구조조정 해고 공시가 주가에 미치는 영향: Earnings Conference Call 텍스트 분석을 이용하여

This study investigates how the stock market responds differently to layoff announcements depending on the strategic orientation of firms, as inferred from their Earnings Conference Call (ECC) transcripts. As AI and other advanced technologies have emerged as central elements of corporate strategy, some firms have framed layoffs not merely as cost-cutting measures but as signals of future transformation, which tend to be interpreted positively by investors. Using text mining techniques, this study classifies U.S. based firms into seven distinct strategic groups based on their ECC language and applies an event study methodology to measure cumulative abnormal returns (CAR) following layoff disclosures. The results show that firms with technology-oriented, forward-looking language experienced significantly positive market reactions, whereas those emphasizing operational efficiency elicited limited responses. Methodologically, this study contributes by structuring textual differences among firms into quantifiable strategic groupings. Substantively, the findings suggest that market reactions to negative events such as layoffs are not uniform but are contingent on the strategic signals embedded in a firm’s language and orientation. This implies that how a company is perceived strategically-through its public discourse-can critically shape investor response during periods of organizational change.