Gu-Hong Lin

534 total citations
33 papers, 389 citations indexed

About

Gu-Hong Lin is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research and Statistics and Probability. According to data from OpenAlex, Gu-Hong Lin has authored 33 papers receiving a total of 389 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Statistics, Probability and Uncertainty, 20 papers in Management Science and Operations Research and 8 papers in Statistics and Probability. Recurrent topics in Gu-Hong Lin's work include Advanced Statistical Process Monitoring (22 papers), Optimal Experimental Design Methods (15 papers) and Scientific Measurement and Uncertainty Evaluation (14 papers). Gu-Hong Lin is often cited by papers focused on Advanced Statistical Process Monitoring (22 papers), Optimal Experimental Design Methods (15 papers) and Scientific Measurement and Uncertainty Evaluation (14 papers). Gu-Hong Lin collaborates with scholars based in Taiwan, Vietnam and Malaysia. Gu-Hong Lin's co-authors include W. L. Pearn, Kuen‐Suan Chen, Thanh‐Tuan Dang, Jia‐Hao Chang, Juing‐Huei Su, Cheng Ling Tan, Tsang-Chuan Chang, Sook Fern Yeo, Chun-Min Yu and Chih-Yuan Chang and has published in prestigious journals such as International Journal of Production Economics, The International Journal of Advanced Manufacturing Technology and Industrial Management & Data Systems.

In The Last Decade

Gu-Hong Lin

32 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gu-Hong Lin Taiwan	10	227	151	81	67	58	33	389
Chunghun Ha South Korea	12	97 0.4×	43 0.3×	31 0.4×	25 0.4×	14 0.2×	27	359
Tsang-Chuan Chang Taiwan	15	414 1.8×	189 1.3×	126 1.6×	25 0.4×	9 0.2×	37	629
Chun-Min Yu Taiwan	11	165 0.7×	63 0.4×	48 0.6×	17 0.3×	7 0.1×	42	323
Kellie Schneider United States	10	86 0.4×	26 0.2×	62 0.8×	33 0.5×	4 0.1×	26	362
Mehmet Savsar Kuwait	15	55 0.2×	55 0.4×	10 0.1×	35 0.5×	4 0.1×	67	630
Lu Zhen China	6	16 0.1×	190 1.3×	17 0.2×	49 0.7×	6 0.1×	25	327
Ana Paula Henriques de Gusmão Brazil	10	45 0.2×	74 0.5×	4 0.0×	39 0.6×	12 0.2×	30	373
Yu-Cheng Lin Taiwan	9	9 0.0×	115 0.8×	40 0.5×	28 0.4×	6 0.1×	12	300
M. Jeya Chandra United States	12	67 0.3×	98 0.6×	40 0.5×	47 0.7×	1 0.0×	38	459
Nani Kurniati Indonesia	9	105 0.5×	76 0.5×	32 0.4×	22 0.3×		95	345

Countries citing papers authored by Gu-Hong Lin

Since Specialization

Citations

This map shows the geographic impact of Gu-Hong Lin'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 Gu-Hong Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gu-Hong Lin more than expected).

Fields of papers citing papers by Gu-Hong Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gu-Hong Lin. 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 Gu-Hong Lin. The network helps show where Gu-Hong Lin may publish in the future.

Co-authorship network of co-authors of Gu-Hong Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Gu-Hong Lin. A scholar is included among the top collaborators of Gu-Hong Lin 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 Gu-Hong Lin. Gu-Hong Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chen, Kuen‐Suan, Gu-Hong Lin, & Chun-Min Yu. (2025). A Quality Decision-Making Approach Based on the Asymptotic Distribution of the Taguchi Index Estimator. International Journal of Reliability Quality and Safety Engineering. 32(4).

Lin, Gu-Hong, et al.. (2023). Supplier selection criteria using analytical hierarchy process (AHP)-based approach: a study in refractory materials manufacturers. Industrial Management & Data Systems. 123(6). 1814–1839. 7 indexed citations

Lin, Gu-Hong, et al.. (2021). A Two Phase Integrated Fuzzy Decision-Making Framework for Green Supplier Selection in the Coffee Bean Supply Chain. Mathematics. 9(16). 1923–1923. 30 indexed citations

Lin, Gu-Hong, et al.. (2021). Fuzzy Multi-Criteria Decision-Making Approach for Online Food Delivery (OFD) Companies Evaluation and Selection: A Case Study in Vietnam. Processes. 9(8). 1274–1274. 33 indexed citations

Lin, Gu-Hong, et al.. (2017). Assessing Nanofabrication Performance Based on the Estimated Taguchi Capability Index with Subsamples. 28(1). 33–52. 2 indexed citations

Lin, Gu-Hong, et al.. (2017). Using Super SBM Model for ranking: A case study of banks in Vietnam. 625–628. 4 indexed citations

Su, Juing‐Huei, et al.. (2008). A Hands-on Laboratory for Introductory Automatic Control Courses. IFAC Proceedings Volumes. 41(2). 9737–9742. 2 indexed citations

Lin, Gu-Hong, et al.. (2007). A Bayesian approach on monitoring process capability. Journal of Statistics and Management Systems. 10(2). 241–252. 2 indexed citations

Lin, Gu-Hong. (2006). A decision-making procedure on process centering: a lower bound of the estimated accuracy index. Journal of Statistics and Management Systems. 9(1). 205–224. 1 indexed citations

10.

Lin, Gu-Hong. (2006). A Bayesian approach based on multiple samples for measuring process performance with incapability index. International Journal of Production Economics. 106(2). 506–512. 6 indexed citations

11.

Lin, Gu-Hong. (2006). A hypothesis testing procedure on assessing process performance. Journal of Statistics and Management Systems. 9(2). 319–339. 4 indexed citations

12.

Lin, Gu-Hong. (2005). Process performance assessment based on sub-samples – a large sample approach. The International Journal of Advanced Manufacturing Technology. 27(11-12). 1223–1227. 1 indexed citations

13.

Lin, Gu-Hong. (2005). A random interval estimation of the estimated process accuracy index. The International Journal of Advanced Manufacturing Technology. 27(9-10). 969–974. 5 indexed citations

14.

Lin, Gu-Hong. (2005). Evaluating process centering with large samples – an approximate lower bound on the accuracy index. The International Journal of Advanced Manufacturing Technology. 28(1-2). 149–153. 2 indexed citations

15.

Pearn, W. L., et al.. (2004). (Quality and Quantity International Journal of Methodology,38(1):095-111)Normal Approximation to the Distribution of the Estimated Yield Index Spk. 1 indexed citations

16.

Pearn, W. L., et al.. (2004). Normal Approximation to the Distribution of the Estimated Yield Index Spk. Quality & Quantity. 38(1). 95–111. 23 indexed citations

17.

Pearn, W. L. & Gu-Hong Lin. (2003). A reliable procedure for testing linear regulators with one-sided specification limits based on multiple samples. Microelectronics Reliability. 43(4). 651–664. 7 indexed citations

18.

Pearn, W. L. & Gu-Hong Lin. (2003). A Bayesian-like estimator of the process capability index Cpmk. Metrika. 57(3). 303–312. 5 indexed citations

19.

Pearn, W. L. & Gu-Hong Lin. (2001). On the reliability of the estimated incapability index. Quality and Reliability Engineering International. 17(4). 279–290. 18 indexed citations

20.

Pearn, W. L., Gu-Hong Lin, & Kuen‐Suan Chen. (1998). Distributional and inferential properties of the process accuracy and process precision indices. Communication in Statistics- Theory and Methods. 27(4). 985–1000. 94 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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