Interorganizational Collaboration Networks in Economic Development Policy: An Exponential Random Graph Model Analysis

被引:81
|
作者
Lee, Youngmi [1 ]
Lee, In Won [2 ]
Feiock, Richard C. [3 ]
机构
[1] Kyonggi Univ, Dept Publ Adm, Seoul, South Korea
[2] Dankook Univ, Dept Publ Adm, Cheonan, South Korea
[3] Florida State Univ, Tallahassee, FL 32306 USA
关键词
interorganizational collaboration; exponential random graph model; economic development policy network; COLLECTIVE ACTION; RATIONAL CHOICE; PARTNERSHIPS; COMPETITORS; COOPERATION; GOVERNANCE; RISK;
D O I
10.1111/j.1541-0072.2012.00464.x
中图分类号
D0 [政治学、政治理论];
学科分类号
0302 ; 030201 ;
摘要
Regional economic development competition can be inefficient and destructive because decisions by one governmental unit can impose both externalities on its neighbors. Collaborative networks of multiple stakeholders within and across jurisdictions are an increasingly crucial component of regional economic development. In this article, we focus on the emergence of voluntary and self-organizing network relationships among local governments to address economic development concerns. The motivations and decisions of local actors play a critical role in shaping and implementing regional collaboration. On a micro level, the collaboration choices are shaped by three primary factors: the transaction costs reflected in the configuration of relationships in which an actor is embedded; the organizational similarities (homophily); and the resource dependencies that shape the local actors' preferences for forming relationships with other specific actors. We utilize an exponential random graph model (ERGM) to test hypotheses regarding the most prominent observed patterns of network relationships within and across different organizational sectors. The results demonstrate that both reciprocity and social clustering structures are preferred by both government and nongovernment organizations. These results suggest that interorganizational collaboration for economic development requires more than simple exchange relationships. Rather, network actors may be better served by participating in a densely clustered network that is capable of maintaining credible commitments to collective solutions.
引用
收藏
页码:547 / 573
页数:27
相关论文
共 50 条
  • [21] Exponential random graph models for networks with community structure
    Fronczak, Piotr
    Fronczak, Agata
    Bujok, Maksymilian
    [J]. PHYSICAL REVIEW E, 2013, 88 (03)
  • [22] Exponential Random Graph Modeling for Complex Brain Networks
    Simpson, Sean L.
    Hayasaka, Satoru
    Laurienti, Paul J.
    [J]. PLOS ONE, 2011, 6 (05):
  • [23] Exponential random graph models of preschool affiliative networks
    Daniel, Joao R.
    Santos, Antonio J.
    Peceguina, Ines
    Vaughn, Brian E.
    [J]. SOCIAL NETWORKS, 2013, 35 (01) : 25 - 30
  • [24] Statistical Inference for Valued-Edge Networks: The Generalized Exponential Random Graph Model
    Desmarais, Bruce A.
    Cranmer, Skyler J.
    [J]. PLOS ONE, 2012, 7 (01):
  • [25] An introduction to exponential random graph (p*) models for social networks
    Robins, Garry
    Pattison, Pip
    Kalish, Yuval
    Lusher, Dean
    [J]. SOCIAL NETWORKS, 2007, 29 (02) : 173 - 191
  • [26] Exponential random graph models for networks resilient to targeted attacks
    Zhang, Jingfei
    Chen, Yuguo
    [J]. STATISTICS AND ITS INTERFACE, 2015, 8 (03) : 267 - 276
  • [27] A multilayer exponential random graph modelling approach for weighted networks
    Caimo, Alberto
    Gollini, Isabella
    [J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2020, 142
  • [28] Exponential-family random graph models for valued networks
    Krivitsky, Pavel N.
    [J]. ELECTRONIC JOURNAL OF STATISTICS, 2012, 6 : 1100 - 1128
  • [29] Bayesian model selection for exponential random graph models
    Caimo, A.
    Friel, N.
    [J]. SOCIAL NETWORKS, 2013, 35 (01) : 11 - 24
  • [30] Regional Governance and Multiplex Networks in Environmental Sustainability: An Exponential Random Graph Model Analysis in the Chinese Local Government Context
    Shen, Ruowen
    [J]. URBAN AFFAIRS REVIEW, 2024, 60 (02) : 571 - 613