Jun Dai

1.9k total citations · 2 hit papers
35 papers, 1.2k citations indexed

About

Jun Dai is a scholar working on Information Systems, Management Information Systems and Artificial Intelligence. According to data from OpenAlex, Jun Dai has authored 35 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Information Systems, 11 papers in Management Information Systems and 5 papers in Artificial Intelligence. Recurrent topics in Jun Dai's work include Blockchain Technology Applications and Security (11 papers), Big Data and Business Intelligence (10 papers) and Digital Transformation in Industry (3 papers). Jun Dai is often cited by papers focused on Blockchain Technology Applications and Security (11 papers), Big Data and Business Intelligence (10 papers) and Digital Transformation in Industry (3 papers). Jun Dai collaborates with scholars based in United States, China and South Korea. Jun Dai's co-authors include Miklos A. Vasarhelyi, Yu Gu, Diane J. Janvrin, Gary P. Schneider, Robyn L. Raschke, He Li, Na He, Xulong Chen, Qiao Li and Yong Wu and has published in prestigious journals such as Accounting Horizons, Accounting and Finance and Atmosphere.

In The Last Decade

Jun Dai

29 papers receiving 1.1k citations

Hit Papers

Toward Blockchain-Based Accounting and Assurance 2017 2026 2020 2023 2017 2023 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. Toward Blockchain-Based Accounting and Assurance
    2017 510 citations Jun Dai, Miklos A. Vasarhelyi Journal of Information Systems profile →
  2. Ethical impact of artificial intelligence in managerial accounting
    2023 62 citations Chao Zhang, Weidong Zhu et al. International Journal of Accounting Information Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Dai United States 14 608 596 245 166 163 35 1.2k
Ogan Yigitbasioglu Australia 11 281 0.5× 607 1.0× 229 0.9× 261 1.6× 133 0.8× 23 1.2k
Deniz Appelbaum United States 13 297 0.5× 676 1.1× 417 1.7× 153 0.9× 274 1.7× 28 1.2k
Julia Kokina United States 11 366 0.6× 475 0.8× 305 1.2× 116 0.7× 139 0.9× 17 988
Yong Jae Shin South Korea 6 410 0.7× 816 1.4× 238 1.0× 143 0.9× 76 0.5× 22 1.3k
Birendra K. Mishra United States 17 838 1.4× 606 1.0× 216 0.9× 457 2.8× 253 1.6× 35 1.8k
Alessio Faccia United Kingdom 16 348 0.6× 320 0.5× 97 0.4× 105 0.6× 96 0.6× 59 836
Heinz Roland Weistroffer United States 18 224 0.4× 338 0.6× 123 0.5× 225 1.4× 150 0.9× 88 1.2k
Fiona Rohde Australia 15 240 0.4× 516 0.9× 164 0.7× 153 0.9× 112 0.7× 55 988
Cristiano Bellavitis United States 17 483 0.8× 465 0.8× 360 1.5× 302 1.8× 110 0.7× 46 1.2k
Mauro de Mesquita Spínola Brazil 11 254 0.4× 459 0.8× 59 0.2× 226 1.4× 84 0.5× 61 1.1k

Countries citing papers authored by Jun Dai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Dai. A scholar is included among the top collaborators of Jun Dai 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 Jun Dai. Jun Dai 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.
Zhu, Weidong, et al.. (2025). Drivers and concerns of adopting Artificial Intelligence in managerial accounting. Accounting and Finance. 1 indexed citations
3.
Dai, Jun, et al.. (2024). Using Artificial Intelligence in ESG Assurance. Journal of Emerging Technologies in Accounting. 21(2). 83–99. 11 indexed citations
4.
Gu, Yu, et al.. (2024). Using Blockchain and Smart Contracts to Combat Greenwashing in Environmental Disclosures. SSRN Electronic Journal. 2 indexed citations
5.
Gu, Yu, Jun Dai, & Miklos A. Vasarhelyi. (2023). Audit 4.0-based ESG assurance: An example of using satellite images on GHG emissions. International Journal of Accounting Information Systems. 50. 100625–100625. 20 indexed citations
6.
Dai, Jun & Miklos A. Vasarhelyi. (2023). Management Accounting 4.0: The Future of Management Accounting. Journal of Emerging Technologies in Accounting. 20(1). 1–13. 8 indexed citations
7.
Gu, Yu, et al.. (2023). Environmental, Social, and Governance Taxonomy Simplification: A Hybrid Text Mining Approach. Journal of Emerging Technologies in Accounting. 20(1). 305–325. 13 indexed citations
8.
Gu, Yu, et al.. (2023). Internet of Things and Blockchain-Based Smart Contracts: Enabling Continuous Risk Monitoring and Assessment in Peer-to-Peer Lending. Journal of Emerging Technologies in Accounting. 20(2). 181–194. 5 indexed citations
9.
Zhang, Chao, Weidong Zhu, Jun Dai, Yong Wu, & Xulong Chen. (2023). Ethical impact of artificial intelligence in managerial accounting. International Journal of Accounting Information Systems. 49. 100619–100619. 62 indexed citations breakdown →
10.
Gu, Yu, et al.. (2022). Industry 4.0-Enabled Environment, Social, and Governance Reporting: A Case from a Chinese Energy Company. Journal of Emerging Technologies in Accounting. 20(1). 245–258. 19 indexed citations
11.
Gu, Yu, et al.. (2022). Blockchain-based Life Cycle Assessment System for ESG Reporting. SSRN Electronic Journal. 14 indexed citations
12.
Dai, Jun & Miklos A. Vasarhelyi. (2020). Continuous Audit Intelligence as a Service (CAIaaS) and Intelligent App Recommendations. Journal of Emerging Technologies in Accounting. 17(2). 1–15. 9 indexed citations
13.
14.
Dai, Jun, et al.. (2019). Utilizing Blockchain and Smart Contracts to Enable Audit 4.0: From the Perspective of Accountability Audit of Air Pollution Control in China. Journal of Emerging Technologies in Accounting. 16(2). 23–41. 52 indexed citations
15.
Li, He, et al.. (2018). Understanding usage and value of audit analytics for internal auditors: An organizational approach. International Journal of Accounting Information Systems. 28. 59–76. 105 indexed citations
16.
Dai, Jun. (2017). Three essays on audit technology. Rutgers University Community Repository (Rutgers University). 15 indexed citations
17.
Dai, Jun & Miklos A. Vasarhelyi. (2017). Toward Blockchain-Based Accounting and Assurance. Journal of Information Systems. 31(3). 5–21. 510 indexed citations breakdown →
18.
Dai, Jun. (2010). Data-frame Parsing and Processing Based on Tree-structured. Journal of Chinese Computer Systems.
19.
Dai, Jun, et al.. (2010). Development of exercise program of improving dynamic balance function for elderly people. 24(1). 57–71. 1 indexed citations
20.
Dai, Jun. (2009). Design of Piston for Internal Combustion Engine. Science and Technology Information.

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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