Factors influencing regional disparities in online shopping

Online shopping has grown exponentially in the Russian Federation (hereinafter referred to as RF, Russia) in recent years. This growth has significantly accelerated during the COVID-19 pandemic. However, data shows that there are inter-regional disparities in the use of online shopping. This includes intergenerational and rural-urban disparities. This study investigates the factors responsible for inter-regional differences in the development of online shopping in Russia. The author has identified 5 main factors that can influence the development: internet infrastructure (measured by regional expenses for the introduction of digital technologies and the number of connected mobile subscribers), economic wealth (measured by gross regional product), standard of living (measured by the population income), rate of poverty, and the region’s population. The research uses data of the Federal State Statistics Service and Association of Internet Trade Companies to analyse 85 regions in the RF. A multi-level regression analysis has enabled examination of the 5 factors and the contextual influence of 8 federal districts of Russia in level 2. The results show that internet infrastructure, economic wealth, population size, and the 8 federal districts has influenced the development of online shopping in the RF, but standard of living is not statistically significant. The author recommends that policymakers pay attention to these underlying factors.

Authors

Institutions

Publication Details

Journal
Digital sociology
Published
2024-10-20
DOI
https://doi.org/10.26425/2658-347x-2024-7-3-15-23
Citations
2
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
2.10

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Factors influencing regional disparities in online shopping

Michael Olumekor
2 citations
Digital sociology
Technology Adoption and User Behaviour
2.10
article

Factors influencing regional disparities in online shopping

Michael Olumekor
article en
2 citations

Abstract

Online shopping has grown exponentially in the Russian Federation (hereinafter referred to as RF, Russia) in recent years. This growth has significantly accelerated during the COVID-19 pandemic. However, data shows that there are inter-regional disparities in the use of online shopping. This includes intergenerational and rural-urban disparities. This study investigates the factors responsible for inter-regional differences in the development of online shopping in Russia. The author has identified 5 main factors that can influence the development: internet infrastructure (measured by regional expenses for the introduction of digital technologies and the number of connected mobile subscribers), economic wealth (measured by gross regional product), standard of living (measured by the population income), rate of poverty, and the region’s population. The research uses data of the Federal State Statistics Service and Association of Internet Trade Companies to analyse 85 regions in the RF. A multi-level regression analysis has enabled examination of the 5 factors and the contextual influence of 8 federal districts of Russia in level 2. The results show that internet infrastructure, economic wealth, population size, and the 8 federal districts has influenced the development of online shopping in the RF, but standard of living is not statistically significant. The author recommends that policymakers pay attention to these underlying factors.

Digital sociologyVol. 7(3)
Ural Federal University (RU)
Ural Federal University
No poverty
Openalex Percentile: Top 8%
Technology Adoption and User Behaviour
2.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.