Jia Xin Xiao

Dr. Jia Xin Xiao


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 May 2024 in Heliyon
Verified
Journal Article
Open access
JXJia Xin Xiao
Jia Xin Xiao
JLJieying Liao
Jieying Liao
BZBi Zhao
Bi Zhao
YLYiLan Long
YiLan Long
XXXuan Xu
Xuan Xu
TXTiansheng Xia
Tiansheng Xia
Community parks in old urban areas have problems such as outdated facilities and low quality, which inhibit the development of healthy aging. However, limited research has examined the correlation between such park characteristics and park satisfaction among elderly individuals. Additionally, the mechanisms underlying this association remain unclear. In this investigation, a moderated mediation framework grounded in self-determination theory was formulated to probe the interplay between these variables, with a specific focus on the mediating influence of social self-efficacy among the elderly and the moderating effect of use intention. A questionnaire survey (N = 319) was conducted in Shamian Park, Guangzhou, employing structural equation modeling for data analysis. Findings indicate that, even after controlling for demographic factors, park characteristics not only exert a direct influence on satisfaction but also exhibit an indirect impact through the mediation of social self-efficacy, with both pathways being moderated by use intention. This study has implications for how to improve the design of community parks in old urban areas in developing countries to better meet the basic needs of the elderly and promote healthy aging.

17 April 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
XZXiaochen ZHANG
Xiaochen ZHANG
LXLiu Xinyu
Liu Xinyu
YZYang Zhang
Yang Zhang
XXXing Xu
Xing Xu
JXJia Xin Xiao
Jia Xin Xiao
DLDing-Bang Luh
Ding-Bang Luh
This paper delves into the feasibility of implementing Cradle to Cradle (C2C) principles in conceptual product design to achieve sustainability objectives. By developing two concept products and conducting a series of qualitative and quantitative experiments, this research demonstrates the potential of the C2C approach as a crucial guide in the design process and emphasizes its significance in creating environmentally and socially responsible products. Nevertheless, this study also highlights the challenges and limitations associated with the practical application of C2C theory and the attainment of optimal product performance. These findings underline the importance of integrating C2C principles into conceptual product design and call for further research to address the limitations of the theory and optimize its application in sustainable design. Overall, this research contributes to the growing body of literature on sustainable design and provides valuable insights into the potential benefits and challenges of adopting the C2C approach in conceptual product design.

1 July 2021 in Waste Management
Verified
Journal Article
Closed access
JXJia Xin Xiao
Jia Xin Xiao
MLMing Jun Luo
Ming Jun Luo
WLWenhua Li
Wenhua Li

30 September 2025 in Applied Sciences
Verified
Journal Article
Open access
PDF file
JXJia Xin Xiao
Jia Xin Xiao
DPDuohui Pan
Duohui Pan
RGRuining Gong
Ruining Gong
TXTiansheng Xia
Tiansheng Xia
XZXiaochen ZHANG
Xiaochen ZHANG
DYDan Yao
Dan Yao
AI chatbots have the potential to facilitate students’ academic progress and enhance knowledge accessibility in higher education, yet learners’ attitudes toward these technologies vary amid AI-driven disruptions, with factors influencing acceptance remaining debated. The current study constructs an integrated model based on Technology Acceptance Model 3 (TAM3), an extension of the original TAM, incorporating factors including Self-Efficacy, Perceived Enjoyment, Anxiety, Perceived Ease of Use, Perceived Usefulness, Output Quality, Social Influence, and Behavioral Intention, to explore determinants and mechanisms influencing learners’ acceptance of AI chatbots. This addresses key challenges in AI-augmented learning, such as personalization benefits versus risks like information inaccuracy and ethical concerns. Results from the questionnaire survey analysis with 265 valid responses reveal significant relationships: (1) self-efficacy significantly predicts perceived ease of use; (2) both perceived enjoyment and perceived ease of use positively influence perceived usefulness; and (3) self-efficacy, perceived usefulness, and social influence collectively exert significant effects on behavioral intention. Measurement invariance tests further indicate significant differences in acceptance between undergraduate and graduate students, suggesting academic level moderates behavioral intentions. Findings offer principled guidance for designing inclusive AI tools that mitigate accessibility barriers and promote equitable adoption in educational environments.

31 May 2025
Verified
Book Chapter
Closed access
PDF file
BZBoyu Zhang
Boyu Zhang
LZLi Zhang
Li Zhang
JXJia Xin Xiao
Jia Xin Xiao