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Measuring the Impact Factor of Agents within an Organization Using Communication Patterns

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  • Palacios-Huerta, Ignacio
  • Prat, Andrea

Abstract

Organizational economics predicts that communication patterns within an organization should reflect the relative value of their members to the organization. We propose to measure the impact factor of an agent by applying the Invariant Method–also known as Google’s PageRank algorithm–to electronic communication data. To explore the validity of this measure, we analyze email exchanges among the top executives of a large retail company. We construct their individual impact factors based only on email patterns and we compare them to standard economic measures of organizational importance. We find that: (i) The impact-factor ranking of executives mirrors perfectly their hierarchical ranking; (ii) Impact factor variability is significantly correlated with salary differences; (iii) Subsequent promotions (dismissals) affect executives with unusually high (low) impact factors. We conclude that simple communication-based impact factors may be a useful tool to measure the relative importance of agents in organizations.

Suggested Citation

  • Palacios-Huerta, Ignacio & Prat, Andrea, 2010. "Measuring the Impact Factor of Agents within an Organization Using Communication Patterns," CEPR Discussion Papers 8040, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:8040
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    References listed on IDEAS

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    1. Andrea Prat, 2005. "The Wrong Kind of Transparency," American Economic Review, American Economic Association, vol. 95(3), pages 862-877, June.
    2. Mathias Dewatripont & Patrick Bolton, 1994. "The firm as a communication network," ULB Institutional Repository 2013/9595, ULB -- Universite Libre de Bruxelles.
    3. Jacques Crémer & Luis Garicano & Andrea Prat, 2007. "Language and the Theory of the Firm," The Quarterly Journal of Economics, Oxford University Press, vol. 122(1), pages 373-407.
    4. Timothy Van Zandt, 2004. "Information Overload in a Network of Targeted Communication," RAND Journal of Economics, The RAND Corporation, vol. 35(3), pages 542-560, Autumn.
    5. Ignacio Palacios-Huerta & Oscar Volij, 2004. "The Measurement of Intellectual Influence," Econometrica, Econometric Society, vol. 72(3), pages 963-977, May.
    6. Timothy van Zandt, 1999. "Real-Time Decentralized Information Processing as a Model of Organizations with Boundedly Rational Agents," Review of Economic Studies, Oxford University Press, vol. 66(3), pages 633-658.
    7. Timothy Van Zandt & Roy Radner, 1998. "Real-Time Decentralized Information Processing and Returns to Scale," Discussion Papers 1233, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    8. Wouter Dessein & Tano Santos, 2006. "Adaptive Organizations," Journal of Political Economy, University of Chicago Press, vol. 114(5), pages 956-985, October.
    9. Raymond Fisman & Sheena S. Iyengar & Emir Kamenica & Itamar Simonson, 2006. "Gender Differences in Mate Selection: Evidence From a Speed Dating Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 121(2), pages 673-697.
    10. Luis Garicano, 2000. "Hierarchies and the Organization of Knowledge in Production," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 874-904, October.
    11. Radner, Roy, 1993. "The Organization of Decentralized Information Processing," Econometrica, Econometric Society, vol. 61(5), pages 1109-1146, September.
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    Cited by:

    1. Calvó-Armengol, Antoni & de Martí, Joan & Prat, Andrea, 2015. "Communication and influence," Theoretical Economics, Econometric Society, vol. 10(2), May.
    2. Garicano, Luis & Prat, Andrea, 2011. "Organizational Economics with Cognitive Costs," CEPR Discussion Papers 8372, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    impact factor; organizational economics; pagerank;

    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General

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