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.
A comparative assessment of ensemble learning for credit scoring
2010386 citationsGang Wang, Jin‐Xing Hao et al.Expert Systems with Applicationsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Jin‐Xing Hao'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 Jin‐Xing Hao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin‐Xing Hao more than expected).
This network shows the impact of papers produced by Jin‐Xing Hao. 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 Jin‐Xing Hao. The network helps show where Jin‐Xing Hao may publish in the future.
Co-authorship network of co-authors of Jin‐Xing Hao
This figure shows the co-authorship network connecting the top 25 collaborators of Jin‐Xing Hao.
A scholar is included among the top collaborators of Jin‐Xing Hao 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 Jin‐Xing Hao. Jin‐Xing Hao is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hao, Jin‐Xing, et al.. (2016). Exploring the expenditure-based profile of Macao visitors ? A cluster analysis. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 133.2 indexed citations
7.
Yu, Yan, Jin‐Xing Hao, & Dong Xiao-ying. (2015). Social Identification Mediated Interdependence Designs for Team Knowledge Sharing. Journal of the Association for Information Systems. 153.2 indexed citations
8.
Hao, Jin‐Xing, Yan Yu, & Ron Chi-Wai Kwok. (2013). The Learning Impacts of a Concept Map based Classroom Response System. Pacific Asia Conference on Information Systems. 204.2 indexed citations
Hao, Jin‐Xing, Angela Yan Yu, & Dong Xiao-ying. (2011). Bridging Role Of Absorptive Capacity For Knowledge Management Systems Success. Journal of the Association for Information Systems. 73.6 indexed citations
14.
Yu, Angela Yan, Jin‐Xing Hao, Dong Xiao-ying, & Mohamed Khalifa. (2010). REVISITING THE EFFECT OF SOCIAL CAPITAL ON KNOWLEDGE SHARING IN WORK TEAMS : A MULTILEVEL APPROACH. Journal of the Association for Information Systems. 159.11 indexed citations
15.
Wang, Gang, Jin‐Xing Hao, Jian Ma, & Hongbing Jiang. (2010). A comparative assessment of ensemble learning for credit scoring. Expert Systems with Applications. 38(1). 223–230.386 indexed citations breakdown →
Ma, Jian, et al.. (2009). USING SOCIAL NETWORK ANALYSIS AS A STRATEGY FOR E-COMMERCE RECOMMENDATION. Journal of the Association for Information Systems. 86. 106–7.18 indexed citations
18.
Hao, Jin‐Xing, Ron Chi-Wai Kwok, & Raymond Y.K. Lau. (2007). Predicting Problem-Solving Performance Using Concept Map. Journal of the Association for Information Systems. 104.1 indexed citations
19.
Hao, Jin‐Xing, Ron Chi-Wai Kwok, & Angela Yan Yu. (2007). Automatic semantic causal map integration. Journal of the Association for Information Systems. 67.1 indexed citations
20.
Du, Helen S., Jin‐Xing Hao, Ron Chi-Wai Kwok, & Christian Wagner. (2006). Can Lean Media Enhance Large Group Learning? An Empirical Investigation of Mobile Information and Communication Technology. Journal of the Association for Information Systems. 64.1 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.