Sustainability is a major contemporary issue that affects everyone. Many companies now produce an annual sustainability report, mainly intended for their stakeholders and the public, enumerating their goals and degrees of achievement regarding sustainable development. Although sustainability reports are an important resource to understand a company’s sustainability strategies and practices, the difficulty of extracting key information from dozens or hundreds of pages with sustainability and business jargon has highlighted the need for metrics to effectively measure the content of such reports. Accordingly, many researchers have attempted to analyze the concepts and messages from sustainability reports using various natural language processing (NLP) methods. In this study, we propose a novel approach that overcomes the shortcomings of previous studies. Using the sentence similarity method and sentiment analysis, the study clearly shows thematic practices and trends, as well as a significant difference in the balance of positive and negative information in the reports across companies. The results of sentiment analysis prove that the new approach of this study is very useful. It confirms that companies actively use the sustainability report to improve their positive image when they experience a crisis. It confirms that companies actively use the sustainability report to improve their positive image when they experience a crisis. The inferences gained from this method will not only help companies produce better reports that can be utilized effectively, but also provide researchers with ideas for further research. In the concluding section, we summarize the implications of our approach and discuss limitations and future research areas.

India has a longstanding reputation in the film industry, whereas South Korean films have only recently achieved notable success globally. Despite their significant positions in the global film market, there are very few studies that compare and analyze the competitive advantage of the two countries in the film industry. This paper adopts the ABCD model as a complementary framework to the two mainstream theories of strategic management (i.e., industry-based view and resource-based view) to analyze and compare the competitiveness of the industrial success of emerging countries. For the empirical test, this paper uses natural language processing methods to operationalize the theoretical model. After collecting text data from news articles in English related to the Korean and Indian film industries, this study analyzes how many keywords with regards to the 8 sub-factors of the ABCD model are mentioned in the articles using the document similarity measurement. The results reveal the different but complementary areas of strengths. India has higher competitiveness in the factor of Agility while Korea has higher competitiveness in Convergence. This study also highlights the areas for further development and potential partnership between the two countries by leveraging each other’s strengths.