年轻数字原住民对数字营销的看法:通过眼动追踪分析探究恼怒与效果

IF 2.8 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Future Internet Pub Date : 2024-04-08 DOI:10.3390/fi16040125
Stefanos Balaskas, Georgia Kotsari, Maria Rigou
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引用次数: 0

摘要

目前,部署数字广告的方法多种多样,人们利用先进技术制作出引人入胜的广告,甚至根据个人兴趣和偏好量身定制广告,但这些广告也可能会分散注意力,使人厌烦。本研究旨在通过评估当代数字广告方法对用户的烦扰程度,尤其是当这些方法分散用户注意力或导致常规在线活动延迟时,对其进行评估。为此,我们进行了一项眼动跟踪研究,让 51 名参与者浏览一个专门设计的网站,网站上有七种不同类型的广告,但没有特定内容,以避免广告内容对所收集数据的影响。参与者被要求在实验过程中执行特定的信息搜索任务,并在实验结束后报告他们是否记得看到过每种广告以及每种广告类型的烦扰程度。广告效果通过眼动跟踪指标(首次定格时间、平均定格时间、停留时间、定格次数和重访次数)来评估,这些指标描述了广告作为营销刺激的吸引力。研究结果表明,弹出式广告、内容重组广告和不可跳转视频是最令人讨厌的广告形式。相反,无内容重组的内容内广告、横幅广告和右栏广告则被认为是干扰性较小的选择,似乎在有效性和用户接受度之间取得了平衡。
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Perspectives of Young Digital Natives on Digital Marketing: Exploring Annoyance and Effectiveness with Eye-Tracking Analysis
Currently, there are a wide range of approaches to deploying digital ads, with advanced technologies now being harnessed to craft advertising that is engaging and even tailored to personal interests and preferences, yet potentially distracting and irritating. This research seeks to evaluate contemporary digital advertising methods by assessing how annoying they are to users, particularly when they distract users from intended tasks or cause delays in regular online activities. To pursue this, an eye-tracking study was conducted, with 51 participants navigating a specially designed website featuring seven distinct types of advertisements without a specific content to avoid the effect of ad content on the collected data. Participants were asked to execute specific information-seeking tasks during the experiment and afterwards to report if they recalled seeing each ad and the degree of annoyance by each ad type. Ad effectiveness is assessed by eye-tracking metrics (time to first fixation, average fixation duration, dwell time, fixation count, and revisit count) depicting how appealing an ad is as a marketing stimulus. Findings indicated that pop-ups, ads with content reorganization, and non-skippable videos ranked as the most annoying forms of advertising. Conversely, in-content ads without content reorganization, banners, and right rail ads were indicated as less intrusive options, seeming to strike a balance between effectiveness and user acceptance.
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来源期刊
Future Internet
Future Internet Computer Science-Computer Networks and Communications
CiteScore
7.10
自引率
5.90%
发文量
303
审稿时长
11 weeks
期刊介绍: Future Internet is a scholarly open access journal which provides an advanced forum for science and research concerned with evolution of Internet technologies and related smart systems for “Net-Living” development. The general reference subject is therefore the evolution towards the future internet ecosystem, which is feeding a continuous, intensive, artificial transformation of the lived environment, for a widespread and significant improvement of well-being in all spheres of human life (private, public, professional). Included topics are: • advanced communications network infrastructures • evolution of internet basic services • internet of things • netted peripheral sensors • industrial internet • centralized and distributed data centers • embedded computing • cloud computing • software defined network functions and network virtualization • cloud-let and fog-computing • big data, open data and analytical tools • cyber-physical systems • network and distributed operating systems • web services • semantic structures and related software tools • artificial and augmented intelligence • augmented reality • system interoperability and flexible service composition • smart mission-critical system architectures • smart terminals and applications • pro-sumer tools for application design and development • cyber security compliance • privacy compliance • reliability compliance • dependability compliance • accountability compliance • trust compliance • technical quality of basic services.
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