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.
Blood Pressure and Nutrient Intake in the United States
Countries citing papers authored by John L. Stanton
Since
Specialization
Citations
This map shows the geographic impact of John L. Stanton'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 John L. Stanton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John L. Stanton more than expected).
This network shows the impact of papers produced by John L. Stanton. 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 John L. Stanton. The network helps show where John L. Stanton may publish in the future.
Co-authorship network of co-authors of John L. Stanton
This figure shows the co-authorship network connecting the top 25 collaborators of John L. Stanton.
A scholar is included among the top collaborators of John L. Stanton 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 John L. Stanton. John L. Stanton is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Stanton, John L. & Rosa Caiazza. (2023). Agricultural Value Chains - Some Selected Issues. CINECA IRIS Institutial research information system (Parthenope University of Naples).1 indexed citations
Badghish, Saeed, et al.. (2018). Consumer Complaint Behavior: A comparison between Saudi Consumers and Filipino Migrants. The Journal of Consumer Satisfaction, Dissatisfaction & Complaining Behavior. 31. 40–66.1 indexed citations
5.
Darian, Jean C., et al.. (2017). An Investigation of Factors Influencing Consumer Responses To Health-Related Food Product Claims. DigitalCommons - Kennesaw State University (Kennesaw State University). 6(1). 1.1 indexed citations
6.
Stanton, John L.. (2016). Food Innovation: The Good, the Bad and the Ugly. Management Science. 11(3). 193–202.5 indexed citations
Fletcher, Richard, et al.. (2012). An exploratory study of consumer complaining behaviour (CCB) in Saudi Arabia.1 indexed citations
9.
Stanton, John L.. (2007). Evolutionary Cognitive Neuroscience: Dual Use Discipline for Understanding & Managing Complexity and Altering Warfare. SSRN Electronic Journal.2 indexed citations
10.
Herbst, Kenneth C., John L. Stanton, & Gillian Armstrong. (2006). Don't be Fooled: Profits Result from Being Innovative and Meeting Consumers' Need for Convenience. SHILAP Revista de lepidopterología.1 indexed citations
Stanton, John L., et al.. (2000). Market orientation in Australian SMEs: A size based comparison. 8(1). 3.1 indexed citations
14.
Stanton, John L.. (1998). Comparative Effectiveness of Executional Elements in TV Advertising: 15- versus 30-second Commercials. Journal of Advertising Research. 38(6). 7–8.60 indexed citations
15.
Stanton, John L., et al.. (1982). Marketing research problems in Latin America.. Market Research Society Journal. 24(2). 124.5 indexed citations
Stanton, John L., et al.. (1980). An Investigation of the Differential Impact of Purchase Situation on Levels of Consumer Choice Behavior. ACR North American Advances. 7.17 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.