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A new approach of social media analytics to predict service quality: evidence from the airline industry

Xin Tian (Department of Information Technology, Kennesaw State University, Kennesaw, Georgia, USA)
Wu He (Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, Virginia, USA)
Chuanyi Tang (Department of Marketing, Old Dominion University, Norfolk, Virginia, USA)
Ling Li (Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, Virginia, USA)
Hangjun Xu (Department of Marketing, Union University, Jackson, Tennessee, USA)
David Selover (Department of Economics, Old Dominion University, Norfolk, Virginia, USA)

Journal of Enterprise Information Management

ISSN: 1741-0398

Article publication date: 13 November 2019

Issue publication date: 22 January 2020

2068

Abstract

Purpose

Research on how to use social media data to measure and evaluate service quality is still limited. To fill the research gap in the literature, the purpose of this paper is to open a new avenue for future work to measure the service quality in the service industry by developing a new analytical approach of using social media analytics to evaluate service quality.

Design/methodology/approach

This paper uses social media data to measure the service quality of the airline industry with the SERVQUAL metrics. A novel benchmark data set was created for each SERVQUAL metric. The data set was analyzed through text mining and sentiment analysis.

Findings

By comparing the results from social media with official service quality report from the Department of Transportation, the authors found that the proposed service quality metrics from social media are valid and can be used to estimate the service quality.

Practical implications

This paper presents service quality metrics and a methodology that can be easily adopted by other businesses to assess service quality. This study also provides guidance and suggestions to help businesses understand how to collect and analyze social media data for the purpose of evaluating service quality.

Originality/value

This paper offers a novel methodology that uses text mining and sentiment analysis to help the airline industry assess its service quality.

Keywords

Citation

Tian, X., He, W., Tang, C., Li, L., Xu, H. and Selover, D. (2020), "A new approach of social media analytics to predict service quality: evidence from the airline industry", Journal of Enterprise Information Management, Vol. 33 No. 1, pp. 51-70. https://doi.org/10.1108/JEIM-03-2019-0086

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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