Gyeongcheol Cho

1.3k total citations · 2 hit papers
27 papers, 811 citations indexed

About

Gyeongcheol Cho is a scholar working on Management Science and Operations Research, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Gyeongcheol Cho has authored 27 papers receiving a total of 811 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Management Science and Operations Research, 5 papers in Computer Networks and Communications and 4 papers in Artificial Intelligence. Recurrent topics in Gyeongcheol Cho's work include Multi-Criteria Decision Making (6 papers), Advanced Statistical Modeling Techniques (5 papers) and Psychometric Methodologies and Testing (5 papers). Gyeongcheol Cho is often cited by papers focused on Multi-Criteria Decision Making (6 papers), Advanced Statistical Modeling Techniques (5 papers) and Psychometric Methodologies and Testing (5 papers). Gyeongcheol Cho collaborates with scholars based in Canada, United States and South Korea. Gyeongcheol Cho's co-authors include Heungsun Hwang, Marko Sarstedt, Christian M. Ringle, Kwanghee Jung, Younyoung Choi, Jinyeong Yim, Seoung‐Hwan Lee, Jaehoon Lee, Vibhuti Gupta and Hosung Choo and has published in prestigious journals such as PLoS ONE, eLife and Frontiers in Psychology.

In The Last Decade

Gyeongcheol Cho

22 papers receiving 790 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Cutoff criteria for overall model fit indexes in generalized structured component analysis

2020 197 citations Gyeongcheol Cho, Heungsun Hwang et al. profile →
Same model, same data, but different outcomes: Evaluating the impact of method choices in structural equation modeling

2024 41 citations Marko Sarstedt, Christian M. Ringle et al. Journal of Product Innovation Management profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gyeongcheol Cho Canada	14	156	118	107	101	94	27	811
Enrico Ciavolino Italy	19	215 1.4×	149 1.3×	212 2.0×	125 1.2×	103 1.1×	81	1.1k
Miguel I. Aguirre‐Urreta United States	12	252 1.6×	173 1.5×	185 1.7×	110 1.1×	95 1.0×	41	970
Germán Molina United States	14	153 1.0×	125 1.1×	107 1.0×	63 0.6×	242 2.6×	46	1.3k
Wenqing Wu China	20	108 0.7×	152 1.3×	148 1.4×	68 0.7×	88 0.9×	58	1.2k
Tracey E. Rizzuto United States	14	159 1.0×	83 0.7×	152 1.4×	122 1.2×	32 0.3×	24	695
Junhui Yang China	5	112 0.7×	89 0.8×	147 1.4×	108 1.1×	66 0.7×	13	566
Tron Foss Norway	8	112 0.7×	43 0.4×	71 0.7×	100 1.0×	85 0.9×	9	994
Kurt A. Carlson United States	19	325 2.1×	282 2.4×	87 0.8×	148 1.5×	107 1.1×	48	1.3k
Gary F. Templeton United States	11	243 1.6×	74 0.6×	181 1.7×	112 1.1×	60 0.6×	31	1.3k
Joshua M. Davis United States	17	282 1.8×	95 0.8×	104 1.0×	71 0.7×	47 0.5×	30	1.1k

Countries citing papers authored by Gyeongcheol Cho

Since Specialization

Citations

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

Fields of papers citing papers by Gyeongcheol Cho

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gyeongcheol Cho. 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 Gyeongcheol Cho. The network helps show where Gyeongcheol Cho may publish in the future.

Co-authorship network of co-authors of Gyeongcheol Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Gyeongcheol Cho. A scholar is included among the top collaborators of Gyeongcheol Cho 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 Gyeongcheol Cho. Gyeongcheol Cho 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

Cho, Gyeongcheol, et al.. (2025). Comparison of Component-Based Structural Equation Modeling Methods in Testing Component Interaction Effects. Structural Equation Modeling A Multidisciplinary Journal. 32(5). 753–765.

Sarstedt, Marko, Christian M. Ringle, Gyeongcheol Cho, et al.. (2024). Same model, same data, but different outcomes: Evaluating the impact of method choices in structural equation modeling. Journal of Product Innovation Management. 41(6). 1100–1117. 41 indexed citations breakdown →

Cho, Gyeongcheol & Heungsun Hwang. (2024). Generalized Structured Component Analysis Accommodating Convex Components: A Knowledge-Based Multivariate Method with Interpretable Composite Indexes. Psychometrika. 89(1). 241–266.

Cho, Gyeongcheol, et al.. (2024). Gene–environment pathways to cognitive intelligence and psychotic-like experiences in children. eLife. 12. 2 indexed citations

Cho, Gyeongcheol, et al.. (2023). Gene–environment pathways to cognitive intelligence and psychotic-like experiences in children. eLife. 12.

Cho, Gyeongcheol & Heungsun Hwang. (2023). Deep Learning Generalized Structured Component Analysis: An Interpretable Artificial Neural Network Model with Composite Indexes. Structural Equation Modeling A Multidisciplinary Journal. 31(2). 265–279. 2 indexed citations

Hwang, Heungsun, Gyeongcheol Cho, & Hosung Choo. (2023). GSCA Pro—Free Stand-Alone Software for Structural Equation Modeling. Structural Equation Modeling A Multidisciplinary Journal. 31(4). 696–711. 11 indexed citations

Hwang, Heungsun, Marko Sarstedt, Gyeongcheol Cho, Hosung Choo, & Christian M. Ringle. (2023). A primer on integrated generalized structured component analysis. European Business Review. 35(3). 261–284. 28 indexed citations

Cho, Gyeongcheol, et al.. (2022). A comparative study of the predictive power of component-based approaches to structural equation modeling. European Journal of Marketing. 57(6). 1641–1661. 33 indexed citations

10.

Cho, Gyeongcheol, Heungsun Hwang, Marko Sarstedt, & Christian M. Ringle. (2022). A Prediction-Oriented Specification Search Algorithm for Generalized Structured Component Analysis. Structural Equation Modeling A Multidisciplinary Journal. 29(4). 611–619. 8 indexed citations

11.

Cho, Gyeongcheol & Heungsun Hwang. (2022). Structured Factor Analysis: A Data Matrix-Based Alternative Approach to Structural Equation Modeling. Structural Equation Modeling A Multidisciplinary Journal. 30(3). 364–377. 3 indexed citations

12.

Fakfare, Pipatpong, Gyeongcheol Cho, Heungsun Hwang, & Noppadol Manosuthi. (2021). Examining the sensory impressions, value perception, and behavioral responses of tourists: the case of floating markets in Thailand. Journal of Travel & Tourism Marketing. 38(7). 666–681. 32 indexed citations

13.

Hwang, Heungsun, Gyeongcheol Cho, Min Jin Jin, et al.. (2021). A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis. PLoS ONE. 16(3). e0247592–e0247592. 8 indexed citations

14.

Cho, Gyeongcheol, Marko Sarstedt, & Heungsun Hwang. (2021). A comparative evaluation of factor‐ and component‐based structural equation modelling approaches under (in)correct construct representations. British Journal of Mathematical and Statistical Psychology. 75(2). 220–251. 35 indexed citations

15.

Hwang, Heungsun, Gyeongcheol Cho, Kwanghee Jung, et al.. (2020). An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis.. Psychological Methods. 26(3). 273–294. 56 indexed citations

16.

Cho, Gyeongcheol, Younyoung Choi, & Jihyun Kim. (2020). Investigating the Unintended Consequences of the High School Equalization Policy on the Housing Market. Sustainability. 12(20). 8496–8496. 1 indexed citations

17.

Cho, Gyeongcheol, et al.. (2019). Review of Machine Learning Algorithms for Diagnosing Mental Illness. Psychiatry Investigation. 16(4). 262–269. 144 indexed citations

18.

Jung, Kwanghee, Jaehoon Lee, Vibhuti Gupta, & Gyeongcheol Cho. (2019). Comparison of Bootstrap Confidence Interval Methods for GSCA Using a Monte Carlo Simulation. Frontiers in Psychology. 10. 2215–2215. 84 indexed citations

19.

Kim, Ye-Seul, Yeonsoo Park, Gyeongcheol Cho, et al.. (2018). Screening Tool for Anxiety Disorders: Development and Validation of the Korean Anxiety Screening Assessment. Psychiatry Investigation. 15(11). 1053–1063. 17 indexed citations

20.

Cho, Gyeongcheol, et al.. (2017). A Study on the Interrelationship among Interest Rate, Housing Consumer Sentiment and Housing Market Using SVAR Model. The Korea Spatial Planning Review. 95(null). 3–20.

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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