Customer Satisfaction Modelling for Healthcare Wearable Devices Through Online Reviews

被引：0
|
作者：
Lin W. [1 ]
Liu H. [1 ]
Chen Y. [1 ]
Wen Z. [1 ]
Yi M. [1 ]
机构：
[1] School of Management, Guangdong University of Technology, Guangzhou
来源：
Data Analysis and Knowledge Discovery | 2023年 / 7卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Customer Satisfaction; Healthcare Wearable Devices; Machine Learning; Online Reviews; Topic Models;
D O I：
10.11925/infotech.2096-3467.2022.0420
中图分类号：
学科分类号：
摘要：
[Objective] This paper identifies the dimensions of customer interest in wearable healthcare devices and their impact on satisfaction, aiming to inspire businesses to optimize their products and services. [Methods] First, we retrieved 11,349 online reviews from Amazon.com as the corpus. Then, we used the LDA model to identify customer satisfaction dimensions. Finally, we constructed a satisfaction model using machine learning algorithms. [Results] The satisfaction model constructed with the Multi-Layer Perceptron (MLP) had the best prediction effect (F1 = 0.6534). Customers’attention on products focused on 13 dimensions across seven comprehensive attributes: functionality attributes, service attributes, quality attributes, value attributes, ease of use attributes, social attributes, usefulness attributes. Functionality attributes was the most important product feature for customers. Social, quality, and service attributes had a negative impact on customer satisfaction and should be the priority for businesses to improve products and services. [Limitations] We did not consider the reviews’ authenticity and in future will include cases of false and malicious reviews in the analysis process. [Conclusions] This paper identifies the dimensions of customer attention to products, their impact on satisfaction, and the order in which improvement should be made, providing management insights for business. © 2023 Tunnel Construction. All rights reserved.
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收藏
页码：145 / 154
页数：9
相关论文
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