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Corporate communication during the COVID-19 crisis in a multicultural environment: culture and tweet impact

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Abstract

This study aims to explore the variation across corporate crisis communication strategies for companies traded in the Dubai and Abu Dhabi stock exchanges through their use of Twitter during the COVID-19 crisis. We analyze communication activity in light of UAE residents’ cultural dimensions and linguistic attributes. Specifically, we assess the impact of the tweets’ orientation in terms of social versus business COVID-related tweets based on Hofstede’s dimensions of culture (power distance, uncertainty avoidance, collectivism, and masculinity) from one side, and the tweets’ language in terms of Arabic versus English COVID-related tweets from the other side. We find evidence to suggest that the impact of COVID-19 related tweets is significantly higher for social tweets relative to business tweets across all the time periods. As for language, mean retweets are significantly higher for Arabic tweets relative to English tweets. Specifically, Arabic social tweets have a significantly higher retweet impact compared to English social, Arabic business, and English business COVID tweet subgroups, consistent with the high collectivism and high uncertainty avoidance of Arabic-speaking cultures. Based on our findings, companies in highly diverse cultural and linguistic settings are urged to be active in communicating with stakeholders in their own languages, taking into account the cultural environment in which stakeholders participate, and with a focus on an appropriate mix of business and non-business (social) messages during periods of significant exogenous shocks.

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Notes

  1. The Streisand Effect occurs when efforts to suppress information have the unintended effect of bringing attention to the information that the entity seeks to suppress.

  2. Recent researches on corporate social media communication (such as (Lei et al., [5]) identified Twitter to be superior when compared with other social media platforms such as Facebook and YouTube.

  3. Contrary to common perception, the masculinity/femininity factor does not reflect the extent to which women are equal with regards to power in the society. It refers to whether people “live to work” (masculinity) or “work to live” (femininity). Perhaps more contemporary or appropriate terminology for this attribute will surface over time.

  4. Pointing to a limitation of Twitter for the transmission of information across linguistic groups, they note that although multilingual communities can use Twitter in a variety of languages, the burden of translation falls on the user, as Twitter functionality does not presently support instantaneous translation.

  5. This is when the WHO started responding to the disease [92].

  6. Charise [93] indicates that English is often the “language of higher education” in the UAE

  7. The main technique to generate word cloud image from a set of tweets starts with finding the frequency of each word after eliminating the stop words and any Word clouds provide a novel and reader-friendly approach for analysis and presentation of qualitative data. They are useful for quality control to help ensure that the intent of the program is achieved.

  8. All continuous variables are winsorized at the 1st and 99th percentiles.

  9. We rely on the GLM function, regressing the impact measure on the 4 dichotomous groups to determine the significant in mean impact differences among the four subgroups.

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Kharbat, F.F., Kannan, Y., Gleason, K. et al. Corporate communication during the COVID-19 crisis in a multicultural environment: culture and tweet impact. Electron Commer Res 24, 675–709 (2024). https://doi.org/10.1007/s10660-023-09777-3

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