Yuanxin Jia

Dr. Yuanxin Jia

orcid

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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30 May 2025 in Applied System Innovation
Verified
Journal Article
Open access
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JZJiong Zhou
Jiong Zhou
YJYuanxin Jia
Yuanxin Jia
YYYixin Yang
Yixin Yang
Wenbing ZhaoWenbing Zhao
Wenbing Zhao
Innovation-driven development is the main driving strategy for promoting high-quality economic development. Technological innovation is the core of innovation-driven development. Financial innovation is an important aspect of promoting financial development. As such, the coupling and coordination of the technological innovation and financial development in developing countries, such as China, is an important issue. The topic has been extensively studied over the last decade in the context of China, and a dominating method has emerged on how to model the technological innovation subsystem and the financial development subsystem, and how to quantitatively determine the degree of coupling and coordination of the two subsystems. A variety of predictors have been proposed to model each subsystem. The coupling degree and the coordination degree are then calculated, and then they are used to analyze the current development status for potential issues. However, we make an effort to validate the calculated degree of coupling and coordination before the results are used for the analysis.Without validation, the outcomes of the analysis not only might not be useful but also could lead to inappropriate governmental policies. That said, it is tremendously challenging to validate the results due to the lack of the ground truth. The goal of this study is to work towards objectively determining the reliability of the degree of coupling and coordination from an engineering perspective. Specifically, we accomplish this task by evaluating the regression performance and projection performance. We demonstrate that the use of a carefully crafted set of predictors for each subsystem is the foundation for deriving the reliable coordination degree of the two subsystems.