David Dann

18 papers receiving 445 citations

Peers

David Dann
Comparison fields: 5 of 64
  • Marketing 186
  • Tourism, Leisure and Hospitality Management 21
  • Automotive Engineering 153
  • Management Science and Operations Research 86
  • Management Information Systems 39
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Upender Subramanian United States
Jean‐Pierre van der Rest Netherlands
Christian Nedu Osakwe South Africa
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Carmen Kar Hang Lee Singapore
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Citations per year

Countries citing papers authored by David Dann

Since Specialization
Citations

This map shows the geographic impact of David Dann'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 David Dann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Dann more than expected).

Fields of papers citing papers by David Dann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Dann. 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 David Dann. The network helps show where David Dann may publish in the future.

Co-authors

The 19 scholars most cited alongside David Dann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Dann Line = papers co-authored together David Dann links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2018145
2 202196
3 202081
4 199032
5 201923
6 198614
7 201812
8
Manpower Management in the Hotel and Catering Industry
198411
9 202011
10 199110
11 20229
12 20227
13
DISKNET – A Platform for the Systematic Accumulation of Knowledge in IS Research
20194
14 20234
15 20184
16 20203
17
Reconstructing the Giant: Automating the Categorization of Scientific Articles with Deep Learning Techniques
20173
18 20222
19 20250

About David Dann

David Dann is a scholar working on Marketing, Sociology and Political Science, Automotive Engineering, Organizational Behavior and Human Resource Management and Management Information Systems, having authored 19 papers that have together received 471 indexed citations. Recurring topics across this work include Sharing Economy and Platforms (8 papers), Digital Marketing and Social Media (5 papers), Transportation and Mobility Innovations (4 papers), FinTech, Crowdfunding, Digital Finance (3 papers), Management and Organizational Studies (3 papers), Hospitality and Tourism Education (2 papers), Blockchain Technology Applications and Security (2 papers) and Privacy, Security, and Data Protection (2 papers). The work is most often cited by research in Marketing (186 citations), Tourism, Leisure and Hospitality Management (21 citations), Automotive Engineering (153 citations), Management Science and Operations Research (86 citations) and Management Information Systems (39 citations). David Dann has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Christof Weinhardt, Timm Teubner, Julian Huber, Marc T. P. Adam, Fabian Braesemann, Minh Ha‐Duong, Matthias Hauser, Christian Meske, Alexander Maedche and Benjamin Mueller. Their work appears in journals such as Journal of the Association for Information Systems, International Journal of Contemporary Hospitality Management, Applied Energy, International Journal of Hospitality Management and Electronic Commerce Research and Applications.

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.

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