Could e-commerce activities drive to climate change mitigation? Novel evidence from panel quantile regression model
Abstract
This study aims at shedding light on how e-commerce contributes to climate change in European Union countries. To explore this relationship, we introduced a novel index designed to measure the evolution of climate change as the dependent variable, while considering e-commerce activities as the independent variable within 2011 to 2022 period. Our investigation of the correlation between these variables employed a panel quantile regression model. The outcomes revealed a statistically significant increasing trend for higher quantiles. This finding indicates that, as we traverse the climate change index from lower to higher percentiles, the impact of e-commerce becomes more conspicuous and is statistically significant. This underscores that the influence of e-commerce on climate change intensifies as we move towards the upper percentiles of the climate change index. To address how e-commerce affects climate change, it becomes imperative to introduce and enforce the concept of environmental responsibility in the management of e-commerce activities. This could involve adopting sustainable practices, optimizing packaging materials, and encouraging eco-friendly delivery methods. Policymakers and businesses alike should consider these findings in their efforts to strike an equilibrium between the convenience of e-commerce and the need to curb its environmental impact.
Keyword : e-commerce, climate change index, quantile regression, climate risks, mitigation, quantiles
How to Cite
Doran, N. M., Manta, A. G., Badareu, G., Berceanu, D., Doran, M. D., & Manta, F. L. (2025). Could e-commerce activities drive to climate change mitigation? Novel evidence from panel quantile regression model. Journal of Business Economics and Management, 26(2), 255–276. https://doi.org/10.3846/jbem.2025.23604
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Fichter, K. (2002). E-commerce: Sorting out the environmental consequences. Journal of Industrial Ecology, 6(2), 25–41. https://doi.org/10.1162/108819802763471762
Gracceva, F., & Zeniewski, P. (2014). A systemic approach to assessing energy security in a low-carbon EU energy system. Applied Energy, 123, 335–348. https://doi.org/10.1016/j.apenergy.2013.12.018
Grand View Research. (2021). Online grocery market size, share & trends analysis report by product type (Fresh produce, breakfast & dairy, snacks & beverages, staples & cooking essentials), by region, and segment forecasts, 2022–2030. https://www.grandviewresearch.com/industry-analysis/online-grocery-market
Guo, J., Wang, X., Fan, S., & Gen, M. (2017). Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food e-commerce enterprises. Computers & Industrial Engineering, 106, 351–360. https://doi.org/10.1016/j.cie.2017.02.002
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Han, A., Liu, P., Wang, B., & Zhu, A. (2023). E-commerce development and its contribution to agricultural non-point source pollution control: Evidence from 283 cities in China. Journal of Environmental Management, 344, Article 118613. https://doi.org/10.1016/j.jenvman.2023.118613
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Heydari, M. (2024). Cultivating sustainable global food supply chains: A multifaceted approach to mitigating food loss and waste for climate resilience. Journal of Cleaner Production, 442, Article 141037. https://doi.org/10.1016/j.jclepro.2024.141037
Hollaus, M., & Schantl, J. (2022, January 14–17). Incentivizing consumers towards a more sustainable online shopping behavior: A study on nudging strategies in B2C E-Commerce. In Proceedings of the 2022 13th International Conference on E-Education, E-Business, E-Management, and E-Learning (pp. 372–376). Tokyo, Japan. ACM Digital Library. https://doi.org/10.1145/3514262.3514268
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