Raymond Hubbard

2.9k citations
57 papers · 2.1k · h-index 21

Impact in

Papers in

Raymond Hubbard

54 papers receiving 1.9k citations

Peers

Raymond Hubbard
Comparison fields: 5 of 176
  • Statistics, Probability and Uncertainty 356
  • Statistics and Probability 309
  • Organizational Behavior and Human Resource Management 358
  • Tourism, Leisure and Hospitality Management 51
  • Marketing 294
Replace William F. Massy with:
William F. Massy United States
Roger Lindsay Canada
Willem E. Saris Spain
Ulf Böckenholt United States
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Eli P. Cox United States
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Citations per field
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Citations per year

Countries citing papers authored by Raymond Hubbard

Since Specialization
Citations

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

Fields of papers citing papers by Raymond Hubbard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Raymond Hubbard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Raymond Hubbard Line = papers co-authored together Raymond Hubbard links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998231
2 2007215
3 1996191
4 2003162
5 2008158
6 2016112
7 1987103
8 200469
9 200069
10 198855
11 199749
12 200049
13 197848
14 200247
15 200647
16 198644
17
Regression Equations for the Latent Roots of Random Data Correlation Matrices with Unities on the Diagonal.
198639
18 201937
19 201236
20 199734

About Raymond Hubbard

Raymond Hubbard is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability, Sociology and Political Science, Management of Technology and Innovation and Marketing, having authored 57 papers that have together received 2.1k indexed citations. Recurring topics across this work include Meta-analysis and systematic reviews (11 papers), Management and Marketing Education (9 papers), scientometrics and bibliometrics research (5 papers), Wine Industry and Tourism (5 papers), Consumer Behavior in Brand Consumption and Identification (5 papers), Advanced Statistical Methods and Models (4 papers), Sensory Analysis and Statistical Methods (4 papers) and Philosophy and History of Science (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (356 citations), Statistics and Probability (309 citations), Organizational Behavior and Human Resource Management (358 citations), Tourism, Leisure and Hospitality Management (51 citations) and Marketing (294 citations). Raymond Hubbard has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Daniel E. Vetter, Eldon L. Little, J. Scott Armstrong, Roger Lindsay, Stuart J. Allen, M. J. Bayarri, Patricia Ryan, Carsten Baumgarth, Heiner Evanschitzky and Rahul Parsa. Their work appears in journals such as The American Statistician, Journal of Business Research, Theory & Psychology, Marketing Theory and Journal of the Academy of Marketing Science.

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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