Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Data Collection in a Flat World: The Strengths and Weaknesses of Mechanical Turk Samples
20121.8k citationsJoseph K. Goodman, Cynthia Cryder et al.Journal of Behavioral Decision Makingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Amar Cheema'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 Amar Cheema with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amar Cheema more than expected).
This network shows the impact of papers produced by Amar Cheema. 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 Amar Cheema. The network helps show where Amar Cheema may publish in the future.
Co-authorship network of co-authors of Amar Cheema
This figure shows the co-authorship network connecting the top 25 collaborators of Amar Cheema.
A scholar is included among the top collaborators of Amar Cheema 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 Amar Cheema. Amar Cheema is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cheema, Amar, et al.. (2012). Bidding Behavior in Descending and Ascending Auctions. SSRN Electronic Journal.1 indexed citations
4.
Goodman, Joseph K., Cynthia Cryder, & Amar Cheema. (2012). Data Collection in a Flat World: Strengths and Weaknesses of Mechanical Turk Samples. SSRN Electronic Journal.5 indexed citations
Goodman, Joseph K., Cynthia Cryder, & Amar Cheema. (2012). Data Collection in a Flat World: The Strengths and Weaknesses of Mechanical Turk Samples. Journal of Behavioral Decision Making. 26(3). 213–224.1775 indexed citations breakdown →
Cheema, Amar & Rajesh Bagchi. (2010). The Effect of Goal Visualization on Goal Pursuit: Implications for Individuals and Managers. SSRN Electronic Journal.1 indexed citations
Cheema, Amar. (2008). A Reason to Spend? the Effect of Unexpected Price and Wealth Changes on Hedonic Purchases. ACR North American Advances.1 indexed citations
Cheema, Amar & Purushottam Papatla. (2008). Relative Importance of Online Versus Offline Information for Internet Purchases: The Effect of Product Category and Internet Experience. SSRN Electronic Journal.10 indexed citations
Cheema, Amar, Shyam Sunder, Peter T. L. Popkowski Leszczyc, et al.. (2005). Economics, Psychology, and Social Dynamics of Consumer Bidding in Auctions ∗. Queensland's institutional digital repository (The University of Queensland).1 indexed citations
18.
Cheema, Amar, Sucharita Chandran, & Vicki G. Morwitz. (2004). Drivers and Contextual Moderators of Consumer Value Formation in Participative Pricing Mechanisms.1 indexed citations
19.
Cheema, Amar & Dilip Soman. (2002). Consumer Responses to Unexpected Price Changes: Affective Reactions and Mental Accounting Effects. Advances in consumer research. 29(1). 342–343.1 indexed citations
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.