小规模综合商业农业供应链管理模式设计

Q1 Decision Sciences
Seyed Hasan Hosseini Khesht Masjedi, Sahar Dehyouri, Seyed Jamal Farajolah Hosseini, Maryam Omidi Najafabadi
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引用次数: 0

摘要

本文对供应链管理对小规模综合商业农业的影响进行了实证研究,重点研究了障碍和义务的调节作用,为农业政策制定者、规划者和决策者提供了解决方案。以吉兰地区423名小规模稻农为研究对象,采用问卷调查的方式收集数据。路径分析结果显示,供应链管理对义务有影响(β = 0.641)。此外,障碍和义务都影响小规模综合商业农业(β = 0.879) (β = 0.971)。这项工作表明,供应链管理必须努力执行小规模综合商业农业的义务,同时消除小规模综合商业农业的障碍,直到它能够提供小规模商业农业的利益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Designing Supply Chain Management Pattern in Small Scale Integrated Commercial Agriculture

Designing Supply Chain Management Pattern in Small Scale Integrated Commercial Agriculture

Designing Supply Chain Management Pattern in Small Scale Integrated Commercial Agriculture

This paper has investigated an empirical study to consider the impact of supply chain management on small scale integrated commercial agriculture by focusing on the moderator role of impediments and obligations to offer solutions for agricultural policymakers, planners, and decision-makers. The target group was 423 small-scale rice farmers in Gilan province, and their data was collected by questionnaire. The results of path analysis show that supply chain management has an impact on obligations (β = 0.641). Also, both impediments and obligations affect small scale integrated commercial agriculture (β = 0.879) (β = 0,971). This work showed that supply chain management must try to enforce the obligations of small scale integrated commercial agriculture, also eliminate impediments of small scale integrated commercial agriculture until it could provide small-scale commercial farming benefits.

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来源期刊
Annals of Data Science
Annals of Data Science Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
6.50
自引率
0.00%
发文量
93
期刊介绍: Annals of Data Science (ADS) publishes cutting-edge research findings, experimental results and case studies of data science. Although Data Science is regarded as an interdisciplinary field of using mathematics, statistics, databases, data mining, high-performance computing, knowledge management and virtualization to discover knowledge from Big Data, it should have its own scientific contents, such as axioms, laws and rules, which are fundamentally important for experts in different fields to explore their own interests from Big Data. ADS encourages contributors to address such challenging problems at this exchange platform. At present, how to discover knowledge from heterogeneous data under Big Data environment needs to be addressed.     ADS is a series of volumes edited by either the editorial office or guest editors. Guest editors will be responsible for call-for-papers and the review process for high-quality contributions in their volumes.
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