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Organizational Structure, Policy Learning, and Economic Performance

Evidence from the Chinese Commune

Bibliographic Data

ID2423720
AuthorsJoshua Eisenman (0000-0002-4709-4353, The University of Texas at Austin, corresponding author), Feng Yang (0009-0008-1432-2234, University of California, Los Angeles, corresponding author)
Year2018
Volume4
Publication date2018-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSocius Sociological Research for a Dynamic World (JOURNAL)
Journal identifiersISSN: 2378-0231 • E-ISSN: 2378-0231
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/2378023118757650
OpenAlexW2790108534
LanguageEN
Citations received1
References cited57

Using original county-level panel data on Chinese communes over two decades, 1958 to 1979, this article builds upon existing theories about the influence of organizational size and structure on institutional performance. We found a consistent and robust interaction effect among the size of the commune (i.e., the coordination level) and its subunits, the brigade (i.e., the supervisory level) and production teams (i.e., the working level), on agricultural productivity. Future work on the relationship between organizational performance and size would likely benefit from including such interaction variables. We also provide evidence that to create a more productive institution, county-level officials learned from their most productive neighbors and adjusted the size of their communes accordingly. This work explains the role of organizational structure as a driver of economic performance and how policy diffusion occurred during China's Maoist era-a period generally treated as a monolith rather than a period of institutional change

Business · China · Economic geography · Economic growth · Economic system · Economics · Institution · Management · Organizational learning · Organizational structure · Political science · Productivity · Social science · Sociology · Work (physics · China's Socioeconomic Reforms and Governance · Culture, Economy, and Development Studies · Engineering · Social Capital and Networks

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Unique citing works1
Citations per year0,33
Citation span2023 - 2023 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1

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