Yu Gong

4.7k total citations · 2 hit papers
119 papers, 3.3k citations indexed

About

Yu Gong is a scholar working on Strategy and Management, Marketing and Management Information Systems. According to data from OpenAlex, Yu Gong has authored 119 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Strategy and Management, 21 papers in Marketing and 19 papers in Management Information Systems. Recurrent topics in Yu Gong's work include Sustainable Supply Chain Management (48 papers), Environmental Sustainability in Business (20 papers) and Supply Chain Resilience and Risk Management (16 papers). Yu Gong is often cited by papers focused on Sustainable Supply Chain Management (48 papers), Environmental Sustainability in Business (20 papers) and Supply Chain Resilience and Risk Management (16 papers). Yu Gong collaborates with scholars based in China, United Kingdom and Australia. Yu Gong's co-authors include Fu Jia, Steve Brown, Xiangfeng Chen, Yifan Xu, Changping Zhao, Steve Brown, Jiang Duan, Zhi Li, Chen Zhang and Lenny Koh and has published in prestigious journals such as Journal of Cleaner Production, IEEE Transactions on Power Systems and IEEE Access.

In The Last Decade

Yu Gong

113 papers receiving 3.2k citations

Hit Papers

Supply chain finance: A systematic literature review and ... 2018 2026 2020 2023 2018 2020 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yu Gong China 30 1.8k 781 728 479 363 119 3.3k
V. G. Venkatesh France 27 1.8k 1.0× 721 0.9× 781 1.1× 467 1.0× 479 1.3× 92 3.2k
Bhaskar B. Gardas India 32 1.7k 0.9× 921 1.2× 668 0.9× 331 0.7× 524 1.4× 87 3.4k
Nishikant Mishra United Kingdom 28 1.9k 1.1× 948 1.2× 682 0.9× 210 0.4× 624 1.7× 78 3.3k
Manu Sharma India 30 1.4k 0.8× 574 0.7× 425 0.6× 259 0.5× 398 1.1× 103 2.8k
Piera Centobelli Italy 39 2.7k 1.5× 942 1.2× 1.4k 1.9× 617 1.3× 707 1.9× 107 5.2k
Manoj Dora United Kingdom 32 2.3k 1.3× 1.3k 1.7× 673 0.9× 478 1.0× 687 1.9× 75 4.0k
Arvind Upadhyay United Kingdom 26 2.0k 1.1× 648 0.8× 999 1.4× 306 0.6× 571 1.6× 64 3.0k
Andrea Appolloni Italy 34 2.1k 1.2× 521 0.7× 1.1k 1.5× 232 0.5× 294 0.8× 132 3.8k
Qingyun Zhu United States 22 1.5k 0.8× 508 0.7× 894 1.2× 575 1.2× 304 0.8× 47 2.5k
Pankaj Dutta India 28 1.5k 0.8× 1.1k 1.5× 317 0.4× 726 1.5× 336 0.9× 67 3.0k

Countries citing papers authored by Yu Gong

Since Specialization
Citations

This map shows the geographic impact of Yu Gong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yu Gong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Gong more than expected).

Fields of papers citing papers by Yu Gong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu Gong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yu Gong. The network helps show where Yu Gong may publish in the future.

Co-authorship network of co-authors of Yu Gong

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Gong. A scholar is included among the top collaborators of Yu Gong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yu Gong. Yu Gong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shi, Yangyan, Xiangdong Li, Yu Gong, et al.. (2025). Carbon trade finance: a perspective of supply chain management. International Journal of Production Research. 63(22). 8125–8127.
2.
Dai, J. P., et al.. (2025). Temperature-Adaptive TRNG-Encrypted MRAM PUF: Enhancing Resistance to Machine Learning Attacks. IEEE Transactions on Magnetics. 61(5). 1–8. 1 indexed citations
3.
Yan, Ji, et al.. (2025). How does blockchain application impact on supply chain alliance?. Technovation. 143. 103199–103199. 3 indexed citations
4.
Gu, Bingmei, et al.. (2024). Data-driven approach for port resilience evaluation. Transportation Research Part E Logistics and Transportation Review. 186. 103570–103570. 26 indexed citations
5.
Wang, Yuyan, et al.. (2024). Does blockchain technology need to be introduced in the closed-loop supply chain based on product lifecycle management?. Computers & Industrial Engineering. 188. 109881–109881. 12 indexed citations
6.
Gong, Yu, et al.. (2024). Multi-Tier Supply Chain Learning Networks: A Simulation Study Based on the Experience-Weighted Attraction (EWA) Model. Sustainability. 16(10). 4085–4085. 1 indexed citations
7.
Gong, Yu, et al.. (2024). Examining Strategies Developed by Insurance Companies for Addressing Carbon Emissions in the Automotive Supply Chain in the UK. Sustainability. 16(22). 9895–9895. 1 indexed citations
8.
Gong, Yu, et al.. (2024). Waste Cooking Oil Recycling and the Potential Use of Blockchain Technology in the UK. Sustainability. 16(14). 6197–6197. 4 indexed citations
9.
Mahdiraji, Hannan Amoozad, et al.. (2024). Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework: Evidence from an emerging economy. Transportation Research Part A Policy and Practice. 186. 104151–104151. 5 indexed citations
10.
Gong, Yu, Tao Chen, S. Wang, Shukai Duan, & Lidan Wang. (2023). Lightweight spiking neural network training based on spike timing dependent backpropagation. Neurocomputing. 570. 127059–127059. 5 indexed citations
11.
Zhang, Abraham, et al.. (2023). Barriers to compulsory waste sorting for a circular economy in China. Journal of Environmental Management. 342. 118180–118180. 25 indexed citations
13.
Gong, Yu, et al.. (2023). From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges. International Journal of Operations & Production Management. 43(8). 1177–1194. 17 indexed citations
14.
Jamalnia, Aboozar, Yu Gong, Kannan Govindan, Michael Bourlakis, & Sachin Kumar Mangla. (2023). A decision support system for selection and risk management of sustainability governance approaches in multi-tier supply chain. International Journal of Production Economics. 264. 108960–108960. 13 indexed citations
15.
Gong, Yu, Tianyu Zhang, Peiwu Dong, Xiangfeng Chen, & Yangyan Shi. (2022). Innovation adoption of blockchain technology in supply chain finance. Production Planning & Control. 35(9). 992–1008. 21 indexed citations
16.
Gong, Yu, et al.. (2022). The application of blockchain technology in the recycling chain: a state-of-the-art literature review and conceptual framework. International Journal of Production Research. 61(24). 8692–8718. 29 indexed citations
17.
Wang, Liukai, et al.. (2022). Director's network location and corporate environmental investment in the carbon neutrality age. Business Strategy and the Environment. 32(6). 3178–3196. 16 indexed citations
18.
Zhao, Changping, et al.. (2021). The Evolutionary Trend and Impact of Global Plastic Waste Trade Network. Sustainability. 13(7). 3662–3662. 50 indexed citations
19.
Xu, Xin, Yingying Hou, Changping Zhao, Лей Ши, & Yu Gong. (2021). Research on cooperation mechanism of marine plastic waste management based on complex network evolutionary game. Marine Policy. 134. 104774–104774. 31 indexed citations
20.
Gong, Yu, et al.. (2020). A SWOT Analysis of the UK EV Battery Supply Chain. Sustainability. 12(23). 9807–9807. 14 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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