Michael Nofer
Impact in
- Information Systems top 1%
- Blockchain Technology Applications and Security
- Information and Cyber Security
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- FinTech, Crowdfunding, Digital Finance
Papers in
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- Experimental Behavioral Economics Studies 3
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- Sports Analytics and Performance 2
- Complex Systems and Time Series Analysis 1
- Co-authors
- Oliver Fast Hinz (8 shared papers)Dirk Schiereck (2 shared papers)Peter Gomber (1 shared paper)Michele Costola (1 shared paper)Loriana Pelizzon (1 shared paper)Heiko Roßnagel (1 shared paper)Jan Muntermann (1 shared paper)Jan Zibuschka (1 shared paper)
In The Last Decade
Michael Nofer
12 papers receiving 1.3k citations
Michael Nofer's Hit Papers
Peers
Comparison fields: 5 of 106
- Information Systems 885
- Management Information Systems 194
- Computer Networks and Communications 279
- Management Science and Operations Research 137
- Finance 86
Countries citing papers authored by Michael Nofer
This map shows the geographic impact of Michael Nofer'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 Michael Nofer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Nofer more than expected).
Fields of papers citing papers by Michael Nofer
This network shows the impact of papers produced by Michael Nofer. 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 Michael Nofer. The network helps show where Michael Nofer may publish in the future.
Co-authors
The 13 scholars most cited alongside Michael Nofer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Blockchain Hit paper breakdown → | 2017 | 942 |
| 2 | 2015 | 104 | |
| 3 | 2023 | 92 | |
| 4 | 2014 | 61 | |
| 5 | 2014 | 52 | |
| 6 | 2014 | 42 | |
| 7 | 2015 | 16 | |
| 8 | 2023 | 12 | |
| 9 | 2015 | 7 | |
| 10 | 2015 | 6 | |
| 11 | Users’ Preferences Concerning Privacy Properties of Assistant Systems on the Internet of Things | 2019 | 6 |
| 12 | 2015 | 3 | |
| 13 | 2015 | 0 | |
| 14 | 2026 | 0 |
About Michael Nofer
Michael Nofer is a scholar working on Safety Research, Economics and Econometrics, Management Science and Operations Research, Information Systems and Health Information Management, having authored 14 papers that have together received 1.3k indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (3 papers), Experimental Behavioral Economics Studies (3 papers), Sports Analytics and Performance (2 papers), Privacy, Security, and Data Protection (2 papers), Cybercrime and Law Enforcement Studies (2 papers), Complex Systems and Time Series Analysis (1 paper), Blockchain Technology Applications and Security (1 paper) and Digital Marketing and Social Media (1 paper). The work is most often cited by research in Information Systems (885 citations), Management Information Systems (194 citations), Computer Networks and Communications (279 citations), Management Science and Operations Research (137 citations) and Finance (86 citations). Michael Nofer has collaborated with scholars based in Germany and Italy. Frequent co-authors include Oliver Fast Hinz, Dirk Schiereck, Peter Gomber, Michele Costola, Loriana Pelizzon, Heiko Roßnagel, Jan Muntermann, Jan Zibuschka, Christian Georg Zimmermann and Wil M. P. van der Alast. Their work appears in journals such as Business & Information Systems Engineering, Journal of the Association for Information Systems, Journal of Business Economics, Research in International Business and Finance and Information & Management.
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.