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.
Trustworthy artificial intelligence
2020307 citationsScott Thiebes, Sebastian Lins et al.profile →
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 Ali Sunyaev'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 Ali Sunyaev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ali Sunyaev more than expected).
This network shows the impact of papers produced by Ali Sunyaev. 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 Ali Sunyaev. The network helps show where Ali Sunyaev may publish in the future.
Co-authorship network of co-authors of Ali Sunyaev
This figure shows the co-authorship network connecting the top 25 collaborators of Ali Sunyaev.
A scholar is included among the top collaborators of Ali Sunyaev 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 Ali Sunyaev. Ali Sunyaev 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.
Sunyaev, Ali, Alexander Benlian, Jella Pfeiffer, et al.. (2025). High-Risk Artificial Intelligence. Business & Information Systems Engineering. 67(6). 981–994.6 indexed citations
2.
Maedche, Alexander, Hartmut Hoehle, Christiane Lehrer, et al.. (2024). Open Science. Business & Information Systems Engineering. 66(4). 517–532.6 indexed citations
Sunyaev, Ali, Tobias Dehling, Susanne Strahringer, et al.. (2023). The Future of Enterprise Information Systems. Business & Information Systems Engineering. 65(6). 731–751.5 indexed citations
Lins, Sebastian, Jan-Michael Becker, Kalle Lyytinen, & Ali Sunyaev. (2023). A Design Theory for Certification Presentations. ACM SIGMIS Database the DATABASE for Advances in Information Systems. 54(3). 75–118.4 indexed citations
Sunyaev, Ali, Niclas Kannengießer, Roman Beck, et al.. (2021). Token Economy. Business & Information Systems Engineering. 63(4). 457–478.63 indexed citations
Sturm, Benjamin & Ali Sunyaev. (2019). A Good Beginning Makes a Good Ending: Incipient Sources of Knowledge in Design Science Research. Journal of the Association for Information Systems.
16.
Sturm, Benjamin, Stephan Schneider, & Ali Sunyaev. (2015). Leave No Stone Unturned: Introducing a Revolutionary Meta-search Tool for Rigorous and Efficient Systematic Literature Searches.. Journal of the Association for Information Systems. 34.3 indexed citations
17.
Dehling, Tobias & Ali Sunyaev. (2013). Improved Medication Compliance Through Health IT: Design and Mixed Methods Evaluation of the Application ePill. SSRN Electronic Journal.2 indexed citations
18.
Sunyaev, Ali, et al.. (2012). Risk Evaluation and Security Analysis of the Clinical Area within the German Health Information Infrastructure. SSRN Electronic Journal.2 indexed citations
19.
Sunyaev, Ali, et al.. (2010). Strategies for Development and Adoption of EHR in German Ambulatory Care. SSRN Electronic Journal.
20.
Sunyaev, Ali, et al.. (2009). Integration of patient health portals into the German healthcare telematics infrastructure. Alexandria (UniSG) (University of St.Gallen). 754.2 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.