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Income Groups, Social Capital, and Collective Action on Small‐Scale Irrigation Facilities: A Multigroup Analysis Based on a Structural Equation Model
Author(s) -
Miao Shanshan,
Heijman Wim,
Zhu Xueqin,
Qiao Dan,
Lu Qian
Publication year - 2018
Publication title -
rural sociology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.083
H-Index - 65
eISSN - 1549-0831
pISSN - 0036-0112
DOI - 10.1111/ruso.12214
Subject(s) - social capital , reciprocity (cultural anthropology) , collective action , structural equation modeling , economics , demographic economics , socioeconomics , sociology , social psychology , psychology , political science , social science , statistics , mathematics , politics , law
This article examines whether relationships between social capital characteristics and the willingness of farmers to cooperate in collective action is moderated by the farmers' income level. We employed a structural equation model to analyze the influence of social capital components (social networks, interpersonal trust, social reciprocity, and social participation) on the willingness of farmers to cooperate in collective small‐scale irrigation in Guangling County, Shanxi Province of China. This analysis was complemented by a multigroup analysis to measure the potential variance effects across income groups. Our results show that low‐ and middle‐income farmers give more importance to the aspects of social networks, social reciprocity, and social participation, while high‐income farmers place emphasis on interpersonal trust and social participation. Accordingly, the willingness of farmers to cooperate for the different income groups was influenced in different ways in relation to the various social capital components. Therefore, social capital and income differences have complex effects on the willingness of farmers to cooperate. In this regard, our research provides an alternative way to understand the complex process involved in the formation of collective action under the presence of increasing economic heterogeneity in local communities.