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作 者:张宇航
机构地区:[1]上海工程技术大学管理学院,上海
出 处:《运筹与模糊学》2023年第5期5002-5016,共15页Operations Research and Fuzziology
摘 要:由于个性化推荐系统产生的推荐是提升人气和消费者活跃度的重要手段,因此目前已被电商平台广泛的应用。然而由于各类推荐信息不同的影响机制等复杂性问题,消费者可能会短暂的被吸引,但却不做出购买选择,进而形成一种假性活跃,这对注重消费转化率的商家来说并不是一件好事。如何选择有效的推荐策略,避免消费者的“假性活跃”,提升消费者的购买转化率,对营销人员来说是一项挑战。本文基于国内某大型电商平台信息流数据,分析曝光信息多样性对消费者不同行为决策的影响,研究发现消费者对多样性信息的处理在不同行为决策时是不同的,尽管与用户消费行为相关的因素多种多样,但直观的电商平台推荐信息多样性设计是营销人员需要考虑的核心方面,丰富了当前信息科学领域的推荐多样性问题研究,并给予电商企业在个性化推荐系统多样性投放方面一定的建议。Due to the fact that personalized recommendation systems generate recommendations as an important means of increasing popularity and consumer activity, they have been widely used on e-commerce platforms. However, due to the complexity of the impact mechanisms of different types of recommendation information, consumers may be briefly attracted but do not make purchasing choices. Forming a pseudo activity is not a good thing for businesses that focus on consumption conversion rates. How to choose effective recommendation strategies, avoid consumers’ false activity, and improve their purchase conversion rate is a challenge for marketers. Although there are various factors related to user consumption behavior, the design of intuitive e-commerce platform recommendation information diversity is a core aspect that marketers need to consider. While ensuring the accuracy and efficiency of personalized recommendations on e-commerce platforms, enriching recommendation diversity has become an important issue in the current field of information science.
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