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The Impact of Supply Chains on Firm-Level Productivity

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  • Juan Camilo Serpa

    (Desautels Faculty of Management, McGill University, Montreal, Quebec H3A 1G5, Canada)

  • Harish Krishnan

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada)

Abstract

Firms in a vertical relationship are likely to affect each other’s productivity. Exactly how does productivity spill over across this type of relationship (i.e., through which mechanisms)? Additionally, how does the relative importance of these mechanisms depend on the structure of the supply chain? To answer these questions, we decompose the channels of upstream productivity spillovers—from customers to suppliers—by developing a structural econometric model on a sample of approximately 22,500 supply chain dyads. We find that the “endogenous channel” (i.e., the effect of the customer’s own productivity on the supplier’s productivity) is by far the most important source of spillovers. This is especially true if (i) the supplier has a concentrated customer base, (ii) the supplier and the customer have similar operational characteristics, and (iii) the relationship has medium maturity. In the converse scenarios, we find, it is more important to have a partner with a portfolio of favorable “contextual” characteristics (high inventory turnover, financial liquidity, and asset turnover) than to have a productive partner. The online appendix is available at https://doi.org/10.1287/mnsc.2016.2632 . This paper was accepted by Serguei Netessine, operations management.

Suggested Citation

  • Juan Camilo Serpa & Harish Krishnan, 2018. "The Impact of Supply Chains on Firm-Level Productivity," Management Science, INFORMS, vol. 64(2), pages 511-532, February.
  • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:2:p:511-532
    DOI: mnsc.2016.2632
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    Cited by:

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    2. Gu, Haoran & Yang, Shenggang & Xu, Zhaoyi & Cheng, Cheng, 2023. "Supply chain finance, green innovation, and productivity: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    3. Maxime C. Cohen & Michael D. Fiszer & Baek Jung Kim, 2022. "Frustration-Based Promotions: Field Experiments in Ride-Sharing," Management Science, INFORMS, vol. 68(4), pages 2432-2464, April.
    4. Soledad Giardili & Kamalini Ramdas & Jonathan W. Williams, 2023. "Leadership and Productivity: A Study of U.S. Automobile Assembly Plants," Management Science, INFORMS, vol. 69(3), pages 1500-1517, March.
    5. Nicola Gagliardi & Benoît Mahy & François Rycx, 2018. "Upstreamness, social upgrading and gender: Equal benefits for all?," Working Paper Research 359, National Bank of Belgium.
    6. Nicola Gagliardi & Benoît Mahy & François Rycx, 2019. "Does firms’ position in global value chains matter for workers’ wages?. An overview with a gender perspective," Reflets et perspectives de la vie économique, De Boeck Université, vol. 0(4), pages 55-62.
    7. Nicola Gagliardi & Benoît Mahy & François Rycx, 2021. "Upstreamness, Wages and Gender: Equal Benefits for All?," British Journal of Industrial Relations, London School of Economics, vol. 59(1), pages 52-83, March.
    8. Wetzel, Philipp & Hofmann, Erik, 2019. "Supply chain finance, financial constraints and corporate performance: An explorative network analysis and future research agenda," International Journal of Production Economics, Elsevier, vol. 216(C), pages 364-383.
    9. Kovach, Jeremy J. & Swink, Morgan & Rodriguez, Mauricio, 2023. "A novel measure of firm-level production outsourcing," International Journal of Production Economics, Elsevier, vol. 263(C).
    10. Eduard Calvo & Ruomeng Cui & Juan Camilo Serpa, 2019. "Oversight and Efficiency in Public Projects: A Regression Discontinuity Analysis," Management Science, INFORMS, vol. 65(12), pages 5651-5675, December.
    11. Park, Sohee, 2023. "Customer prospects and pay-performance sensitivity: Evidence from Korea," Research in International Business and Finance, Elsevier, vol. 64(C).
    12. Emir Malikov & Jingfang Zhang & Shunan Zhao & Subal C. Kumbhakar, 2023. "Accounting for Cross-Location Technological Heterogeneity in the Measurement of Operations Efficiency and Productivity," Papers 2302.13430, arXiv.org.

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