IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v50y2019ics1062940818304133.html
   My bibliography  Save this article

Impact of CEO media appearance on corporate performance in social media

Author

Listed:
  • Bai, Lijuan
  • Yan, Xiangbin
  • Yu, Guang

Abstract

The impact of CEOs’ media appearance in social media on corporate performance (financial performance) has received little research attention. In this paper, we propose the CEO media appearance indexes, namely CEO media coverage, CEO media transmission, and CEO media sentiment, and CEO searching attention indexes, namely media searching attention and user searching attention, then analyze the influence of CEO media appearance and CEO searching attention on corporate performance. The results show that the media transmission and media searching attention indexes have significant positive effects on corporate performance. The media sentiment and user searching attention indexes have significant negative effects on corporate performance; however, the same effect was not observed formedia coverage. The effects of the above indexes were consistent with the interaction analyses. We discuss theoretical implications for research on CEO and corporate performance and management implications for corporate social media marketing.

Suggested Citation

  • Bai, Lijuan & Yan, Xiangbin & Yu, Guang, 2019. "Impact of CEO media appearance on corporate performance in social media," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    • Handle: RePEc:eee:ecofin:v:50:y:2019:i:c:s1062940818304133
    DOI: 10.1016/j.najef.2019.100996
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940818304133
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2019.100996?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    2. Bangwayo-Skeete, Prosper F. & Skeete, Ryan W., 2015. "Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach," Tourism Management, Elsevier, vol. 46(C), pages 454-464.
    3. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    4. D’Amuri, Francesco & Marcucci, Juri, 2010. "“Google it!” Forecasting the US Unemployment Rate with a Google Job Search index," Global Challenges Papers 60680, Fondazione Eni Enrico Mattei (FEEM).
    5. D'Amuri, Francesco & Marcucci, Juri, 2009. "‘Google it!’ Forecasting the US unemployment rate with a Google job search index," ISER Working Paper Series 2009-32, Institute for Social and Economic Research.
    6. Ilaria Bordino & Stefano Battiston & Guido Caldarelli & Matthieu Cristelli & Antti Ukkonen & Ingmar Weber, 2012. "Web Search Queries Can Predict Stock Market Volumes," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-17, July.
    7. Shivaram Rajgopal & Terry Shevlin & Valentina Zamora, 2006. "CEOs' Outside Employment Opportunities and the Lack of Relative Performance Evaluation in Compensation Contracts," Journal of Finance, American Finance Association, vol. 61(4), pages 1813-1844, August.
    8. Cianci, Anna M. & Kaplan, Steven E., 2010. "The effect of CEO reputation and explanations for poor performance on investors' judgments about the company's future performance and management," Accounting, Organizations and Society, Elsevier, vol. 35(4), pages 478-495, May.
    9. Michael K. Bednar & Steven Boivie & Nicholas R. Prince, 2013. "Burr Under the Saddle: How Media Coverage Influences Strategic Change," Organization Science, INFORMS, vol. 24(3), pages 910-925, June.
    10. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    11. Lynn Wu & Erik Brynjolfsson, 2015. "The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 89-118, National Bureau of Economic Research, Inc.
    12. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    13. Michael S. Drake & Darren T. Roulstone & Jacob R. Thornock, 2012. "Investor Information Demand: Evidence from Google Searches Around Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 50(4), pages 1001-1040, September.
    14. Mathew L. A. Hayward & Violina P. Rindova & Timothy G. Pollock, 2004. "Believing one's own press: the causes and consequences of CEO celebrity," Strategic Management Journal, Wiley Blackwell, vol. 25(7), pages 637-653, July.
    15. Robert Strand, 2014. "Strategic Leadership of Corporate Sustainability," Journal of Business Ethics, Springer, vol. 123(4), pages 687-706, September.
    16. Li, Xin & Pan, Bing & Law, Rob & Huang, Xiankai, 2017. "Forecasting tourism demand with composite search index," Tourism Management, Elsevier, vol. 59(C), pages 57-66.
    17. Jian, Ming & Lee, Kin Wai, 2011. "Does CEO reputation matter for capital investments?," Journal of Corporate Finance, Elsevier, vol. 17(4), pages 929-946, September.
    18. Jennifer Francis & Allen H. Huang & Shivaram Rajgopal & Amy Y. Zang, 2008. "CEO Reputation and Earnings Quality," Contemporary Accounting Research, John Wiley & Sons, vol. 25(1), pages 109-147, March.
    19. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yanpeng Chen & Wenjun Mai, 2024. "Investor attention and environmental performance of Chinese high-tech companies: the moderating effects of media attention and coverage sentiment," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-16, December.
    2. Ahmed, Mohamed Shaker & Kumar, Satish & Gupta, Prashant & Bamel, Nisha, 2024. "CEO media coverage and cash holdings," International Review of Financial Analysis, Elsevier, vol. 91(C).
    3. Nor Hasliza Md Saad & Zulnaidi Yaacob, 2021. "Building a Personal Brand as a CEO: A Case Study of Vivy Yusof, the Cofounder of FashionValet and the dUCk Group," SAGE Open, , vol. 11(3), pages 21582440211, July.
    4. Luis Manuel Cerdá Suárez & Jesús Perán López & Belén Cambronero Saiz, 2020. "The Influence of Heuristic judgments in Social Media on Corporate Reputation: A Study in Spanish Leader Companies," Sustainability, MDPI, vol. 12(4), pages 1-17, February.
    5. Aabo, Tom & Jacobsen, Mikkel Lilholt & Stendys, Kasper, 2022. "Pay me with fame, not mammon: CEO narcissism, compensation, and media coverage," Finance Research Letters, Elsevier, vol. 46(PB).
    6. Yongkyu Choi & Keun Tae Cho, 2021. "Analysis of Environmental Management Characteristics Using Network Analysis of CEO Communication in the Automotive Industry," Sustainability, MDPI, vol. 13(21), pages 1-23, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
    2. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    3. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
    4. Ramya Rajajagadeesan Aroul & Sanjiv Sabherwal & Sergiy Saydometov, 2022. "FEAR Index, city characteristics, and housing returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 173-205, March.
    5. Li, Xin & Pan, Bing & Law, Rob & Huang, Xiankai, 2017. "Forecasting tourism demand with composite search index," Tourism Management, Elsevier, vol. 59(C), pages 57-66.
    6. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
    7. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    8. Monge, Manuel & Claudio-Quiroga, Gloria & Poza, Carlos, 2024. "Chinese economic behavior in times of covid-19. A new leading economic indicator based on Google trends," International Economics, Elsevier, vol. 177(C).
    9. Abay,Kibrom A. & Hirfrfot,Kibrom Tafere & Woldemichael,Andinet, 2020. "Winners and Losers from COVID-19 : Global Evidence from Google Search," Policy Research Working Paper Series 9268, The World Bank.
    10. Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
    11. Serhan Cevik, 2022. "Where should we go? Internet searches and tourist arrivals," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4048-4057, October.
    12. Meshcheryakov, Artem & Winters, Drew B., 2022. "Retail investor attention and the limit order book: Intraday analysis of attention-based trading," International Review of Financial Analysis, Elsevier, vol. 81(C).
    13. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
    14. Ahmed Shoukry Rashad, 2022. "The Power of Travel Search Data in Forecasting the Tourism Demand in Dubai," Forecasting, MDPI, vol. 4(3), pages 1-11, July.
    15. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.
    16. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
    17. Chien-jung Ting & Yi-Long Hsiao, 2022. "Nowcasting the GDP in Taiwan and the Real-Time Tourism Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-2.
    18. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
    19. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
    20. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:50:y:2019:i:c:s1062940818304133. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.