World's Best Scientists 2026 revealed!

D-Index & Metrics

Economics and Finance

D-Index
53
Citations
8406
World Ranking
1205
National Ranking
7

Mika Goto publication distribution in Economics and Finance in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Economics and Finance in 2026. The highlighted bar marks where Mika Goto sits on this spectrum.

42–46 publications: 1 scientists 47–51 publications: 12 scientists 52–56 publications: 7 scientists 57–61 publications: 23 scientists 62–66 publications: 32 scientists 67–71 publications: 36 scientists 72–76 publications: 56 scientists 77–81 publications: 57 scientists 82–86 publications: 70 scientists 87–91 publications: 86 scientists 92–96 publications: 72 scientists 97–101 publications: 106 scientists 102–106 publications: 97 scientists 107–111 publications: 96 scientists 112–116 publications: 101 scientists 117–121 publications: 103 scientists 122–126 publications: 102 scientists 127–131 publications: 108 scientists 132–136 publications: 107 scientists 137–141 publications: 111 scientists 142–146 publications: 94 scientists 147–151 publications: 96 scientists 152–156 publications: 100 scientists 157–161 publications: 74 scientists 162–166 publications: 68 scientists 167–171 publications: 91 scientists 172–176 publications: 76 scientists 177–181 publications: 75 scientists 182–186 publications: 61 scientists 187–191 publications: 66 scientists 192–196 publications: 68 scientists 197–201 publications: 71 scientists 202–206 publications: 60 scientists 207–211 publications: 56 scientists 212–216 publications: 44 scientists 217–221 publications: 51 scientists 222–226 publications: 65 scientists 227–231 publications: 48 scientists 232–236 publications: 59 scientists 237–241 publications: 37 scientists 242–246 publications: 37 scientists 247–251 publications: 41 scientists 252–256 publications: 43 scientists 257–261 publications: 33 scientists 262–266 publications: 34 scientists 267–271 publications: 39 scientists 272–276 publications: 25 scientists 277–281 publications: 29 scientists 282–286 publications: 29 scientists 287–291 publications: 26 scientists 292–296 publications: 31 scientists 297–301 publications: 31 scientists 302–306 publications: 24 scientists 307–311 publications: 28 scientists 312–316 publications: 24 scientists 317–321 publications: 13 scientists 322–326 publications: 14 scientists 327–331 publications: 25 scientists 332–336 publications: 18 scientists 337–341 publications: 16 scientists 342–346 publications: 18 scientists 347–351 publications: 15 scientists 352–356 publications: 17 scientists 357–361 publications: 19 scientists 362–366 publications: 16 scientists 367–371 publications: 17 scientists 372–376 publications: 7 scientists 377–381 publications: 18 scientists 382–386 publications: 13 scientists 387–391 publications: 19 scientists 392–396 publications: 9 scientists 397–401 publications: 10 scientists 402–406 publications: 13 scientists 407–411 publications: 13 scientists 412–416 publications: 5 scientists 417–421 publications: 10 scientists 422–426 publications: 6 scientists 427–431 publications: 12 scientists 432–436 publications: 9 scientists 437–441 publications: 9 scientists 442–446 publications: 10 scientists 447–451 publications: 12 scientists 452–456 publications: 8 scientists 457–461 publications: 4 scientists 462–466 publications: 7 scientists 467–471 publications: 4 scientists 472–476 publications: 5 scientists 477–481 publications: 6 scientists 482–486 publications: 7 scientists 487–491 publications: 8 scientists 492–496 publications: 5 scientists 497–501 publications: 4 scientists 502–506 publications: 4 scientists 507–511 publications: 5 scientists 512–516 publications: 7 scientists 517–520 publications: 7 scientists 521+ publications: 99 scientists
42 publications 521+

This scientist: 144 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 521 publications or more.

Mika Goto D-index placement in Economics and Finance in 2026

The chart shows the D-index (discipline H-index) distribution of Economics and Finance scientists ranked by Research.com in 2026. The highlighted bar marks where Mika Goto sits on this spectrum.

30 D-Index: 126 scientists 31 D-Index: 147 scientists 32 D-Index: 157 scientists 33 D-Index: 178 scientists 34 D-Index: 171 scientists 35 D-Index: 141 scientists 36 D-Index: 132 scientists 37 D-Index: 129 scientists 38 D-Index: 130 scientists 39 D-Index: 120 scientists 40 D-Index: 117 scientists 41 D-Index: 113 scientists 42 D-Index: 114 scientists 43 D-Index: 97 scientists 44 D-Index: 115 scientists 45 D-Index: 86 scientists 46 D-Index: 78 scientists 47 D-Index: 83 scientists 48 D-Index: 62 scientists 49 D-Index: 74 scientists 50 D-Index: 50 scientists 51 D-Index: 66 scientists 52 D-Index: 69 scientists 53 D-Index: 55 scientists 54 D-Index: 67 scientists 55 D-Index: 61 scientists 56 D-Index: 62 scientists 57 D-Index: 45 scientists 58 D-Index: 34 scientists 59 D-Index: 47 scientists 60 D-Index: 46 scientists 61 D-Index: 36 scientists 62 D-Index: 37 scientists 63 D-Index: 56 scientists 64 D-Index: 50 scientists 65 D-Index: 32 scientists 66 D-Index: 28 scientists 67 D-Index: 30 scientists 68 D-Index: 24 scientists 69 D-Index: 25 scientists 70 D-Index: 22 scientists 71 D-Index: 21 scientists 72 D-Index: 26 scientists 73 D-Index: 24 scientists 74 D-Index: 23 scientists 75 D-Index: 12 scientists 76 D-Index: 14 scientists 77 D-Index: 15 scientists 78 D-Index: 15 scientists 79 D-Index: 17 scientists 80 D-Index: 17 scientists 81 D-Index: 11 scientists 82 D-Index: 10 scientists 83 D-Index: 16 scientists 84 D-Index: 11 scientists 85 D-Index: 5 scientists 86 D-Index: 9 scientists 87 D-Index: 13 scientists 88 D-Index: 9 scientists 89 D-Index: 7 scientists 90 D-Index: 6 scientists 91 D-Index: 4 scientists 92 D-Index: 8 scientists 93 D-Index: 10 scientists 94 D-Index: 11 scientists 95 D-Index: 6 scientists 96 D-Index: 4 scientists 97 D-Index: 4 scientists 98 D-Index: 6 scientists 99 D-Index: 6 scientists 100 D-Index: 8 scientists 101+ D-Index: 100 scientists
30 D-Index 101+

This scientist: 53 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 101 D-Index or more.

Overview

Mika Goto is affiliated with the Tokyo Institute of Technology in Japan. Their research predominantly spans the field of Engineering, with a specialized focus on Electrical and Electronic Engineering as well as Management Science and Operations Research. Additional subfields in their work include Automotive Engineering, Strategy and Management, and Economics and Econometrics.

The main research topics explored by Mika Goto include Smart Grid Energy Management, Electric Vehicles and Infrastructure, and Efficiency Analysis using Data Envelopment Analysis (DEA). Their work also covers Energy Load and Power Forecasting, Transportation and Mobility Innovations, Advanced Battery Technologies Research, and Transport and Economic Policies.

Frequent collaborators in Mika Goto's research efforts are Reza Nadimi, Toshiyuki Sueyoshi, Hiroshi Kitamura, Kenji Tanaka, and Daishi Sagawa.

Their research has been published in multiple venues, with the most frequent publication outlets being:

  • Energies
  • Energy
  • Applied Energy
  • SSRN Electronic Journal
  • Renewable and Sustainable Energy Reviews

Selected papers authored or coauthored by Mika Goto include:

  • "Sustainable development and corporate social responsibility in Japanese manufacturing companies," 2020, Sustainable Development
  • "Challenges and opportunities of blockchain energy applications: Interrelatedness among technological, economic, social, environmental, and institutional dimensions," 2022, Renewable and Sustainable Energy Reviews
  • "Feasibility of vehicle-to-grid (V2G) implementation in Japan: A regional analysis of the electricity supply and demand adjustment market," 2024, Energy
  • "Efficiency assessment of Japanese National Railways before and after privatization and divestiture using data envelopment analysis," 2022, Transport Policy
  • "Energy Intensity, Energy Efficiency and Economic Growth among OECD Nations from 2000 to 2019," 2023, Energies

Best Publications

  • A literature study for DEA applied to energy and environment

    Toshiyuki Sueyoshi;Yan Yuan;Mika Goto

  • DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation

    Toshiyuki Sueyoshi;Mika Goto

  • Performance analysis of US coal-fired power plants by measuring three DEA efficiencies

    Toshiyuki Sueyoshi;Toshiyuki Sueyoshi;Mika Goto;Takahiro Ueno

  • Measurement of Dynamic Efficiency in Production : An Application of Data Envelopment Analysis to Japanese Electric Utilities

    Jiro Nemoto;Mika Goto

  • Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies

    Jiro Nemoto;Mika Goto

  • Data envelopment analysis for environmental assessment: Comparison between public and private ownership in petroleum industry

    Toshiyuki Sueyoshi;Mika Goto

  • Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: Comparison between Japanese electric power industry and manufacturing industries

    Toshiyuki Sueyoshi;Mika Goto

  • Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA-Discriminant Analysis (DA)

    Toshiyuki Sueyoshi;Mika Goto

  • Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis

    Toshiyuki Sueyoshi;Toshiyuki Sueyoshi;Mika Goto

  • Measurement of Returns to Scale and Damages to Scale for DEA-based operational and environmental assessment: How to manage desirable (good) and undesirable (bad) outputs?

    Toshiyuki Sueyoshi;Mika Goto

  • Exploring blockchain for the energy transition: Opportunities and challenges based on a case study in Japan

    A. Ahl;M. Yarime;M. Yarime;M. Yarime;M. Goto;Shauhrat S. Chopra

  • Photovoltaic power stations in Germany and the United States: A comparative study by data envelopment analysis

    Toshiyuki Sueyoshi;Mika Goto

  • Comparison of Productive and Cost Efficiencies among Japanese and US Electric Utilities

    mika goto;miki tsutsui

  • Can environmental investment and expenditure enhance financial performance of US electric utility firms under the clean air act amendment of 1990

    Toshiyuki Sueyoshi;Toshiyuki Sueyoshi;Mika Goto

  • DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations

    Toshiyuki Sueyoshi;Mika Goto

  • DEA environmental assessment of coal fired power plants: Methodological comparison between radial and non-radial models

    Toshiyuki Sueyoshi;Mika Goto

  • DEA window analysis for environmental assessment in a dynamic time shift: Performance assessment of U.S. coal-fired power plants

    Toshiyuki Sueyoshi;Mika Goto;Manabu Sugiyama

  • Methodological comparison between two unified (operational and environmental) efficiency measurements for environmental assessment

    Toshiyuki Sueyoshi;Mika Goto

  • Slack-adjusted DEA for time series analysis: Performance measurement of Japanese electric power generation industry in 1984–1993

    Toshiyuki Sueyoshi;Mika Goto

  • Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: A use of Data Envelopment Analysis with strong complementary slackness condition

    Toshiyuki Sueyoshi;Mika Goto

  • Returns to scale and damages to scale under natural and managerial disposability: Strategy, efficiency and competitiveness of petroleum firms

    Toshiyuki Sueyoshi;Mika Goto

Frequent Co-Authors

Toshiyuki Sueyoshi
Toshiyuki Sueyoshi New Mexico Institute of Mining and Technology
George Andrew Karolyi
George Andrew Karolyi Cornell University
Jennifer Shang
Jennifer Shang University of Pittsburgh

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