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Analysis of Influencing Factors of Farmers' Satisfaction with Industrial Poverty Alleviation Effect Based on Ordinal Logistic Model: Take the three prefectures of southern Xinjiang in China as an example

Published: 29 May 2020 Publication History

Abstract

Based on a sample survey of 600 farmers in the three prefectures of southern Xinjiang, China, this paper uses questionnaire survey and ordinal Logistic model to study the influencing factors of farmers' satisfaction with the effect of industrial poverty alleviation from a microscopic perspective. The research shows that the cumulative percentage of farmers' satisfaction with the effect of industrial poverty alleviation is 90.7%, and the factors that influence the evaluation of farmers' satisfaction with industrial poverty alleviation are the educational level, the amount of household labor, the annual household income, the types of roads in front of farmers' doors, household fuel, whether rural cadres help farmers to alleviate poverty and the main poverty alleviation methods of the government. Based on this, the corresponding countermeasures are put forward: to continue to improve the embodiment of precision poverty alleviation, to strengthen the intensity of industrial precision poverty alleviation, to increase vocational skills training, to speed up infrastructure construction, based on its own advantages, to develop characteristic industries, to realize the precision poverty alleviation of industries, and to enhance the satisfaction of farmers with industrial poverty alleviation.

References

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  1. Analysis of Influencing Factors of Farmers' Satisfaction with Industrial Poverty Alleviation Effect Based on Ordinal Logistic Model: Take the three prefectures of southern Xinjiang in China as an example

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    MSIE '20: Proceedings of the 2020 2nd International Conference on Management Science and Industrial Engineering
    April 2020
    341 pages
    ISBN:9781450377065
    DOI:10.1145/3396743
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • College of Technology Management, National Tsing Hua University, Taiwan

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 29 May 2020

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    Author Tags

    1. Industrial Poverty Alleviation
    2. Influencing Factors
    3. Ordinal Logistic Model

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