Abstract
With the rapid growth of Chin's green consumer groups, green consumption has shown great environmental value while driving consumption upgrades. The impact of energy saving information exposure on green consumption behavior has also attracted scholars' attention. Data-driven and model-driven methods have been combined. Natural language processing technology has been adopted to construct energy-saving information exposure indicators, and propensity score matching and quantile regression have-been used to conduct empirical research on 5,889 household appliances consumption and comment data on an e-commerce platform in China. It has been indicated that the overall energy-saving information exposure of e-commerce platforms in China is not high. The marginal effect of energy-saving information exposure on the sales of energy-saving home appliances shows a monotonous upward trend, and the inflection point of information redundancy has not yet appeared. At the same time, inverted U-shaped change in the impact of home appliances with different sales scalesto energy saving information exposure has been found, which has a greater impact on home appliances with medium sales scale. Finally, the adjustment effect of the "platform effect" on energy saving information exposure has been further verified. which provides a reference for the research on green consumption behavior based on large-scale multi-source heterogeneous data.
| Translated title of the contribution | The Impact of Energy-saving Information Exposure on Green Consumption Behavior—An Empirical Study of Large-scale Text Data from E-commerce Data Platforms |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 241-251 |
| Number of pages | 11 |
| Journal | Chinese Journal of Management Science |
| Volume | 30 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 20 Jan 2022 |
| Externally published | Yes |
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