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The Strength of Strong Ties

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  • 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
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    References listed on IDEAS

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    2. 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.
    3. 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.
    4. Brousselle, Astrid & Champagne, François, 2011. "Program theory evaluation: Logic analysis," Evaluation and Program Planning, Elsevier, vol. 34(1), pages 69-78, February.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.

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