A systematic estimation approach for the importance of engineering characteristics based on online reviews

Online reviews are a new source for the valuable voice of customers. By identifying the customer’s opinion, designers can comprehend the important features of a product to satisfy customer demand, thus enhancing the market competitiveness of the product. Customers have opinions on multiple aspects o...

Full description

Saved in:
Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture Journal of engineering manufacture, 2020-09, Vol.234 (11), p.1433-1447
Main Authors: Xing, Tao, Wang, Guan, Yuan, Lin, Liu, Yusheng, Ye, Xiaoping, Zhao, Jianjun
Format: Article
Language:English
Subjects:
Artificial neural networks
Customer satisfaction
Customers
Data mining
Design
Fuzzy logic
Hair stylers
Product design
Sentiment analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Online reviews are a new source for the valuable voice of customers. By identifying the customer’s opinion, designers can comprehend the important features of a product to satisfy customer demand, thus enhancing the market competitiveness of the product. Customers have opinions on multiple aspects of products hidden in reviews, and sentiment divergence may exist. Moreover, there is a gap between customer requirements and the product’s system requirements. How to effectively analyze a large number of reviews to extract the aspect-level customer opinion and thus determine the most important product engineering characteristics in design are the critical challenges for market-driven design. A systematic requirement analysis framework is proposed in this work. First, a convolutional neural network and sentiment analysis are used for opinion mining of online reviews. Then, based on fuzzy logic, the customer sentiment divergence (which is quantified by controversy indexes) and the average sentiment of a requirement are used to determine the degree of satisfaction. Finally, based on the product’s quality function development matrix, the satisfaction and frequency of the customer requirements are used to estimate the importance of the product’s engineering characteristics, which identifies the focus of product design. A case study of a hair dryer is given to demonstrate the effectiveness of the proposed methods.
ISSN:0954-4054
2041-2975
DOI:10.1177/0954405420918156