Sushil Bikhchandani

14.4k citations
55 papers · 4.8k indexed · 3 hit papers · h-index 23
Topics
Auction Theory and Applications (34 papers)Consumer Market Behavior and Pricing (19 papers)Game Theory and Applications (17 papers)

In The Last Decade

Sushil Bikhchandani

52 papers receiving 4.4k citations

Hit Papers

Learning from the Behavior of Others: Conformity, Fads, a...19922026200320141998199220004008001.2k

Peers

Sushil Bikhchandani
Comparison fields: 5 of 121
  • Economics and Econometrics 2.2k
  • Management Science and Operations Research 1.9k
  • Finance 1.3k
  • Marketing 911
  • Accounting 809
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Citations per field
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Citations per year

Countries citing papers authored by Sushil Bikhchandani

Since Specialization
Citations

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

Fields of papers citing papers by Sushil Bikhchandani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sushil Bikhchandani

This figure shows the co-authorship network connecting the top 25 collaborators of Sushil Bikhchandani. A scholar is included among the top collaborators of Sushil Bikhchandani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sushil Bikhchandani. Sushil Bikhchandani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 18
2 5
3 20
4 5
5 2
6 14
7
Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades
37
8 120
9
Ex post implementation in environments with private goods
40
10
Optimal Search with Learning
10
11
The Limits of Ex Post Implementation Revisited
5
12
Incentive Compatibility in Multi-unit Auctions
11
13 4
14
Comportamiento gregario o de rebaño en los mercados financieros: una reseña
1
15 12
16 44
17 47
18 194
19
A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascadesbreakdown →
1124
20
Market games with few traders
3

About Sushil Bikhchandani

Sushil Bikhchandani is a scholar working on Management Science and Operations Research, Marketing and General Decision Sciences, having authored 55 papers that have together received 4.8k indexed citations. Recurring topics across this work include Auction Theory and Applications (34 papers), Consumer Market Behavior and Pricing (19 papers) and Game Theory and Applications (17 papers). The work is most often cited by research in Management Science and Operations Research (1.9k citations), Finance (1.3k citations) and Marketing (911 citations). Sushil Bikhchandani has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Ivo Welch, David Hirshleifer, Sunil Sharma, Joseph M. Ostroy, John W. Mamer, John G. Riley, Chi-fu Huang, Arunava Sen, S. Chatterji and Noam Nisan. Their work appears in journals such as Econometrica, Journal of Political Economy and European Journal of Operational Research.

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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