Member heterogeneity is often seen as a disadvantage of cooperatives.Though, a comprehensive understanding of member heterogeneity, its dimensions and impacts on member interests, organizations and their performance is still missing. The following literature review is intended to summarize the existing literature on member heterogeneity with a focus on agricultural cooperatives in order to provide further areas of research. Different dimensions of heterogeneity are identified and ways of measuring their impact on cooperative organization are proposed.
The use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis (1989) and the theory of planned behavior (TPB) of Ajzen (1991) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.
Studies on cooperatives and cooperative performance have a long empirical tradition. This study provides new data on the multifaceted positions and functions of farmer cooperatives in the food supply chains in eight sectors of EU‐27. Cooperatives in this area are facing changes in competition, institutional framework and marketing conditions. What is the significance of cooperatives in the European food supply chains and which positions do they take up? Which conclusions on their handling of the changes can be derived from the development of their functions in the supply chain and which growth and marketing strategies do they pursue? By providing insights into recent literature as well as presenting and evaluating results of the EU‐project ‘Support for Farmers’ Cooperatives’, we seek to provide answers on the questions raised above.
This study uses the Propensity Score Matching to examine the income impact of different credit sources on accessed households in the Northern Mountains of Vietnam. Results show that overall rural credit serves an important role in improving household income with respect to total income, per capita income and nonfarm income. However, different credit affects recipients heterogeneously. Whereas a significant increase in household income can be achieved through accessing commercial and informal loans, there is no significant increase of all income components associated recipients of preferential credit. These results imply that a successful credit scheme needs to consider variations in transaction costs, disbursement scheme, loan characteristics and typical socio-economic conditions of credit recipients.
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