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.
The technology acceptance model and the World Wide Web
2000972 citationsAlbert L. Lederer, Mark Sena et al.Decision Support Systemsprofile →
Designing multifunctional quantum dots for bioimaging, detection, and drug delivery
2010806 citationsPavel Zrazhevskiy, Mark Sena et al.Chemical Society Reviewsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Mark Sena'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 Mark Sena with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Sena more than expected).
This network shows the impact of papers produced by Mark Sena. 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 Mark Sena. The network helps show where Mark Sena may publish in the future.
Co-authorship network of co-authors of Mark Sena
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Sena.
A scholar is included among the top collaborators of Mark Sena 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 Mark Sena. Mark Sena is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sena, Mark, et al.. (2017). Rate My Information Systems Professor: Exploring the Factors That Influence Student Ratings.. Information Systems Education Journal. 15(6). 56–61.
Sena, Mark, et al.. (2010). A Modular Approach to Delivering an Introductory MIS Course. Exhibit - A Showcase of Scholarship, Creativity and Preservation Provided by Xavier University Library (Xavier University). 8(36). 1.13 indexed citations
11.
Zrazhevskiy, Pavel, Mark Sena, & Xiaohu Gao. (2010). Designing multifunctional quantum dots for bioimaging, detection, and drug delivery. Chemical Society Reviews. 39(11). 4326–4326.806 indexed citations breakdown →
12.
Sena, Mark, et al.. (2009). Faculty Perceptions on the Goals and Achievements of Information Systems Executive Advisory Boards. Exhibit - A Showcase of Scholarship, Creativity and Preservation Provided by Xavier University Library (Xavier University). 8(41). 1.2 indexed citations
Sena, Mark & Clyde W. Holsapple. (2001). Enterprise systems for organizational decision support: an examination of objectives, characteristics, and benefits.1 indexed citations
Lederer, Albert L., et al.. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems. 29(3). 269–282.972 indexed citations breakdown →
Lederer, Albert L., et al.. (1997). TAM and the World Wide Web. Journal of the Association for Information Systems.8 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.