The Uniqueness of Attention Affecting Corporate Growth: An Analysis of Annual Securities Reports Using Machine Learning

It is known that strategic actions affecting corporate performance are heavily influenced by a firm's cognitive structure, which determines the management issues it focuses on (attention). This study proposes the concept of "uniqueness of attention"—the deviation of a firm's attention allocation patterns from those of its competitors. Using a machine learning method called the "structural topic model," we analyzed annual securities reports to quantify this "uniqueness of attention" in comparison to competitors.

The data analysis revealed that when the uniqueness of attention to a firm's management issues is not excessively high, it tends to promote strategic growth actions and result in the highest level of financial performance.

Furthermore, the study found that the impact of the uniqueness of attention on financial performance is more pronounced when the firm operates in a market with limited growth. This suggests that the uniqueness of attention is more critical in mature or saturated markets.