题　目：What Do Resumes Tell Us About Accounting Rookie Job Candidates’ Research Potential?

嘉　宾：柯滨Bin Ke 教授 新加坡国立大学

主持人：黄立 助理教授 BAT365唯一官网

时　间：2024年12月27日（周五）14:00-15:30

地　点：BAT365唯一官网 徐汇校区安泰楼A511室

内容简介:

Universities allocate significant resources each year to recruit faculty from PhD programs, yet many hires fail to achieve tenure, often due to insufficient research productivity. This study explores whether the faculty recruitment process can be enhanced by using machine learning to identify candidates with higher research potential earlier in the hiring process. Focusing on the accounting rookie job market, we develop a research productivity prediction model that leverages readily available job application materials: (i) candidate resumes, (ii) the rankings of their educational institutions and the research productivity of their dissertation advisors and coauthors, and (iii) their dissertations. Despite human recruiters having access to broader information than our prediction model, our findings show that the model consistently outperforms traditional human judgment in predicting future research productivity. Notably, resumes prove to be the most powerful predictors of research productivity, while the dissertation contributes minimal predictive value once resume data is incorporated.

演讲人简介：

柯滨教授，现任新加坡国立大学商学院教务长讲席教授。获聘中国教育部“长江学者” 讲座教授，并担任过北美华人会计教授会会长。柯滨教授在The Accounting Review, Journal of Accounting and Economics, Journal of Accounting Research等顶级期刊发表论文超过20篇。其研究兴趣包括通过采用传统或跨学科研究方法来探索并解决当今日益复杂的商业问题。近年来，柯滨教授尤为关注中国转型经济和新兴市场背景下的数字化转型问题的研究。

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