Hua Dai

76 total papers · 1.2k total citations
54 papers, 986 citations indexed

About

Hua Dai is a scholar working on Sociology and Political Science, Information Systems and Management and Organizational Behavior and Human Resource Management. According to data from OpenAlex, Hua Dai has authored 54 papers receiving a total of 986 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Sociology and Political Science, 26 papers in Information Systems and Management and 19 papers in Organizational Behavior and Human Resource Management. Recurrent topics in Hua Dai's work include Technology Adoption and User Behaviour (26 papers), Digital Marketing and Social Media (24 papers) and Customer Service Quality and Loyalty (19 papers). Hua Dai is often cited by papers focused on Technology Adoption and User Behaviour (26 papers), Digital Marketing and Social Media (24 papers) and Customer Service Quality and Loyalty (19 papers). Hua Dai collaborates with scholars based in United States, China and United Kingdom. Hua Dai's co-authors include A. F. Salam, Tao Hu, Prashant Palvia, Rong Guan, Hua Zou, Deping Lu, Lü Li, Xin Luo, Nir Kshetri and Qinyu Liao and has published in prestigious journals such as Journal of Power Sources, Journal of Applied Polymer Science and Information & Management.

In The Last Decade

Hua Dai

51 papers receiving 945 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Hua Dai 342 342 193 178 177 54 986
Yi Wu 439 1.3× 222 0.6× 105 0.5× 176 1.0× 109 0.6× 73 1.1k
Seung‐Bae Park 375 1.1× 93 0.3× 170 0.9× 380 2.1× 221 1.2× 25 799
Kwang‐Ho Ahn 315 0.9× 79 0.2× 212 1.1× 226 1.3× 204 1.2× 87 901
Hope Koch 455 1.3× 267 0.8× 271 1.4× 41 0.2× 90 0.5× 62 1.2k
Xixi Li 175 0.5× 234 0.7× 193 1.0× 30 0.2× 72 0.4× 44 831
Ji Wu 287 0.8× 104 0.3× 342 1.8× 153 0.9× 57 0.3× 39 1.0k
Peng Hui 233 0.7× 179 0.5× 110 0.6× 351 2.0× 94 0.5× 56 1.2k
Dohoon Kim 143 0.4× 167 0.5× 600 3.1× 65 0.4× 62 0.4× 116 1.2k
Yan Li 114 0.3× 94 0.3× 136 0.7× 33 0.2× 35 0.2× 63 1.0k
Junghun Kim 209 0.6× 187 0.5× 287 1.5× 160 0.9× 51 0.3× 59 1.0k

Countries citing papers authored by Hua Dai

Since Specialization
Citations

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

Fields of papers citing papers by Hua Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hua Dai

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

All Works

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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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