Service Experience and Servicescape in Sustainable Consumption

Dear Colleagues,

This Special Issue of Sustainability seeks to investigate the crucial role that service environments and experiences play in fostering sustainable consumption across diverse sectors, including digital platforms, healthcare, education, tourism, and retail. Consumption experiences, both of individuals and groups, have emerged as important determinants of sustainable behavior, especially in high-involvement environments such as healthcare, education, travel, and interactions with digital services. To strengthen its theoretical and practical relevance, this Special Issue emphasizes the role of behavioral science and service design in shaping sustainable consumer decisions and highlights actionable implications for managing data-driven and resource-efficient services. We believe that it could be beneficial if emotional, cognitive, and behavioral reactions to service environments could be modeled, optimized, and predicted using data-driven methods.

This Special Issue focuses on three main areas: (a) examining how service experience design and delivery affect sustainable consumer behavior; (b) incorporating cutting-edge technological tools, including digital twins, simulation, machine learning, and decision support systems (DSSs), into the study of servicescapes and their sustainability implications; and (c) differentiating itself from existing trends by fostering interdisciplinary insights into smart and sustainable service ecosystems (especially in high-involvement, public-facing contexts), particularly those that seek to improve patient satisfaction, student experience,  visitor engagement, and environmentally conscious decision-making.

This Special Issue aims to contribute to the existing literature by embedding the scientific, technological, and socioeconomic dimensions of sustainability into service design and experience management. Its objective is to quantify and assess how service interactions affect consumer well-being, environmental efficiency, and resource utilization. Applications of explainable AI (XAI), behavioral analytics, predictive models, and integrated DSS frameworks are encouraged to measure and track sustainable consumption, particularly in the contexts of public services, healthcare delivery, tourism systems, and digital transformation.

Where earlier studies by Zhou et al. (2022), Pappas et al. (2023), and Shah et al. (2025) explored sustainability largely within isolated sectors and treated consumer emotions and operational data as distinct lines of inquiry, this Special Issue deliberately converges service experience design, behavioral science, and intelligent systems to narrow that divide. It emphasizes the integration of socio-emotional responses with data-driven optimization techniques, extends the analysis across high-involvement public services and digitally mediated contexts, and advances explainable AI decision-support frameworks capable of quantifying consumer well-being while simultaneously monitoring environmental performance and resource efficiency.

We look forward to receiving your contributions.

Prof. Dr. Cristian Rusu
Dr. Nicolás Matus
Dr. Fabián Silva-Aravena
Guest Editors

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• service experience
• servicescape and environmental design
• sustainable consumption and behavior
• tourism experience and tourist behavior
• health service management and patient experience
• education and student experience
• predictive analytics and consumer modeling
• decision support systems (DSS) and explainable AI
• digital transformation and smart services
• service ecosystems