Kai‐Yu Tang

2.2k total citations · 2 hit papers
54 papers, 1.6k citations indexed

About

Kai‐Yu Tang is a scholar working on Sociology and Political Science, Information Systems and Management and Information Systems. According to data from OpenAlex, Kai‐Yu Tang has authored 54 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Sociology and Political Science, 18 papers in Information Systems and Management and 10 papers in Information Systems. Recurrent topics in Kai‐Yu Tang's work include Technology Adoption and User Behaviour (17 papers), Digital Marketing and Social Media (16 papers) and Online Learning and Analytics (7 papers). Kai‐Yu Tang is often cited by papers focused on Technology Adoption and User Behaviour (17 papers), Digital Marketing and Social Media (16 papers) and Online Learning and Analytics (7 papers). Kai‐Yu Tang collaborates with scholars based in Taiwan, China and India. Kai‐Yu Tang's co-authors include Chun‐Hua Hsiao, Jung‐Jung Chang, Gwo‐Jen Hwang, Ching‐Yi Chang, Chin‐Chung Tsai, Yun‐Fang Tu, Tzu‐Chiang Lin, Raghu Raman, Prema Nedungadi and Yu-Sheng Su and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Kai‐Yu Tang

52 papers receiving 1.5k citations

Hit Papers

Exploring the influential factors in continuance usage of... 2015 2026 2018 2022 2015 2021 100 200 300 400 500
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.

  1. Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives
    2015 526 citations Chun‐Hua Hsiao, Kai‐Yu Tang et al. profile →
  2. Trends in artificial intelligence-supported e-learning: a systematic review and co-citation network analysis (1998–2019)
    2021 199 citations Kai‐Yu Tang, Ching‐Yi Chang et al. Interactive Learning Environments profile →

Peers

Kai‐Yu Tang
Zhen Shao China
Noorminshah A. Iahad Malaysia
Sevgi Özkan Türkiye
Patricio Ramírez-Correa Chile
Yu-Min Wang Taiwan
H. Joseph Wen United States
Rupert Ward United Kingdom
Julián Chaparro-Peláez Spain
Jorge Arenas-Gaitán Spain
Charlie C. Chen United States
Zhen Shao China
Kai‐Yu Tang
Citations per year, relative to Kai‐Yu Tang Kai‐Yu Tang (= 1×) peers Zhen Shao

Countries citing papers authored by Kai‐Yu Tang

Since Specialization
Citations

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

Fields of papers citing papers by Kai‐Yu Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai‐Yu Tang. 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 Kai‐Yu Tang. The network helps show where Kai‐Yu Tang may publish in the future.

Co-authorship network of co-authors of Kai‐Yu Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Kai‐Yu Tang. A scholar is included among the top collaborators of Kai‐Yu Tang 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 Kai‐Yu Tang. Kai‐Yu Tang 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.
2.
Nedungadi, Prema, et al.. (2025). AI Techniques and Applications for Online Social Networks and Media: Insights From BERTopic Modeling. IEEE Access. 13. 37389–37407. 1 indexed citations
3.
4.
Tang, Kai‐Yu, et al.. (2023). Review of TAM used in Educational Technology Research: A Proposal. International Conference on Computers in Education. 1 indexed citations
5.
Hsu, Ying‐Shao, Kai‐Yu Tang, & Tzu‐Chiang Lin. (2023). Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of Literature Published in 2011–2020. Science & Education. 33(4). 1069–1092. 13 indexed citations
6.
Tang, Kai‐Yu, et al.. (2023). Diagnosis of hypertrophic cardiomyopathy accompanied with primary aldosteronism—Case report. SHILAP Revista de lepidopterología. 11(11). e8218–e8218. 1 indexed citations
7.
Hwang, Gwo‐Jen, Kai‐Yu Tang, & Yun‐Fang Tu. (2022). How artificial intelligence (AI) supports nursing education: profiling the roles, applications, and trends of AI in nursing education research (1993–2020). Interactive Learning Environments. 32(1). 373–392. 42 indexed citations
8.
Tang, Kai‐Yu, Chun‐Hua Hsiao, & Gwo‐Jen Hwang. (2022). A scholarly network of AI research with an information science focus: Global North and Global South perspectives. PLoS ONE. 17(4). e0266565–e0266565. 6 indexed citations
9.
Lin, Tzu‐Chiang, et al.. (2022). A Co-word Analysis of Selected Science Education Literature: Identifying Research Trends of Scaffolding in Two Decades (2000–2019). Frontiers in Psychology. 13. 844425–844425. 19 indexed citations
10.
11.
Tang, Kai‐Yu, Ching‐Yi Chang, & Gwo‐Jen Hwang. (2021). Trends in artificial intelligence-supported e-learning: a systematic review and co-citation network analysis (1998–2019). Interactive Learning Environments. 31(4). 2134–2152. 199 indexed citations breakdown →
12.
Tang, Kai‐Yu, Chun‐Hua Hsiao, Yun‐Fang Tu, Gwo‐Jen Hwang, & Youmei Wang. (2021). Factors influencing university teachers’ use of a mobile technology-enhanced teaching (MTT) platform. Educational Technology Research and Development. 69(5). 2705–2728. 26 indexed citations
13.
Hsiao, Chun‐Hua, Kai‐Yu Tang, & Yu-Sheng Su. (2021). An Empirical Exploration of Sports Sponsorship: Activation of Experiential Marketing, Sponsorship Satisfaction, Brand Equity, and Purchase Intention. Frontiers in Psychology. 12. 677137–677137. 19 indexed citations
14.
Chang, Ching‐Yi, De-Chih Lee, Kai‐Yu Tang, & Gwo‐Jen Hwang. (2021). Effect sizes and research directions of peer assessments: From an integrated perspective of meta-analysis and co-citation network. Computers & Education. 164. 104123–104123. 29 indexed citations
15.
Tang, Kai‐Yu, Chun‐Hua Hsiao, & Yu-Sheng Su. (2020). How Has E-Book Research Evolved? A Bibliometric Comparison of International Journal Publications (2000-2019). 網際網路技術學刊. 21(7). 1941–1948. 3 indexed citations
16.
Chang, Ching‐Yi, Meei‐Ling Gau, Kai‐Yu Tang, & Gwo‐Jen Hwang. (2020). Directions of the 100 most cited nursing student education research: A bibliometric and co-citation network analysis. Nurse Education Today. 96. 104645–104645. 37 indexed citations
17.
Tang, Kai‐Yu, et al.. (2019). A Content Analysis of Computational Thinking Research: An International Publication Trends and Research Typology. The Asia-Pacific Education Researcher. 29(1). 9–19. 69 indexed citations
18.
19.
Tang, Kai‐Yu, et al.. (2016). A co-citation network of young children's learning with technology. Educational Technology & Society. 19(3). 294–305. 5 indexed citations
20.
Hsiao, Chun‐Hua, Mei‐Chun Chen, & Kai‐Yu Tang. (2013). Investigating the Success Factors for the Acceptance of Mobile Healthcare Technology.. Pacific Asia Conference on Information Systems. 199. 7 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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