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Studying the variables that separate entrepreneurial and non-entrepreneurial agricultural producer cooperatives (APCs) for predicting group membership

机译:研究将企业家和非企业家农业生产合作社(APC)分开的变量,以预测团体成员身份

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The main purpose of this study is to predict the group membership of entrepreneurial or non-entrepreneurial agricultural producer cooperative based on a linear combination of the interval variables. Discriminant function analysis was used in this research for access purpose. The study’s sample consisted of 250 agricultural cooperatives in Iran. The variables that indicate the entrepreneurial situation of a cooperative include the number of jobs that were created by cooperatives, increase or decrease of cooperative members, number of enterprise(s) created by cooperatives and growth in cooperatives' funds or possession. After recognition of these two types of cooperative, independent variables [individual, educational, economic, managerial (structural), managerial (financial), policy making, social and psychological] were entered into the discriminant function. The independent variables were obtained by factor analysis technique and each of them consists of many components. A questionnaire that was made by researchers based on literature review was used for data gathering. The questionnaire’s content and face validity were established by a panel of experts consisting of faculty members and managers in cooperation ministry. The reliability of the questionnaire was measured by Cronbach Alpha (α=0.88). The results obtained based on the structure matrix of independent variables showed that the individual characteristics of cooperative members have the most discriminant power of separating entrepreneurial from non-entrepreneurial APCs. After this variable, psychological, social and managerial (structural) variables have more discriminant power to separate these two kinds of agricultural producer cooperatives.
机译:这项研究的主要目的是基于区间变量的线性组合来预测企业家或非企业家农业生产者合作社的团体成员。判别函数分析在本研究中用于访问目的。该研究的样本包括伊朗的250个农业合作社。表示合作社创业状况的变量包括:合作社创造的工作数量,合作社成员的增加或减少,合作社创造的企业数量以及合作社资金或拥有量的增长。在识别了这两种类型的合作,独立变量[个体,教育,经济,管理(结构),管理(财务),政策制定,社会和心理]之后,就进入了判别函数。自变量是通过因子分析技术获得的,每个变量都包含许多成分。研究人员根据文献综述制作的调查表用于数据收集。问卷的内容和面部有效性由合作部的教职员工和管理人员组成的专家小组建立。问卷的信度由Cronbach Alpha(α= 0.88)衡量。基于自变量的结构矩阵获得的结果表明,合作成员的个体特征具有区分企业家和非企业家APC的最大区别力。在这个变量之后,心理,社会和管理(结构)变量具有区分这两种农业生产者合作社的更大判别力。

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