新冠肺炎疫情后影响哈萨克斯坦农村妇女网购增加的因素

A. Nurbatsin, A. Kireyeva
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引用次数: 0

摘要

在哈萨克斯坦的农村地区,人口稳步下降,首先是由于自然减少,与生活质量低下有关的移民外流,以及获得包括互联网在内的资源。农村妇女与城市妇女有着相似的精神价值观、社会经历和生活方式。本文讨论了与有限获取资源,即数字资源和互联网相关的问题的一个重要部分。本研究是基于结构和功能的方法进行的,使用了广泛的分析和评估方法。为了回答研究问题,来自哈萨克斯坦所有地区的女性受访者接受了采访。结果,265名不同财富和教育水平的女性给出了答案。该调查于2022年9月10日至10月10日进行,是农村妇女获得资源资助项目研究的一部分。使用分类预测因子的线性回归将确定影响在线购物者行为的主要因素。本文调查了哈萨克斯坦女性受访者的各种因素对COVID-19大流行后购买次数变化的影响。这项工作使用了在哈萨克斯坦境内对妇女进行的社会学调查的数据。结果显示,网络素养、家庭状况、在家工作、在线购物时间和使用社交网络推荐等因素对在线购物有显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Influencing the Increase in Online Purchases by Rural Women after the COVID-19 in Kazakhstan
In rural areas of Kazakhstan, there is a steady decline in the population due first to natural decline, migration outflow associated with a low quality of life, and access to resources, including the Internet. Rural women have similar spiritual values, social experience and lifestyles as urban women. This paper discusses an essential part of the problems associated with limited access to resources, namely digital resources and the Internet. The study was conducted based on structural and functional approaches using a wide range of analysis and evaluation methods. To answer the research questions, female respondents from all regions of Kazakhstan were interviewed. As a result, it got answers from 265 women with different levels of wealth and education. The survey was conducted between September 10 and October 10, 2022, as part of the research on the grant project on rural women's access to resources. Linear regression with categorical predictors will determine the main factors' influence on online shoppers' behaviour. In this paper, the influence of various factors of the respondents of women in Kazakhstan on the change in the number of purchases after the COVID-19 pandemic was investigated. The work used data from a sociological survey conducted on the territory of Kazakhstan among women. The results show that factors such as Internet literacy, family status, working from home, the amount of time to buy online and using recommendations in social networks significantly impact online purchases.  
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