Mining Express Service Innovation Opportunity From Online Reviews

被引：18

作者：

Zhang, Ning ^{[1
]}

Zhang, Rui ^{[2
]}

Pang, Zhiliang ^{[2
]}

Liu, Xue ^{[2
]}

Zhao, Wenfei ^{[2
]}

机构：

[1] Qingdao Univ, Business Sch, Qingdao, Peoples R China

[2] Qingdao Univ, Qingdao, Peoples R China

来源：

JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING | 2021年 / 33卷 / 06期

关键词：

Express Service; Online Reviews; Opportunity Algorithm; Service Innovation; Text Mining; FEATURE-SELECTION; PRODUCT;

D O I：

10.4018/JOEUC.20211101.oa3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to further meet the diversified needs of customers and enhance market competitiveness, it is necessary for express delivery enterprises to carry out service innovation. From the perspective of customer demand, this paper proposes a framework for mining service innovation opportunities. This framework uses text mining to analyze user-generated content and tries to provide a scientific service innovation scheme for express enterprises. Firstly, the authors crawl online reviews of express companies and use LDA model to identify service attributes. Secondly, customer satisfaction is calculated by sentiment analysis, and simultaneously, the importance of each service attribute is calculated. Finally, the authors carry out an opportunity algorithm with the results of text mining to quantify the innovation opportunities of service attributes. The results show that the framework can effectively identify service innovation opportunities from the perspective of customer demand. This study provides a new way to explore the direction of service innovation from the perspective of customer demand.

引用

页数：15