Journal
MANAGEMENT SCIENCE
Volume -, Issue -, Pages -Publisher
INFORMS
DOI: 10.1287/mnsc.2023.4927
Keywords
natural language processing; supply chain risk; empirical operations management
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Using textual analysis techniques, researchers have developed a measure of firm-level supply chain risk exposure based on unstructured data from discussions between managers and equity analysts. This measure successfully captures both routine and systematic supply chain risk events and correlates with stock return volatility. It is also indicative of the supply chain component of risk exposure. Firms with higher supply chain risks have higher inventory buffers, increased cash holdings, lower trade credit received, and worse operating and financial performance during unexpected risk episodes.
Using textual analysis techniques, including seeded word embedding and bagof-words-based content analysis, I develop a firm-level measure of supply chain risk exposure from a novel source of unstructured data-the discussion between managers and equity analysts on supply chain-related topics during firms' quarterly earnings conference calls. I validate the measure by showing that (1) the measure exhibits intuitive variations over time and across firms, successfully capturing both routine and systematic supply chain risk events; and (2) the measure is about risk exposure, as it significantly correlates with realized and options-implied stock return volatility, even after controlling for wellknown aggregate risk measures. I then demonstrate that the measure is specifically indicative of the supply chain component of risk exposure. (3) Consistent with theoretical predictions, firms facing higher supply chain risks have higher inventory buffers, particularly in raw materials and intermediate inputs, increased cash holdings in lieu of investments, and significantly lower trade credit received from suppliers. Moreover, (4) during unexpected risk episodes, such as the Tohoku earthquake, firms with higher ex ante risk exposure have worse operating and financial performance. These results indicate that the text-based measure provides a credible quantification of firm-level exposure to supply chain risks and can thus be reliably utilized as outcome or explanatory variables in empirical supply chain research.
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