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SCHOOL OF ECONOMIC SCIENCES WSU JIKHAN JEONG

JIKHAN JEONG



EMPLOYMENT HISTORY


 Research Fellow: Research on Electricity Market Design, Energy Policy, and In-House Consulting

  • Carbon Disclosure Project (International NGO), Jun. 2011 – Aug. 2011

 Research Assistant (Internship): Research on Sustainable Management in 94 Firms In S. Korea

  • Green Cross International (International NGO), Dec. 2010 – Feb. 2011

 Research Assistant (Volunteer): Research On Energy Efficiency

 Researcher: Research on Li-Ion Rechargeable Battery Technology


EDUCATION


  • Washington State University, Aug. 2017 – July. 2021 (Expected)

 Ph.D. Student in Economics (Passed Microeconomics Ph.D. Qualifying Exams with Distinction)

  • Korea Advanced Institute of Science and Technology, Mar. 2011 – Feb. 2013

 MSc. in Management Sciences Specialized in Quantitative Marketing

  • Sung Kyun Kwan University, Mar. 2002– Feb. 2010

 BS in Chemical Engineering

 Study Abroad in the US to learn English as a Secondary Language, March. 2007 – Dec. 2007

 Military Service in the South Korean Air Force SWAT, May. 2003 – Oct. 2005


RESEARCH FIELDS



JOB MARKET PAPER


  • Identifying Consumer Preferences from User- and Crowd- Generated Digital Footprints on Amazon.com by Leveraging Machine Learning and Natural Language Processing (Job Market Paper) [S1][M2][M3][M4]

Abstract: Inexperienced consumers may have high uncertainty about experienced goods that require technical knowledge and skills to operate effectively; therefore, experienced consumers’ prior reviews can be useful for inexperienced ones. Furthermore, analyzing and understanding the effects of prior reviews on consumers is important to firms. Consequently, this study analyzes consumers’ digital footprints (DFs) to identify their latent preferences. In particular, this paper makes use of 230 pages of python coding along with high-performance-computing (HPC) to extract reviewers’ DFs for a specific product group from a dataset of 141 million Amazon reviews including consumer reviews and product-specific information. However, some questionable reviews (posted by ‘suspicious one-time reviewers’ and ‘always-the-same raters’) were excluded.

This paper focus on programmable thermostats and shows how to: 1) identify consumer preference from DFs; 2) predict potential consumers’ rating before they buy or write reviews; and 3) classify the reviewer’s attitude toward product content dimension extracted from topic modeling. First, heteroskedastic ordered probit analysis shows that user DFs (e.g., length of review for the product, average rating across all categories, the volume of reviews in all- and sub-categories), reviewers’ attitudes towards product content dimensions (smart connectivity, easiness, energy-saving, functionality, support, price worthy, privacy, and Amazon service), and other prior reviewers DFs (e.g., length of review summary) affects the rates. Second, Extreme Gradient Boosting shows the highest F1 score for predicting the ratings of potential consumers. Third, a Convolutional Neural Network (CNN) on the top of Bidirectional Encoder Representations from Transformers (BERT) embedding shows the highest F1 score to classify individual consumers’ sentiment. Finally, this paper’s approach will be applicable for different goods, scalable for bigger data, and interpretable for a specific industry.


WORKING PAPERS


  • Identifying Always the Same Raters in One-sided-Review System by Leveraging Deep Learning and Natural Language Processing [S1][M2][M3][M4]
  • Predicting US Stock Market Risk in The Daily Trading Beginning Hour Using News in After-Market Period [S1][S2][M2][M3][M4]
  • AI and Big Data in an Entry Game [S1][M5]
  • The Effect of Experienced Consumers’ Stated Concerns about Electric Vehicles on Willingness to Purchase [S3][M2]

WORKS IN PROGRESS


  • The effect of Increasing Block Pricing Reform on Consumer, Producer, and Carbon Emission [S3][M1]
  • Predicting Imported LNG Price for Power Generation from an Imported Regional Oil price [S3][M1]

PUBLISHED RESEARCH REPORTS AND LETTERS



SELECTED CONFERENCES


  • 2021 American Economic Association (AEA) , Jan 2021, forthcoming (Poster)

ž Identifying Consumer Preferences for Smart and Non-Smart Thermostats from User-Generated Content on Amazon.com

  • 2020 WSU SES Seminar, Nov 2021, forthcoming

ž Identifying Consumer Preferences from User- and Crowd- Generated Digital Footprints on Amazon.com by Leveraging Machine Learning and Natural Language Processing

  • The Rocky Mountain Advanced Computing Consortium 2020, May. 2020. presented (Poster)

ž Identifying Consumer Preferences for Smart and Non-Smart Thermostats from User-Generated Content on Amazon.com

  • 2019 Python conference (Pycon) Korea, Aug. 2019, presented

ž Ensemble Model and Bayesian Hyperparameter Tunning for Classification, Presented (Light Talk)

  • Korea AI Society The AI Korea 2019 Conference, July. 2019

ž Predicting Stock Price Index Movement From News Headline Data, Presented (Poster)

  • The Rocky Mountain Advanced Computing Consortium 2019, May. 2019

ž Predicting Stock Price Index Movement from News Headline Data, presented (Poster)

  • 36th United States Association for Energy Economics (USAEE) North American Conference, Sep. 2018

ž The Effect of a Monopoly Increasing Block Pricing Reform on Electricity Demand, presented (Poster)

  • United States Association for Energy Economics (USAEE) North American Conference, Oct. 2016

ž The Effect of Falling Oil Prices on South Korean Imported LNG price for Power Generation, presented

  • International Association for Energy Economics (IAEE) Antalya Conference, May 2015

ž Who among South Korean User Groups Wants to Buy Electric Vehicles? presented

  • Industry Electricity Commission Fall Conference, Oct. 2014

ž Big-data-Centered Demand Side Management Business Model, presented

  • Conference of Electricity Power Supply Industry (CEPSI), Oct. 2014

ž What is the Winning Strategy for Global Utility Companies in the Green Era?, author

  • International Association for Energy Economics (IAEE) Asia Conference, Sep. 2014

ž Relationship between Attitude and Actual Behavior in Electricity Conservation in S.Korea, presented 

  • International Conference on Social Science and Management (ICSSAM), May 2014

ž Does Clean Energy Cause Economic Growth? presented

  • Korea Academy of International Business Spring Conference, Apr. 2014

ž Energy Transitions in Germany, presented


RESEARCH PROJECTS


  • Research Assistant, WSU SES, 2019 Summer (PI: Prof. A.love)

 Design a Smart Thermostats algorithm

  • Research Assistant, WSU SES, 2019 Spring (PI: Prof. Vicki McCracken)

 Design the Financial Statement for Small and Middle Enterprise

  • Research Assistant, WSU SES, 2017 Fall – 2018 Winter (PI: Prof. Yoder)

 Collecting data related to Hurricane IRMA

  • (Project) Improving Efficiency in Regulated Electricity Market, Dec. 2015 – Aug. 2016

 Served as a Project Manager (Advisor: Prof. JongSoon Kim, Prof. Dong-Gi Min, Prof. Young Bum Lee)

  • (Project) Customers’ Stated Preference for Energy Mix in South Korea, Aug. 2015 – May. 2016

 Served as a Project Manager (Advisor: Prof. Jeong Hwan Bae)

  • (Project) Designing a Bilateral Contract in South Korea, Mar. 2015 – Dec. 2015

 Served as a Task Force Member

  • (Project) Designing a Bilateral Contract and Capacity Market in South Korea, Mar. 2014 – Feb. 2015

 Served as a Research Project Manager (Advisor: Prof. Dae-Woo Kim, Prof. Jong-Ho Kim)


SEMINAR AND FORUMS


  • 2020 Digital Economy Network Seminar, attended in Spring and will attend  in Fall 2020
  • 2020 Standford Human-Centered Artificial Intelligence COVID-19 and AI: A Virtual Conference, attend
  • 2019 Korea Economic Review International Conference, attended
  • 2019 Korea AI Society Machine Learning Summer School, attended
  • 2019 AI Expo Korea, July. 2019, attended
  • Korea Advanced Institute of Science & Technology AI Festival, July. 2019, attended
  • Daewoong Inc. Smart Health Care Conference. July, 2019, attended
  • 2019 Washington State University Sustainability Fair 2019, presented

ž Predicting Experienced Consumers’ Stated Preference

  • 2019 WSU School of Economics Science Poster Competition, presented

ž Predicting Experienced Consumers’ Stated Willingness to Buy Electric Vehicles

  • R Working Group Research Profile Seminar, Mar. 2019, presented

ž Time Series Analysis Basic to Bayesian Structural Time Series

  • Python Working Group, Feb. 2019, presented

ž Deep Learning from Scratch to Practice

  • Python Working Group Research Profile Seminar, Nov. 2018, presented

ž Discrete Choice Model: Logistic Regression, Random Forest, and Ada – Boosting

  • WSU Half-Backed Seminar 2, Aug. 2018, presented

ž How to Apply Machine Learning for Prediction of Customers’ Stated Preference

  • WSU Half-Backed Seminar 1, Aug. 2018, presented

ž How to Apply Machine Learning for Causal Inference

  • 2018 Berkeley/Sloan Summer School in Environmental and Energy Economics, Aug. 2018, attended
  • WSU School of Economic Sciences Poster Competition Mar. 2018, presented

ž Effects of Falling Oil Price on Korean LNG Price for Power Generation

  • International Association for Energy Economics Summer School, July. 2017, attended
  • National Research Foundation of Korea, SSK Networking, April 2017

ž Fourth Industrial Innovation Section Panel

  • Korea Ministry of Trade, Industry & Energy Seminar, Nov. 2015

ž The Status of Self-Generation Incentive Program and Net Energy Metering in California, presented

  • Harvard Project for Asian and International Relationships, Aug. 2013, attended

ž Selected South Korean delegation of the energy panel section

  • KAIST Management Science Brown Bag Seminar, April. 2012

ž Nuclear Energy Adoption” (Research Profile), “Survival Analysis based on COX (Tutorial), presented

  • 2012 Economic Development Cooperation Fund Winter Camp, Jan. 2012, attended
  • 2012 ASEAN Korea Frontier Forum, Sep. 2012, attended

ž Selected South Korean delegation

  • Harvard Project for Asian and International Relationships, Aug. 2011, attended

ž Selected South Korean delegation of energy panel section

  • 2006 Youth Camp for ASIA’S Future, Aug. 2006, attended

ž Selected South Korean delegation

  • 2005 Korea-ASEAN Youth Camp, Dec. 2005, attended

ž Selected South Korean delegation


GRANTS AND HONORS


  • Honorable Mention Award in The AI Korea 2019 Conference Poster Competition,, $50 (approx.), July. 2019
  • 2019 WSU GPSA Travel and Registration Grant for Summer and Fall, $420 (approx.), 2019
  • The Rocky Mountain Advanced Computing Consortium High-Performance Computing Scholarship, $ 500, 2019
  • 2018 WSU GPSA Travel and Registration Grant for Summer and Fall, $1,100 (approx.), 2018
  • 2018 Alaska Airlines Travel Award, $2,200 (approx.) 2018
  • Honorable Mention Award in WSU School of Economic Sciences Poster Competition, WSU, $100 (approx.), 2018
  • Korea Electric Power Corporation CEO Award for Outstanding Researcher, 2015
  • Korea Electric Power Corporation Business Development Challenge Award, 2015

 Big data for New Demand Side Consumer Services, presented

  • Korea Advanced Institute of Science and Technology Fellowship, Mar. 2011 – Feb. 2013
  • Korea Finance Cooperation Research Paper Competition, $3,000, Second Place Award, 2012

 Analyzing the effect of venture business policy financing through dynamic panel analysis, presented

  • Korea International Cooperation Agency Green ODA Presentation Competition, Second Place Award, 2012
  • Accenture Idea Competition, $1,400 (approx.), Second Place Award, 2011

 Managing diversity to improve business performance: centering around gender and cultural issues, presented

  • KOREA Institute of Energy Research Idea Competition, $200 (approx.), Second Place Award, 2010
  • South Chungcheng Province Policy Suggestion IDEA Challenge, $300 (approx.), Governor Award, 2009
  • Japan KoBe University Summer Program Fellowship, Aug 2009
  • SKKU English Presentation Competition, Best Award, 2008
  • Korea Air-force Outstanding Military Police Award, 2004

TEACHING EXPERIENCE


  • Instructor, WSU

EconS 352 Ph.D. Business Management Economics, Fall 2020 (Online)

  • Teaching Assistant, WSU

EconS 511 Ph.D. Econometrics 1, Spring 2020. Teaching Evaluation (4.0/5.0)

EconS 594 Ph.D. Theory Of Industrial Organization, Fall 2019

 EconS 506 Ph.D. Mathematics Primer for Economists, Fall 2019

  • Instructor, Korea Power Economics Summer School, June 2016
  • Undergraduate Research Program Teaching Assistant, KAIST, 2011-2012
  • Teaching Assistant, KAIST

 Entrepreneurship and Venture, Fall 2012

 Knowledge Service Engineering, Fall 2011-Spring 2012


EXTRACURRICULAR ACTIVITIES


  • WSU Kamiak High-Performance Computer Club, 2018 Fall – Present
  • WSU Python Working Group, 2018 Fall – Present
  • WSU R Working Group, 2018 Fall – Present
  • KAIST Quantitative Analysis for Business Economics Lab Leader, 2011-2012

    Presented and discussed Quantitative Theory and Econometrics (Advisor: Prof. Minki Kim)

  • Tae Kwon Maru Team Member, 2012 – 2014
  • KAIST Tae Kwon Do Team Member, 2011-2012
  • Sung Kyun Kwan University Mixed Martial Art Team Member, 2002-2009

COMPUTER SKILLS



LANGUAGE


  • Native Korean, Fluent in English, Intermediate in Japanese, Beginner in Chinese

REFERENCE


Contact Info:

E-mail: Jikhan.Jeong@wsu.edu

Office Location:

313 Hulbert Hall
School of Economic Sciences
Washington State University
Pullman, WA 99164-6210