营销管理前沿系列讲座四
时间：2024年1月8日（星期一），北京时间9：30am（EST: Jan. 7, 8:30pm）
会议平台及会议号：腾讯会议：964-969-684（密码：202401）
主讲人：陈铭助理教授，北卡罗莱纳大学夏洛特分校
主持人：栗跃峰博士
主讲人简介：
陈铭助理教授，目前任北卡罗莱纳大学夏洛特分校贝尔克商学院营销系助理教授和数据科学学院助理教授（联合任命）。她在担任助理教授之前，在休斯顿大学鲍尔商学院获得工商管理（市场营销）博士学位，约翰斯霍普金斯大学获得金融MBA学位，和电子科技大学计算机学院和bob半岛平台官方网站获得计算机与金融双学士学位。她的研究领域主要是使用实证统计数据模型通过分析消费者的视觉注意力（眼动跟踪）探索线上与线下消费者购物行为的影响因素，并挖掘对零售业以及电子商务平台的商业启示。她的研究结果已发表在包括Journal of Marketing Research,Marketing Letters,Journal of Advertising等顶级学术期刊上。她曾获得2020年AMA（American Marketing Association）冬季年会“市场调研”类最佳论文奖，亚马逊全球研究奖(Amazon Research Awards)2021年在线广告研究奖，北卡罗莱纳大学夏洛特分校贝尔克商学院2022年杰出研究奖等奖项。
讲座简介：
题目:Understanding Consumers’ Shopping Behaviors from Their Attention Using Eye-tracking Study
In this seminar, I will discuss two research papers with both utilized eye-tracking methodology to collect data from consumers’ visual movement during their shopping journey. The first paper investigates the extent to which lateral and vertical biases drive consumers’ attention in a grocery store environment. The dataset, collected using in-store ambulatory eye-tracking device, offers a complete picture of both where the shopper is located and the shopper’s field of view and visual fixations during the trip. We find that shoppers pay more attention to products on their right side (vs. left side) when traversing an aisle. Contrary to many practitioners’ belief, eye level is not “buy level”; rather, the product level that has the greatest propensity to capture shoppers’ attention is approximately 14.7 inches below eye level (which is around chest level).
In the second paper, we focus on understanding how consumers visually attend to mobile advertisements in online shopping environment. However, scant eye-tracking research exists in mobile settings due to technical challenges, e.g., cumbersome data annotation. To tackle these challenges, this paper proposes an object-detection machine learning (ML) algorithm—You Only Look Once (YOLO) v3—to analyze eye-tracking videos automatically. Through a lab experiment, we investigate how two types of ad elements (i.e., textual vs. pictorial) and shopping devices (i.e., mobile vs. PC) affect consumers’ visual attention. Our findings suggest that (1) textual ad elements receive more attention than pictorial ones; and (2) mobile ads receive less attention than PC ads. Our findings provide managerial insights into developing effective digital advertising strategies to improve consumers’ visual attention in online and mobile advertisements.
