nach oben

Electronic Commerce Research

Erschienen in:

09.11.2023

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

verfasst von: Faten F. Kharbat, Yezen Kannan, Kimberly Gleason, Amer Qasim

Erschienen in: Electronic Commerce Research | Ausgabe 1/2024

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

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.

Vorheriger Artikel The impact of electronic word-of-mouth on corporate performance during COVID-19

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

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.

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.

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.

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.

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

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

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.

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

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.

Eriksson, M. (2018). Lessons for crisis communication on social media: A systematic review of what research tells the practice. International Journal of Strategic Communication, 12, 526–551. https://doi.org/10.1080/1553118X.2018.1510405CrossRef

ncema.gov.ae (2020) UAE Coronavirus (Covid-19) Updates. https://covid19.ncema.gov.ae/en

Siemund, P., Al-Issa, A., & Leimgruber, J. R. E. (2020). Multilingualism and the role of english in the United Arab Emirates. World Englishes Weng. https://doi.org/10.1111/weng.12507CrossRef

Hofstede, G., Van Deusen, C., Mueller, C., & Charles, T. (2020). What goals do business leaders pursue? : A study in fifteen countries. Organizational Collaboration (pp. 35–48). Routledge.CrossRef

Lei, L., & (Gillian), Li Y, Luo Y,. (2019). Social media and voluntary nonfinancial disclosure: Evidence from twitter presence and corporate political disclosure. Journal of Information Systems, 33, 99–128. https://doi.org/10.2308/isys-52189CrossRef

Sharma, A., Adhikary, A., & Borah, S. B. (2020). Covid-19′s impact on supply chain decisions: Strategic insights from NASDAQ 100 firms using Twitter data. Journal of Business Research, 117, 443–449. https://doi.org/10.1016/j.jbusres.2020.05.035CrossRef

Price, V. (2008). The public and public opinion in political theories. SAGE Handb public Opinion Research (pp. 11–24). Sage Publications.CrossRef

Price, V. (1992). Public opinion. Sage.CrossRef

Rathnayake C, Suthers DD (2018) Twitter issue response hashtags as affordances for momentary connectedness. Soc Media+ Soc 4:2056305118784780

10.

Starbird K, Palen L (2011) “Voluntweeters”: self-organizing by digital volunteers in times of crisis. In Proceedings of the 2011 annual conference on Human factors in computing systems–CHI ’11. ACM Press, New York, p 1071

11.

Bruns A, Burgess J (2012) Local and global responses to disaster:# eqnz and the Christchurch earthquake. In Proceedings of the 2012 Australian and New Zealand Disaster and Emergency Management Conference. (pp 86–103)

12.

Bruns, A., Highfield, T., & Burgess, J. (2013). The Arab spring and social media audiences. American Behavioral Scientist, 57, 871–898. https://doi.org/10.1177/0002764213479374CrossRef

13.

Bruns A, Burgess JE (2011) The use of twitter hashtags in the formation of ad hoc publics. In Proceedings of the 6th European consortium for political research (ECPR) general conference 2011

14.

Hofstede, G. H., Hofstede, G. J., & Minkov, M. (2005). Cultures and organizations: Software of the mind. New York: Mcgraw-hill.

15.

Miller, G. S., & Skinner, D. J. (2015). The evolving disclosure landscape: how changes in technology, the media, and capital markets are affecting disclosure. Journal of Accounting Research, 53, 221–239. https://doi.org/10.1111/1475-679X.12075CrossRef

16.

Arnaboldi, M., Busco, C., & Cuganesan, S. (2017). Accounting, accountability, social media and big data: Revolution or hype? Accounting, Audit Account J, 30, 762–776. https://doi.org/10.1108/AAAJ-03-2017-2880CrossRef

17.

Debreceny, R. S., Wang, T., Zhou, M., & (Jamie),. (2019). Research in social media: Data sources and methodologies. Journal of Information Systems, 33, 1–28. https://doi.org/10.2308/isys-51984CrossRef

18.

Chahine, S., & Malhotra, N. K. (2018). Impact of social media strategies on stock price: The case of Twitter. European Journal of Marketing, 52, 1526–1549. https://doi.org/10.1108/EJM-10-2017-0718CrossRef

19.

Kesavan, R., Bernacchi, M. D., & Mascarenhas, O. A. J. (2013). Word of Mouse: CSR communication and the social media. International Management Review, 9(1), 58–66.

20.

Okazaki, S., Plangger, K., West, D., & Menéndez, H. D. (2020). Exploring digital corporate social responsibility communications on Twitter. Journal of Business Research, 117, 675–682. https://doi.org/10.1016/j.jbusres.2019.09.006CrossRef

21.

Boyd D, Golder S, Lotan G (2010) Tweet, Tweet, retweet: Conversational aspects of retweeting on twitter. In 2010 43rd Hawaii International Conference on System Sciences, (pp 1–10) IEEE

22.

Kelton, A. S., & Pennington, R. R. (2020). If you tweet, they will follow: CEO tweets, social capital, and investor say-on-pay judgments. Journal of Information Systems, 34, 105–122. https://doi.org/10.2308/isys-52449CrossRef

23.

Blankespoor, E. (2018). Firm communication and investor response: A framework and discussion integrating social media. Accounting, Organ Soc, 68–69, 80–87. https://doi.org/10.1016/j.aos.2018.03.009CrossRef

24.

Heller Baird, C., & Parasnis, G. (2011). From social media to social customer relationship management. Strateg Leadersh, 39, 30–37. https://doi.org/10.1108/10878571111161507CrossRef

25.

Kesavan, R., Bernacchi, M., & Mascarenha, O. A. J. (2013). Word of mouse: CSR communication and the social media. Eng Int Manag Rev, 9, 58–66.

26.

Jansen, F. (2010). Digital activism in the middle east: Mapping issue networks in Egypt, Iran, Syria and Tunisia. Knowledge Management for Development Journal, 6, 37–52. https://doi.org/10.1080/19474199.2010.493854CrossRef

27.

Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 60, 2169–2188. https://doi.org/10.1002/ASI.21149CrossRef

28.

Schaupp, L. C., & Bélanger, F. (2014). The value of social media for small businesses. Journal of Information Systems, 28, 187–207. https://doi.org/10.2308/isys-50674CrossRef

29.

Majumdar, A., & Bose, I. (2019). Do tweets create value? A multi-period analysis of Twitter use and content of tweets for manufacturing firms. International Journal of Production Economics, 216, 1–11. https://doi.org/10.1016/j.ijpe.2019.04.008CrossRef

30.

Blankespoor, E., Miller, G. S., & White, H. D. (2014). The role of dissemination in market liquidity: Evidence from firms’ Use of Twitter™. The Accounting Review, 89, 79–112. https://doi.org/10.2308/accr-50576CrossRef

31.

Curtis, A., Richardson, V. J., & Schmardebeck, R. (2014). Investor attention and the pricing of earnings news. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2467243CrossRef

32.

Lee, L. F., Hutton, A. P., & Shu, S. (2015). The role of social media in the capital market: Evidence from consumer product recalls. Journal of Accounting Research, 53, 367–404. https://doi.org/10.1111/1475-679X.12074CrossRef

33.

Bartov, E., Faurel, L., & Mohanram, P. S. (2018). Can twitter help predict firm-level earnings and stock returns? The Accounting Review, 93, 25–57. https://doi.org/10.2308/accr-51865CrossRef

34.

Ruan, Y., Durresi, A., & Alfantoukh, L. (2018). Using twitter trust network for stock market analysis. Knowledge-Based Syst, 145, 207–218. https://doi.org/10.1016/j.knosys.2018.01.016CrossRef

35.

Sul, H. K., Dennis, A. R., & Yuan, L. I. (2017). Trading on twitter: Using social media sentiment to predict stock returns. Decision Sciences, 48, 454–488. https://doi.org/10.1111/deci.12229CrossRef

36.

Cade, N. L. (2018). Corporate social media: How two-way disclosure channels influence investors. Accounting, Organ Soc, 68–69, 63–79. https://doi.org/10.1016/j.aos.2018.03.004CrossRef

37.

Kim, E.-H., & Youm, Y. N. (2017). How do social media affect analyst stock recommendations? Evidence from S&P 500 electric power companies’ twitter accounts. Strategic Management Journal, 38, 2599–2622. https://doi.org/10.1002/smj.2678CrossRef

38.

Elliott, W. B., Grant, S. M., & Hodge, F. D. (2018). Negative news and investor trust: The role of $Firm and #CEO twitter use. Journal of Accounting Research, 56, 1483–1519. https://doi.org/10.1111/1475-679X.12217CrossRef

39.

Hofstede, G. (2003). What is culture? A reply to Baskerville. Accounting, Organ Soc, 28, 811–813. https://doi.org/10.1016/S0361-3682(03)00018-7CrossRef

40.

Hofstede Insights National Culture. https://hi.hofstede-insights.com/national-culture. Accessed 20 Nov 2021

41.

Kim, I., & Kuljis, J. (2010). Manifestations of CULTURE IN WEBSITE DESIGN. Journal of Computing and Information Technology, 18, 125–132. https://doi.org/10.2498/CIT.1001806CrossRef

42.

Yeniyurt, S., & Townsend, J. D. (2003). Does culture explain acceptance of new products in a country?: An empirical investigation. International Marketing Review, 20, 377–396. https://doi.org/10.1108/02651330310485153/FULL/XMLCrossRef

43.

Tong, M., & Robertson, K. (2008). Political and cultural representation in Malaysian websites. International Journal of Design, 2, 67–79.

44.

Hofstede, G. (1991). Empirical models of cultural differences. In N. Bleichrodt & P. J. D. Drenth (Eds.), Contemporary issues in cross-cultural psychology (pp. 4–20). Swets & Zeitlinger Publishers.

45.

Herbig, P., & Dunphy, S. (1998). Culture and innovation. Cross Cult Manag An Int J, 5, 13–21. https://doi.org/10.1108/13527609810796844/FULL/XMLCrossRef

46.

Al-Rasheed,. (2001). Features of traditional Arab management and organization in the Jordan business environment. Journal of Transnational Management Development, 6(1–2), 27–53.CrossRef

47.

Bjerke, B., & Al-Meer, A. (1993). Culture’s consequences: Management in Saudi Arabia. Leadership & Organization Development Journal, 14(2), 30–354.CrossRef

48.

Al-Rasheed, A. (1997). Factors affecting managers’ motivation and job satisfaction: The case of Jordanian bank managers. Middle East Business Review, 2, 112–117.

49.

Kalliny, M., & Gentry, L. (2007). Cultural values reflected in Arab and american television advertising. Journal of Current Issues & Research in Advertising, 29, 15–32. https://doi.org/10.1080/10641734.2007.10505205CrossRef

50.

Migliore, L. A. (2011). Relation between big five personality traits and Hofstede’s cultural dimensions. Cross Cult Manag An Int J, 18, 38–54. https://doi.org/10.1108/13527601111104287CrossRef

51.

Choi, K. S., Im, I., & Hofstede, G. J. (2016). A cross-cultural comparative analysis of small group collaboration using mobile twitter. Comput Human Behav, 65, 308–318. https://doi.org/10.1016/J.CHB.2016.08.043CrossRef

52.

Garcia-Gavilanes, R., Quercia, D., & Jaimes, A. (2013). Cultural dimensions in twitter: Time, individualism and power. Proceedings of the International AAAI Conference on Web and Social Media, 7, 195–204.CrossRef

53.

Khan, G. F., Yoon, H. Y., Kim, J., & Park, H. W. (2014). From e-government to social government: Twitter use by Korea’s central government. Online Information Review, 38, 95–113. https://doi.org/10.1108/OIR-09-2012-0162/FULL/XMLCrossRef

54.

Khashman, N., Large, A. (2011) Measuring cultural markers in arabic government websites using hofstede’s cultural dimensions. Lecture Notes Computer Science (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) 6770 LNCS:431–439. https://doi.org/10.1007/978-3-642-21708-1_49

55.

Khashman, N., Large, A. (2013) Arabic Website Design: User Evaluation from a Cultural Perspective. Lecture Notes Computer Science (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) 8024 LNCS:424–431. https://doi.org/10.1007/978-3-642-39137-8_47

56.

Marcos, M. C., García-Gavilanes, R., Bataineh, E., Pasarin, L. (2013). Cultural differences on seeking information: an eye tracking study. In: CIH’13: Workshop Many People, Many Eyes; April 27-May 2, Paris, France.

57.

Araujo, T., & Kollat, J. (2018). Communicating effectively about CSR on Twitter. Internet Research, 28, 419–431. https://doi.org/10.1108/IntR-04-2017-0172CrossRef

58.

Zhou, X., Chen, Z., Zhan, X., et al. (2021). Improved policy mechanisms for the promotion of future digital business economy during covid-19 pandemic. Electronic Commerce Research. https://doi.org/10.1007/s10660-021-09484-xCrossRef

59.

Momin, M. A., Chong, S., van Staden, C., & Ma, L. (2022). Stakeholder engagement during COVID-19: Evidence from corporate use of Twitter. Soc Responsib J. https://doi.org/10.1108/SRJ-08-2022-0314CrossRef

60.

Rangel-Pérez, C., Monfort, A., & Miquel, S. (2022). Thematic dis/connection of Ibex35 companies to generate dialogue with their stakeholders via Twitter during the pandemic. Communication & Society. https://doi.org/10.15581/003.35.2.169-183CrossRef

61.

Iazzi, A., Ligorio, L., & Iaia, L. (2022). Were we prepared to face a pandemic? Exploring companies’ CSR disclosure on social media before COVID-19 outbreak. Management Decision, 60, 2849–2874. https://doi.org/10.1108/MD-12-2021-1651CrossRef

62.

Singhal, A., Baxi, M. K., & Mago, V. (2022). Synergy between public and private health care organizations during COVID-19 on twitter: Sentiment and engagement analysis using forecasting models. JMIR Medical Informatics, 10, e37829. https://doi.org/10.2196/37829CrossRef

63.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53, 59–68. https://doi.org/10.1016/j.bushor.2009.09.003CrossRef

64.

Zeledon M (2009) Stock twits may change how you Trade. In bloomberg.com. https://www.bloomberg.com/news/articles/2009-02-10/stocktwits-may-change-how-you-trade. Accessed 6 Nov 2020

65.

Securities and Exchange Commission (SEC) (2015) Updated Investor Alert: Social Media and Investing -- Stock Rumors. In Secur. Exch. Comm. https://www.sec.gov/oiea/investor-alerts-bulletins/ia_rumors.html. Accessed 6 Nov 2020

66.

Durham, M. (2006). Language choice on a swiss mailing list. Journal of Computer Mediated Communication. https://doi.org/10.1111/j.1083-6101.2003.tb00359.xCrossRef

67.

Eleta, I., & Golbeck, J. (2014). Multilingual use of twitter: Social networks at the language frontier. Comput Human Behav, 41, 424–432. https://doi.org/10.1016/j.chb.2014.05.005CrossRef

68.

Hong L, Convertino G, Chi E (2011) Language matters in twitter: A large scale study. In Proceedings of the international AAAI conference on web and social media. (pp. 518–521)

69.

Poell, T., & Darmoni, K. (2012). Twitter as a multilingual space: The articulation of the Tunisian revolution through #sidibouzid. NECSUS Eur J Media Stud, 1, 14–34. https://doi.org/10.5117/NECSUS2012.1.POELCrossRef

70.

Mourtada R, Salem F (2014) Citizen engagement and public services in the arab world: The potential of social media, 6th edition. Mohammed Bin Rashid School of Government

71.

Aladwani, A. M. (2015). Facilitators, characteristics, and impacts of Twitter use: Theoretical analysis and empirical illustration. International Journal of Information Management, 35, 15–25. https://doi.org/10.1016/j.ijinfomgt.2014.09.003CrossRef

72.

Ahmad, S. Z., Abu Bakar, A. R., & Ahmad, N. (2019). Social media adoption and its impact on firm performance: The case of the UAE. International Journal of Entrepreneurial Behavior & Research, 25, 84–111. https://doi.org/10.1108/IJEBR-08-2017-0299CrossRef

73.

Twitter (2020) Get Tweet timelines. In: Twitter. https://developer.twitter.com/en/docs/twitter-api/v1/tweets/timelines/guides/migration-guide

74.

Mitchell, R. (2018). Web scraping with Python: Collecting more data from the modern web. O’Reilly Media Inc.

75.

Jimenez-Marquez, J. L., Gonzalez-Carrasco, I., Lopez-Cuadrado, J. L., & Ruiz-Mezcua, B. (2019). Towards a big data framework for analyzing social media content. International Journal of Information Management, 44, 1–12. https://doi.org/10.1016/j.ijinfomgt.2018.09.003CrossRef

76.

Albarrak, M. S., Elnahass, M., Papagiannidis, S., & Salama, A. (2020). The effect of twitter dissemination on cost of equity: A big data approach. International Journal of Information Management, 50, 1–16. https://doi.org/10.1016/j.ijinfomgt.2019.04.014CrossRef

77.

Hoffmann C, Kamps B (2020) Covid-19 reference book, 3rd ed

78.

Dinov, I. D. (2018). Natural language processing text mining. Data science and predictive analytics (pp. 659–95). Springer.CrossRef

79.

Ramos J (2003) Using tf-idf to determine word relevance in document queries. In Proceedings of the first instructional conference on machine learning. (pp 133–142)

80.

Jung, S. H., & Jeong, Y. J. (2020). Twitter data analytical methodology development for prediction of start-up firms’ social media marketing level. Technology in Society, 63, 101409. https://doi.org/10.1016/j.techsoc.2020.101409CrossRef

81.

Santarone, K., Meneses, E., Shepherd, A., et al. (2020). Surgeons and social media: The use of twitter hashtags at the academic surgical congress 2015–2019: A cross sectional study. Ann Med Surg, 58, 151–155. https://doi.org/10.1016/j.amsu.2020.09.004CrossRef

82.

Macskassy SA, Michelson M (2011) Why do people retweet? anti-homophily wins the day! In ICWSM. (pp 209–216)

83.

Haouari F, Hasanain M, Suwaileh R, Elsayed T (2020) ArCOV-19: The first Arabic COVID-19 Twitter dataset with propagation networks

84.

Hanini F (2009) A thesis in teaching English to speakers of other languages. American University of Sharjah

85.

Abbas W (2015) How good is your English? UAE residents not proficient, says study. In: Emirates247. https://www.emirates247.com/news/emirates/how-good-is-your-english-uae-residents-not-proficient-says-study-2015-11-05-1.609287. Accessed 5 Nov 2020

86.

Mathews, D., Franzen-Castle, L., Colby, S., et al. (2015). Use of word clouds as a novel approach for analysis and presentation of qualitative data for program evaluation. Journal of Nutrition Education and Behavior, 47, S26. https://doi.org/10.1016/j.jneb.2015.04.071CrossRef

87.

Sillup, G. P., Klimberg, R. K., Sullivan, E. L., et al. (2018). P1–538: Assessing an activity for nursing home staff and residents with dementia and early onset alzheimer’s disease using an artbus and word clouds. Alzheimer’s Dement, 14, P539–P540. https://doi.org/10.1016/j.jalz.2018.06.549CrossRef

88.

Ning, W., Lin, S., Zhou, J., et al. (2018). WocEA: The visualization of functional enrichment results in word clouds. Journal of Genetics and Genomics, 45, 415–417. https://doi.org/10.1016/j.jgg.2018.02.008CrossRef

89.

Ibrahim, N. F., Wang, X., & Bourne, H. (2017). Exploring the effect of user engagement in online brand communities: Evidence from Twitter. Comput Human Behav, 72, 321–338. https://doi.org/10.1016/j.chb.2017.03.005CrossRef

90.

Al Kuwaiti A (2019) Corporate governance, institutional framework, and firm performance: Evidence from the UAE. United Arab Emirates University

91.

Kabasakal, H., & Bodur, M. (2002). Arabic cluster: A bridge between East and West. Journal of World Business, 37, 40–54.CrossRef

92.

WHO (2020) Timeline of WHO’s response to COVID-19. https://www.who.int/news/item/29-06-2020-COVIDtimeline

93.

Charise A (2007) More english, Less Islam? An overview of english language functions in the Arabian/Persian Gulf. http://homes.chass.utoronto.ca/~cpercy/courses/eng6365-charise.htm. Accessed 5 Nov 2020

Titel: Corporate communication during the COVID-19 crisis in a multicultural environment: culture and tweet impact
verfasst von: Faten F. Kharbat
Yezen Kannan
Kimberly Gleason
Amer Qasim
Publikationsdatum: 09.11.2023
Verlag: Springer US
Erschienen in: Electronic Commerce Research / Ausgabe 1/2024
Print ISSN: 1389-5753
Elektronische ISSN: 1572-9362
DOI: https://doi.org/10.1007/s10660-023-09777-3

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 1/2024

Fintech Growth during COVID-19 in MENA Region: Current Challenges and Future prospects

Securing blockchain-based crowdfunding platforms: an integrated graph neural networks and machine learning approach

Barriers to blockchain adoption for supply chain finance: the case of Indian SMEs

Kickstarting blockchain: designing blockchain-based tokens for equity crowdfunding

The role of expertise in herding behaviors: evidence from a crowdfunding market

Open banking on the horizon: a scientometric analysis and research agenda