MOTOHASHI Eiji

Affiliation

Faculty of International Social Sciences, Division of International Social Sciences

Job Title

Associate Professor

Mail Address

E-mail address



ORCID  https://orcid.org/0000-0002-2088-1170

The Best Research Achievement in Research Career 【 display / non-display

  • 【Published Thesis】 市場構造の変化を考慮したブランド選択モデルによる購買履歴データの解析  2013.03

    【Awards】 2010年度統計関連学会連合大会コンペティション講演優秀報告賞  2010.09

    【Awards】 日本マーケティング・サイエンス学会若手研究者発表セッション審査員特別賞  2005.12

The Best Research Achievement in the last 5 years 【 display / non-display

Education 【 display / non-display

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    2013.3

    The Graduate University for Advanced Studies   Doctor Course   Completed

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    2009.9

    カリフォルニア大学アーバイン校   インフォメーション・アンド・コンピュータ・サイエンス研究科   統計学専攻   Master Course   Completed

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    2005.3

    Rikkyo University   Master Course   Completed

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    2003.3

    Rikkyo University   Graduated

Degree 【 display / non-display

  • Doctor of Philisophy - The Graduate University for Advanced Studies

Campus Career 【 display / non-display

  • 2014.4
     
     

    Duty   Yokohama National UniversityFaculty of International Social Sciences   Division of International Social Sciences   Associate Professor  

  • 2013.4
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    2014.3

    Duty   Yokohama National UniversityFaculty of International Social Sciences   Division of International Social Sciences   Lecturer  

  • 2021.4
     
     

    Concurrently   Yokohama National UniversityInterfaculty Graduate School of Innovative and Practical Studies   Associate Professor  

  • 2017.4
     
     

    Concurrently   Yokohama National UniversityCollege of Business Administration   Department of Business Administration   Specialization in Management Science    Associate Professor  

  • 2014.4
     
     

    Concurrently   Yokohama National UniversityGraduate School of International Social Sciences   Department of Business Administration   Associate Professor  

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External Career 【 display / non-display

  • 2010.4
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    2013.3

      Special researcher of the Japan Society for the Promotion of Science  

Academic Society Affiliations 【 display / non-display

  • 2008
     
     
     

    INFORMS

  • 2008
     
     
     

    American Statistical Association

  • 2004
     
     
     

    Japan Institute of Marketing Science

  • 2009
     
     
     

    Japan Statistical Society

  • 2016.6
     
     
     

    人工知能学会

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Research Areas 【 display / non-display

  • Humanities & Social Sciences / Commerce

 

Books 【 display / non-display

  • Rで学ぶ統計データ分析

    本橋 永至( Role: Sole author)

    オーム社  ( ISBN:9784274217814

    Amazon

     More details

    Total pages:262   Language:Japanese Book type:Textbook, survey, introduction

Papers 【 display / non-display

  • スタッキングアルゴリズムを用いた特許拒絶理由類型の判別

    本橋永至, 髙橋省吾, 真鍋誠司, 鈴井智史, 井田英紀, 松井重明

    横浜経営研究   2022.3

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    Language:Japanese   Publishing type:Research paper (bulletin of university, research institution)   Joint Work  

  • Contribution Analysis of Video Advertising with Topic Model and Ensemble Learning

    Eiji Sakihama, Yasukazu Kawasaki, Eiji Motohashi

    Artificial Intelligence   36 ( 3 )   1 - 8   2021.5  [Reviewed]

    DOI CiNii Research

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society for Artificial Intelligence   Joint Work  

    Other Link: https://www.jstage.jst.go.jp/article/tjsai/36/3/36_36-3_B-K91/_pdf/-char/ja

  • Emergent-Nature Consumers as the Source of Innovation for Rapid Change::Analyses of Social Media Usage during the COVID-19 Outbreak

    Akihiro Nishimoto, Sotaro Katsumata, Eiji Motohashi

    Japan Marketing Journal   40 ( 4 )   44 - 57   2021.3  [Reviewed]

    DOI CiNii Research

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japan Marketing Academy   Joint Work  

    <p>The aim of this study is to show the value of emergent-nature consumers (ENCs) as a source of next-generation innovation during periods of rapid change such as the COVID-19 outbreak. We collected application startup logs from smartphones and conducted a survey during the COVID-19 pandemic crisis. We found that ENCs were more adaptable to environmental change due to the COVID-19 outbreak than lead-users (LUs). In addition, ENCs increased or decreased their usage of social media less than LUs and general-users (GUs), and used these media broadly during the COVID-19 crisis. These results suggest that ENCs use their social media more broadly and frequently than other consumers.</p>

    Other Link: https://ci.nii.ac.jp/naid/130008009636

  • The Empirical Study of Effects of Image Components in Ad Creative to Click by Computer Vision

    Toyosawa-Sakihama Eiji, Kawasaki Yasukazu, Motohashi Eiji

    Ouyou toukeigaku   48 ( 3 )   59 - 70   2020.3  [Reviewed]

    DOI

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japanese Society of Applied Statistics   Joint Work  

    Other Link: https://ci.nii.ac.jp/naid/130007833658

  • A Study on Statistical Forecasting Methods of Foreign Patent Cost

    TAKAHASHI Shogo, MANABE Seiji, MOTOHASHI Eiji, KISHIMOTO Shigeo, HAGIHARA Toru, KIM Eunhun

    Journal of the Japan Society for Intellectual Production   16 ( 1 )   35 - 43   2020.1  [Reviewed]

    DOI CiNii Research

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japan Society for Intellectual Production   Joint Work  

    <p>Filing a foreign patent is extremely expensive. The indirect costs have a major impact on corporate earnings. Therefore, firms must manage the cost of filing for a foreign patent by forecasting such costs in the forthcoming fiscal years and including them into their management strategy. However, costs vary with the timing and number of inventions, thus complicating cost forecasting. Thus, firms need to use simple methods to predict foreign patent costs for the fiscal year in question by referencing the previous year's actual numbers. The present study compares multiple statistical forecasting methods to find a more accurate method of estimating foreign patent costs, particularly for the United States, and to apply this method to corporate practice. The study found a precise method of forecasting future overseas patent costs by selecting the most appropriate methodology for the existing circumstances from among multiple forecasting methodologies by using a certain algorithm and developing a forecasting system.</p>

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Charge of on-campus class subject 【 display / non-display

  • 2022   Seminar 2b (Master's Programs)

    Graduate School of International Social Sciences

  • 2022   Seminar 2a (Master's Programs)

    Graduate School of International Social Sciences

  • 2022   Seminar : Marketing Science 1

    College of Business Administration

  • 2022   Statistics2-A

    Liberal Arts Education

  • 2022   Market analysis

    Graduate School of International Social Sciences

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