IDEAS home Printed from https://ideas.repec.org/a/bit/bsrysr/v6y2015i2p41-51.html
   My bibliography  Save this article

Industry Productivity Growth: A Network Perspective

Author

Listed:
  • Teng Joe

    (Troy University, United States)

  • Wu Dazhong

    (Troy University, United States)

  • Smith Fran

    (Troy University, United States)

Abstract

Background: This study investigates the determinants of industrial productivity growth from a network perspective.Objectives: The research focuses on the influence on a focal industry’s productivity growth by its partner industries’ productivity growth, and the impact of the focal industry’s position in the supply chain network.Method/Approach: The paper models the economy as a customer-supplier industry network and empirically investigates how a focal industry’s multifactor productivity is influenced by the productivities of industries that are connected to it, and how this influence is moderated by its position in the network.Results: Based on a balanced panel dataset of 55 industries from the United States Bureau of Economic Analysis (BEA) input-output accounts, the results indicate that a focal industry’s productivity growth is positively associated with its partner industries’ productivity growth, and that industries with higher centrality in the network tend to have higher productivity growth.Conclusions: The study concludes with a discussion on the implications of the findings and the contribution to the productivity literature. Several directions for further research were identified.

Suggested Citation

  • Teng Joe & Wu Dazhong & Smith Fran, 2015. "Industry Productivity Growth: A Network Perspective," Business Systems Research, Sciendo, vol. 6(2), pages 41-51, September.
  • Handle: RePEc:bit:bsrysr:v:6:y:2015:i:2:p:41-51
    DOI: 10.1515/bsrj-2015-0010
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/bsrj-2015-0010
    Download Restriction: no

    File URL: https://libkey.io/10.1515/bsrj-2015-0010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kenneth R. Ahern & Jarrad Harford, 2014. "The Importance of Industry Links in Merger Waves," Journal of Finance, American Finance Association, vol. 69(2), pages 527-576, April.
    2. Jovanovic, Boyan & MacDonald, Glenn M, 1994. "Competitive Diffusion," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 24-52, February.
    3. Ulrich Doraszelski & Jordi Jaumandreu, 2013. "R&D and Productivity: Estimating Endogenous Productivity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1338-1383.
    4. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    5. Ahern, Kenneth R., 2012. "Bargaining power and industry dependence in mergers," Journal of Financial Economics, Elsevier, vol. 103(3), pages 530-550.
    6. repec:bla:econom:v:72:y:2005:i:286:p:287-305 is not listed on IDEAS
    7. Wakelin, Katharine, 2001. "Productivity growth and R&D expenditure in UK manufacturing firms," Research Policy, Elsevier, vol. 30(7), pages 1079-1090, August.
    8. Huergo, Elena & Jaumandreu, Jordi, 2004. "Firms' age, process innovation and productivity growth," International Journal of Industrial Organization, Elsevier, vol. 22(4), pages 541-559, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Felipe Cortes & Francisco Marcet, 2023. "Analysts’ Connections and M&A Outcomes," Management Science, INFORMS, vol. 69(7), pages 4108-4133, July.
    2. Ioannis Bournakis & Dimitris Christopoulos & Sushanta Mallick, 2018. "Knowledge Spillovers And Output Per Worker: An Industry‐Level Analysis For Oecd Countries," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1028-1046, April.
    3. Chandan Sharma, 2016. "R&D, Technology Transfer And Productivity In The Indian Pharmaceutical Industry," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-24, January.
    4. Yongqiang Chu & Xuan Tian & Wenyu Wang, 2019. "Corporate Innovation Along the Supply Chain," Management Science, INFORMS, vol. 67(6), pages 2445-2466, June.
    5. Giuseppe Medda & Claudio Piga, 2014. "Technological spillovers and productivity in Italian manufacturing firms," Journal of Productivity Analysis, Springer, vol. 41(3), pages 419-434, June.
    6. Liu, Ting-Kun & Chen, Jong-Rong & Huang, Cliff C.J. & Yang, Chih-Hai, 2013. "E-commerce, R&D, and productivity: Firm-level evidence from Taiwan," Information Economics and Policy, Elsevier, vol. 25(4), pages 272-283.
    7. Ugur, Mehmet & Trushin, Eshref & Solomon, Edna & Guidi, Francesco, 2016. "R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis," Research Policy, Elsevier, vol. 45(10), pages 2069-2086.
    8. Doraszelski, Ulrich & Jaumandreu, Jordi, 2006. "R&D and productivity: Estimating production functions when productivity is endogenous," MPRA Paper 1246, University Library of Munich, Germany.
    9. Esther Goya & Esther Vayá & Jordi Suriñach, 2011. "Productivity and innovation spillovers: Micro evidence from Spain," IREA Working Papers 201126, University of Barcelona, Research Institute of Applied Economics, revised Dec 2011.
    10. Huang, Jingong & Xie, Taojun, 2023. "Technology centrality, bilateral knowledge spillovers and mergers and acquisitions," Journal of Corporate Finance, Elsevier, vol. 79(C).
    11. Fich, Eliezer M. & Nguyen, Tu, 2020. "The value of CEOs' supply chain experience: Evidence from mergers and acquisitions," Journal of Corporate Finance, Elsevier, vol. 60(C).
    12. Bryan S. Graham, 2019. "Network Data," Papers 1912.06346, arXiv.org.
    13. Castellani, Davide & Piva, Mariacristina & Schubert, Torben & Vivarelli, Marco, 2019. "R&D and productivity in the US and the EU: Sectoral specificities and differences in the crisis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 279-291.
    14. Jongsub Lee & Hayong Yun, 2023. "Learning Production Process Heterogeneity Across Industries: Implications of Deep Learning for Corporate M&A Decisions," Papers 2301.08847, arXiv.org.
    15. Banholzer, Nicolas & Behrens, Vanessa & Feuerriegel, Stefan & Heinrich, Sebastian & Rammer, Christian & Schmoch, Ulrich & Seliger, Florian & Wörter, Martin, 2019. "Knowledge spillovers from product and process inventions in patents and their impact on firm performance. End report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222367.
    16. Hall, Bronwyn H. & Mairesse, Jacques & Mohnen, Pierre, 2010. "Measuring the Returns to R&D," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1033-1082, Elsevier.
    17. Kim, Joon Ho, 2018. "Asset specificity and firm value: Evidence from mergers," Journal of Corporate Finance, Elsevier, vol. 48(C), pages 375-412.
    18. René Belderbos & Martin Carree & Boris Lokshin, 2006. "Complementarity in R&D Cooperation Strategies," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 28(4), pages 401-426, June.
    19. Dong, Yizhe & Li, Chang & Li, Haoyu, 2021. "Customer concentration and M&A performance," Journal of Corporate Finance, Elsevier, vol. 69(C).
    20. Stucchi, Rodolfo, 2008. "Catching up in total factor productivity through the business cycle : evidence from Spanish manufacturing surveys," UC3M Working papers. Economics we085125, Universidad Carlos III de Madrid. Departamento de Economía.

    More about this item

    Keywords

    industry network; multi-productivity; network centrality; network perspective; customer-supplier industry network;
    All these keywords.

    JEL classification:

    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bit:bsrysr:v:6:y:2015:i:2:p:41-51. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.