Xingyuan Wang
- Marketing top 5%
- Sociology and Political Science top 10%
- Economics and Econometrics top 10%
- Artificial Intelligence
- Management Science and Operations Research top 5%
- Co-authors
- Yun LiuFan JiaHongkai ZhaoYuanyuan LiuFuan LiHaipeng ChenQin SunRajiv Kashyap
- Topics
- Consumer Behavior in Brand Consumption and Identification (13 papers)Digital Marketing and Social Media (8 papers)AI in Service Interactions (5 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Xingyuan Wang
41 papers receiving 535 citations
Peers
Comparison fields: 5 of 105
- Marketing 187
- Sociology and Political Science 130
- Economics and Econometrics 101
- Artificial Intelligence 91
- Management Science and Operations Research 89
Countries citing papers authored by Xingyuan Wang
This map shows the geographic impact of Xingyuan Wang'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 Xingyuan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xingyuan Wang more than expected).
Fields of papers citing papers by Xingyuan Wang
This network shows the impact of papers produced by Xingyuan Wang. 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 Xingyuan Wang. The network helps show where Xingyuan Wang may publish in the future.
Co-authorship network of co-authors of Xingyuan Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Xingyuan Wang. A scholar is included among the top collaborators of Xingyuan Wang 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 Xingyuan Wang. Xingyuan Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 17 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 10 | |
| 7 | 32 | |
| 8 | 2 | |
| 9 | 8 | |
| 10 | 21 | |
| 11 | 4 | |
| 12 | 84 | |
| 13 | 43 | |
| 14 | 17 | |
| 15 | Research on Enterprise Marketing Risk Premonition based on BP Neural Network Optimized by Genetic Algorithm | 1 |
| 16 | An Empirical Study on the Relationship between the Brand Distribution and Regional Economic Development | 1 |
| 17 | Extended fractal L-systems and dynamic simulation of the scenery | 1 |
| 18 | 1 | |
| 19 | Research on the Measurement and Evaluation Methods for the Brand-niche | 0 |
| 20 | The Cause-results Analysis for Importance-Possibility(IPCA) and It's Applications | 0 |
About Xingyuan Wang
Xingyuan Wang is a scholar working on Marketing, Information Systems and Management and Medical Laboratory Technology, having authored 45 papers that have together received 549 indexed citations. Recurring topics across this work include Consumer Behavior in Brand Consumption and Identification (13 papers), Digital Marketing and Social Media (8 papers) and AI in Service Interactions (5 papers). The work is most often cited by research in Marketing (187 citations), Information Systems and Management (54 citations) and Management Science and Operations Research (89 citations). Xingyuan Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yun Liu, Fan Jia, Hongkai Zhao, Yuanyuan Liu, Fuan Li, Haipeng Chen, Qin Sun, Rajiv Kashyap, Zhilin Yang and Hongchen Liu. Their work appears in journals such as Journal of Cleaner Production, Journal of Business Research and Expert Systems with Applications.
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.