In today\u2019s business environment, firms are increasingly struggling to navigate through volatility and uncertainty. Therefore, successful cooperation across corporate and even industry boundaries is becoming highly important. In this context, interfirm cooperation (IFC) refers to an informal, non-equity-based arrangement typically formed by a small and limited number of independent firms pursuing individual, compatible, or concurrent, joint goals. A recent example of this is the partnership between heavy equipment manufacturer Caterpillar and technology firm Nvidia, which aims to accelerate the integration of AI in heavy machinery and manufacturing in order to drive industrial innovation. Similarly, conglomerate 3M has partnered with technology firm Microsoft, combining advanced materials science with digital resources and capabilities to enhance data centre infrastructure and enterprise transformation. In these and many other cases, the partners gain access to each other\u2019s resources, capabilities, and expertise. This enables them to strengthen their competitive position and thus secure their long-term viability. Despite their high strategic relevance, however, IFCs are not yet subject to mandatory disclosure requirements. Consequently, partnering firms may voluntarily disclose IFC-related information to reduce information asymmetries between managers and investors, which can eventually improve their capital market performance.<\/p>\n
Against this background, the study \u2018Interfirm cooperation and capital market performance: automated textual analysis of voluntary disclosures in Form 10-Ks<\/em>\u2019 examines how the extent of voluntary IFC-related disclosures relates to various capital market performance indicators of U.S.-listed firms. Drawing on signalling theory, the authors propose a non-linear relationship: While increasing disclosure levels may initially enhance capital market performance by reducing information asymmetries, higher levels could raise concerns about proprietary costs and information overload, ultimately triggering detrimental effects. To test this assumption, the study focuses on Form 10-K filings of 208 firms listed in the Standard & Poor\u2019s (S&P) 500 stock market index between 2008 and 2020. Using a rule\u2011based approach of automated textual analysis supported by a newly developed dictionary, the authors construct a novel, text\u2011based measure of voluntary IFC-related disclosures. Subsequent multivariate analyses applying this new measure confirm the proposed non-linear pattern. More specifically, the results reveal U-shaped associations for market value and trading volume, as well as U-shaped associations for the cost of equity capital and the bid-ask spread. These findings remain consistent across multiple robustness checks and sample splits.<\/p>\n Overall, this study highlights the value relevance of voluntary IFC-related disclosures and their importance for investor decision-making. Contrary to previous findings, it contributes to the accounting literature by unveiling the non-linear effects of these disclosures. In terms of corporate practice, the study shows how a balanced IFC-related disclosure strategy can help to improve firms\u2019 capital market performance compared to low or excessive disclosure levels.<\/p>\n