In an era where public health concerns intersect profoundly with urban mobility, a groundbreaking study has emerged to redefine the future of transit services. The research, conducted by Jiang, Lin, Yao, and colleagues, introduces an innovative framework integrating the Fuzzy Analytic Hierarchy Process (FAHP), the Kano model, and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to systematically evaluate health-oriented transit services. This synthesis not only elevates the understanding of user preferences but also elucidates the behavioral mechanisms driving adoption during health crises, setting a new benchmark for autonomous medical public transportation systems.
At the core of the study lies an intricate analysis of service attributes that can mitigate public health risks while ensuring user satisfaction. Timely sanitation emerged as a paramount concern, assigned the highest weight of 0.133 in the FAHP evaluation, underscoring the critical demand for cleanliness in shared transit environments. Complementing this, the Kano model identified contactless entry as an “Attractive” attribute, emphasizing the desire for seamless, touch-free interactions that minimize pathogen transmission risks. These findings converge to highlight how meticulous design rigor in health-centric transit solutions is indispensable to user acceptance.
Delving into the behavioral acceptance model, the researchers extended the UTAUT2 framework to encompass perceptions unique to health-oriented mobility systems. Seven determinants of behavioral intention were validated: performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price sensitivity, and perceived risk. Intriguingly, social influence surfaced as a dominant positive factor (β = 0.274), suggesting that community norms and peer support significantly affect user willingness to embrace autonomous medical transit. In stark contrast, perceived risk bore a negative influence (β = −0.266), reaffirming individuals’ hesitancy rooted in safety and reliability concerns. This dichotomy elucidates the nuanced interplay between societal endorsement and personal apprehension.
The inclusion of price sensitivity as a strict barrier (β = −0.34, p < 0.001) marks a novel insight within the domain of autonomous public transport adoption. The implication is clear: affordability and transparent pricing structures wield substantial power over mass acceptance, particularly among low-income demographics. In parallel, hedonic motivation (β = 0.33, p < 0.01)—reflecting enjoyment and experiential satisfaction—demonstrated elevated significance, surpassing its traditional influence in UTAUT2 applications. This indicates that beyond functional utility, user experience and engagement play pivotal roles in sustaining long-term commitment to health-oriented transit technologies.
Drawing upon these multifaceted insights, the study proposes three actionable strategies to maximize the uptake of the Autonomous Intelligent Medical Public Transit System (AIM-PTS). Firstly, embedding real-time hygiene indicators directly addresses perceived risk by offering transparent, dynamic feedback on sanitation status and operational safety. Such metrics empower users with enhanced situational awareness, augmenting trust in the system’s health protocols. Secondly, implementing tiered pricing schemes specifically tailored for low-income commuters aims to mitigate economic barriers, fostering equitable access and social inclusion. Lastly, gamified health alerts leverage hedonic motivation, transforming routine health monitoring into engaging, interactive experiences that encourage proactive participation.
The practical implications of these recommendations are profound. By seamlessly integrating rapid health screening technologies—such as temperature checks and combined health code-boarding pass systems—AIM-PTS can significantly elevate user confidence and perceived safety. Furthermore, adopting pricing models that transparently reflect cost advantages over traditional public transport and ride-hailing alternatives can shift user preferences decisively. The inclusion of gamified elements creates an emotional bond with the service, potentially improving compliance with health protocols and enhancing overall satisfaction.
Statistically, the study’s validation of the augmented UTAUT2 framework solidifies its theoretical contribution to the field. Notably, the research underscores the amplified effect of social influence and hedonic motivation within health-focused transport contexts compared to conventional technology adoption scenarios. This amplification may be attributed to heightened communal awareness and the intrinsic human desire for enjoyable, meaningful interactions during times of crisis. Such findings invite a re-examination of technology acceptance models to incorporate context-specific psychological and cultural factors.
Despite its pioneering scope, the study prudently acknowledges limitations that frame future research directives. Data collection occurred during the nascent adoption stages of AIM-PTS in China, encompassing five provinces that may not fully represent broader sociocultural and economic heterogeneity. As technology matures and user familiarity deepens, evolving patterns of trust, habit formation, and automation acceptance are anticipated. Longitudinal investigations tracking these dynamics will be essential to refine the framework and validate factor stability over time.
Furthermore, the reliance on self-reported survey data introduces susceptibility to response biases, including recall inaccuracies and social desirability effects. The incorporation of objective metrics—such as accelerometer data to gauge usage intensity or physiological stress indicators—would enhance the robustness of future assessments. Mixed-method approaches integrating qualitative interviews could also uncover latent factors beyond those captured by quantitative models, such as ethical considerations and policy impacts, which are increasingly relevant in autonomous health service deployment.
Technologically, AIM-PTS exemplifies the frontier of autonomous transit, merging artificial intelligence, real-time data analytics, and public health imperatives. The integration of automation with medical screening functions within a public transit framework offers transformative potential for urban mobility. By prioritizing pathogen transmission reduction, user-centric design, and behavioral acceptance, AIM-PTS aligns with broader goals of resilient, adaptive smart cities capable of weathering future health emergencies.
The study’s interdisciplinary methodology, bridging decision science (via FAHP), customer satisfaction theory (via Kano), and technology adoption behavioral frameworks (via UTAUT2), represents a landmark in transit service research. This comprehensive approach enables nuanced prioritization of service features while simultaneously contextualizing user acceptance within psychological and socioeconomic landscapes. Such holistic evaluation is indispensable for designing interventions that are not only technically feasible but also pragmatically viable and socially acceptable.
Moreover, the implications extend beyond AIM-PTS to other domains where health and technology intersect, including telemedicine, smart home healthcare, and wearable health devices. The lessons learned regarding hygiene transparency, affordability, and experiential engagement can inform cross-sector strategies to enhance public trust and adoption rates. The study thus contributes foundational knowledge with broad applicability to the health-technology nexus.
Ultimately, this research exemplifies how rigorous empirical investigation can inform the design and implementation of next-generation public health infrastructure. By dissecting the complex factors that govern user behavior and service preference during health crises, it charts a roadmap toward safer, more efficient, and equitable urban transit. The marriage of advanced analytics with behavioral insight promises to elevate public health outcomes and societal resilience in unprecedented ways.
The journey towards seamless, health-oriented autonomous transit is poised to revolutionize urban landscapes. This study’s robust framework and insightful findings offer a beacon for policymakers, technologists, and urban planners seeking to harness innovation for the collective good. As autonomous intelligent medical public transit evolves from concept to reality, such evidence-based blueprints will be critical in navigating the challenges and embracing the opportunities of a healthier, more connected future.
Given the accelerating pace of urbanization and the omnipresent threat of infectious diseases, integrating behavioral science with transit technology is not a luxury but a necessity. The Jiang et al. study stands as a call to action to prioritize user-centric design, transparent communication, and equitable access within health-oriented mobility solutions. In doing so, it not only advances scholarly discourse but also empowers communities to thrive amidst evolving public health landscapes.
This pioneering research ushers in a new paradigm wherein autonomous transit systems serve as vital vectors for public health promotion. By championing hygiene innovation, economic inclusivity, and engaging user experiences, AIM-PTS embodies the confluence of technology and humanity. As cities worldwide grapple with the aftermath of health crises, such integrated frameworks will underpin resilient, adaptive infrastructures shaping the future of mobility and well-being.
Subject of Research:
Enhancing user acceptance and service design of health-oriented autonomous public transit through integrated decision-making and behavioral frameworks.
Article Title:
Enhancing public health-oriented travel services: an integrated framework combining FAHP, Kano model, and UTAUT2.
Article References:
Jiang, M., Lin, S., Yao, Y. et al. Enhancing public health-oriented travel services: an integrated framework combining FAHP, Kano model, and UTAUT2. Humanit Soc Sci Commun 12, 1759 (2025). https://doi.org/10.1057/s41599-025-06050-w
Image Credits:
AI Generated
DOI:
https://doi.org/10.1057/s41599-025-06050-w
