Industrial Engineering and Economics News

Assistant Professor CHEN YING, Associate Professor Yosuke Kimura, and Professor Kotaro Inoue Receive the “Best Paper Award” of the Corporate Finance Research Award

March 13, 2026

A joint research project by Assistant Professor CHEN YING, Associate Professor Yosuke Kimura, and Professor Kotaro Inoue has received the Best Paper Award of the Corporate Finance Research Award from the Corporate Finance and Capital Markets (Mizuho Securities) Endowed Chair at the Kyoto University Graduate School of Management.

About the Corporate Finance and Capital Markets
(Mizuho Securities) Endowed Chair

The Corporate Finance and Capital Markets (Mizuho Securities) Endowed Chair was established at the Kyoto University Graduate School of Management in 2005 and is one of the longest-standing endowed chairs at the university. The chair aims to promote advanced research in corporate finance, its practical applications, and the development of human resources, with the goal of supporting the sound development of financial and capital markets. From the perspectives of economics and management, the program examines the institutional and behavioral characteristics of corporate finance in Japan in a theoretical and systematic manner, while promoting research and education that balance academic theory and practical relevance. Under this mission, the award is presented to research that makes outstanding academic contributions to the fields of corporate finance and capital markets.

Awarded Research

Paper Title：

Self-serving Attribution Bias and Corporate Actions

This study empirically examines how self-serving attribution bias (SAB) among corporate managers influences corporate decision-making and investment behavior from the perspective of behavioral finance. Self-serving attribution bias refers to the cognitive bias of managers to attribute positive firm performance to their own abilities and efforts, while attributing poor performance to external factors such as unfavorable economic conditions. To quantitatively capture this subjective bias, the study applies AI techniques, including natural language processing (NLP) and text mining, to analyze managerial language in corporate disclosure documents (annual reports and earning calls). By doing so, the research proposes a novel empirical approach to measuring managerial overconfidence, which has traditionally been difficult to quantify. The study further provides new empirical evidence on how managerial behavioral bias influences corporate acquisition decisions, an important research question in behavioral finance. The study was highly recognized for employing innovative AI-based methodologies to address an important corporate finance question that had previously been difficult to examine empirically, and it was therefore selected to receive the Best Paper Award.