农业大数据学报 ›› 2023, Vol. 5 ›› Issue (4): 95-102.doi: 10.19788/j.issn.2096-6369.230412

• 农业农村社会经济数据:资源与方法 • 上一篇    下一篇

中国农村电商研究数据集分析

贾铖1,2(), 易红梅2,3,*()   

  1. 1.山东农业大学经济管理学院,山东 泰安 271000
    2.北京大学现代农学院,北京100081
    3.北京大学中国农业政策研究中心,北京100081
  • 收稿日期:2023-08-30 接受日期:2023-10-10 出版日期:2023-12-26 发布日期:2024-01-05
  • 通讯作者: 易红梅,E-mail: hmyi.ccap@pku.edu.cn。
  • 作者简介:贾铖,E-mail: 1791143392@qq.com
  • 基金资助:
    山东省社科基金青年项目(23DGLJ25);国家自然科学基金面上项目(72273003);国家社科基金一般项目(23BJY170)

Analysis of China's Rural E-commerce Research Dataset

JIA Cheng1,2(), YI HongMei2,3,*()   

  1. 1. School of Economics and Management, Shandong Agricultural University, Taian 271000, Shandong, China
    2. School of Advanced Agricultural Sciences, Peking University, Beijing 100081, China
    3. China Center for Agricultural Policy, Peking University, Beijing 100081, China
  • Received:2023-08-30 Accepted:2023-10-10 Online:2023-12-26 Published:2024-01-05

摘要:

本研究以中国农村电商实证数据为综述对象,按照电商定向干预和农产品交易地的特征将农村电商数据类型分为两类数据集。其中,数据集Ⅰ包括电子商务进农村综合示范县数据库、淘宝村与电商指数数据库;数据集Ⅱ包括农产品电商数据库与农产品跨境电商数据库。以此探讨不同数据集内若干农村电商研究主题所用数据的来源、指标内容、时间跨度、优劣势等内容,系统性梳理农村电商研究所用数据的来龙去脉,为该领域实证检验提供数据库筛选的参考,从而有效推动农村电商发展研究的理论进程。

关键词: 中国农村电商, 数据集, 样本, 指标

Abstract:

This study reviewed the data used in the studies on rural e-commerce in China. The rural e-commerce data are divided into two types of datasets based on the characteristics of targeted e-commerce interventions and agricultural product trading locations. The first dataset includes databases on comprehensive demonstration of e-commerce in rural counties, and Taobao Villages and e-commerce index. The second dataset involves databases on e-commerce of agricultural products, and cross-border e-commerce agrarian products. We presented the data sources, the definition of related indicators, and the time span of each dataset, and analyze the pros and cons of each data in answering the related research topics. This systematic review can be a benchmark for researchers interested in rural e-commerce to understand the data and assess the related studies using these datasets.

Key words: rural e-commerce in China, dataset, sample, indicators