Changjun Lee

1.2k total citations
85 papers, 797 citations indexed

About

Changjun Lee is a scholar working on Economics and Econometrics, Finance and Sociology and Political Science. According to data from OpenAlex, Changjun Lee has authored 85 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Economics and Econometrics, 21 papers in Finance and 18 papers in Sociology and Political Science. Recurrent topics in Changjun Lee's work include Financial Markets and Investment Strategies (19 papers), Technology Adoption and User Behaviour (12 papers) and Digital Marketing and Social Media (7 papers). Changjun Lee is often cited by papers focused on Financial Markets and Investment Strategies (19 papers), Technology Adoption and User Behaviour (12 papers) and Digital Marketing and Social Media (7 papers). Changjun Lee collaborates with scholars based in South Korea, Ireland and Singapore. Changjun Lee's co-authors include Daeho Lee, Ahreum Hong, Junseok Hwang, Dieter F. Kogler, Jangkoo Kang, Jieun Shin, Jongwook Park, Keungoui Kim, Inyoung Park and Hongbum Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and PLoS ONE.

In The Last Decade

Changjun Lee

73 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Changjun Lee South Korea	15	238	168	122	116	101	85	797
Regan Stevenson United States	20	600 2.5×	269 1.6×	153 1.3×	75 0.6×	33 0.3×	39	1.6k
Choon‐Woo Lee South Korea	9	333 1.4×	116 0.7×	832 6.8×	66 0.6×	20 0.2×	24	1.6k
Yaniv Dover Israel	10	88 0.4×	697 4.1×	115 0.9×	36 0.3×	20 0.2×	27	1.1k
Paul Olk United States	15	141 0.6×	197 1.2×	480 3.9×	23 0.2×	15 0.1×	28	1.1k
Wan Fauziah Wan Yusoff Malaysia	15	62 0.3×	71 0.4×	227 1.9×	22 0.2×	18 0.2×	74	702
Mitsuru Kodama Japan	20	127 0.5×	130 0.8×	789 6.5×	70 0.6×	20 0.2×	111	1.3k
Natarajan Balasubramanian United States	16	650 2.7×	83 0.5×	407 3.3×	14 0.1×	52 0.5×	58	1.3k
Pier A. Abetti United States	17	375 1.6×	54 0.3×	341 2.8×	311 2.7×	37 0.4×	89	1.5k
Sungmin Ryu South Korea	13	54 0.2×	109 0.6×	488 4.0×	21 0.2×	10 0.1×	38	960

Countries citing papers authored by Changjun Lee

Since Specialization

Citations

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

Fields of papers citing papers by Changjun Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changjun Lee

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

Lee, Changjun, et al.. (2025). From similarity to multiplicity: Avatar multi-persona tendencies and cognitive responses in the Metaverse. Computers in Human Behavior. 172. 108750–108750.

Lee, Changjun, et al.. (2025). Exploring the competitive market structure of digital-based subscription economy: The empirical investigation of South Korea. Telematics and Informatics. 98. 102264–102264.

Kim, Sujin, et al.. (2025). The Basic Study for the Development Non Face-to-Face Dog Training Programs Suitable for Preventing and Correcting Behavioral Problems in Dogs. The Journal of the Korea Contents Association. 25(3). 385–394.

Lee, Changjun, et al.. (2024). Predicting wearable IoT Adoption: Identifying core consumers through Machine learning algorithms. Telematics and Informatics. 93. 102176–102176. 2 indexed citations

Han, Sangpil, et al.. (2024). Exploring drivers of fintech adoption among elderly consumers. Technology in Society. 78. 102669–102669. 11 indexed citations

Lee, Changjun, et al.. (2024). Strategies for launching streaming content: Assessing movie-country relatedness and its impact on international popularity. PLoS ONE. 19(6). e0305433–e0305433.

Lee, Changjun, et al.. (2024). Profiling the AI speaker user: Machine learning insights into consumer adoption patterns. PLoS ONE. 19(12). e0315540–e0315540. 1 indexed citations

Lee, Changjun, et al.. (2023). The Return of the King: The Importance of Killer Content in a Competitive OTT Market. Journal of theoretical and applied electronic commerce research. 18(2). 976–994. 9 indexed citations

Lee, Changjun, et al.. (2023). Time-of-Day and Day-of-Week Effects on TV and OTT Media Choices: Evidence from South Korea. Journal of theoretical and applied electronic commerce research. 19(1). 1–19. 2 indexed citations

10.

Lee, Changjun, et al.. (2023). The effect of watching OTT late at night on the sleep pattern of users. Sleep and Biological Rhythms. 21(4). 395–407.

11.

Kim, Keungoui, et al.. (2022). Changes in regional knowledge bases and its effect on local labour markets in the midst of transition: Evidence from France over 1985–2015. Applied Spatial Analysis and Policy. 16(3). 1255–1276. 2 indexed citations

12.

Park, Inyoung, et al.. (2021). Changes in consumption patterns during the COVID-19 pandemic: Analyzing the revenge spending motivations of different emotional groups. Journal of Retailing and Consumer Services. 65. 102874–102874. 60 indexed citations

13.

Lee, Changjun, et al.. (2021). Estimating cost of fighting against fake news during catastrophic situations. Telematics and Informatics. 66. 101734–101734. 6 indexed citations

14.

Kim, Keungoui, et al.. (2021). The nature of ICT in technology convergence: A knowledge-based network analysis. PLoS ONE. 16(7). e0254424–e0254424. 11 indexed citations

15.

Park, Inyoung, et al.. (2020). The effects of popularity metrics in news comments on the formation of public opinion: Evidence from an internet portal site. The Social Science Journal. 60(2). 367–382. 6 indexed citations

16.

Lee, Changjun, et al.. (2020). Analyzing Relationships Between Project Characteristic and Public Conflict Characteristic in Public Construction Using Fuzzy Analytical Hierarchy Process (FAHP). Korean Journal of Construction Engineering and Management. 21(1). 70–77. 1 indexed citations

17.

Kang, Jangkoo, et al.. (2013). A Construction of the Korean Stock Database and its Applications. 26(3). 311–352. 2 indexed citations

18.

Lee, Changjun, et al.. (2012). On the Investigation of Investment Style Consistency in Korean Equity Funds. 29(3). 83–106. 2 indexed citations

19.

Kang, Jangkoo, et al.. (2010). An Empirical Analysis on the Determinants of Credit Default Swap Spreads. 24(2). 99–128. 1 indexed citations

20.

Lee, Changjun, et al.. (2007). ORGANIZATIONAL DATA MINING IN KOREA. Issues in Information Systems. 1 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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