Journal of Information Systems Engineering and Management

Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration
Lian Wang 1, Chanoknart Mayusoh 2 * , Akapong Inkuer 3
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1 Doctoral Student of Philosophy Program in Visual Arts and Design, Faculty of Fine and Applied Arts, Suan Sunandha Rajabhat University, Bangkok, Thailand
2 Assistant Professor, Advisor in Visual Arts and Design, Faculty of Fine and Applied Arts, Suan Sunandha Rajabhat University, Bangkok, Thailand
3 Assistant Professor, Visual Arts and Design, Faculty of Fine and Applied Arts Suan Sunandha Rajabhat University, Bangkok, Thailand
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2024 - Volume 9 Issue 2, Article No: 23945
https://doi.org/10.55267/iadt.07.14748

Published Online: 24 Apr 2024

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How to cite this article
APA 6th edition
In-text citation: (Wang et al., 2024)
Reference: Wang, L., Mayusoh, C., & Inkuer, A. (2024). Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration. Journal of Information Systems Engineering and Management, 9(2), 23945. https://doi.org/10.55267/iadt.07.14748
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Wang L, Mayusoh C, Inkuer A. Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration. J INFORM SYSTEMS ENG. 2024;9(2):23945. https://doi.org/10.55267/iadt.07.14748
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Wang L, Mayusoh C, Inkuer A. Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration. J INFORM SYSTEMS ENG. 2024;9(2), 23945. https://doi.org/10.55267/iadt.07.14748
Chicago
In-text citation: (Wang et al., 2024)
Reference: Wang, Lian, Chanoknart Mayusoh, and Akapong Inkuer. "Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration". Journal of Information Systems Engineering and Management 2024 9 no. 2 (2024): 23945. https://doi.org/10.55267/iadt.07.14748
Harvard
In-text citation: (Wang et al., 2024)
Reference: Wang, L., Mayusoh, C., and Inkuer, A. (2024). Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration. Journal of Information Systems Engineering and Management, 9(2), 23945. https://doi.org/10.55267/iadt.07.14748
MLA
In-text citation: (Wang et al., 2024)
Reference: Wang, Lian et al. "Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration". Journal of Information Systems Engineering and Management, vol. 9, no. 2, 2024, 23945. https://doi.org/10.55267/iadt.07.14748
ABSTRACT
Big Data usage and Artificial Intelligence (AI) technology combined offer a potential approach to solving challenging problems. AI-driven solutions provide insightful analysis and creative solutions by utilizing the power of big data analytics. With an emphasis on the mediating role of technological literacy and the moderating effect of resource availability, this study investigates the effects of low-cost techniques, the usage of Big Data, and the integration of Artificial Intelligence (AI) on sustainability in landscape design. The purpose of this study is to look at the intricate connections between these factors and how they affect sustainable landscape design methods and results as a whole. A standardized questionnaire was answered by a sample of 458 landscape experts as part of a quantitative approach. Smart PLS (Partial Least Squares), which incorporates evaluations of measurement models, structural models, and mediation and moderation studies, was utilized for data analysis. The study found that using Big Data, implementing low-cost techniques, and incorporating AI all had very favourable effects on sustainability in landscape design. The efficient use of Big Data and AI was found to be mediated by technological literacy, highlighting the importance of this concept in this context. Additionally, resource availability emerged as a critical moderating factor, influencing the strength of these relationships. This research contributes to the field by offering a holistic understanding of the dynamics within sustainable landscape design, emphasizing the importance of integration of AI and utilization of Big Data. It provides practical insights for landscape professionals, informs policy development, and advances educational curricula about AI and Big Data in landscape architecture. The study's limitations include potential response bias due to self-reported data and the cross-sectional design, which restricts the establishment of causal relationships. Additionally, the study focused on professionals, limiting the generalizability of findings to broader community perspectives.
KEYWORDS
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