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.
Using the Technology Acceptance Model in Understanding Academics’ Behavioural Intention to Use Learning Management Systems
2014409 citationsSaleh Alharbi, Steve Drewprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Steve Drew'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 Steve Drew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Drew more than expected).
This network shows the impact of papers produced by Steve Drew. 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 Steve Drew. The network helps show where Steve Drew may publish in the future.
Co-authorship network of co-authors of Steve Drew
This figure shows the co-authorship network connecting the top 25 collaborators of Steve Drew.
A scholar is included among the top collaborators of Steve Drew 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 Steve Drew. Steve Drew is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Alghamdi, Bader, Leigh Ellen Potter, & Steve Drew. (2016). Identifying best practices in organisational SOA governance adoption: case study of Saudi Arabia’s e-government programme. eCite Digital Repository (University of Tasmania). 365.3 indexed citations
Kelder, Jo‐Anne, Angela Carbone, JT Walls, et al.. (2015). Variations on PATS: Choices in the Design of a Peer Assisted Teaching Scheme. eCite Digital Repository (University of Tasmania).1 indexed citations
Alharbi, Saleh & Steve Drew. (2014). Mobile Learning-system usage: Scale development and empirical tests. Figshare. 31–47.1 indexed citations
10.
Carbone, Angela, et al.. (2013). A peer assisted teaching scheme. eCite Digital Repository (University of Tasmania).1 indexed citations
11.
Pullan, Wayne, et al.. (2013). A Problem Based Approach to Teaching Programming. Griffith Research Online (Griffith University, Queensland, Australia). 1–6.2 indexed citations
Drew, Steve, et al.. (2012). The Effects of Website Quality on Adoption of E-Government Service: An Empirical Study Applying UTAUT Model Using SEM. Journal of the Association for Information Systems. 1–13.50 indexed citations
AlGhamdi, Rayed, A. N. Nguyen, Jeremy Nguyen, & Steve Drew. (2011). Factors Influencing Saudi Customers' Decisions to Purchase from Online Retailers in Saudi Arabia: A Quantitative Analysis. Swinburne Research Bank (Swinburne University of Technology).12 indexed citations
16.
Drew, Steve, et al.. (2011). Issues Influencing Saudi Customers' Decisions to Purchase from Online Retailers in the KSA :A Qualitative Analysis. eCite Digital Repository (University of Tasmania). 55(4). 580–593.26 indexed citations
17.
AlGhamdi, Rayed & Steve Drew. (2011). SEVEN KEY DRIVERS TO ONLINE RETAILING GROWTH IN KSA. Griffith Research Online (Griffith University, Queensland, Australia). 237–244.6 indexed citations
18.
Alkhalaf, Salem, Jeremy Nguyen, Anne Nguyen, & Steve Drew. (2011). The potential role of collaborative learning in enhancing e-learning systems: evidence from Saudi Arabia. eCite Digital Repository (University of Tasmania). 2011(1). 47–58.6 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.