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Dual-Channel Technology Diffusion: Spatial Decay and Network Contagion in Supply Chain Networks

Tatsuru Kikuchi

arXiv 25 Oct 2025 · Econometrics

arXiv:2510.24781 · PDF · Extracted main text

Abstract

This paper develops a dual-channel framework for analyzing technology diffusion that integrates spatial decay mechanisms from continuous functional analysis with network contagion dynamics from spectral graph theory. Building on our previous studies, which establish Navier-Stokes-based approaches to spatial treatment effects and financial network fragility, we demonstrate that technology adoption spreads simultaneously through both geographic proximity and supply chain connections. Using comprehensive data on six technologies adopted by 500 firms over 2010-2023, we document three key findings. First, technology adoption exhibits strong exponential geographic decay with spatial decay rate $κ\approx 0.043$ per kilometer, implying a spatial boundary of $d^* \approx 69$ kilometers beyond which spillovers are negligible (R-squared = 0.99). Second, supply chain connections create technology-specific networks whose algebraic connectivity ($λ_2$) increases 300-380 percent as adoption spreads, with correlation between $λ_2$ and adoption exceeding 0.95 across all technologies. Third, traditional difference-in-differences methods that ignore spatial and network structure exhibit 61 percent bias in estimated treatment effects. An event study around COVID-19 reveals that network fragility increased 24.5 percent post-shock, amplifying treatment effects through supply chain spillovers in a manner analogous to financial contagion documented in our recent study. Our framework provides micro-foundations for technology policy: interventions have spatial reach of 69 kilometers and network amplification factor of 10.8, requiring coordinated geographic and supply chain targeting for optimal effectiveness.

Citation extraction

29
references
111
in-text mentions
29
distinct cited
9
self-citations
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main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Kikuchi, T (2024) Dynamic spatial treatment effect boundaries: A continuous functional framework from Navier-Stokes equations self1.000257100%
2Kikuchi, T (2024) Spatial and temporal boundaries in difference-in-differences: A framework from Navier-Stokes equation self1.000177100%
3Kikuchi, T (2024) Network contagion dynamics in European banking: A Navier-Stokes framework for systemic risk assessment self0.874162100%
4Kikuchi, T (2024) Emergent dynamical spatial boundaries in emergency medical services: A Navier-Stokes framework from first principles self0.87452100%
5Kikuchi, T (2024) Dynamic spatial treatment effects as continuous functionals: Theory and evidence from healthcare access self0.87452100%
6Kikuchi, T (2024) Nonparametric identification and estimation of spatial treatment effect boundaries: Evidence from 42 million pollution observati… self0.87452100%
7Kikuchi, T (2024) Nonparametric identification of spatial treatment effect boundaries: Evidence from bank branch consolidation self0.87452100%
8Jackson, Matthew O (2008) Social and Economic Networks0.84333100%
9Kikuchi, T (2024) Stochastic boundaries in spatial general equilibrium: A diffusion-based approach to causal inference with spillover effects self0.81142100%
10Kikuchi, T (2024) A unified framework for spatial and temporal treatment effect boundaries: Theory and identification self0.81142100%

Showing the top 10 of 29 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Dynamic Spatial Treatment Effects and Network Fragility: Theory and Evidence from the 2008 Financial Crisis1.00053