Sponsored search and organic listings in online food delivery platforms: The role of keyword categories

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Guo Chen, Siyu Zhang, Luning Liu, Yuqiang Feng
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引用次数: 0

Abstract

Online sellers appear in search results through sponsored listings (paid advertising links) or organic listings (unpaid links) based on their associations with keywords in consumer search queries. This approach allows sellers to deduce consumers' purchasing preferences, thereby ultimately increasing their economic payoffs. Therefore, selecting appropriate keywords is critical for online sellers. Although previous research has explored the effectiveness of keyword categories in traditional e-commerce settings (e.g., online retail), there are limited studies within the quick e-commerce context (e.g., online food delivery). Moreover, the extent to which keyword categories influence the spillover effects between sponsored and organic listings remains unclear. This study leverages a large panel dataset from an online food delivery platform to analyze the impact of keyword categories on the performance of both sponsored and organic listings. We also examine how keyword categories moderate the spillover effects of sponsored listings on competitors' performance in organic listings. The results reveal that dish keywords achieve the highest click-through rate (CTR), whereas cuisine keywords lead to the lowest conversion rate (CVR). Furthermore, sponsored listings reduce competitors' CTR in organic listings, although this adverse effect is not significant for seller keywords. However, sponsored listings increase the CVR of competitors in organic listings, and this positive spillover effect is exclusively limited to seller keywords. These findings have direct implications for sellers in online food delivery markets in terms of effective keyword selection and for online food delivery platforms in terms of informing more profitable keyword sets.
在线外卖平台的赞助搜索和自然列表:关键词类别的作用
在线卖家通过赞助列表(付费广告链接)或自然列表(免费链接)出现在搜索结果中,这是基于他们与消费者搜索查询中的关键字的关联。这种方法允许卖家推断消费者的购买偏好,从而最终增加他们的经济回报。因此,选择合适的关键词对网上卖家来说至关重要。虽然以前的研究已经探讨了关键词类别在传统电子商务环境(如在线零售)中的有效性,但在快速电子商务环境(如在线食品配送)中的研究有限。此外,关键字类别在多大程度上影响赞助和自然列表之间的溢出效应仍不清楚。本研究利用来自在线外卖平台的大型面板数据集来分析关键字类别对赞助和自然列表性能的影响。我们还研究了关键词类别如何调节赞助列表对竞争对手在有机列表中的表现的溢出效应。结果显示,菜品关键词的点击率(CTR)最高,而烹饪关键词的转化率(CVR)最低。此外,赞助列表会降低竞争对手在有机列表中的点击率,尽管这种不利影响对卖家关键字并不显著。然而,赞助列表增加了竞争对手在有机列表中的CVR,这种积极的溢出效应仅限于卖家关键字。这些发现对在线外卖市场的卖家在有效的关键词选择方面和在线外卖平台在提供更有利可图的关键词集方面有直接的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
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