Product innovation based on online review data mining: a case study of Huawei phones

Hui Zhang (), Huguang Rao and Junzheng Feng
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Hui Zhang: Hangzhou Dianzi University
Huguang Rao: Hangzhou Dianzi University
Junzheng Feng: Hangzhou Dianzi University

Electronic Commerce Research, 2018, vol. 18, issue 1, No 2, 3-22

Abstract: Abstract Online reviews contain a plethora of useful information that plays a vital role in consumer choices and provides a dominant reference for enterprises to adopt strategies for product development and improvement. The paper examines the www.zol.com.cn website as a source of information and Huawei Mate phones as a research target, processes the data of consumers’ online reviews on three types of Huawei Mate phones, discusses the correlations between online reviews and phone improvement, and proposes some suggestions for future product improvement. This empirical study shows that the correlation between the change in the degree of feature satisfaction and phone improvement is strong; the correlation between the change in the degree of feature satisfaction and product improvement is stronger than that between the change in the degree of feature attention and product improvement. Enterprises can determine the direction and contents of phone improvement based on information from reviews on its preceding phone model. This study can help enterprises master market requirements, understand consumers’ behaviour and improve the quality and efficiency of product innovation.

Keywords: Online review; Product innovation; Data mining; Feature extraction; Sentiment analysis (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (13)

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DOI: 10.1007/s10660-017-9279-2

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