Jay Beaman

2.7k total citations · 1 hit paper
48 papers, 1.9k citations indexed

About

Jay Beaman is a scholar working on Sociology and Political Science, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, Jay Beaman has authored 48 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Sociology and Political Science, 19 papers in Economics and Econometrics and 9 papers in Statistics and Probability. Recurrent topics in Jay Beaman's work include Economic and Environmental Valuation (19 papers), Diverse Aspects of Tourism Research (11 papers) and Survey Methodology and Nonresponse (8 papers). Jay Beaman is often cited by papers focused on Economic and Environmental Valuation (19 papers), Diverse Aspects of Tourism Research (11 papers) and Survey Methodology and Nonresponse (8 papers). Jay Beaman collaborates with scholars based in United States, Taiwan and Canada. Jay Beaman's co-authors include Jerry J. Vaske, Carly C. Sponarski, Rand D. Conger, Ronald L. Simons, Tzung‐Cheng Huan, Lori B. Shelby, Les B. Whitbeck, Christine A. Johnson, Chao Wei and Chao Wei and has published in prestigious journals such as Tourism Management, Journal of Marriage and the Family and Annals of Tourism Research.

In The Last Decade

Jay Beaman

46 papers receiving 1.7k citations

Hit Papers

Rethinking Internal Consistency in Cronbach's Alpha 2016 2026 2019 2022 2016 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jay Beaman United States 20 878 384 360 252 237 48 1.9k
Paul Stenner United Kingdom 25 1.0k 1.2× 632 1.6× 344 1.0× 188 0.7× 562 2.4× 101 4.1k
Fern K. Willits United States 24 1.1k 1.2× 494 1.3× 113 0.3× 215 0.9× 174 0.7× 64 2.5k
Jessica M. Nolan United States 11 1.5k 1.8× 440 1.1× 135 0.4× 522 2.1× 156 0.7× 19 4.2k
Joar Vittersø Norway 32 1.0k 1.2× 1.6k 4.2× 517 1.4× 101 0.4× 320 1.4× 60 3.2k
Barbara Finlay United States 11 752 0.9× 366 1.0× 167 0.5× 108 0.4× 179 0.8× 25 2.0k
Steven R. Brown United States 22 807 0.9× 421 1.1× 172 0.5× 192 0.8× 228 1.0× 81 3.7k
Rebecca Weston United States 19 906 1.0× 851 2.2× 1.1k 3.1× 82 0.3× 517 2.2× 37 3.4k
Christina Derrick United States 7 467 0.5× 136 0.4× 237 0.7× 116 0.5× 344 1.5× 8 2.0k
Mark Tranmer United Kingdom 20 624 0.7× 210 0.5× 112 0.3× 200 0.8× 176 0.7× 44 1.5k
Patrick Sturgis United Kingdom 31 2.7k 3.0× 475 1.2× 184 0.5× 268 1.1× 457 1.9× 95 4.3k

Countries citing papers authored by Jay Beaman

Since Specialization
Citations

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

Fields of papers citing papers by Jay Beaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jay Beaman

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Beaman. A scholar is included among the top collaborators of Jay Beaman 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 Jay Beaman. Jay Beaman 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
1.
Vaske, Jerry J., Jay Beaman, & Craig A. Miller. (2020). Minimal effect sizes do not imply minimal effects for differences in long-tailed distributions. Human Dimensions of Wildlife. 25(3). 281–290. 1 indexed citations
2.
Beaman, Jay, Jerry J. Vaske, Jennifer I. Schmidt, & Tzung‐Cheng Huan. (2015). Measuring and Correcting Response Heaping Arising From the Use of Prototypes. Human Dimensions of Wildlife. 20(2). 167–173. 4 indexed citations
3.
Huan, Tzung‐Cheng & Jay Beaman. (2007). Executive learning exercise and trainer's notes for importance‐performance analysis (IPA). International Journal of Culture Tourism and Hospitality Research. 1(4). 315–327.
4.
Vaske, Jerry J. & Jay Beaman. (2006). Lessons Learned in Detecting and Correcting Response Heaping: Conceptual, Methodological, and Empirical Observations. Human Dimensions of Wildlife. 11(4). 285–296. 13 indexed citations
5.
Beaman, Jay & Jerry J. Vaske. (2005). Reliability, accuracy and bias in survey estimates in tourism surveys.. Ereview of tourism research. 3(3). 54–60. 3 indexed citations
6.
Beaman, Jay, et al.. (2004). Tourism Surveys: Sample Size, Accuracy, Reliability, and Acceptable Error. Journal of Travel Research. 43(1). 67–74. 12 indexed citations
7.
Huan, Tzung‐Cheng, Jay Beaman, & Lori B. Shelby. (2004). No-escape natural disaster. Annals of Tourism Research. 31(2). 255–273. 115 indexed citations
8.
Huan, Tzung‐Cheng, Jay Beaman, & Metin Kozak. (2003). Issues in Modeling Repeat Leisure Consumption: Markov Modeling Examples. Loisir et Société / Society and Leisure. 26(1). 183–207. 3 indexed citations
9.
Huan, Tzung‐Cheng & Jay Beaman. (2003). CONTEXTS AND DYNAMICS OF SOCIAL INTERACTION AND INFORMATION SEARCH IN DECISION MAKING FOR DISCRETIONARY TRAVEL. Tourism Analysis. 8(2). 177–182. 23 indexed citations
10.
Kozak, Metin, Tzung‐Cheng Huan, & Jay Beaman. (2002). A Systematic Approach to Non-Repeat and Repeat Travel. Journal of Travel & Tourism Marketing. 12(4). 19–38. 36 indexed citations
11.
Beaman, Jay. (2002). Comment on "Digit Preference in Reported Harvest Among Illinois Waterfowl Hunters" by Craig A. Miller and William L. Anderson. Human Dimensions of Wildlife. 7(1). 67–72. 7 indexed citations
12.
Beaman, Jay, et al.. (1998). A Prototype Model for Estimating and Correcting Bias in Number Preference. Tourism Analysis. 2(2). 77–89. 11 indexed citations
13.
Beaman, Jay, et al.. (1997). Clarification of Cumulative Attractivity as a Concept and its Measurement: Comments on Lue, Crompton, and Stewart. Journal of Travel Research. 36(2). 74–77. 9 indexed citations
14.
Beaman, Jay, Jerry J. Vaske, Maureen P. Donnelly, & Michael J. Manfredo. (1997). Individual versus aggregate measures of digit preference. Human Dimensions of Wildlife. 2(1). 71–80. 12 indexed citations
15.
Simons, Ronald L., Christine A. Johnson, Jay Beaman, Rand D. Conger, & Les B. Whitbeck. (1996). Parents and peer group as mediators of the effect of community structure on adolescent problem behavior. American Journal of Community Psychology. 24(1). 145–171. 167 indexed citations
16.
Vaske, Jerry J., et al.. (1996). Response strategy, recall frame and digit preference in self—reports of angling participation. Human Dimensions of Wildlife. 1(4). 54–68. 15 indexed citations
17.
Beaman, Jay, Yoon Kim, & Stephen L. Smith. (1979). The effect of recreation supply on participation. Leisure Sciences. 2(1). 71–87. 15 indexed citations
18.
Beaman, Jay. (1975). Comments on the Paper “The Substitutability Concept: Implications for Recreation Research and Management,” by Hendee and Burdge. Journal of Leisure Research. 7(2). 146–152. 20 indexed citations
19.
Beaman, Jay. (1974). Distance and the ‘Reaction’ to Distance as a Function of Distance. Journal of Leisure Research. 6(3). 220–231. 30 indexed citations
20.
Beaman, Jay, et al.. (1970). Fundamentals of Nonparametric Statistics. 21 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.

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