Effect of Firms’ Responsive Strategies in Crisis: Based on Big Data Analysis in Social Media

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Abstract

In the age of social media, after a crisis event, firms will immediately take responsive actions and publicly announce what they do in news media, in order to attenuate the potential negative impact of crisis. Afterwards, the public in social media will freely discuss and deliver their opinions in the form of word-of-mouths (WOMs), which directly reflect their feeling of firms’ responsive strategy. Therefore, based on big data analysis in social media, we attempt to establish the link between crisis firms’ responsive actions and public perceptions reflected in online WOMs. Large quantities of secondary panel data are crawled from both search engine and social media. To obtain a robust result, we adopt Panel Vector Auto Regression model to conduct our data analysis. The results show that increased responsive strategies of crisis firms will lead to a significant increasement in the strength of online WOMs, while a more positive responsive strategy can significantly decrease the strength of online WOMs in contrary. Our research provides profound theoretical and practical contributions.

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APA

Wang, X., & Liu, L. (2019). Effect of Firms’ Responsive Strategies in Crisis: Based on Big Data Analysis in Social Media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11589 LNCS, pp. 256–265). Springer Verlag. https://doi.org/10.1007/978-3-030-22338-0_21

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