Philipp Diebold
Impact in
- Information Systems top 1%
- Software Engineering Techniques and Practices
- Software Engineering Research
- Software top 5%
- Software Reliability and Analysis Research
Papers in
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- Software Engineering Techniques and Practices 53
- Software Engineering Research 41
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- Business Process Modeling and Analysis 8
- Big Data and Business Intelligence 4
- Co-authors
- Marco Kuhrmann (15 shared papers)Jürgen Münch (15 shared papers)Paolo Tell (5 shared papers)Oliver Linssen (5 shared papers)Christian R. Prause (5 shared papers)Michael Felderer (4 shared papers)Fergal Mc Caffery (3 shared papers)Eckhart Hanser (3 shared papers)
In The Last Decade
Philipp Diebold
61 papers receiving 843 citations
Peers
Comparison fields: 5 of 51
- Information Systems 737
- Software 103
- Management Information Systems 179
- Computer Science Applications 109
- Management of Technology and Innovation 84
Countries citing papers authored by Philipp Diebold
This map shows the geographic impact of Philipp Diebold'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 Philipp Diebold with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Diebold more than expected).
Fields of papers citing papers by Philipp Diebold
This network shows the impact of papers produced by Philipp Diebold. 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 Philipp Diebold. The network helps show where Philipp Diebold may publish in the future.
Co-authors
The 25 scholars most cited alongside Philipp Diebold, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 151 | |
| 2 | 2015 | 87 | |
| 3 | 2015 | 70 | |
| 4 | 2014 | 60 | |
| 5 | 2018 | 51 | |
| 6 | 2016 | 49 | |
| 7 | 2016 | 25 | |
| 8 | 2018 | 22 | |
| 9 | 2019 | 17 | |
| 10 | Moonlighting SCRUM: an agile method for distributed teams with part-time developers working during non-overlapping hours | 2013 | 16 |
| 11 | 2023 | 16 | |
| 12 | 2015 | 15 | |
| 13 | 2017 | 15 | |
| 14 | 2017 | 14 | |
| 15 | 2015 | 14 | |
| 16 | 2019 | 14 | |
| 17 | 2018 | 14 | |
| 18 | 2018 | 13 | |
| 19 | 2015 | 13 | |
| 20 | 2016 | 13 |
About Philipp Diebold
Philipp Diebold is a scholar working on Information Systems, Management Information Systems, Computer Networks and Communications, Software and Computer Science Applications, having authored 63 papers that have together received 867 indexed citations. Recurring topics across this work include Software Engineering Techniques and Practices (53 papers), Software Engineering Research (41 papers), Software System Performance and Reliability (15 papers), Advanced Software Engineering Methodologies (11 papers), Business Process Modeling and Analysis (8 papers), Software Reliability and Analysis Research (7 papers), Open Source Software Innovations (6 papers) and Big Data and Business Intelligence (4 papers). The work is most often cited by research in Information Systems (737 citations), Software (103 citations), Management Information Systems (179 citations), Computer Science Applications (109 citations) and Management of Technology and Innovation (84 citations). Philipp Diebold has collaborated with scholars based in Germany, Denmark and Spain. Frequent co-authors include Marco Kuhrmann, Jürgen Münch, Paolo Tell, Oliver Linssen, Christian R. Prause, Michael Felderer, Fergal Mc Caffery, Eckhart Hanser, Vahid Garousi and Stefan Wagner. Their work appears in journals such as Lecture notes in computer science, IEEE Software, Journal of Industrial Information Integration, PeerJ Computer Science and Lecture notes in business information processing.
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.