Организационные характеристики, корпоративное управление и раскрытие корпоративных рисков: Обзор
Аннотация
Определенные особенности поведения в области корпоративного управления были выделены в академических исследованиях как основные факторы, коррелирующие с раскрытием корпоративных рисков среди публичных компаний. Тем не менее, несмотря на это, множество эмпирических исследований в данной области демонстрируют неоднозначные результаты. Настоящее исследование анализирует практику раскрытия корпоративных рисков публичными компаниями и изучает, можно ли объяснить такие разночтения нормативно-правовой базой, юрисдикцией, отраслью деятельности, бизнес-средой или используемыми методологиями. Для этого мы использовали ключевые слова "раскрытие рисков", "корпоративное управление" и "организационные характеристики" при поиске релевантных исследований, отобрав 46 эмпирических научных работ, и применили процедуру мета-анализа для оценки их выводов. Наш анализ показал, что размер компании — это основная организационная характеристика, на которую влияют модераторы, а размер совета директоров и наличие институциональных инвесторов — главные переменные корпоративного управления, оказывающие влияние на модераторы. При анализе характера раскрытия информации выяснилось, что раскрытие финансовых рисков чаще встречается у компаний банковского сектора, тогда как раскрытие операционных рисков более характерно для нефинансовых компаний. Кроме того, исследование выявило, что метод получения данных, временной интервал, разнообразие и объем выборки, а также применяемые статистические методы — это ключевые факторы, влияющие на расхождения между предыдущими исследованиями. Подобные переменные затрудняют понимание заинтересованными сторонами основных факторов, побуждающих компании раскрывать информацию о своих рисках. Мы утверждаем, что существующий процесс сбора данных трудозатратен и требует много времени, что приводит к использованию более малых выборок по сравнению с большинством текущих исследований. Возможным решением этих ограничений может стать применение автоматизированных процедур анализа текстовых данных в будущих научных работах.
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