预测可穿戴物联网的采用情况:通过机器学习算法识别核心消费者

IF 7.6 2区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
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引用次数: 0

摘要

物联网(IoT)技术已被集成到手表、眼镜、照明系统和家庭服务等各种产品中,并获得了消费者的广泛认可。虽然整个物联网市场已经进入成熟阶段,但作为物联网技术的一个重要子集,可穿戴设备的采用却相对滞后。认识到有必要确定这些可穿戴设备的潜在需求,本研究利用 2019 年 MCR 调查(N=3,922)的数据,并采用五种机器学习算法进行分析。其中,随机森林模型在预测消费者采用可穿戴设备方面的准确率最高。根据该模型,确定了影响采用率的 17 个主要预测因素。研究结果表明,10 至 20 岁的女性最有可能成为可穿戴设备的潜在核心消费者。这些人的特点是支出收入比高,消费标准严格,会考虑产品质量、价格、设计、购物效率和品牌声誉。本研究首次将机器学习技术应用于可穿戴设备领域的消费者定位策略,为广告营销文献的扩展做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting wearable IoT Adoption: Identifying core consumers through Machine learning algorithms

Internet of Things (IoT) technology has been integrated into a diverse array of products, including watches, glasses, lighting systems, and home services, and has garnered widespread consumer acceptance. While the overall IoT market has reached a stage of maturity, the adoption of wearable devices, a key subset of IoT technologies, lags behind. Recognizing the need to identify potential demand for these wearable devices, this study leverages data from the 2019 MCR survey (N=3,922) and employs five machine learning algorithms for analysis. Among these, the random forest model demonstrates the highest accuracy in predicting consumer adoption of wearable devices. Based on this model, 17 major predictors influencing adoption have been identified. The study’s findings suggest that women in their 10 s and 20 s are the most likely potential core consumers for wearable devices. These individuals are characterized by a high expenditure-to-income ratio and stringent consumption standards that take into account product quality, price, design, shopping efficiency, and brand reputation. This research contributes to the expansion of the advertising marketing literature by being among the first to employ machine learning techniques for consumer targeting strategies in the wearable device sector.

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来源期刊
Telematics and Informatics
Telematics and Informatics INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
17.00
自引率
4.70%
发文量
104
审稿时长
24 days
期刊介绍: Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.
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