Daniel Veit

123 papers receiving 2.6k citations

Hit Papers

More than fun and money. Worker motivation in crowdsourcing - a study on mechanical turk 2011 · 330 citations
3300+5+10Years since publication100200300

Peers

Daniel Veit
Comparison fields: 5 of 148
  • Computer Science Applications 283
  • Marketing 477
  • Information Systems and Management 341
  • Management Information Systems 301
  • Management Science and Operations Research 303
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Alan D. Smith United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Veit

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Veit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Veit, 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 Daniel Veit Line = papers co-authored together Daniel Veit links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 130 papers — load more, or switch the sort, to bring in the rest.

#Work
1
More than fun and money. Worker motivation in crowdsourcing - a study on mechanical turk
Hit paper breakdown →
2011330
2 2008255
3 2014207
4 2017154
5 2019123
6 2014120
7 201495
8 201779
9 200675
10 201862
11 201357
12 200955
13 202054
14 201546
15 201743
16 201342
17 201838
18 202137
19 200635
20 200729

About Daniel Veit

Daniel Veit is a scholar working on Sociology and Political Science, Management Science and Operations Research, Strategy and Management, Marketing and Information Systems and Management, having authored 130 papers that have together received 2.8k indexed citations. Recurring topics across this work include Auction Theory and Applications (22 papers), Technology Adoption and User Behaviour (19 papers), Privacy, Security, and Data Protection (12 papers), E-Government and Public Services (11 papers), Digital Platforms and Economics (11 papers), Electric Power System Optimization (10 papers), Digital Marketing and Social Media (9 papers) and Sharing Economy and Platforms (8 papers). The work is most often cited by research in Computer Science Applications (283 citations), Marketing (477 citations), Information Systems and Management (341 citations), Management Information Systems (301 citations) and Management Science and Operations Research (303 citations). Daniel Veit has collaborated with scholars based in Germany, United States and Denmark. Frequent co-authors include Anke Weidlich, Manuel Trenz, Nicolas Kaufmann, Thimo Schulze, Saonee Sarker, Dennis M. Steininger, Alexander Frey, Meredith C. Schuman, Jonathan Gershenzon and Christof Weinhardt. Their work appears in journals such as Journal of the Association for Information Systems, Journal of Business Economics, Journal of Chemical Ecology, Information Systems Journal and Nature Communications.

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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