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Customer Concentration and SME Survival : The Role of Network Structure and Dynamic Adaptation

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  • HARA, Yasushi

Abstract

This study revisits the impact of customer concentration on the performance and survival of Small and Medium-sized Enterprises (SMEs) by proposing an integrated “Quantity-Quality-Structure” framework. Utilizing a large-scale panel dataset of Japanese manufacturing SMEs, we employ rigorous empirical methods—including two-way fixed-effects models with controls for export status, Cox proportional hazards models, and dynamic event studies—to disentangle the complex effects of inter-firm relationships. While the static relationship between customer concentration (Quantity) and sales growth is found to be inconsistent across industries, our survival analysis reveals a robust and critical finding: high concentration significantly increases the risk of firm exit, supporting the vulnerability tenet of Resource Dependency Theory. Conversely, simple network connectivity (Degree Centrality) acts as a powerful buffer, significantly reducing exit risk and functioning as “structural insurance, ” whereas network brokerage (Betweenness Centrality) can exacerbate risks in certain assembly industries. Furthermore, dynamic analyses of strategic change reveal that firms “decoupling” from major customers face a multiyear “danger zone” of increased vulnerability before achieving diversification. Successful growth strategies are shown to be driven not by expanding existing B2B ties, but by a strategic pivot to new market types, specifically direct-to-consumer (B2C) segments. These findings reframe the debate on customer concentration from one of performance optimization to one of existential risk management and dynamic adaptation.

Suggested Citation

  • HARA, Yasushi, 2025. "Customer Concentration and SME Survival : The Role of Network Structure and Dynamic Adaptation," TDB-CAREE Discussion Paper Series E-2025-02, Teikoku Databank Center for Advanced Empirical Research on Enterprise and Economy, Graduate School of Economics, Hitotsubashi University.
  • Handle: RePEc:hit:tdbcdp:e-2025-02
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    File URL: https://hit-u.repo.nii.ac.jp/record/2061534/files/070careeDP-E-2502.pdf
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    References listed on IDEAS

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    1. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    2. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    3. Toshihiro Okubo & Tetsuji Okazaki & Eiichi Tomiura, 2022. "Industrial cluster policy and transaction networks: Evidence from firm‐level data in Japan," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(4), pages 1990-2035, November.
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    Keywords

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    JEL classification:

    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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