Purpose

The extant literature has utilized the SERVQUAL scale to measure service quality dimensions and their importance towards customer-satisfaction using close-ended survey-based questions and not open-ended questions and/or user-generated qualitative responses. On the other hand, while measuring customer-satisfaction drivers from user-generated content (UGC), extant studies have majorly used overall or aspect-wise evaluations and not evaluations specific to SERVQUAL dimensions. In this study, the authors try to bridge the gap.

Design/methodology/approach

The authors suggest a methodology consisting of text mining, machine learning and econometric techniques that can measure consumer evaluations of SERVQUAL dimensions. The authors used qualitative and quantitative UGC obtained from 27,052 online reviews on 362 airlines by reviewers of 158 nationalities for our analysis.

Findings

The authors established a unique method which combines qualitative and qualitative UGC to measure service quality. The authors have also uncovered the comparative importance of such dimensions in creating customer-satisfaction and recommendation in the context of the airline industry.

Originality/value

The paper is one of the pioneering studies that try to find measures of SERVQUAL dimensions from online consumer reviews and their influence on customer satisfaction.

中文翻译：

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使用在线评论测量 SERVQUAL 维度及其对客户满意度的重要性：一种文本挖掘方法

目的

现有文献利用 SERVQUAL 量表来衡量服务质量维度及其对客户满意度的重要性，使用基于封闭式调查的问题，而不是开放式问题和/或用户生成的定性回答。另一方面，在从用户生成的内容 (UGC) 衡量客户满意度驱动因素时，现有研究主要使用整体或方面评估，而不是特定于 SERVQUAL 维度的评估。在这项研究中，作者试图弥合差距。

设计/方法/途径

作者提出了一种由文本挖掘、机器学习和计量经济学技术组成的方法，可以衡量消费者对 SERVQUAL 维度的评价。作者使用从来自 158 个国家的评论者对 362 家航空公司的 27,052 条在线评论中获得的定性和定量 UGC 进行分析。

发现

作者建立了一种独特的方法，将定性和定性 UGC 相结合来衡量服务质量。作者还揭示了这些维度在航空业背景下创造客户满意度和推荐方面的相对重要性。

原创性/价值

该论文是试图从在线消费者评论及其对客户满意度的影响中寻找 SERVQUAL 维度度量的开创性研究之一。