Learning a Board Balanced Scorecard to Improve Corporate Performance
Stevens Institute of Technology - Wesley J. Howe School of Technology Management
University of California, San Diego
November 11, 2013
Howe School Research Paper No. 2013-4
The objective of this paper is to demonstrate how the boosting approach can be used to define a data-driven board balanced scorecard (BSC) with applications to S&P 500 companies. Using Adaboost, we can generate alternating decision trees (ADTs) that explain the relationship between corporate governance variables, and firm performance.
We also propose an algorithm to build a representative ADT based on cross-validation experiments.The representative ADT selects the most important indicators for the board BSC. As a final result, we propose a partially automated strategic planning system combining Adaboost with the board BSC forboard-level or investment decisions.
Number of Pages in PDF File: 46
Keywords: Boosting, machine learning, corporate governance, balanced scorecard, planning, performance management
JEL Classification: C53, C63, G12, G14, F30working papers series
Date posted: January 5, 2013 ; Last revised: December 5, 2013
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