IDEAS home Printed from https://ideas.repec.org/a/sae/ratsoc/v15y2003i4p411-440.html
   My bibliography  Save this article

The Strength of Strong Ties

Author

Listed:
  • Daniel Carpenter
  • Kevin Esterling
  • David Lazer

Abstract

Interest groups establish contacts with each other as a way of gaining useful policy information, and in this article we develop and test a model to explain this political phenomenon. Our simulation model suggests that when few need information, groups will pursue an acquaintance strategy by investing time and resources in gaining `weak tie' political acquaintances rather than in gaining `strong tie' political friends, but that as the collective demand for information rises, groups increasingly follow a chum strategy , placing greater emphasis on establishing strong ties. We test these hypotheses in an analysis of inter-organizational contact-making in U.S. health politics, using the data of Laumann and Knoke (1987), with OLS regressions of average group contacts over lobbying events over time and maximum likelihood count models of contacts across interest groups. Both analyses show that as collective demand for information increases, interest groups place greater priority on establishing strong ties, even while controlling for organizational attributes such as budget, mobilization capacity and organization age. The results suggest some conditions where policy networks in the aggregate are less likely to distribute information efficiently, and, in particular, that policy networks are less efficient at distributing information when information is most in demand.

Suggested Citation

  • Daniel Carpenter & Kevin Esterling & David Lazer, 2003. "The Strength of Strong Ties," Rationality and Society, , vol. 15(4), pages 411-440, November.
  • Handle: RePEc:sae:ratsoc:v:15:y:2003:i:4:p:411-440
    DOI: 10.1177/1043463103154001
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1043463103154001
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1043463103154001?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. Scott A. Boorman, 1975. "A Combinatorial Optimization Model for Transmission of Job Information through Contact Networks," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 216-249, Spring.
    2. Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July.
    3. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    4. Hojnacki, Marie & Kimball, David C., 1998. "Organized Interests and the Decision of Whom to Lobby in Congress," American Political Science Review, Cambridge University Press, vol. 92(4), pages 775-790, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ornit Raz & Peter A. Gloor, 2007. "Size Really Matters--New Insights for Start-ups' Survival," Management Science, INFORMS, vol. 53(2), pages 169-177, February.
    2. Jan Beyers & Tom Donas, 2014. "Inter-regional networks in Brussels: Analyzing the information exchanges among regional offices," European Union Politics, , vol. 15(4), pages 547-571, December.
    3. Galaz, Victor & Crona, Beatrice & Österblom, Henrik & Olsson, Per & Folke, Carl, 2012. "Polycentric systems and interacting planetary boundaries — Emerging governance of climate change–ocean acidification–marine biodiversity," Ecological Economics, Elsevier, vol. 81(C), pages 21-32.
    4. Megan S. Patterson & Katie M. Heinrich & Tyler Prochnow & Taylor Graves-Boswell & Mandy N. Spadine, 2020. "Network Analysis of the Social Environment Relative to Preference for and Tolerance of Exercise Intensity in CrossFit Gyms," IJERPH, MDPI, vol. 17(22), pages 1-20, November.
    5. Adam W Chalmers, 2013. "With a lot of help from their friends: Explaining the social logic of informational lobbying in the European Union," European Union Politics, , vol. 14(4), pages 475-496, December.
    6. Federico Holm & Ramiro Berardo, 2020. "Coalitional Architecture of Climate Change Litigation Networks in the United States," Review of Policy Research, Policy Studies Organization, vol. 37(6), pages 797-822, November.
    7. Schulz, Celine, 2006. "The Secret to Successful User Communities: An Analysis of Computer Associates’ User Groups," Discussion Papers in Business Administration 1257, University of Munich, Munich School of Management.
    8. Brousselle, Astrid & Champagne, François, 2011. "Program theory evaluation: Logic analysis," Evaluation and Program Planning, Elsevier, vol. 34(1), pages 69-78, February.
    9. Dagenais, Christian & Laurendeau, Marie-Claire & Briand-Lamarche, Mélodie, 2015. "Knowledge brokering in public health: A critical analysis of the results of a qualitative evaluation," Evaluation and Program Planning, Elsevier, vol. 53(C), pages 10-17.

    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. Marco Casari, 2002. "Can genetic algorithms explain experimental anomalies? An application to common property resources," UFAE and IAE Working Papers 542.02, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    2. Scott E. Page, 2008. "Uncertainty, Difficulty, and Complexity," Journal of Theoretical Politics, , vol. 20(2), pages 115-149, April.
    3. Sylvie Geisendorf, 2018. "Evolutionary Climate-Change Modelling: A Multi-Agent Climate-Economic Model," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 921-951, October.
    4. Sylvie Geisendorf, 2016. "The impact of personal beliefs on climate change: the “battle of perspectives” revisited," Journal of Evolutionary Economics, Springer, vol. 26(3), pages 551-580, July.
    5. Duffy, John & Ünver, M.Utku, 2008. "Internet auctions with artificial adaptive agents: A study on market design," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 394-417, August.
    6. Marco Casari, 2003. "Does bounded rationality lead to individual heterogeneity? The impact of the experimentation process and of memory constraints," UFAE and IAE Working Papers 583.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    7. Marco Casari, 2004. "Can Genetic Algorithms Explain Experimental Anomalies?," Computational Economics, Springer;Society for Computational Economics, vol. 24(3), pages 257-275, March.
    8. Jasmina Arifovic & James B. Bullard & John Duffy, 1995. "Learning in a model of economic growth and development," Working Papers 1995-017, Federal Reserve Bank of St. Louis.
    9. William Tracy, 2014. "Paradox Lost: The Evolution of Strategies in Selten’s Chain Store Game," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 83-103, January.
    10. Georges, Christophre, 2006. "Learning with misspecification in an artificial currency market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(1), pages 70-84, May.
    11. Tomohiro Hayashida & Ichiro Nishizaki & Rika Kambara, 2014. "Simulation Analysis for Network Formulation," Computational Economics, Springer;Society for Computational Economics, vol. 43(3), pages 371-394, March.
    12. Bullard, James & Duffy, John, 1998. "A model of learning and emulation with artificial adaptive agents," Journal of Economic Dynamics and Control, Elsevier, vol. 22(2), pages 179-207, February.
    13. Sylvie Geisendorf, 2011. "Internal selection and market selection in economic Genetic Algorithms," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 817-841, December.
    14. Brown, Paul M., 1996. "Experimental evidence on money as a medium of exchange," Journal of Economic Dynamics and Control, Elsevier, vol. 20(4), pages 583-600, April.
    15. DeCanio, Stephen J. & Watkins, William E., 1998. "Information processing and organizational structure," Journal of Economic Behavior & Organization, Elsevier, vol. 36(3), pages 275-294, August.
    16. Roland Pongou & Roberto Serrano, 2009. "A dynamic theory of fidelity networks with an application to the spread of HIV/AIDS," Working Papers 2009-03, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    17. Benoît Desmarchelier & Faridah Djellal & Faïz Gallouj, 2018. "Public Service Innovation Networks (PSINs): Collaborating for Innovation and Value Creation," Working Papers halshs-01934275, HAL.
    18. Casari, Marco, 2008. "Markets in equilibrium with firms out of equilibrium: A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 65(2), pages 261-276, February.
    19. Brian Kelleher Richter & Krislert Samphantharak & Jeffrey F. Timmons, 2009. "Lobbying and Taxes," American Journal of Political Science, John Wiley & Sons, vol. 53(4), pages 893-909, October.
    20. Ian McCarthy, 2008. "Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings, Taxes, Advertising and Welfare," CAEPR Working Papers 2008-010, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.

    More about this item

    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:sae:ratsoc:v:15:y:2003:i:4:p:411-440. 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: SAGE Publications (email available below). General contact details of provider: .

    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.