下游(制造业)
计算机科学
排名(信息检索)
上游(联网)
启动(农业)
领域(数学)
个性化
产品(数学)
空格(标点符号)
点(几何)
接口(物质)
启发式
信息过载
人机交互
移动设备
消费者行为
认知
息票
搜索成本
消费者选择
搜索引擎
认知需要
数据科学
随机试验
情报检索
用户参与度
作者
Shuang Zheng,Siliang Tong,Sihan Fang,Anandasivam Gopal,Xianneng Li,Qiancheng Jiang
标识
DOI:10.1287/isre.2024.1041
摘要
Mobile commerce platforms face persistent search frictions because of limited screen space and input constraints, making it difficult for consumers to initiate effective searches. This study evaluates a scalable, low-cost design intervention—the popular ranking search aid (PRSA)—that presents aggregated popular search categories at the entry point of the search interface. Using a large-scale randomized field experiment on a major mobile platform, we show that PRSA significantly reshapes consumer behavior and platform outcomes. From a practice perspective, PRSA reduces cognitive barriers in query formation by guiding users toward broader, category-level searches, leading to increased product views and higher purchase rates. However, this benefit comes with a trade-off; broader queries expand the choice set, increasing downstream decision complexity. For platform managers, this highlights the importance of balancing upstream guidance with downstream decision support. From a policy perspective, PRSA offers a privacy-compliant alternative to personalized recommendation systems as it relies on aggregated, nonpersonalized data. This makes it particularly relevant in regulatory environments with growing data protection constraints (e.g., General Data Protection Regulation-like regimes). Overall, the findings demonstrate that simple, nonpersonalized interface designs can meaningfully improve consumer engagement and market efficiency while aligning with emerging privacy standards.
科研通智能强力驱动
Strongly Powered by AbleSci AI