Analysis of a Framework for E-Commerce Consumer Behavior before and During Covid-۱۹

The Covid-۱۹ pandemic has caused changes in the field of business activities. The fear of the pandemic has increased consumer awareness of the economic benefits of e-commerce platforms and the desire of people to absentee shopping, resulting in the growth of e-commerce in the world. Iran is not an exception to this rule. In this article, in order to analyze the behavior of e-commerce consumers, before and during covid-۱۹, Iran's largest online retail site has been studied. In the analysis of consumers' behavior, parameters such as spatial distribution, gender and age range of consumers, product groups, payment method for orders according to the amount of use of information and communication technology in the country before and during covid-۱۹ and the death rate due to corona, were considered. In this research, data mining method has been used to analyze the behavior of e-commerce consumers. In the procedure, first the required data is collected and then in the next step, the data has been refined with the KNIME Analytics platform, and then consumer behavior has been analyzed using k-means and Fuzzy c-means algorithms. The results of the analysis showed that the spread of covid-۱۹ has made the amount of shopping at the country level more uniform, leading older people to shop online and increasing their share of the total e-commerce consumers and the desire to pay for orders online. Also, the examination of product groups showed that the sales growth of health product groups was higher than other groups.

کلیدواژه ها:

Data mining ، consumer behavior analysis ، e-commerce ، COVID-۱۹ ، Clustering