Contemporarily, almost all the global IT giants have aimed at the smart home industry and made an active strategic business layout. As the early-stage and entry-level product of the voice-enabled smart home industry, the smart speakers have been going through rapid development and rising fierce market competition globally in recent years. China, one of the most populous and largest markets in the world, has tremendous business potential in the smart home industry. The market sales of smart speakers in China have gone through rapid growth in the past three years. However, the market penetration rate of related smart home devices and equipment still stays extremely low and far from mass adoption. Moreover, the market sales of smart speakers have also entered a significant slowdown and adjustment period since 2020. Chinese consumers have moved from early impulsive consumption to a rational consumption phase about this early-stage smart home product. Trust in the marketing field is considered an indispensable component of all business transactions, which plays a crucial role in adopting new technologies. This study explores the influencing factors of Chinese users’ perceived trust in the voice-enabled smart home systems, uses structural equation modeling (SEM) to analyze the interaction mechanism between different variables, and establishes a perceived trust model through 475 valid samples. The model includes six variables: system quality, familiarity, subjective norm, technology optimism, perceived enjoyment, and perceived trust. The result shows that system quality is the essential influence factor that impacts all other variables and could significantly affect the perceived trust. Perceived enjoyment is the most direct influence variable affected by system quality, subjective norm, and technology optimism, and it positively affects the perceived trust in the end. The subjective norm is one of the most distinguishing variables for Chinese users, since China has a collectivist consumption culture. People always expect their behavior to meet social expectations and standards to avoid criticism and acquire social integration. Therefore, policy guidance, authoritative opinions, and people with important reference roles will significantly affect consumers’ perceived trust and purchase intention. Familiarity and technology optimism are important influential factors that will have an indirect impact on the perceived trust. The related results of this study can help designers, practitioners, and researchers of the smart home industry produce products and services with higher perceived trust to improve consumers’ adoption and acceptance so that the market penetration rate of related products and enterprises could be increased, and the maturity and development of the voice-enabled smart home industry could be promoted.

Background: An infectious disease can affect human beings at an alarming speed in modern society, where Coronavirus Disease 2019 (COVID-19) has led to a worldwide pandemic, posing grave threats to public security and the social economies. However, as one of the closest attachments of urban dwellers, urban furniture hardly contributes to pandemic prevention and control. Methods: Given this critical challenge, this article aims to propose a feasible solution to coping with pandemic situations through urban furniture design, using an integrated method of Quality Function Deployment (QFD) and Analytic Network Process (ANP). Eight communities in China are selected as the research sites, since people working and living in these places have successful experience preventing and containing pandemics. Results: Three user requirements (URs), namely, usability and easy access, sanitation, and health and emotional pleasure, are determined. Meanwhile, seven design requirements (DRs) are identified, including contact reduction, effective disinfection, good appearance, social and cultural symbols, ergonomics, smart system and technology and sustainability. The overall priorities of URs and DRs and their inner dependencies are subsequently determined through the ANP-QFD method, comprising the House of Quality (HQQ). According to the theoretical results, we propose five design strategies for pandemic prevention and control. Conclusion: It is demonstrated that the incorporated method of ANP-QFD has applicability and effectiveness in the conceptual product design process. This article can also provide a new perspective for pandemic prevention and control in densely populated communities in terms of product design and development.

The emergence of AI companion robots is transforming the landscape of elderly care, offering numerous conveniences to senior citizens when their children are not around. This trend is particularly pertinent in ageing societies such as China. Against this backdrop, the present study aims to explore the acceptance of AI companion robots among the elderly from a user-centric perspective. By leveraging insights from existing studies in the literature, we identified three individual characteristic variables—technology optimism, innovativeness, and familiarity—to extend the Artificial Intelligence Device Use Acceptance (AIDUA) model. Subsequently, we developed a conceptual model which was empirically tested through structural equation modelling (SEM) analysis. Our dataset comprised responses from 452 elderly individuals in China. The results revealed that technology optimism and innovativeness were positively associated with performance expectancy and effort expectancy, whereas familiarity inversely predicted perceived risk. Furthermore, emotion was found to be positively influenced by performance expectancy and effort expectancy but negatively impacted by perceived risk. This research extends the AIDUA model within the context of AI companion robots by integrating individual characteristic variables. These findings offer valuable insights for the design and development of companion robots and enrich the domain of Human–Robot Interaction (HRI).

Voice-based digital assistants are growing in popularity and have been acknowledged as a crucial part of in-car interaction. Currently, academic attention is being paid to various voice assistant scenarios. However, sparse literature focuses on the adoption of voice assistants within the in-vehicle context. The objective of this paper is to examine key factors influencing people’s willingness to use voice assistance in electric cars. First, eight general variables were identified based on the literature review, as well as four demographic variables. These factors were then integrated to construct a hypothetical research model. After that, we carried out an empirical study to examine the structural relationships in the model based on the questionnaire survey results (N = 427). The hypothesis testing results indicated that most path relationships among variables were validated. Finally, we discussed the research findings and developed corresponding design strategies to enhance user acceptance towards in-car voice assistants, both from designers’ and car enterprises’ viewpoints. This article offers valuable theoretical and practical implications for the development of such technologies.

A thriving electric vehicles (EVs) market serves as a pivotal embodiment of the global push towards sustainable mobility. As one of the leading global EV sellers, China owns a huge used EV market, which should be spotlighted. While most studies focus on the mechanism of new EV purchases, few put their insight into the trade of used EVs. To fill this gap, this paper aims to clarify the mechanism of consumption behaviour towards used EVs. First, we identified 11 variables that have a direct or indirect impact on consumers’ purchase intention and constructed a conceptual framework. Then, we checked the structural relationships of the model through an empirical study (n = 431). The results showed that purchase intention was determined by two variables: perceived risk and attitude. We also observed an association between income and purchase intention. Functional risk had a direct and significant impact on perceived risk. Economic value, brand trust, and after-sales service were crucial predictors of attitude. Education could moderate the relationship between attitudes and purchase intention. Based on theoretical findings, we present the design strategies to enhance consumers’ purchase willingness from car companies’ and policymakers’ viewpoints. In practical situations, this article offers valuable insights for stakeholders related to the used EV industry, providing a critical reference for advancing sustainable mobility.

Preventive behavior, such as hand hygiene, facemask wearing, and social distancing, plays a vital role in containing the spread of viruses during pandemics. However, people in many parts of the world usually encounter difficulties adhering to this behavior due to various causes. Thus, this article aims to develop a research framework and propose design strategies to prompt individuals’ behavior change during pandemics. Initially, we integrated a literature review and a structured interview (n = 22) to ascertain the core factors impacting behavior change during pandemics. These factors were categorized into four aspects: perceptional factors (attitudes, subjective norms and perceived behavior control, risk perceptions); social factors (knowledge and information dissemination, governmental regulations); physical factors (tools and facilities and surveillance); and sociocultural factor (cultural contexts). Then, a theoretical framework with antecedents was developed to reveal behavior intention and formation process. After that, an empirical study was carried out to test the research framework through a questionnaire survey (n = 549). The research findings indicated that all derived factors could directly or indirectly affect individuals’ preventive behavior during pandemics. This article strives to provide valuable insights for different stakeholders when coping with pandemic situations.