使用可解释的AI对女性学生对金融技术的看法进行细分
1Department of Economics, University of Crete, Rethymnon, Greece.
Frontiers in artificial intelligence
|December 27, 2024
概括
女性采用金融技术 (金融科技) 显示出两个群体:"金融科技友好"和"金融科技怀疑". 感知到的好处,如方便驱动Fintech采用,告知利益相关者战略.
科学领域:
- 社会科学 社会科学 社会科学
- 技术与创新 技术与创新
- 性别研究是性别研究.
背景情况:
- 建议金融技术 (金融科技) 减少性别差距.
- 有证据表明,金融科技尚未实现这一目标.
- 妇女对金融科技工具的看法和采用情况尚不清楚.
研究的目的:
- 细分女性对金融科技工具的看法.
- 使用机器学习来解释这些细分.
- 确定影响女性采用金融科技的因素.
主要方法:
- 机器学习技术用于细分.
- 分析的重点是确定细分市场之间的关键差异化因素.
- 对细分特征的定性解释.
主要成果:
- 两个不同的细分市场出现了:"金融科技友好"和"金融科技怀疑".
- "金融科技友好"群体的关键驱动因素包括感知到的好处:易用性,时空便利性和整体优势性质.
- 导致怀疑的因素需要进一步调查.
结论:
- 女性对金融科技的看法不均,需要有针对性的方法.
- 强调方便性和易用性可以鼓励金融科技的采用.
- 利益相关者应该考虑为不同细分市场量身定制的教育和用户体验.
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