Yung‐ho Chiu

5.6k total citations
258 papers, 4.3k citations indexed

About

Yung‐ho Chiu is a scholar working on Economics and Econometrics, Management Science and Operations Research and Environmental Engineering. According to data from OpenAlex, Yung‐ho Chiu has authored 258 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 185 papers in Economics and Econometrics, 160 papers in Management Science and Operations Research and 97 papers in Environmental Engineering. Recurrent topics in Yung‐ho Chiu's work include Efficiency Analysis Using DEA (156 papers), Energy, Environment, Economic Growth (113 papers) and Environmental Impact and Sustainability (96 papers). Yung‐ho Chiu is often cited by papers focused on Efficiency Analysis Using DEA (156 papers), Energy, Environment, Economic Growth (113 papers) and Environmental Impact and Sustainability (96 papers). Yung‐ho Chiu collaborates with scholars based in Taiwan, China and Netherlands. Yung‐ho Chiu's co-authors include Tai‐Yu Lin, Chin-Wei Huang, Yuchuan Chen, Ching‐Ren Chiu, Tzu‐Han Chang, Jin‐Li Hu, Qunwei Wang, Ching‐Cheng Lu, Yang Li and Ying Li and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, The Science of The Total Environment and Journal of Power Sources.

In The Last Decade

Yung‐ho Chiu

249 papers receiving 4.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yung‐ho Chiu Taiwan 34 2.4k 1.8k 1.3k 558 462 258 4.3k
Jin‐Li Hu Taiwan 35 4.1k 1.7× 2.6k 1.4× 2.2k 1.8× 389 0.7× 368 0.8× 222 6.8k
Zhongfei Chen China 39 3.1k 1.3× 640 0.4× 861 0.7× 480 0.9× 686 1.5× 135 5.5k
Jie Wu China 45 3.3k 1.4× 4.8k 2.7× 1.7k 1.3× 328 0.6× 132 0.3× 128 6.3k
Michael G. Pollitt United Kingdom 44 2.1k 0.9× 1.7k 1.0× 563 0.4× 396 0.7× 302 0.7× 166 6.3k
Miki Tsutsui Japan 10 1.9k 0.8× 2.1k 1.2× 702 0.6× 294 0.5× 114 0.2× 17 3.2k
Carl A. Pasurka United States 24 3.2k 1.3× 2.5k 1.4× 1.8k 1.4× 439 0.8× 221 0.5× 53 4.3k
Ana S. Camanho Portugal 32 1.5k 0.6× 2.5k 1.4× 291 0.2× 377 0.7× 248 0.5× 98 4.0k
Tooraj Jamasb United Kingdom 38 1.8k 0.7× 1.1k 0.6× 347 0.3× 334 0.6× 150 0.3× 135 4.8k
Jiahai Yuan China 43 3.2k 1.3× 590 0.3× 2.2k 1.7× 141 0.3× 119 0.3× 166 6.5k

Countries citing papers authored by Yung‐ho Chiu

Since Specialization
Citations

This map shows the geographic impact of Yung‐ho Chiu'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 Yung‐ho Chiu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yung‐ho Chiu more than expected).

Fields of papers citing papers by Yung‐ho Chiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yung‐ho Chiu. 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 Yung‐ho Chiu. The network helps show where Yung‐ho Chiu may publish in the future.

Co-authorship network of co-authors of Yung‐ho Chiu

This figure shows the co-authorship network connecting the top 25 collaborators of Yung‐ho Chiu. A scholar is included among the top collaborators of Yung‐ho Chiu 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 Yung‐ho Chiu. Yung‐ho Chiu 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.
Pang, Qinghua, et al.. (2025). How industrial agglomeration and technological innovation affect carbon emission efficiency: Evidence from China. Geoenergy Science and Engineering. 257. 214256–214256.
2.
3.
Zhang, Lina, et al.. (2024). Water-energy-food nexus efficiency and its factor analysis in China: A dynamic series-loop DDF model. Journal of Cleaner Production. 436. 140524–140524. 16 indexed citations
4.
Teng, Xiangyu, et al.. (2024). Policy choices for China to reduce carbon emissions in coping with extreme weather: Applying a dynamic two-stage undesirable non-radial directional distance function. The Science of The Total Environment. 939. 173590–173590. 3 indexed citations
5.
Pang, Qinghua, et al.. (2024). Congestion effects of energy and its influencing factors: China's transportation sector. Socio-Economic Planning Sciences. 92. 101850–101850. 6 indexed citations
6.
Pang, Qinghua, Xuan Liu, Lina Zhang, & Yung‐ho Chiu. (2024). Temporal-spatial evolution of environmental inequality of embodied energy transfer within inter-provincial trade of China. Energy. 299. 131476–131476. 8 indexed citations
7.
Sheng, Bin, et al.. (2024). Evaluating Bank Efficiency with Risk Management by Optimal Common Resource and Three-Parallel Two-Stage Dynamic DEA Model. Computational Economics. 65(6). 3545–3571. 1 indexed citations
8.
Fang, Zhong, Yung‐ho Chiu, Yiqin Chen, Tai‐Yu Lin, & Tzu‐Han Chang. (2024). Linkage analysis for water-energy-economic system efficiency in China. Environment Development and Sustainability. 27(6). 12745–12767.
9.
Chiu, Yung‐ho, et al.. (2024). Reassessment of industrial eco-efficiency in China under the sustainable development goals: A meta two-stage parallel entropy dynamic DDF-DEA model. Journal of Cleaner Production. 447. 141275–141275. 15 indexed citations
10.
11.
Fang, Zhong, et al.. (2023). ECONOMIC AND ENVIRONMENTAL EFFICIENCY OF JOINT R&D BETWEEN UNIVERSITIES AND FIRMS. Technological and Economic Development of Economy. 29(2). 591–617. 1 indexed citations
12.
Lin, Tai‐Yu, et al.. (2023). Non‐performance loans, operation, and recycle efficiency analysis—Dynamic Two‐stage Directional Distance Function Recycle with Assurance Regions model. Managerial and Decision Economics. 45(2). 952–974. 3 indexed citations
13.
Yang, Chih‐Yu, et al.. (2023). Evaluating the impact of agricultural production efficiency on sustainable development goals in coffee‐producing countries in Africa. Sustainable Development. 32(4). 3375–3388. 3 indexed citations
14.
Teng, Xiangyu, et al.. (2023). China's path of carbon neutralization to develop green energy and improve energy efficiency. Renewable Energy. 206. 397–408. 35 indexed citations
15.
Lu, Yung-Hsiang, Yung‐ho Chiu, Ching‐Ren Chiu, & Yi‐Ting Wang. (2018). METAFRONTIER ANALYSIS OF THE HIGH-TECH INDUSTRYʼS ENVIRONMENTAL EFFCIENCY IN JAPAN AND TAIWAN. Hitotsubashi journal of economics. 59(1). 9–24. 1 indexed citations
16.
Liu, Hsiang‐Hsi, et al.. (2015). USING A THREE STAGE SUPER-SBM MODEL TO ANALYZE THE INFLUENCE OF BANK'S INTERNATIONALIZATION AND RISK ON THE OPERATIONAL EFFICIENCY. Hitotsubashi journal of economics. 56(2). 213–229. 1 indexed citations
17.
Chen, Tser‐Yieth, et al.. (2013). A Comparison of Three-Stage DEA and Artificial Neural Network on the Operational Efficiency of Semi-Conductor Firms in Taiwan. Modern Economy. 4(1). 20–31. 23 indexed citations
18.
Chiu, Yung‐ho, et al.. (2013). Carbon Emission Allowances of Efficiency Analysis: Application of Super SBM ZSG-DEA Model. Polish Journal of Environmental Studies. 22(3). 26 indexed citations
19.
Chiu, Yung‐ho & Ming‐Feng Wu. (2010). Environmental efficiency evaluation in China: application of 'undesirable' data envelopment analysis.. Polish Journal of Environmental Studies. 19(6). 1159–1169. 12 indexed citations
20.
Hu, Jin‐Li, et al.. (2008). Shadow Prices of SO 2 Abatements for Regions in China. SSRN Electronic Journal. 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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