Invited Speakers
Assco. Prof. Chi Sheh
University of the West, USA
Dr. Chi Sheh is an Associate Professor at University of the West
(UWest), teaching in the areas of finance, accounting,
statistics, and economics. Dr. Sheh's research interests has
centered around ways to apply Buddhist philosophy and Humanistic
Management principles to corporate and investment decisions,
including the inclusion of environmental, social, and governance
(ESG) factors. He recently published a book chapter titled “A
Buddhist Perspective on Humanizing Business”, where he lays out
practical implications of Buddhism for Humanizing Business.
Dr. Sheh is the Director of the UWest Socially Responsible
Investment Fund, where he directs MBA students in the selection
of socially responsible companies, mutual funds, and ETFs based
on detailed analysis of financial data as well as ESG metrics.
Dr. Sheh is also the founding advisor to the Sustainable
Investing Club at UWest, which seeks concrete and practical ways
to make investing more sustainable, and in the process serve as
a platform to foster innovative ideas in sustainable investment.
His professional experience also includes working as a financial
analyst for Enron Corporation, in the areas of Power Trading,
International Energy and Water Project Development, and
Commercial Energy Risk Management and Services.
Title: Fostering Inclusivity in Small Businesses: Generative AI-Driven Chatbots, Current AI Tools, and ChatGPT Plus as Cost-Effective Catalysts for Effective DEI Training
Abstract: This essay explores the strategic integration of
generative AI-driven chatbots and current AI tools, including
ChatGPT Plus, into diversity, equity, and inclusion (DEI)
training for small businesses.
We find that compared to traditional DEI training methods, the
use of AI-driven chatbots is not just cost-effective, but also
offers an effective DEI training tool for resource constrained
small businesses.
Assoc. Prof. Jing Fu, Fukuoka Institute of Technology, Japan
Dr. Jing Fu is Associate Professor at Department of System
Management, Fukuoka Institute of Technology. Prior to her
current position, she worked as Assistant Professor at Tokyo
Institute of Technology. She is also Adjunct Lecturer at Faculty
of Economics in Fukuoka University, Research Associates at
Systemic Risk Centre in London School of Economics and Political
Science and was a visiting scholar at Arizona State University
and Indiana University Bloomington. She obtained her Ph.D. in
Economics at Tokyo Institute of Technology, and bachelor at
Tsinghua University. She is teaching Advanced Business Systems,
Management Simulation, Operations Research, Game Theory, etc.
Her current research interest lies in discounted stochastic
games and its application to club network formation, systemic
risk and network resilience. She is also interested in
information diffusion game and data envelopment analysis game.
She has published 25 journal and conference papers, including
Dynamic Games and Applications, Journal of Fixed Point Theory
and Applications, Central European Journal of Operations
Research, Journal of Japan Industrial Management Association,
etc. She is a board member of Asian Association of Management
Science and Applications, Operations Research Society of Japan
(Kyushu Branch) and Japan Industrial Management Association
(Kyushu Branch).
Title: A Strong Mechanism for Informed Principal Problem
Abstract: We consider the problem faced by an informed principal in attempting to contract with a privately informed agent who will take an unobservable action. The agent not only has private information about the agent's own type but also holds probability beliefs about the principal's type that are unknown to the principal. The fundamental problem faced by the principal is that the very act of choosing a contracting strategy changes the agent's probability beliefs about the principal's type, and this in turn induces a change in the agent's behavior - the very behavior upon which the principal's contracting strategy was based in the first place. Thus we have a problem of infinite regress - a well-known problem in signaling games, made much more complicated here by the presence of moral hazard. Here we will present a new approach to this problem: we will suppose that in addition to the agent's type, s∈S, the agent has a belief reaction type, μ(dt|s, C), linking the principal's catalog choice to the agent's probability beliefs about the principal's type. Then we will solve the informed principal's contracting problem for a principal who holds set-valued conjectures concerning the agent's reaction types.