System Dynamics Modeling of the Evolutionary Pathway in Building Decoration Industry Empowered by Artificial Intelligence*

This study focuses on the evolutionary path of the architectural decoration industry empowered by artificial intelligence (AI). A system dynamics model is constructed, integrating key modules such as technology adoption, enterprise behavior, policy incentives, talent supply and demand, and market feedback. By setting baseline, optimistic, and pessimistic future scenarios, multiple rounds of simulation are conducted to explore how critical variables affect industrial efficiency and structural transformation. Results reveal a three-phase evolution under AI empowerment: tool substitution, process restructuring, and ecosystem reshaping. Policy incentives and the degree of design modularity significantly influence the speed of AI diffusion. Based on the findings, this paper proposes policy recommendations including the establishment of an AI design tool certification system and a dedicated fund to support intelligent transformation, offering theoretical support and decision-making references for the industry’s smart upgrading.

Authors

Institutions

Publication Details

Published
2025-08-08
DOI
https://doi.org/10.1109/iaeac65194.2025.11165839
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

System Dynamics Modeling of the Evolutionary Pathway in Building Decoration Industry Empowered by Artificial Intelligence*

Caitong Yue, Zhixian Xie
BIM and Construction Integration
article

System Dynamics Modeling of the Evolutionary Pathway in Building Decoration Industry Empowered by Artificial Intelligence*

Caitong Yue, Zhixian Xie
article en

Abstract

This study focuses on the evolutionary path of the architectural decoration industry empowered by artificial intelligence (AI). A system dynamics model is constructed, integrating key modules such as technology adoption, enterprise behavior, policy incentives, talent supply and demand, and market feedback. By setting baseline, optimistic, and pessimistic future scenarios, multiple rounds of simulation are conducted to explore how critical variables affect industrial efficiency and structural transformation. Results reveal a three-phase evolution under AI empowerment: tool substitution, process restructuring, and ecosystem reshaping. Policy incentives and the degree of design modularity significantly influence the speed of AI diffusion. Based on the findings, this paper proposes policy recommendations including the establishment of an AI design tool certification system and a dedicated fund to support intelligent transformation, offering theoretical support and decision-making references for the industry’s smart upgrading.

Guangzhou Academy of Special Equipment Inspection and Testing (CN)
Openalex Percentile: Top 72%
BIM and Construction Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.