IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2101.05010.html
   My bibliography  Save this paper

Quantifying the importance of firms by means of reputation and network control

Author

Listed:
  • Yan Zhang
  • Frank Schweitzer

Abstract

The reputation of firms is largely channeled through their ownership structure. We use this relation to determine reputation spillovers between transnational companies and their participated companies in an ownership network core of 1318 firms. We then apply concepts of network controllability to identify minimum sets of driver nodes (MDS) of 314 firms in this network. The importance of these driver nodes is classified regarding their control contribution, their operating revenue, and their reputation. The latter two are also taken as proxies for the access costs when utilizing firms as driver nodes. Using an enrichment analysis, we find that firms with high reputation maintain the controllability of the network, but rarely become top drivers, whereas firms with medium reputation most likely become top driver nodes. We further show that MDSs with lower access costs can be used to control the reputation dynamics in the whole network.

Suggested Citation

  • Yan Zhang & Frank Schweitzer, 2021. "Quantifying the importance of firms by means of reputation and network control," Papers 2101.05010, arXiv.org.
  • Handle: RePEc:arx:papers:2101.05010
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2101.05010
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Giorgio Fagiolo & Javier Reyes & Stefano Schiavo, 2010. "The evolution of the world trade web: a weighted-network analysis," Journal of Evolutionary Economics, Springer, vol. 20(4), pages 479-514, August.
    2. Sean P. Cornelius & William L. Kath & Adilson E. Motter, 2013. "Realistic control of network dynamics," Nature Communications, Nature, vol. 4(1), pages 1-9, October.
    3. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, 2009. "Economic Networks: What Do We Know And What Do We Need To Know?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(04n05), pages 407-422.
    4. J. B. Glattfelder & S. Battiston, 2009. "Backbone of complex networks of corporations: The flow of control," Papers 0902.0878, arXiv.org, revised Aug 2009.
    5. Vahan Nanumyan & Antonios Garas & Frank Schweitzer, 2015. "The Network of Counterparty Risk: Analysing Correlations in OTC Derivatives," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-23, September.
    6. Robert Sugden, 2009. "On Nudging: A Review of Nudge: Improving Decisions About Health, Wealth and Happiness by Richard H. Thaler and Cass R. Sunstein," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 16(3), pages 365-373.
    7. Ingo Scholtes & Nicolas Wider & Antonios Garas, 2016. "Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(3), pages 1-15, March.
    8. Andrea Landherr & Bettina Friedl & Julia Heidemann, 2010. "A Critical Review of Centrality Measures in Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(6), pages 371-385, December.
    9. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    10. Rebekka Burkholz & Frank Schweitzer, 2019. "International crop trade networks: The impact of shocks and cascades," Papers 1901.05872, arXiv.org.
    11. Ingo Scholtes & Nicolas Wider & Antonios Garas, 2016. "Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(3), pages 1-15, March.
    12. Giacomo Vaccario & Mario V. Tomasello & Claudio J. Tessone & Frank Schweitzer, 2018. "Quantifying knowledge exchange in R&D networks: a data-driven model," Journal of Evolutionary Economics, Springer, vol. 28(3), pages 461-493, August.
    13. Stephen J. Brammer & Stephen Pavelin, 2006. "Corporate Reputation and Social Performance: The Importance of Fit," Journal of Management Studies, Wiley Blackwell, vol. 43(3), pages 435-455, May.
    14. Vahan Nanumyan & Antonios Garas & Frank Schweitzer, 2015. "The Network of Counterparty Risk: Analysing Correlations in OTC Derivatives," Papers 1506.04663, arXiv.org, revised Sep 2015.
    15. Garlaschelli, Diego & Loffredo, Maria I., 2005. "Structure and evolution of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 138-144.
    16. Yan Zhang & Antonios Garas & Frank Schweitzer, 2019. "Control Contribution Identifies Top Driver Nodes In Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(07n08), pages 1-15, December.
    17. Mani , Dalhia & Moody , James, 2014. "Moving Beyond Stylized Economic Network Models: The Hybrid World of the Indian Firm Ownership Network," HEC Research Papers Series 1031, HEC Paris.
    18. Javier Garcia-Bernardo & Jan Fichtner & Eelke M. Heemskerk & Frank W. Takes, 2017. "Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network," Papers 1703.03016, arXiv.org, revised May 2017.
    19. D. Garlaschelli & M. I. Loffredo, 2005. "Structure and Evolution of the World Trade Network," Papers physics/0502066, arXiv.org, revised May 2005.
    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. Hoppe, K. & Rodgers, G.J., 2015. "A microscopic study of the fitness-dependent topology of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 64-74.
    2. Gautier M Krings & Jean-François Carpantier & Jean-Charles Delvenne, 2014. "Trade Integration and Trade Imbalances in the European Union: A Network Perspective," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-14, January.
    3. João Amador & Sónia Cabral, 2017. "Networks of Value-added Trade," The World Economy, Wiley Blackwell, vol. 40(7), pages 1291-1313, July.
    4. Rosanna Grassi & Paolo Bartesaghi & Stefano Benati & Gian Paolo Clemente, 2021. "Multi-Attribute Community Detection in International Trade Network," Networks and Spatial Economics, Springer, vol. 21(3), pages 707-733, September.
    5. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2020. "Community structure in the World Trade Network based on communicability distances," Papers 2001.06356, arXiv.org, revised Jul 2020.
    6. João Amador & Sónia Cabral & Rossana Mastrandrea & Franco Ruzzenenti, 2018. "Who’s Who in Global Value Chains? A Weighted Network Approach," Open Economies Review, Springer, vol. 29(5), pages 1039-1059, November.
    7. Marcos Duenas & Rossana Mastrandrea & Matteo Barigozzi & Giorgio Fagiolo, 2017. "Spatio-Temporal Patterns of the International Merger and Acquisition Network," LEM Papers Series 2017/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Michael Lebacher & Paul W. Thurner & Göran Kauermann, 2021. "Censored regression for modelling small arms trade volumes and its ‘Forensic’ use for exploring unreported trades," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 909-933, August.
    9. Charlie Joyez, 2017. "Network Structure of French Multinational Firms," Working Papers DT/2017/08, DIAL (Développement, Institutions et Mondialisation).
    10. Nobi, Ashadun & Lee, Tae Ho & Lee, Jae Woo, 2020. "Structure of trade flow networks for world commodities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    11. Kang, Xinyu & Wang, Minxi & Chen, Lu & Li, Xin, 2023. "Supply risk propagation of global copper industry chain based on multi-layer complex network," Resources Policy, Elsevier, vol. 85(PA).
    12. Baskaran, Thushyanthan & Blöchl, Florian & Brück, Tilman & Theis, Fabian J., 2011. "The Heckscher-Ohlin model and the network structure of international trade," International Review of Economics & Finance, Elsevier, vol. 20(2), pages 135-145, April.
    13. Vivek Kandiah & Hubert Escaith & Dima L. Shepelyansky, 2015. "Google matrix of the world network of economic activities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(7), pages 1-20, July.
    14. Assaf Almog & Rhys Bird & Diego Garlaschelli, 2015. "Enhanced Gravity Model of trade: reconciling macroeconomic and network models," Papers 1506.00348, arXiv.org, revised Feb 2019.
    15. Frank Schweitzer & Giona Casiraghi & Mario V. Tomasello & David Garcia, 2020. "Fragile, yet resilient: Adaptive decline in a collaboration network of firms," Papers 2011.13369, arXiv.org.
    16. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    17. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, 2009. "Economic Networks: What Do We Know And What Do We Need To Know?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(04n05), pages 407-422.
    18. Liu, Linqing & Shen, Mengyun & Sun, Da & Yan, Xiaofei & Hu, Shi, 2022. "Preferential attachment, R&D expenditure and the evolution of international trade networks from the perspective of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    19. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    20. Dürnecker, Georg & Meyer, Moritz & Vega-Redondo, Fernando, 2014. "The Network Origins of Economic Growth," Working Papers 14-06, University of Mannheim, Department of Economics.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2101.05010. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.