Lawrence M. Ausubel
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- Auction Theory and Applications 32
- Marketing top 0.5%
- Consumer Market Behavior and Pricing 22
- Finance top 1%
- Banking stability, regulation, efficiency 6
- Economics and Econometrics top 0.5%
- Economic theories and models 9
- Merger and Competition Analysis 5
- Game Theory and Voting Systems 5
- General Decision Sciences top 5%
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- Experimental Behavioral Economics Studies 6
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- Digital Platforms and Economics 5
Lawrence M. Ausubel
44 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Management Science and Operations Research 1.7k
- Marketing 1.1k
- Finance 594
- Economics and Econometrics 1.6k
- General Decision Sciences 101
Countries citing papers authored by Lawrence M. Ausubel
This map shows the geographic impact of Lawrence M. Ausubel'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 Lawrence M. Ausubel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence M. Ausubel more than expected).
Fields of papers citing papers by Lawrence M. Ausubel
This network shows the impact of papers produced by Lawrence M. Ausubel. 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 Lawrence M. Ausubel. The network helps show where Lawrence M. Ausubel may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Lawrence M. Ausubel, 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 | 2019 | 17 | |
| 2 | 2018 | 2 | |
| 3 | 2017 | 2 | |
| 4 | Insider Trading In A Rational Expectations Economy | 2016 | 66 |
| 5 | 2009 | 16 | |
| 6 | Common-Value Auctions with Liquidity Needs: An Experimental Test of a Troubled Assets Reverse Auction | 2009 | 6 |
| 7 | 2009 | 0 | |
| 8 | 2004 | 408 | |
| 9 | 2004 | 77 | |
| 10 | 2004 | 114 | |
| 11 | 2002 | 13 | |
| 12 | 2002 | 2 | |
| 13 | Adverse Selection in the Credit Card Market | 1999 | 160 |
| 14 | The Optimality of Being Efficient | 1998 | 1 |
| 15 | 1998 | 25 | |
| 16 | 1993 | 29 | |
| 17 | 1993 | 29 | |
| 18 | 1992 | 26 | |
| 19 | The Failure of Competition in the Credit Card Marketbreakdown → | 1991 | 528 |
| 20 | 1989 | 199 |
About Lawrence M. Ausubel
Lawrence M. Ausubel is a scholar working on Management Science and Operations Research, Marketing, Economics and Econometrics, Finance and Safety Research, having authored 48 papers that have together received 3.0k indexed citations. Recurring topics across this work include Auction Theory and Applications (32 papers), Consumer Market Behavior and Pricing (22 papers), Economic theories and models (9 papers), Experimental Behavioral Economics Studies (6 papers), Banking stability, regulation, efficiency (6 papers), Digital Platforms and Economics (5 papers), Merger and Competition Analysis (5 papers) and Game Theory and Voting Systems (5 papers). The work is most often cited by research in Management Science and Operations Research (1.7k citations), Marketing (1.1k citations), Finance (594 citations), Economics and Econometrics (1.6k citations) and General Decision Sciences (101 citations). Lawrence M. Ausubel has collaborated with scholars based in United States. Frequent co-authors include Paul Milgrom, Raymond Deneckere, Peter Cramton, R. Preston McAfee, John McMillan, Richard M. Hynes, Thayer Morrill, Emel Filiz‐Ozbay, Rafael Romeu and Christina Aperjis. Their work appears in journals such as American Economic Review, The Economists Voice, Economic Theory, Econometrica and American Economic Journal Microeconomics.
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.