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Proactive social learning and green product consumption: Evidence from new energy vehicle sales in China

  • Zhe Jiang
  • , Ning Liu*
  • , Xiaobing Zhang
  • , Yanlai Chu
  • , Lin Zhang*
  • *Corresponding author for this work
  • City University of Hong Kong
  • Renmin University of China

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Growing literature on social norms points to the effectiveness of leveraging social interactions to spur prosocial purchase behaviors. This article studies the effects of proactive social learning, a dynamic social norm formation process measured by the public's online normative information acquisition regarding climate change, on new energy vehicle (NEV) sales in China. Drawing on model–month sales data, we provide robust evidence that citizens' broad searches for information about climate change or global warming boost local NEV sales. By distinguishing between search topics, we find that impact-based learning has a greater influence on NEV sales than reason-based learning. City-level analysis further reveals that local social norms formed through economic openness, public literacy, and strategic government interventions enhance proactive social learning-driven NEV sales. Our findings highlight the importance of understanding proactive social learning embedded in localized social norms in promoting prosocial consumer decisions.

Original languageEnglish
Article number124232
JournalTechnological Forecasting and Social Change
Volume219
ISSN0040-1625
DOIs
Publication statusPublished - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Climate change
  • Green consumption
  • New energy vehicle
  • Proactive social learning
  • Search trend

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