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我国生鲜农产品电商直播发展水平时空演变及影响因素研究——以抖音为例
引用本文:张君慧,马恒运,毕文泰,刘和平,宋宇. 我国生鲜农产品电商直播发展水平时空演变及影响因素研究——以抖音为例[J]. 农业现代化研究, 2024, 45(3): 488-499
作者姓名:张君慧  马恒运  毕文泰  刘和平  宋宇
作者单位:河南农业大学经济与管理学院,河南农业大学经济与管理学院,河南农业大学经济与管理学院,河南农业大学经济与管理学院,河南农业大学经济与管理学院
基金项目:国家自然科学基金项目(72273039);河南省政府决策研究招标课题(2023JC048);河南省教育厅人文社会科学研究一般项目(2024-ZDJH-271);河南省高等学校哲学社会科学创新团队支持计划(2022-CXTD-01)。
摘    要:生鲜农产品电商直播是促进农产品上行和增加农户收入的重要举措。本研究选取生鲜农产品电商直播典型平台抖音作为研究对象,采用数据挖掘法在线抓取2022年4月至2023年3月生鲜农产品电商直播交易数据,对全国各省(区、市)生鲜农产品电商直播发展水平进行了评估,并运用泰尔指数法和莫兰指数法分析区域差异和空间分布特征。此外,通过构建回归模型进一步探讨电商直播销售额的影响因素。研究结果显示,全年电商直播销售额中4月份最低,而12月份最高。东部地区电商直播发展水平普遍较高,但全国不同区域总体差异较低,且差异主要来源于区域内差异,尤其是西部地区的区域内差异贡献率最高。目前,电商直播发展呈现空间负相关性,并未出现显著的空间集聚特征。此外,主播粉丝数、观众点赞数、上播产品数和直播时长对电商直播销售额有显著正向影响,观众停留时间与销售额呈倒“U”型关系。这些发现为推进农产品电商直播提供了实证依据,为各地制定农产品电商直播发展策略提供了理论支持。

关 键 词:生鲜农产品;电商直播;数据挖掘;区域差异;空间分布
收稿时间:2024-01-30
修稿时间:2024-05-07

Research on the spatial-temporal evolution and influencing factors of the development level of E-commerce live broadcast of fresh agricultural products in China: Take Tiktok as an example
ZHANG Jun-hui,MA Heng-yun,BI Wen-tai,LIU He-ping and SONG Yu. Research on the spatial-temporal evolution and influencing factors of the development level of E-commerce live broadcast of fresh agricultural products in China: Take Tiktok as an example[J]. Research of Agricultural Modernization, 2024, 45(3): 488-499
Authors:ZHANG Jun-hui  MA Heng-yun  BI Wen-tai  LIU He-ping  SONG Yu
Affiliation:College of Economics and Management, Henan Agricultural University,College of Economics and Management, Henan Agricultural University,College of Economics and Management, Henan Agricultural University,College of Economics and Management, Henan Agricultural University,College of Economics and Management, Henan Agricultural University
Abstract:The live broadcast of fresh agricultural product E-commerce is a crucial measure for promoting the upward mobility of agricultural products and increasing farmers’ incomes. This paper selects TikTok, a typical platform for the E-commerce live broadcast of fresh agricultural products, as the research subject. It employs data mining techniques to collect online transaction data of live broadcasts from April 2022 to March 2023, assessing the development level of such broadcasts across various provinces, regions, and cities nationwide. The paper analyses regional differences and spatial distribution characteristics using the Theil and Moran indices. Additionally, it constructs a regression model to explore factors influencing the sales of E-commerce live broadcasts. The results indicate that annual sales are lowest in April and peak in December. The eastern region generally exhibits a higher level of development in E-commerce live broadcasting, yet overall disparities across the country are minimal, predominantly stemming from intra-regional differences, especially in the western region, where these contribute most significantly. Currently, the development of E-commerce live broadcasting displays negative spatial correlation without significant spatial clustering. Furthermore, factors such as the number of anchor fans, audience likes, product counts, and broadcast duration significantly positively impact sales, whereas audience retention time shows an inverse U-shaped relationship with sales. These findings offer empirical evidence for advancing live broadcasts in agricultural product E-commerce and provide theoretical support for devising regional development strategies.
Keywords:fresh agricultural products   E-commerce live broadcast   data mining   regional differences   spatial distribution
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