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.
Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis
19821.2k citationsJoel Huber, John W. Payne et al.Journal of Consumer Researchprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Christopher P. Puto
Since
Specialization
Citations
This map shows the geographic impact of Christopher P. Puto'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 Christopher P. Puto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher P. Puto more than expected).
Fields of papers citing papers by Christopher P. Puto
This network shows the impact of papers produced by Christopher P. Puto. 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 Christopher P. Puto. The network helps show where Christopher P. Puto may publish in the future.
Co-authorship network of co-authors of Christopher P. Puto
This figure shows the co-authorship network connecting the top 25 collaborators of Christopher P. Puto.
A scholar is included among the top collaborators of Christopher P. Puto 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 Christopher P. Puto. Christopher P. Puto is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rothausen, Teresa J., et al.. (2019). A Model of Full-Time Professional Graduate Student Satisfaction: Program Design, Delivery, and Outcomes. The Journal of Consumer Satisfaction, Dissatisfaction & Complaining Behavior. 32. 73–97.1 indexed citations
Russell, Cristel Antonia & Christopher P. Puto. (1999). Special Session Summary Novel Experimental Methods: Opportunities and Challenges. ACR North American Advances.1 indexed citations
Rowe, Debra & Christopher P. Puto. (1987). Do Consumers' Reference Points Affect Their Buying Decisions?. ACR North American Advances.14 indexed citations
13.
Puto, Christopher P.. (1987). The Framing of Buying Decisions. Journal of Consumer Research. 14(3). 301–301.237 indexed citations
14.
Johnson, Michael D. & Christopher P. Puto. (1987). A Review of Consumer Judgment and Choice. Cornell Peter and Stephanie Nolan School of Hotel Administration (Cornell University).25 indexed citations
15.
Puto, Christopher P.. (1985). Memory For Scripts in Advertisements. ACR North American Advances.8 indexed citations
Puto, Christopher P. & William D. Wells. (1984). Informational and Transformational Advertising: the Differential Effects of Time. ACR North American Advances.276 indexed citations
Huber, Joel, John W. Payne, & Christopher P. Puto. (1982). Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis. Journal of Consumer Research. 9(1). 90–90.1245 indexed citations breakdown →
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.