Naoki Watanabe, Ph.D.

 

Graduate School of Business Administration, Keio University

4-1-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8526, Japan

 

Email: naoki50<AT>keio.jp (replace <AT> with @)

 

 

<Academic Degree>

2003.8, PhD in Economics, SUNY at Stony Brook, USA

(committee: Yair Tauman, Pradeep Dubey, Thomas Muench, Abraham Neyman)

 

 

<Academic Positions Held>

2023.4-present:  professor, Keio Univ, Business Administration, Japan

2016.4-2023.3:   associate professor, Keio Univ, Business Administration, Japan

2011.10-2016.3:  associate professor, Univ of Tsukuba, Eng, Info & Sys, Japan

2010.1-2011.9:   associate professor, Univ of Tsukuba, Sys & Info Eng, Japan

2006.4-2010.1:   assistant professor, Univ of Tsukuba, Sys & Info Eng, Japan

2005.4-2006.3:   assistant professor, Hitotsubashi Univ, Econ, Japan

2004.1-2005.3:   COE research fellow, Kyoto Univ, Econ and KIER, Japan

 

 

<Published Papers Written in English>

[1] gResale-Proof Trades of Data under Budget Constraints,h

with Kazuhito Ogawa,

Proceedings of 2023 International Conference on Big Data (Big Data 2023), IEEE Xplore, 5665-5673, 2023

 

[2] gConducting an Experiment at Multiple Site with Small Subject Pools: How is raven Score Effective as a Covariate?h

with Kazuhito Ogawa, Yusuke Osaki, Tetsuya Kawamura, Hiromasa Takahashi, Satoshi Taguchi, Yoichiro Fujii,

Kengo Kurosaka, Iyori Kohei,

Proceedings of 2023 International Conference on Big Data (Big Data 2023), IEEE Xplore, 3202-3211, 2023

 

[3] gEfficiency in a College Admission experiment: A Simulation Using Cognitive Ability Scores,h

with Tetsuya Kawamura, Kazuhito Ogawa,

Proceedings of 2023 International Conference on Big Data (Big Data 2023), IEEE Xplore, 3231-3236, 2023

 

[4] gA Subject Experiment of an Approximate DGS Algorithm: Price Increment, Allocative Efficiency, and Seller's Revenue,h

with Yoichi Izunaga, Satoshi Takahashi,

Proceedings of 2022 International Conference on Big Data (Big Data 2022), IEEE Xplore, 3273-3280, 2022

(presentation slide)

 

[5] gA Model of Pricing Data and their Constituent Variables Traded in Two-Sided Markets with Resale: A Subject Experiment,h

with Toshihiko Nanba, Kazuhito Ogawa, Teruaki Hayashi, Hiroki Sakaji,

Proceedings of 2022 International Conference on Big Data (Big Data 2022), IEEE Xplore, 3288-3294, 2022

(presentation slide, typos corrected on Aug 15, 2023)

 

[6] gFeedback Information on Cumulative Payoff in a Bandit Experiment: Meaningful Learning in Weighted Voting,h

with Kazuhito Ogawa,

Proceedings of 2022 International Conference on Big Data (Big Data 2022), IEEE Xplore, 3295-3299, 2022

 

[7] gReconsidering Meaningful Learning in a Bandit Experiment on Weighted Voting: Subjectsf Search Behavior,h

Review of Socionetwork Strategies 16, 81-107, 2022

discussion paper version: Kansai University RISS Discussion Paper Series No.62, June 2018

 

[8] gAn Experimental Study of VCG Mechanism for Multi-unit Auctions: Competing with Machine Bidders,h

with Satoshi Takahashi and Yoichi Izunaga, Evolutionary and Institutional Economics Review 9, 97-117, 2022

discussion paper version: Kansai University RISS Discussion Paper Series No.88, July 2020

(presentation slide)

 

[9] gA Numerical Study with Experimental Data on Risk-Averse Subcontractors in Procurement Auctions

with Subcontract Bids,h

Proceedings of 2021 IEEE International Conference on Big Data, IEEE Xplore, 3495-3499, 2022

@@ (presentation slide)

 

[10] gA Simple Numerical Evaluation of the Incentive Contracts for Japanfs Defense Equipment,h

with Motohiko Kasai, Review of Socionetwork Strategies 15, 575-596, 2021

 

[11] gVCG Mechanism for Multi-unit Auctions and Appearance of Information: An Experiment,"

with Satoshi Takahashi and Yoichi Izunaga, Evolutionary and Institutional Economics Review 16, 357-374, 2019

a brief note version is available as Kansai University RISS Discussion Paper Series No. 68, January 2019

 

[12] gFarsighted Stability in Patent Licensing: An Abstract Game Approach,h

with T. Hirai and S. Muto, Games and Economic Behavior 118, 141-160, 2019

a manuscript version is available here.

(presentation slide)

 

[13] gAn Approximation Algorithm for Multi-unit Auctions: Numerical and Subject Experiments,h

with Satoshi Takahashi and Yoichi Izunaga, Operations Research and Decisions 28, 75-95, 2018

Table 3A. is not the correct one. See the Appendix of the discussion paper version for the correct one:

Kansai University RISS Discussion Paper Series No. 50, November 2017

 

[14] gvon Neumann-Morgenstern Stable Sets of a Patent Licensing Game: The Existence Proof,h

with Toshiyuki Hirai, Mathematical Social Sciences 94, 1-12 (lead article), 2018

(presentation slide)

 

[15] gMeaningful Learning in Weighted Voting Games: An Experiment,ff

with Eric Guerci and Nobuyuki Hanaki, Theory and Decision 83, 131-153, 2017

 

[16] gThe Kernel of a Patent Licensing Game: The Optimal Number of Licensees,h with Shin Kishimoto,

Mathematical Social Sciences 86 37-50, 2017

 

[17] gA Methodological Note on a Weighted Voting Experiment,h with Eric Guerci and Nobuyuki Hanaki,

Gabriele Esposito, Xiaoyan Lu, Social Choice and Welfare 43, 827-850, 2014

 

[18] gCoalition Formation in a Weighted Voting Experiment,h

Japanese Journal of Electoral Studies 30, 56-67, 2014

 

[19] gAn Experimental Study of Bidding Behavior in Procurement Auctions with Subcontract Bids:

Profits, Efficiency, and Policy Implications,h with Jun Nakabayashi,

Proceedings of the SICE Annual Conference 2011, IEEE Xplore, 1202-1207, 2011

 

[20] gBargaining Outcomes in Patent Licensing: Asymptotic Results in a General Cournot Market,h

with Shin Kishimoto and Shigeo Muto, Mathematical Social Sciences 61, 114-123, 2011

 

[21] gQuality Adjusted Prices of Japanese Mobile Phone Handsets and Carriersf Strategies,h

with Ryo Nakajima and Takanori Ida, Review of Industrial Organization 36, 391-314, 2010

 

[22] gStable Profit Sharing in Patent Licensing: General Bargaining Outcomes,ff

with Shigeo Muto, International Journal of Game Theory 37, 505-523, 2008

 

[23] gThe Shapley Value of a Patent Licensing Game: Asymptotic Equivalence to

Noncooperative Results,ff with Yair Tauman, Economic Theory 30, 135-149, 2007

 

[24] gLicensing Agreements as Bargaining Outcomes: General Results and Two Examples,h

with Shigeo Muto, Advances in Mathematical Economics 8, 433-447, 2006

 

[25] gA Note on the Profit Distribution among a Manufacturer and its Retailers,ff

Economics Bulletin 12(16), 1-6, 2005

 

[26] gOn the Neutrality of Coalition Formation in a Pure Bargaining Problem,ff

with Haruo Imai, Japanese Economic Review 56, 352-362, 2005.

 

 

<Working Papers>

(1)   A Mouse-Tracking Bandit Experiment on Meaningful Learning in Weighted Voting

Presentation Slides (European Meeting on Game Theory (SING17), University of Padova (online), Italy, last updated on August 25, 2023)

(2) Can Subjects Meaningfully Learn Actual Voting Powers?: Cognitive Ability and Feedback Information

Presentation Slides (Japanese Economic Association, the Autumnal Meeting, Osaka University (online), on October 10, 2021, updated on January 20, 2022)

(3) Two Topics on Patent Licensing Games: Stable Sets and Farsighted Stability

Presentation Slides (Workshop on Innovation and Licensing, 32nd Intfl Conference on game Theory, Stony Brook (online), July 16 in 2021)

(4) A School Choice Experiment: Cognitive Ability and Information

Presentation Slides (SAET annual meeting, Seoul National University (online), on June 17 in 2021)

(5) Conducting Economic Experiments at Multiple Sites: Subjectsf Cognitive Ability and Attribute Information

Presentation Slides (Intfl Workshop on Lab and Field Experiments, Osaka University (online), on March 18 in 2021)

(6) Franchise Fee is not Advantageous

Presentation Slides (in Japanese, 25th DC Conference, Japan, Osaka University of Economics, October 11, 2019)

 

 

ƒInternational Workshops Organized

 

Large-Scale Data Utilization in Economics of Information and Management Sciences: Theory, Computation, and Experiment

(in IEEE International Conference on Big Data 2023, 15-18 December, 2023, Sorrento, Italy)

 

New Strands of Usage of Big Data in Medical Systems, Market and Institutional Design, and Economic Theory

(in IEEE International Conference on Big Data, 2022, 17-20 December, 2023, Osaka, Japan)

 

<Domestic Workshops Organized>

Workshop on Microeconomic Analysis of Social Systems and Institutions: Theory, Experiment, and Empirical Studies

(in Japanese)

 

 

<Referees for Journal Articles Written in English>

Games and Economic Behavior, Economic Theory, European Journal of Operational Research, International Journal of Game Theory,

Social Choice and Welfare, Group Decision and Negotiation, Journal of Institutional and Theoretical Economics, Economics Letters,

International Journal of Industrial Organization, Review of Industrial Organization, Journal of Industry, Competition and Trade,

Japan and the World Economy, Japanese Economic Review, Hitotsubashi Journal of Economics, Review of Socionetwork Strategies

 

 

<Courses Taught>

Special Topics in Management Science (PhD), Workshop on Data Analysis (EMBA), Information and Decision Making (MBA),

Management Science and Decision Making (MBA, EMBA), Management Science (MBA, EMBA), Game Theory (G),

Game Theory: Applications (G), Industrial Organization (G), Microeconomics (U), Statistics (U), Programming (Java, U),

Information Literacy (U), Contract Theory (U), Law and Economics (U), Economic Experiments (U), Public Economics (U),

Introduction to Multi-Agent Simulation (artisoc, U),

 

 

Studentsf Presentation Slides (Management Science, in Japanese)

(2017)

group1, group2, group3, group4, group5, group6

group7, group8, group9, group10, group11, group12

 

(2018)

group1, group2, group3, group4, group5, group6

group7, group8, group9, group10, group11, group12

 

(2019)

group1, group2, group3, group4, group5, group6

group7, group8, group9, group10, group11, group12

 

 

Slides for Classroom Discussion

(Management Science, 2020-present, in Japanese)

note1: A Personnel Allocation Problem in a Japanese Electric Manufacturer: Examining Algorithmic Solutions

          (typos corrected on 4 Sept, 2023)

note2: A Personnel Allocation Problem in a Japanese Electric Manufacturer: Examining Algorithmic Solutions

note3: A Green Tea Wholesaler in Makinohara (revised on Sept. 17, 2021; one page added)

Leaf Tea and Powdered Tea (Naoya Kawamura, esq., in Japanese, updated on 17 Sept, 2019)

How to Brew Japanese Green Tea (in English, last updated on 16 Feb, 2018)

note4: Subcontractorsf Behavior under Procurement Auctions

note5: Drill; final examination in 2017

note6: Representation of Strategic Situations: An Introduction to Noncooperative Game Theory

note7: Wrap-up 1, notes and comments in 2020

note8: Incentive Provision and Risk Bearing: The Applicability of Contract Theory Reconsidered I

note9: Hidden Information and Sorting Potential Customers: The Applicability of Contract Theory Reconsidered II

          (last updated on 21 Sept, 2022)

note10: Hold-Up Problem: Underinvestment in Parts Transactions

note11: Future Design, Wrap-up 2

note12: Exam and Feedback; final examination 2020

 

Extra1: Interfirm Relationship and Video game Development in the Home Video Industry: Japan in 1990s

           (uploaded on 6 Sept, 2023)

Extra2: R&D Incentives and Organizational Structures

           (uploaded on 18 Nov, 2023)

 

(Information and Decision-Making, 2020-present, in Japanese)

Part1: Game Theory and Organizational Economics for MBA, in Japanese

Meaningful Learning

Note1: Relational Contract 1: Long-term Trading Practice as Nash Equilibrium: A Constrained Case

Note2: Relational Contract 2: Long-term Trading Practice as Nash Equilibrium: Pareto Efficiency

Note3: Corporate Culture and Focal Point: Understanding the Function of a Shared Way of Thinking That Cannot Be Quantified

(updated on 21 June, 2022)

@@@@Supplement: Corporate Culture and Focal Point: Walmart Retreated from Japan's Market after Struggling to Match its Operations

(updated on 27 August, 2023)

Note4: Leadership in Team Production: Understanding the Function of Information Transmission of Leaderfs Behavior (updated on 16 Nov, 2022)

Note5: Informal Delegation and the Function of Commitment (typos corrected on 20 Oct, 2023)

Note6: Measuring Intrinsic Value of Decision-Making: Experiments

 

Extra1: Dijkstrafs Shortest Path Algorithm: An Introduction

Extra2: Markov Process and Markov Decision Process (updated on 10 Nov, 2021)

Extra A: Moral Hazard in Teams and the Role of the Third Party (uploaded on 7 Oct, 2021)

Extra B: Team Performance Contract and Multi-Task Problem (uploaded on 18 Oct, 2021)

Extra C: Relative Performance Evaluation

 

Part2: Statistics for MBA, WS on Data Analysis for EMBA, in Japanese

Installing Easy R

Linear Regression (uploaded on 23 Sept, 2021), data1 (uploaded on 7 Oct, 2021)

Binomial Logistic Regression (uploaded on 7 Oct, 2021), data2 (to be distributed in class)

Discriminant Analysis (last updated on 10 Dec, 2022)

Non-Parametric Tests (uploaded on 18 Oct, 2021)

Propensity Score Matching (uploaded on 25 Oct, 2021), data3 (to be distributed in class)

Difference-in-Difference Estimation (uploaded on 12 Nov, 2023), practice3 (data, to be distributed in class)

Principal Component Analysis (uploaded on 7 Oct, 2021)

Cluster Analysis (last updated on 5 Nov, 2022)

Pearsonfs Chi-Squared Test and Fisherfs Exact Test (uploaded on 10 Nov, 2021)

One-Way Analysis of Variance (one-way ANOVA) (uploaded on 17 Nov, 2021)

Two-Way Analysis of Variance (two-way ANOVA) (uploaded on 5 Nov, 2022)

Introduction to Bayesian Estimation (uploaded on 10 Dec, 2022)

 

 

Data

Data (Management Science and Decision Making, 2017)

Raw Data, Panel Data (Management Science, 2019)

data1, data2 (Management Science 2022)

 

 

Software: The codes were not written for the consecutive execution. If you use the software listed below

in such a way, the codes may refer to numerical values remaining in the cache on your PCs and generate

incorrect matchings. In order to surely avoid this event, please clear your cache or close your Excel file

for every execution.

(a)

Excel for Two-Sided Matching ver.3, last updated on 22 Aug, 2017

Usersf Manual (short version 1) last updated on 20 Jan, 2018

Excel for Two-Sided Matching ver.3.2, last updated on 24 May, 2018

bug-correction history:

(1) May 24, 2018: On the analyze sheet: Values in group_Aup was not the difference in ranks of workers

after their swap but the ranks of workers listed in groupB. We should have taken the difference

between the ranks listed in groupB and groupA. This error was corrected on May 24 in 2018.

Userfs Manual (excerpt), last updated on 25 June, 2023.

A Note, uploaded on Jan 30, 2018.

 

(b)

Excel for Exchange of Indivisible Goods ver.2, last updated on Jan 20, 2018

Excel for Exchange of Indivisible Goods ver.3, uploaded on April 7, 2018

Usersf Manual (excerpt), uploaded on Sept 21, 2018

 

(c)

Excel for Multi-Unit Auction, uploaded on Nov 29, 2018

Excel for Multi-Unit Auction 2, uploaded on December 1, 2019

Usersf Manual (excerpt), uploaded on December 21, 2019