Jing–Rong Chang
- Management Science and Operations Research top 1%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Statistics and Probability top 2%
- Statistics, Probability and Uncertainty top 2%
- Co-authors
- Ching‐Hsue ChengMing‐Hung ShuLong‐Sheng ChenLiang‐Ying WeiKuei‐Hu ChangShu-Hsien LiaoYing-Chieh TsaiMu‐Yen Chen
- Topics
- Multi-Criteria Decision Making (12 papers)Stock Market Forecasting Methods (6 papers)Fuzzy Logic and Control Systems (6 papers)
- Cited by
- Management Science and Operations ResearchStatistics and ProbabilityStatistics, Probability and Uncertainty
- Partner nations
- Taiwan
In The Last Decade
Jing–Rong Chang
31 papers receiving 912 citations
Peers
Comparison fields: 5 of 93
- Management Science and Operations Research 629
- Artificial Intelligence 237
- Control and Systems Engineering 210
- Statistics and Probability 180
- Statistics, Probability and Uncertainty 126
Countries citing papers authored by Jing–Rong Chang
This map shows the geographic impact of Jing–Rong Chang'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 Jing–Rong Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing–Rong Chang more than expected).
Fields of papers citing papers by Jing–Rong Chang
This network shows the impact of papers produced by Jing–Rong Chang. 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 Jing–Rong Chang. The network helps show where Jing–Rong Chang may publish in the future.
Co-authorship network of co-authors of Jing–Rong Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Jing–Rong Chang. A scholar is included among the top collaborators of Jing–Rong Chang 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 Jing–Rong Chang. Jing–Rong Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 11 | |
| 3 | 3 | |
| 4 | 10 | |
| 5 | 5 | |
| 6 | 8 | |
| 7 | 18 | |
| 8 | 1 | |
| 9 | 34 | |
| 10 | 2 | |
| 11 | 8 | |
| 12 | 4 | |
| 13 | 8 | |
| 14 | 35 | |
| 15 | 335 | |
| 16 | 8 | |
| 17 | 64 | |
| 18 | 38 | |
| 19 | 23 | |
| 20 | 8 |
About Jing–Rong Chang
Jing–Rong Chang is a scholar working on Management Science and Operations Research, Software and Artificial Intelligence, having authored 32 papers that have together received 962 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (12 papers), Stock Market Forecasting Methods (6 papers) and Fuzzy Logic and Control Systems (6 papers). The work is most often cited by research in Management Science and Operations Research (629 citations), Statistics and Probability (180 citations) and Statistics, Probability and Uncertainty (126 citations). Jing–Rong Chang has collaborated with scholars based in Taiwan. Frequent co-authors include Ching‐Hsue Cheng, Ming‐Hung Shu, Long‐Sheng Chen, Liang‐Ying Wei, Kuei‐Hu Chang, Shu-Hsien Liao, Ying-Chieh Tsai, Mu‐Yen Chen, Chia‐Wei Chang and Pei‐Yu Yu. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Technological Forecasting and Social Change.
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.