In the rapidly evolving realm of urban transportation, ride-hailing services have emerged as a dominant force. Yet, despite their ubiquity, evaluating the quality of these services from the users’ perspective remains a complex and largely underexplored territory. A groundbreaking study recently published in Humanit Soc Sci Commun offers unprecedented insights into this challenge. The research introduces a novel, generic methodology for developing and validating multidimensional scales to measure customer-perceived service quality, transcending the limitations of any single geographical or service context.
At the heart of this study lies an innovative three-step approach devised to construct robust, reliable, and valid measurement tools. Unlike traditional methods that often start with predefined metrics, this approach harnesses the power of firsthand user knowledge, ensuring the resulting measures are conceptually sound and deeply reflective of actual customer experiences. The sequence begins with data collection through focus group discussions, enabling researchers to gain rich, qualitative insights into user perceptions.
Employing grounded theory coding techniques, the researchers meticulously analyze these discussions, extracting key dimensions and items that form the foundation of the measurement scale. This phase is critical, as it roots the scale firmly in real-world user sentiment rather than theoretical assumptions or benchmarked standards often detached from everyday contexts. The method’s application to ride-hailing in Suzhou, China, exemplifies the technique’s precision in capturing nuanced service elements that resonate with consumers.
Following the qualitative exploration, the study progresses to rigorous scale refinement and validation. Using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), the team purifies the scale, ensuring it not only fits the model statistically but also demonstrates reliability and validity. These steps guarantee that the dimensions identified earlier translate effectively into measurable constructs capable of capturing variations in customer experiences.
Measurement invariance across diverse user cohorts is then scrutinized with Multi-Group Confirmatory Factor Analysis (MGCFA), a vital step rarely emphasized in earlier research. This ensures that the developed scale operates consistently regardless of user demographics or psychographics, confirming its universal applicability. Such attention to invariance is critical in transport services, where user groups can vary widely in expectations and experiences.
A notable innovation of this study is the first-ever use of grounded theory in scale development for service quality measurement. This enriches the methodological toolkit for survey design and enhances the fidelity of the results produced. Grounded theory’s contribution cannot be overstated, as it allows the measure to genuinely reflect the complex, multifaceted nature of service quality as perceived by consumers rather than relying on abstract proxies.
From a practical standpoint, the research unearths a three-dimensional, 12-item scale tailored for the relatively neglected ride-hailing market in Suzhou. This tool enables urban planners, transportation agencies, and Transportation Network Companies (TNCs) to decode customer satisfaction drivers more accurately. It also reveals significant disparities in ride-hailing adoption and frequency of use across different sociodemographic groups in Suzhou, highlighting an essential dimension for targeted policy-making and service improvements.
The scale’s empirical findings carry profound implications. Urban officials and TNC operators now possess a nuanced understanding of service quality elements crucial to users, empowering them to refine offerings, address pain points, and ultimately boost ridership in a competitive market. This localized knowledge, while developed from Suzhou’s context, is designed with broad applicability in mind—showcasing the study’s contribution to universal urban mobility challenges.
However, the study does not shy away from acknowledging its limitations, opening pathways for future inquiry. The reliance on self-reported data poses inherent challenges, including potential biases stemming from social desirability or recall inaccuracies. Such constraints underscore the urgency of integrating objective data, like real-time usage patterns or behavioral analytics, in forthcoming research initiatives to augment and validate subjective assessments.
Cultural factors in shaping perceived service quality emerge as an underexplored domain warranting further investigation. Given the global reach of ride-hailing platforms, cross-cultural studies hold the key to unraveling how cultural norms and values influence user expectations and satisfaction evaluations. This cross-pollination of insights would enrich the global discourse on service quality and adaptation strategies for multinational transportation providers.
Additionally, the dynamic nature of service quality perception remains an open field. The current scale captures static snapshots, whereas real-time feedback mechanisms and longitudinal changes in user demands could redefine service quality benchmarks. Future research focusing on temporal evolution in customer expectations and platform responsiveness promises to yield invaluable strategic insights for ride-hailing firms operating in ever-changing urban environments.
This pioneering study combines theoretical rigor with practical relevance, bridging a critical gap in service quality measurement literature. By prioritizing the voices of users and validating scales meticulously, it sets a new gold standard for subsequent investigations in ride-hailing and beyond. As urban transportation continues to transform, such research tools become indispensable for crafting responsive, equitable, and user-centric mobility ecosystems.
In summation, this research transcends its immediate findings to offer a replicable framework for service quality measurement applicable across services and locales. Its integration of qualitative breadth via grounded theory and quantitative depth through factor analyses presents a comprehensive methodological architecture. This not only advances academic understanding but also delivers pragmatic solutions to enhance ride-hailing services globally.
The implications extend to policy formation, operational improvements, sociotechnical integration, and customer relationship management within urban mobility sectors. Transportation network companies stand to benefit significantly from the scale’s insights, enabling them to optimize service delivery and user engagement through data-driven strategies reflecting actual user needs and expectations.
With urban populations swelling and mobility demands intensifying, the study’s evidence-based approach is timely. It equips stakeholders to navigate complex service landscapes, foster user trust, and encourage mode shifts towards sustainable, efficient transportation alternatives such as ride-hailing. In essence, the research empowers a future where service quality is not an abstract ideal but a measurable, achievable standard shaped collaboratively by users and providers alike.
This contribution marks a pivotal moment in understanding the intersection between technology-enabled mobility and human-centric quality assessment. It underscores the necessity of embedding user experience at the core of service design frameworks to build resilient, adaptive, and inclusive urban transport solutions. The generic approach established here promises to catalyze an era of enhanced service quality measurement benefiting diverse transportation services worldwide.
As urban mobility continues to evolve through digitization and data analytics, this study provides a timely blueprint to assess and elevate customer experiences. Its findings inspire future interdisciplinary collaborations, integrating sociology, psychology, urban planning, and data science to refine service quality metrics further and foster transportation equity.
Altogether, this research represents both a methodological leap and practical roadmap, inviting the transportation research community and industry players to rethink how service quality is conceived, measured, and enhanced in the fast-paced ride-hailing landscape and beyond.
Subject of Research:
Customer-perceived service quality measurement in ride-hailing services, with a focus on developing a validated multidimensional scale applicable across different service settings.
Article Title:
Measuring customer-perceived service quality in the ride-hailing industry: a generic approach for the development and validation of a multidimensional scale.
Article References:
Li, J., Xu, X., Xu, H. et al. Measuring customer-perceived service quality in the ride-hailing industry: a generic approach for the development and validation of a multidimensional scale. Humanit Soc Sci Commun 12, 1570 (2025). https://doi.org/10.1057/s41599-025-05902-9
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