摘要
人工智能在营销领域的大量运用改变了消费市场的整体环境,如何更好地利用人工智能的优势来促进消费者采纳产品,对营销者来说是一个新的挑战。基于自决理论和授权理论,采用田野及组间实验设计,探究人工智能推荐产品类型时消费者采纳意愿的内在机制以及边界条件,研究结果表明:人工智能推荐的实用型产品比享乐型产品更容易获得消费者的采纳,且消费者更愿意采纳人工智能的推荐而不是传统模式的广告;消费者采纳意愿的差异是由于消费者感知自主性的不同所导致的,即人工智能推荐实用型产品能让消费者感知到比推荐享乐型产品更高的自主性,形成更为积极的采纳意愿;但这些差异性会被算法透明度的高低所调节,在高算法透明度的条件下,消费者对于人工智能推荐的产品类型不存在显著的采纳意愿差异。这些发现,为人工智能和营销领域提供了深入的见解并进一步扩展了领域内的研究内容,同时有助于企业和购物平台良好运用人工智能推荐,提升推荐效率,增强营销能力。
The extensive use of artificial intelligence in marketing has changed the environment of the consumer market.These technological changes present a new challenge for managers,especially in considering how to better leverage the benefits of AI to promote consumer’s intention to adopt products.The research object is different product types recommended by artificial intelligence.Based on self-determination theory and delegation theory,field and between-subject experimental designs are used to investigate the intrinsic mechanisms and boundary conditions of consumers’adoption intention of different product types recommended by artificial intelligence from a new perspective.The result of this research shows that,compared with hedonic products,utilitarian products recommended by artificial intelligence are easier to be adopted by consumers,and under the condition of utilitarian products,consumers are more willing to adopt artificial intelligence recommendations rather than traditional advertisements.The difference in consumers’adoption intention is caused by the difference in consumers’perceived autonomy,that is,utilitarian products recommended by artificial intelligence can make consumers perceive higher autonomy and generate more positive adoption intention than hedonic products.However,these differences are moderated by the level of algorithmic transparency,that is,there are no significant differences in consumers’adoption intention of product types recommended by artificial intelligence under the condition of high algorithmic transparency.These findings provide insights and further expand research within the field of artificial intelligence and marketing.The research result is helpful for enterprises and shopping platforms to better utilize artificial intelligence recommendations,improve recommendation efficiency,and enhance the marketing ability of enterprises and shopping platforms.
作者
陈炳霖
薛可
余明阳
Chen Binglin;Xue Ke;Yu Mingyang
出处
《江西社会科学》
北大核心
2023年第1期194-205,208,共13页
Jiangxi Social Sciences