As sustainable tourism practices gain traction globally, immersive technologies such as augmented reality (AR) and virtual reality (VR) have emerged as effective tools to enrich visitor experiences while supporting heritage site preservation. Particularly within built cultural environments, these technologies facilitate non-invasive interpretation of architectural spaces, enabling sustainable interaction with fragile historical structures. Despite growing scholarly attention, existing research has primarily focused on the pre-adoption phase or the technical affordances of AR/VR, with limited understanding of user behavior in the post-adoption phase. To address this gap, this study integrates the Expectation Confirmation Model (ECM) with the experiential attributes of AR/VR-enabled heritage applications, proposing an integrated theoretical model to identify key determinants of tourists’ continuance intention. Based on 434 valid survey responses collected at the Terracotta Warriors Museum, a UNESCO World Heritage Site, and analyzed using structural equation modeling (SEM), the results reveal that perceived usefulness, perceived ease of use, satisfaction, and confirmation directly influence continuance intention, while visual appeal, entertainment, enjoyment, interactivity and confirmation exert indirect effects through mediating mechanisms. The findings contribute theoretically by extending ECM to the heritage tourism domain and empirically by providing robust evidence from a high-profile non-Western site. Practically, this study offers actionable implications for designing immersive experiences that enhance post-visit continuance intention and align with broader sustainability objectives.

As China’s population continues to age rapidly, smart elderly care has become a crucial strategy for addressing this societal challenge. Smart home systems have the potential to significantly enhance the quality of life, safety, and autonomy of the elderly. However, the adoption rate of these systems in this demographic remains relatively low, requiring an exploration of the key factors influencing the behavioral intention to use such systems. This study developed a comprehensive model based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using partial least squares structural equation modeling, this study systematically examined the pathways through which various factors affected the behavioral intentions of the elderly. The findings revealed that perceived usefulness, facilitating conditions, compatibility, and perceived cost had significant direct effects on behavioral intention. Additionally, social influence, perceived trust, facilitating conditions, and compatibility indirectly influenced behavioral intention through perceived usefulness and perceived ease of use. Although perceived trust did not directly affect behavioral intention, it exerted an indirect influence through perceived usefulness. This comprehensive model provides theoretical insights into the behavioral intentions of the elderly toward smart home systems and offers practical guidance for developers, designers, and policymakers in the development, design, and promotion of these systems.

Background: With an aging population and the continuous advancement of smart technology, the Chinese government is exploring smart elderly care models to address the challenges posed by aging. Although smart home systems are viewed as a promising solution, their adoption rate among older people remains low. Objectives: This study aimed to investigate the factors influencing the behavioral intention to use smart home systems among older people in Linyi City, Shandong Province, China. Methods: A literature review revealed a lack of quantitative research on older people’s behavioral intention toward smart home systems based on the Innovation Diffusion Theory. This study developed an extended model based on the Innovation Diffusion Theory, Technology Acceptance Model, and external variables, incorporating eight variables: intergenerational technical support, perceived cost, self-reported health conditions, compatibility, observability, trialability, perceived usefulness, perceived ease of use, and behavioral intention. Results: Analysis of 387 valid questionnaires showed that compatibility and trialability significantly and positively affect perceived ease of use, while self-reported health conditions, perceived ease of use, and perceived usefulness have significant effects on behavioral intention. In addition, perceived cost had a negative influence on behavioral intention. Contributions/Significance: These findings highlight the importance of considering these factors in the design of smart home systems to improve user experience and provide valuable practical guidance to smart home system developers, R&D institutions, and policymakers.

China is experiencing rapid population aging and is actively promoting smart home–based eldercare. Smart homes offer a promising means of supporting older adults in aging in place. However, low adoption and limited sustained use constrain their potential benefits, thereby exacerbating social, economic, and healthcare burdens. This study examined factors influencing older adults’ continuance intention to use smart homes in Shandong Province, China, by integrating the Expectation–Confirmation Model of Information Systems and the Technology Acceptance Model and incorporating China-specific contextual antecedents, including government policy, intergenerational technical support, compatibility, and cost. Data were collected using an online questionnaire survey of older adults aged 60 years and older with prior smart home experience (n = 421) and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results showed that perceived usefulness, perceived ease of use, satisfaction, and cost directly affected continuance intention, whereas government policy, compatibility, and intergenerational technical support influenced continuance intention through perceived usefulness, perceived ease of use, and confirmation. Based on these results, this study proposes a conceptual framework for understanding older adults’ continuance intention toward smart homes. The findings provide implications for inclusive policy, user-centered design, and family-supported digital aging in rapidly aging societies.