Xueqian Yao

Ms. Xueqian Yao


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

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

Representative Publications

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24 January 2025 in Sustainability
Verified
Journal Article
Open access
PDF file
JZJinyu Zhao
Jinyu Zhao
LZLu Zhao
Lu Zhao
YXYinghui Xu
Yinghui Xu
XYXueqian Yao
Xueqian Yao
Exploring pathways for sustainable synergistic development is a challenging issue for the construction industry, which is currently in a critical period of transformation. Current research has confirmed that industrial clusters are an important organizational form for promoting sustainable synergistic development. However, the existing research on construction industry clusters has overly focused on cluster attribute analysis and evaluation. Investigating the core mechanisms of synergistic development within construction industry clusters is particularly crucial. From the perspectives of ecological and synergetic theories, this paper constructs the ecosystem of the construction industry cluster and analyzes its synergistic development process. It identifies the driving factors of the synergistic development of the construction industry cluster and uses the ISM model to determine the structural hierarchical relationships among factors. Taking Shandong Province as the data sample, this study employs the Haken model to conduct an empirical investigation of the level of synergy and its driving mechanisms, establishing a three-stage framework for the driving mechanisms. The results show the following results: (1) Operating efficiency and innovation ability are the top factors to promote the synergistic development of the construction industry. (2) Market demand, as an order parameter, is an important condition for triggering and amplifying fluctuations in the construction industry cluster system, and it acts as a controlling factor to promote the system’s self-organization evolution to a new ordered and stable state. (3) The construction industry cluster in Shandong Province is in the initial stage of low synergy and is gradually evolving to moderate synergy. From a new research perspective, this study helps construction industry planners and policymakers understand the mechanisms of evolution and key driving factors of construction industry clusters.

14 June 2026 in Buildings
Verified
Journal Article
Open access
PDF file
JZJinyu Zhao
Jinyu Zhao
XYXueqian Yao
Xueqian Yao
LZLu Zhao
Lu Zhao
Against the background of profound transformation within the construction industry, the construction industry ecosystem serves as a vital vehicle for regional economic development. Its resilience has become a key factor in influencing the sustainable development of industry. From an ecological perspective, this paper integrated the cusp catastrophe model and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method, using data from Shandong Province to investigate the evolutionary state of the construction industry ecosystem and the diverse concurrent paths driving the system toward high levels of functionality. This study found that: (1) the resilient development of the construction industry ecosystem in Shandong Province presented a differentiated pattern, characterized by dual-core leadership, relative strength in the east, and weakness in the west, and localized catch-up. (2) The results from the cusp catastrophe model indicated that construction industry ecosystems in different regions were primarily undergoing stable evolution, though some cities faced the risk of functional degradation due to the combined effects of insufficient resilience and severe shocks. (3) fsQCA identified three equivalent configuration paths for achieving high system functionality: the “resilience accumulation path”, “resilience synergy path”, and “resilience transition path”, as well as three equivalent configuration paths for low system functionality: the “low resilience-low shocks dependency path”, “low-resilience, fixed-type path”, and “low resilience-high shocks imbalance path”. (4) These paths demonstrated that recovery was the key factor determining a system’s level of functionality.