John M. Miyamoto

1.1k total citations
29 papers, 794 citations indexed

About

John M. Miyamoto is a scholar working on General Decision Sciences, Economics and Econometrics and Management Science and Operations Research. According to data from OpenAlex, John M. Miyamoto has authored 29 papers receiving a total of 794 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in General Decision Sciences, 16 papers in Economics and Econometrics and 6 papers in Management Science and Operations Research. Recurrent topics in John M. Miyamoto's work include Decision-Making and Behavioral Economics (18 papers), Economic and Environmental Valuation (14 papers) and Health Systems, Economic Evaluations, Quality of Life (11 papers). John M. Miyamoto is often cited by papers focused on Decision-Making and Behavioral Economics (18 papers), Economic and Environmental Valuation (14 papers) and Health Systems, Economic Evaluations, Quality of Life (11 papers). John M. Miyamoto collaborates with scholars based in United States, Netherlands and Canada. John M. Miyamoto's co-authors include Stephen A. Eraker, Han Bleichrodt, Peter P. Wakker, Leslie Lenert, Hans Peters, Daniel Cher, Jason N. Doctor, Julie Feldman, Elizabeth F. Loftus and David H. Krantz and has published in prestigious journals such as Journal of the American Statistical Association, Management Science and Journal of Experimental Psychology General.

In The Last Decade

John M. Miyamoto

28 papers receiving 746 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. Miyamoto United States 15 571 311 214 90 68 29 794
James B. Bushyhead United States 7 120 0.2× 187 0.6× 59 0.3× 80 0.9× 48 0.7× 7 636
José‐María Abellán‐Perpiñán Spain 13 354 0.6× 122 0.4× 147 0.7× 30 0.3× 4 0.1× 31 462
Bertrand Munier France 12 186 0.3× 152 0.5× 22 0.1× 148 1.6× 56 0.8× 45 546
Ramesh K. Shukla United States 10 70 0.1× 22 0.1× 109 0.5× 100 1.1× 24 0.4× 17 467
Rosa Hendijani Iran 8 80 0.1× 24 0.1× 19 0.1× 63 0.7× 22 0.3× 23 348
Heidi Kramer United States 14 26 0.0× 13 0.0× 104 0.5× 21 0.2× 67 1.0× 27 497
Scott McLachlan United Kingdom 12 40 0.1× 7 0.0× 95 0.4× 40 0.4× 217 3.2× 30 583
Chris Wolfe United States 10 29 0.1× 30 0.1× 26 0.1× 81 0.9× 31 0.5× 41 421
Bernice B. Brown United States 5 46 0.1× 13 0.0× 35 0.2× 67 0.7× 23 0.3× 12 477
Barry Dewitt United States 9 126 0.2× 8 0.0× 72 0.3× 10 0.1× 13 0.2× 26 373

Countries citing papers authored by John M. Miyamoto

Since Specialization
Citations

This map shows the geographic impact of John M. Miyamoto'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. Miyamoto 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. Miyamoto more than expected).

Fields of papers citing papers by John M. Miyamoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

This figure shows the co-authorship network connecting the top 25 collaborators of John M. Miyamoto. A scholar is included among the top collaborators of John M. Miyamoto 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. Miyamoto. John M. Miyamoto 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.
Doctor, Jason N., John M. Miyamoto, & Han Bleichrodt. (2009). When are person tradeoffs valid?. Journal of Health Economics. 28(5). 1018–1027. 11 indexed citations
2.
Doctor, Jason N. & John M. Miyamoto. (2005). Person tradeoffs and the problem of risk. Expert Review of Pharmacoeconomics & Outcomes Research. 5(6). 677–682. 2 indexed citations
3.
Doctor, Jason N., Han Bleichrodt, John M. Miyamoto, Nancy Temkin, & Sureyya Dikmen. (2004). A new and more robust test of QALYs. Journal of Health Economics. 23(2). 353–367. 23 indexed citations
4.
Bleichrodt, Han & John M. Miyamoto. (2003). A Characterization of Quality-Adjusted Life-Years Under Cumulative Prospect Theory. Mathematics of Operations Research. 28(1). 181–193. 32 indexed citations
5.
Haddawy, Peter, et al.. (2002). Eliciting Utilities by Refining Theories of Monotonicity and Risk. 2 indexed citations
6.
Stalmeier, Peep F. M., Mary K. Goldstein, Ann Holmes, et al.. (2001). What Should Be Reported in a Methods Section on Utility Assessment?. Medical Decision Making. 21(3). 200–207. 43 indexed citations
7.
Miyamoto, John M.. (1999). Quality-Adjusted Life Years (QALY) Utility Models under Expected Utility and Rank Dependent Utility Assumptions. Journal of Mathematical Psychology. 43(2). 201–237. 36 indexed citations
8.
Miyamoto, John M., Peter P. Wakker, Han Bleichrodt, & Hans Peters. (1998). The Zero-Condition: A Simplifying Assumption in QALY Measurement and Multiattribute Utility. Management Science. 44(6). 839–849. 80 indexed citations
9.
Cher, Daniel, John M. Miyamoto, & Leslie Lenert. (1997). Incorporating Risk Attitude into Markov-process Decision Models:. Medical Decision Making. 17(3). 340–350. 51 indexed citations
10.
Miyamoto, John M. & Peter P. Wakker. (1996). Multiattribute Utility Theory without Expected Utility Foundations. Research portal (Tilburg University). 1 indexed citations
11.
Miyamoto, John M. & Peter P. Wakker. (1996). Multiattribute Utility Theory Without Expected Utility Foundations. Operations Research. 44(2). 313–326. 39 indexed citations
12.
13.
Yamagishi, Kimihiko & John M. Miyamoto. (1996). Asymmetries in strength of preference: A focus shift model of valence effects in difference judgments.. Journal of Experimental Psychology Learning Memory and Cognition. 22(2). 493–509. 1 indexed citations
14.
Miyamoto, John M. & Stephen A. Eraker. (1989). Parametric models of the utility of survival duration: Tests of axioms in a generic utility framework. Organizational Behavior and Human Decision Processes. 44(2). 166–202. 25 indexed citations
15.
Miyamoto, John M. & Stephen A. Eraker. (1988). A multiplicative model of the utility of survival duration and health quality.. Journal of Experimental Psychology General. 117(1). 3–20. 79 indexed citations
16.
Miyamoto, John M. & Stephen A. Eraker. (1988). A multiplicative model of the utility of survival duration and health quality.. Journal of Experimental Psychology General. 117(1). 3–20. 79 indexed citations
17.
Miyamoto, John M.. (1988). Generic utility theory: Measurement foundations and applications in multiattribute utility theory. Journal of Mathematical Psychology. 32(4). 357–404. 64 indexed citations
18.
Miyamoto, John M.. (1987). Constraints on the representation of gambles in prospect theory. Journal of Mathematical Psychology. 31(4). 410–418. 4 indexed citations
19.
Miyamoto, John M.. (1983). An axiomatization of the ratio/difference representation. Journal of Mathematical Psychology. 27(4). 439–455. 14 indexed citations
20.
Krantz, David H. & John M. Miyamoto. (1983). Priors and Likelihood Ratios as Evidence. Journal of the American Statistical Association. 78(382). 418–418. 6 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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