Understanding Geopolitical Effects on Consumer Behavior based on Japan’s Nuclear Wastewater Release Signal using Multiple Linear Regression Analysis
- DOI
- 10.2991/978-94-6239-640-1_14How to use a DOI?
- Keywords
- Geopolitical Event; Nuclear Wastewater; Online Purchase
- Abstract
This study employs behavioral economics theory and statistical analysis methods, using big data from HKTVMall, a well-known Hong Kong shopping platform, to analyze targeted consumer boycott patterns following geopolitical events, with a particular focus on food products. The study focuses on consumer reactions to the Japanese government’s decision to release wastewater from the Fukushima nuclear power plant into the ocean. The research provides a detailed assessment of the impact of the Japanese government’s statement on Hong Kong consumers’ purchasing decisions, thus offering insights into broader global consumer attitudes. By clarifying the interaction between government policy decisions and market behavior, it helps to gain a deeper understanding of the dynamic changes in consumers’ decision-making processes when facing environmental issues. Furthermore, this paper emphasizes the significant potential of consumer behavior analysis to provide reference for policy discussions and business ethics practices in a global economy increasingly focused on environmental protection.
- 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.
Cite this article
TY - CONF AU - Honglin Zhang PY - 2026 DA - 2026/04/20 TI - Understanding Geopolitical Effects on Consumer Behavior based on Japan’s Nuclear Wastewater Release Signal using Multiple Linear Regression Analysis BT - Proceedings of the 2026 5th International Conference on Big Data Economy and Digital Management (BDEDM 2026) PB - Atlantis Press SP - 155 EP - 164 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-640-1_14 DO - 10.2991/978-94-6239-640-1_14 ID - Zhang2026 ER -