper argues that AI-mediated markets introduce a prior layer of concentration: control over computational consideration infrastructure. Inferential monopoly describes concentration over the systems that determine which economic entities become admissible to consideration before human choice, price formation, or competitive interaction occurs. The paper defines inferential power, computational consideration sets, computational admissibility, and inferential infrastructure; distinguishes inferential monopoly from platform, data, search, and industrial monopoly; analyzes failure modes including representation exclusion, inferential lock-in, allocative opacity, and protocol capture; and examines theoretical implications for competition policy.
Network-Dependent Allocation
This working paper presents a theoretical framework for analyzing allocation problems where valuations are non-separable. The framework introduces the Network-Dependent Allocation (NDA) problem: selecting a subset R of artifacts with cardinality constraint K that maximizes a non-separable valuation function V(R).