广泛还是小众?基于电子商务平台的决策选择

IF 1.2 4区 工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY Journal of Industrial and Management Optimization Pub Date : 2023-01-01 DOI:10.3934/jimo.2023137
Ruwen Tan, Rujin Liao, Jing Zhang, Minjiu Yu, Qinhong Yu
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引用次数: 0

摘要

先前的研究认为,降低搜索成本会使利基更好地迎合消费者,因此,更多的卖家会转向生产利基,从而导致长尾效应。然而,尽管电子商务和相关技术已经使搜索成本足够低,但市场上仍有大量广泛的产品。为了解决这一问题,本研究通过引入平台决策,构建了一个三方博弈模型来分析平台上广泛产品的比例。结果表明,当搜索成本足够小时,生态位的比例会随着搜索成本的进一步降低而降低,这与长尾效应不一致。通过加入平台决策,本研究更全面地总结了搜索成本与长尾效应之间的关系,解释了市场上大量宽泛的产品是平台刻意安排的。此外,本文还研究了带有推荐机制的扩展场景,以补充消费者随机搜索的基本模型。研究发现,基本模型中的发现得到了加强。
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Broad or niche? decision-making options based on e-commerce platforms
Previous studies believed that reducing search costs would make niches better catered to consumers, and therefore, more sellers would switch to producing niches, thus leading to the long tail effect. However, although E-commerce and related technologies have brought search costs down enough, plenty of broad products are still on the market. To address this, by introducing platform decision, this study constructs a three-way game model to analyze the proportion of broad products on the platform. The results show that when search costs are sufficiently small, the proportion of niches will decrease with the further reduction of search costs, which is inconsistent with the long tail effect. By adding platform decision, this study summarizes the relationship between search costs and the long tail effect more comprehensively and explains that a large number of broad products on the market is deliberately arranged by the platform. In addition, this article studied the extended scenario with a recommendation mechanism to supplement the basic model in which consumers search randomly. The study found that the findings in the basic model were strengthened.
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来源期刊
CiteScore
2.50
自引率
15.40%
发文量
207
审稿时长
18 months
期刊介绍: JIMO is an international journal devoted to publishing peer-reviewed, high quality, original papers on the non-trivial interplay between numerical optimization methods and practically significant problems in industry or management so as to achieve superior design, planning and/or operation. Its objective is to promote collaboration between optimization specialists, industrial practitioners and management scientists so that important practical industrial and management problems can be addressed by the use of appropriate, recent advanced optimization techniques.
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