Digital Insights into Organic Food Consumption Behavior: Multi-Dimensional Analysis Based on Big Data

DOI

10.2991/978-2-38476-551-5_67How to use a DOI?

Keywords

Organic food; Consumer behavior; Big data; E-commerce; Multiple linear regression

Abstract

The rapid development of e-commerce has profoundly changed organic food consumption patterns. This study reveals the multidimensional driving factors of consumer behavior through big data analysis. Based on data from the Hong Kong HKTVmall platform, a multiple linear regression model was used to examine the impact of price, discounts, time factors, membership level, and country of origin on sales volume. The results show that unit price has a significant negative impact on sales volume, Asian origin has a significant positive driving effect, while the weekend effect and membership level have limited impact. This study provides a new perspective on consumption theory under the digital economy and offers practical insights for e-commerce platform strategy optimization.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jianlong Shi
PY  - 2026
DA  - 2026/03/26
TI  - Digital Insights into Organic Food Consumption Behavior: Multi-Dimensional Analysis Based on Big Data
BT  - Proceeding of 2025 8th International Conference on Humanities Education and Social Sciences (ICHESS 2025)
PB  - Atlantis Press
SP  - 635
EP  - 643
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-551-5_67
DO  - 10.2991/978-2-38476-551-5_67
ID  - Shi2026
ER  -