John M. Ennis

1.3k total citations
44 papers, 812 citations indexed

About

John M. Ennis is a scholar working on Food Science, Nutrition and Dietetics and Statistics and Probability. According to data from OpenAlex, John M. Ennis has authored 44 papers receiving a total of 812 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Food Science, 13 papers in Nutrition and Dietetics and 9 papers in Statistics and Probability. Recurrent topics in John M. Ennis's work include Sensory Analysis and Statistical Methods (30 papers), Biochemical Analysis and Sensing Techniques (13 papers) and Multisensory perception and integration (8 papers). John M. Ennis is often cited by papers focused on Sensory Analysis and Statistical Methods (30 papers), Biochemical Analysis and Sensing Techniques (13 papers) and Multisensory perception and integration (8 papers). John M. Ennis collaborates with scholars based in United States, Denmark and Netherlands. John M. Ennis's co-authors include Daniel M. Ennis, Brian J. Spiering, F. Gregory Ashby, M.A. Drake, Benoı̂t Rousseau, S.M. Jervis, Rune Haubo Bojesen Christensen, Michael O’Mahony, Witoon Prinyawiwatkul and Jian Bi and has published in prestigious journals such as Psychological Review, Food Quality and Preference and Foods.

In The Last Decade

John M. Ennis

43 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John M. Ennis United States 15 493 280 158 149 92 44 812
Jennifer A. Stillman New Zealand 18 184 0.4× 234 0.8× 286 1.8× 204 1.4× 21 0.2× 35 882
Daniel M. Ennis United States 23 1.3k 2.6× 802 2.9× 130 0.8× 426 2.9× 183 2.0× 83 1.8k
Robert Frank United States 19 375 0.8× 542 1.9× 182 1.2× 295 2.0× 90 1.0× 66 1.5k
Benoı̂t Rousseau United States 14 557 1.1× 403 1.4× 14 0.1× 176 1.2× 90 1.0× 22 611
Pauline Faye France 9 241 0.5× 139 0.5× 54 0.3× 126 0.8× 42 0.5× 14 377
Richard Popper United States 13 275 0.6× 132 0.5× 54 0.3× 103 0.7× 54 0.6× 28 576
Christelle Chrea Switzerland 10 465 0.9× 291 1.0× 97 0.6× 254 1.7× 38 0.4× 12 909
Wendy V. Parr New Zealand 19 1.1k 2.1× 177 0.6× 69 0.4× 200 1.3× 32 0.3× 40 1.4k
David DiBattista Canada 16 77 0.2× 162 0.6× 40 0.3× 18 0.1× 56 0.6× 51 754
Michael Meyners Germany 16 1.0k 2.1× 476 1.7× 12 0.1× 209 1.4× 214 2.3× 47 1.3k

Countries citing papers authored by John M. Ennis

Since Specialization
Citations

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

Fields of papers citing papers by John M. Ennis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Ennis. 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 M. Ennis. The network helps show where John M. Ennis may publish in the future.

Co-authorship network of co-authors of John M. Ennis

This figure shows the co-authorship network connecting the top 25 collaborators of John M. Ennis. A scholar is included among the top collaborators of John M. Ennis 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 M. Ennis. John M. Ennis 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.
Brooks, D., et al.. (2024). Using Web3 technologies to represent personalized consumer taste preferences in whiskies. Food Quality and Preference. 118. 105201–105201. 4 indexed citations
2.
Ennis, John M., et al.. (2023). Understanding the Effects of Smart-Speaker-Based Surveys on Panelist Experience in Immersive Consumer Testing. Foods. 12(13). 2537–2537. 2 indexed citations
3.
Ennis, John M., et al.. (2022). Sensory interaction effects between capsicum heat and seasoning ingredients applied to unsalted potato chips. Food Quality and Preference. 102. 104682–104682. 1 indexed citations
4.
Ennis, John M., et al.. (2021). Emotional profiles elicited from orthonasal and retronasal perceptions of food (fruit) and non‐food (floral) aromas. Flavour and Fragrance Journal. 36(4). 446–456. 1 indexed citations
5.
Harwood, William S., et al.. (2020). Comparison of preference mapping with projective mapping for characterizing consumer perception of brewed black coffees. Journal of Sensory Studies. 35(3). 18 indexed citations
6.
Ennis, John M., Benoı̂t Rousseau, & Daniel M. Ennis. (2014). Sensory Difference Tests as Measurement Instruments: a Review of Recent Advances. Journal of Sensory Studies. 29(2). 89–102. 30 indexed citations
7.
Ennis, Daniel M. & John M. Ennis. (2013). Analysis and Thurstonian Scaling of Applicability Scores. Journal of Sensory Studies. 28(3). 188–193. 19 indexed citations
8.
Ennis, John M., et al.. (2013). Reconsidering the Specified Tetrad Test. Journal of Sensory Studies. 28(6). 445–449. 7 indexed citations
9.
Ennis, John M. & Rune Haubo Bojesen Christensen. (2013). Precision of measurement in Tetrad testing. Food Quality and Preference. 32. 98–106. 16 indexed citations
10.
Rousseau, Benoı̂t, et al.. (2013). Transitioning from proportion of discriminators to a more meaningful measure of sensory difference. Food Quality and Preference. 32. 77–82. 18 indexed citations
11.
Jervis, S.M., John M. Ennis, & M.A. Drake. (2012). A Comparison of Adaptive Choice‐Based Conjoint and Choice‐Based Conjoint to Determine Key Choice Attributes of Sour Cream with Limited Sample Size. Journal of Sensory Studies. 27(6). 451–462. 59 indexed citations
12.
Ennis, John M., et al.. (2012). Assignment-minimum clique coverings. ACM Journal of Experimental Algorithmics. 17. 1 indexed citations
13.
Ennis, John M. & Daniel M. Ennis. (2012). A COMPARISON OF THREE COMMONLY USED METHODS FOR TREATING NO PREFERENCE VOTES. Journal of Sensory Studies. 27(2). 123–129. 20 indexed citations
14.
Ennis, John M. & Daniel M. Ennis. (2012). JUSTIFYING COUNT‐BASED COMPARISONS. Journal of Sensory Studies. 27(2). 130–136. 2 indexed citations
15.
Ennis, John M. & Guofang Wei. (2010). Describing the universal cover of a noncompact limit. Geometry & Topology. 14(4). 2479–2496. 1 indexed citations
16.
Ashby, F. Gregory, John M. Ennis, & Brian J. Spiering. (2007). A neurobiological theory of automaticity in perceptual categorization.. Psychological Review. 114(3). 632–656. 197 indexed citations
17.
Ennis, John M. & Guofang Wei. (2006). Describing the universal cover of a compact limit. Differential Geometry and its Applications. 24(5). 554–562. 6 indexed citations
18.
Robinson, R. H., Helene Murray, John M. Ennis, & Chery Smith. (2002). Promotion of sustainably produced foods: Customer response in Minnesota grocery stores. American Journal of Alternative Agriculture. 17(2). 96–104. 6 indexed citations
19.
Bi, Jian, et al.. (2000). Replicated difference and preference tests: how to account for inter-trial variation. Food Quality and Preference. 11(4). 269–273. 17 indexed citations
20.
Ennis, John M., et al.. (1998). Thurstonian models for variants of the method of tetrads. British Journal of Mathematical and Statistical Psychology. 51(2). 205–215. 57 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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