JQ Xiao

Dr. JQ Xiao


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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28 September 2025 in Systems
Verified
Journal Article
Open access
PDF file
GSGuangfan Sun
Guangfan Sun
XHXueqin Hu
Xueqin Hu
XCXiaoya Chen
Xiaoya Chen
JXJQ Xiao
JQ Xiao
Supply chain financing offers advantages over traditional channels such as bank loans and equity financing, including greater flexibility, lower transaction costs, and simplified approval procedures. However, when a firm’s sustainability faces uncertainty, access to supply chain financing may become constrained by multiple factors, including the risk tolerance of supply chain partners, market transparency, and corporate reputation. ESG, representing Environmental, Social, and Governance standards, is a critical framework for assessing corporate sustainability performance. Given that divergent ESG evaluations reflect disparate market assessments of a firm’s sustainable development capabilities, such divergence may affect supply chain financing by altering stakeholder trust dynamics. This research examines A-share listed firms in China (2016–2022) and reveals that divergence in ESG evaluations significantly inhibits firms’ access to supply chain financing. Mechanism validation suggests that divergent ESG evaluations amplify informational opacity, operational risks, and negative reputation, thereby influencing supply chain partners’ risk perceptions and trust levels. Heterogeneity analysis shows that corporate governance quality, regional trust levels, and ESG awareness modulate the negative impact of divergent ESG evaluations on supply chain financing. The asymmetric effects of divergent ESG evaluations on supply chain financing are further confirmed, with distinct manifestations between upstream suppliers and downstream customers. By bridging gaps in existing research on divergent ESG evaluations and supply chain finance, this work offers regulatory guidelines, operational recommendations for firms, and investment decision frameworks.

26 April 2026 in Sustainability
Verified
Journal Article
Open access
PDF file
GSGuangfan Sun
Guangfan Sun
YSYue Song
Yue Song
JXJQ Xiao
JQ Xiao
DXDaosheng Xu
Daosheng Xu
In the pursuit of global industrial sustainable development and carbon neutrality goals, the aviation manufacturing sector serves as a strategic pillar for advancing global economic growth, driving technological innovation and enhancing national competitiveness. Its green innovation has thus become a critical pathway to achieving carbon neutrality targets and spearheading the sustainable transformation of the industrial sector. This study investigates the enabling effect of artificial intelligence (AI) on green innovation within aviation manufacturing enterprises. The findings indicate that AI exerts a promotional impact on green innovation via three primary channels: technological empowerment, labor structure optimization and resource access improvement. Specifically, AI drives the digital transformation of operational processes in aviation manufacturing, rationalizes the human resource framework of the sector, and eases the financing pressures confronted by aviation manufacturing enterprises. A heterogeneity analysis reveals that regional resource endowments, enterprise production attribute characteristics and external market attention can form synergistic interactions with AI technology. What is more prominent is that the positive influence of AI on green innovation is especially distinct in three scenarios: in economically developed urban areas, among enterprises with traditional production attributes, and for enterprises that garner high levels of analyst attention.