Measuring customer-perceived service quality in the ride-hailing industry: a generic approach for the development and validation of a multidimensional scale

Jin Li, Xiaomei Xu (), Hui Xu and Yali Song
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Jin Li: School of Intelligent Manufacturing and Smart Transportation, Suzhou City University
Xiaomei Xu: School of Intelligent Manufacturing and Smart Transportation, Suzhou City University
Hui Xu: CCDI (Suzhou) Exploration & Design Consultant CO., Ltd.
Yali Song: School of Intelligent Manufacturing and Smart Transportation, Suzhou City University

Humanities and Social Sciences Communications, 2025, vol. 12, issue 1, 1-13

Abstract: Abstract Service issues and limitations of generic measures (scales, instruments) necessitate well-developed customized measures to evaluate service quality. Against methodological limitations that grounded in researchers’ thoughts and second-hand knowledge (existing literatures and materials) to derive measure items and dimensions, limited considerations for measure validity (e.g., measurement invariance), this study proposes a generic approach for customized measure development firstly by employing grounded theory to preliminarily derive measure items and dimensions from the first-hand knowledge of customers’ thoughts (customers’ experiences and perceptions expressed through focus group discussions), then by combining exploratory factor analysis and confirmatory factor analysis to purify and assess the measure, and finally by conducting multi-group confirmatory factor analysis to test measurement invariance across different user cohorts. This approach was used for the less researched ride-hailing industry. The data were collected from 1464 ride-hailing users in Suzhou, China. The results suggested a 3-dimension 12-item model represented by Service, Integrity and Efficiency being a meaningful and valid measure. This multidimensional model could be viewed as a more parsimonious alternative to using a vast set of measure items individually in analyzing ride-hailing service quality, which may provide operators with managerial implications in improving the service.

Date: 2025
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DOI: 10.1057/s41599-025-05902-9

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