The Effects of Social Media Content on a Firm’s Book-Based and Market-Based Performance Literature Review
Main Article Content
Keywords
social media content, user-generated content, firm-generated content, book-based performance, market-based performance
Abstract
The success of companies is increasingly dependent on their online image. Therefore, the research has called for a better understanding of the characteristics of a firm’s online content that can enhance a firm’s performance. This study delves into the impact of social media content on both book-based and market-based performances of firms, drawing insights from 32 articles published between 2016 and 2022. The present article encompasses the categorisation and explanation of the economic effects of user- and firm-generated social media content, while also exploring cross-firm and cross-industry spillover effects. The study extends prior research that has primarily focused on the effects of one type of content or the other and only on some specific measures. Moreover, the study visually illustrates the economic effects of social media content on book-based and marked-based firm attributes. These insights provide a valuable resource for firms seeking to optimise their social media strategies to improve performance and for researchers choosing a research agenda.
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References
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Reboredo, J. C., & Ugolini, A. (2018). The impact of Twitter sentiment on renewable energy stocks. Energy Economics, 76, 153–169. https://doi.org/10.1016/j.eneco.2018.10.014
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Wardati, N. K., & Er, M. (2019). The impact of social media usage on the sales process in small and medium enterprises (SMEs): A systematic literature review. Procedia Computer Science, 161, 976–983. https://doi.org/10.1016/j.procs.2019.11.207
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Yost, E., Zhang, T., & Qi, R. (2021). The power of engagement: Understanding active social media engagement and the impact on sales in the hospitality industry. Journal of Hospitality and Tourism Management, 46, 83–95. https://doi.org/10.1016/ j.jhtm.2020.10.008
Yu, X., Yuan, C., Kim, J., & Wang, S. (2021). A new form of brand experience in online social networks: An empirical analysis. Journal of Business Research, 130, 426–435. https://doi.org/10.1016/j.jbusres.2020.02.011
Zhang, N., Guo, X., Zhang, L., & He, L. (2021). How to repair public trust effectively: Research on enterprise online public opinion crisis response. Electronic Commerce Research and Applications, 49, 101077. https://doi.org/10.1016/j.elerap.2021.101077
Zhang, W., Wang, P., & Li, Y. (2021). Do messages on online stock forums spur firm productivity? Pacific-Basin Finance Journal, 68, 101609. https://doi.org/10.1016/j.pacfin.2021.101609
Zu, X., Diao, X., & Meng, Z. (2019). The impact of social media input intensity on firm performance: Evidence from Sina Weibo. Physica A: Statistical Mechanics and Its Applications, 536, 122556. https://doi.org/10.1016/j.physa.2019.122556
Audrino, F., Sigrist, F., & Ballinari, D. (2020). The impact of sentiment and attention measures on stock market volatility. International Journal of Forecasting, 36(2), 334–357. https://doi.org/10.1016/j.ijforecast.2019.05.010
Audrino, F., & Tetereva, A. (2019). Sentiment spillover effects for US and European companies. Journal of Banking & Finance, 106, 542–567. https://doi.org/10.1016/j.jbankfin.2019.07.022
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
Benslama, T., & Jallouli, R. (2022). Social media data analytics for marketing strategies: The path from data to value. Journal of Telecommunications and the Digital Economy, 10(2), 96–110. https://doi.org/10.18080/jtde.v10n2.523
Broadstock, D. C., & Zhang, D. (2019). Social-media and intraday stock returns: The pricing power of sentiment. Finance Research Letters, 30, 116–123. https://doi.org/10.1016/j.frl.2019.03.030
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D., Wu, J., Winter, C., … Amodei, D. (2020). Language models are few-shot learners. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), Advances in Neural Information Processing Systems, 33, 1877–1901. [PDF]. Curran Associates, Inc. https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
Byun, S. K., & Oh, J.-M. (2018). Local corporate social responsibility, media coverage, and shareholder value. Journal of Banking & Finance, 87, 68–86. https://doi.org/10.1016/j.jbankfin.2017.09.010
Cioroianu, I., Corbet, S., & Larkin, C. (2021). The differential impact of corporate blockchain-development as conditioned by sentiment and financial desperation. Journal of Corporate Finance, 66, 101814. https://doi.org/10.1016/j.jcorpfin.2020.101814
Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, 95–120. https://doi.org/10.1086/228943
Cui, R., Gallino, S., Moreno, A., & Zhang, D. J. (2018). The operational value of social media information. Production and Operations Management, 27(10), 1749–1769. https://doi.org/10.1111/poms.12707
Derani, N. E. S., & Naidu, P. (2016). The impact of utilizing social media as a communication platform during a crisis within the oil industry. Procedia Economics and Finance, 35, 650–658. https://doi.org/10.1016/S2212-5671(16)00080-0
Ding, R., Zhou, H., & Li, Y. (2020). Social media, financial reporting opacity, and return comovement: Evidence from Seeking Alpha. Journal of Financial Markets, 50, 100511. https://doi.org/10.1016/j.finmar.2019.100511
Ghose, A., & Ipeirotis, P. G. (2011). Estimating the helpfulness and economic impact of product reviews: mining text and reviewer characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498–1512. https://doi.org/10.1109/TKDE.2010.188
Goh, K.-Y., Heng, C.-S., & Lin, Z. (2013). Social media brand community and consumer behavior: Quantifying the relative impact of user- and marketer-generated content. Information Systems Research, 24(1), 88–107. https://doi.org/10.1287/isre.1120.0469
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380. https://doi.org/10.1086/225469
Hanafizadeh, P., Shafia, S., & Bohlin, E. (2021). Exploring the consequence of social media usage on firm performance. Digital Business, 1(2), 100013. https://doi.org/10.1016/j.digbus.2021.100013
Ho, C.-S., Damien, P., Gu, B., & Konana, P. (2017). The time-varying nature of social media sentiments in modeling stock returns. Decision Support Systems, 101, 69–81. https://doi.org/10.1016/j.dss.2017.06.001
Jallouli, R., & Kaabi, S. (2022). Mapping top strategic e-commerce technologies in the digital marketing literature. Journal of Telecommunications and the Digital Economy, 10(3), 149–164. https://doi.org/10.18080/jtde.v10n3.554
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003
Khadjeh Nassirtoussi, A., Aghabozorgi, S., Ying Wah, T., & Ngo, D. C. L. (2014). Text mining for market prediction: A systematic review. Expert Systems with Applications, 41(16), 7653–7670. https://doi.org/10.1016/j.eswa.2014.06.009
Kirchhain, H., Mutl, J., & Zietz, J. (2021). Spillover effects of company news across real estate markets and causal impact analysis. Journal of Housing Economics, 54, 101785. https://doi.org/10.1016/j.jhe.2021.101785
Kumar, V., Choi, J. B., & Greene, M. (2017). Synergistic effects of social media and traditional marketing on brand sales: Capturing the time-varying effects. Journal of the Academy of Marketing Science, 45(2), 268–288. https://doi.org/10.1007/s11747-016-0484-7
Lányi, B., Hornyák, M., & Kruzslicz, F. (2021). The effect of online activity on SMEs’ competitiveness. Competitiveness Review: An International Business Journal, 31(3), 477–496. https://doi.org/10.1108/CR-01-2020-0022
Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., Wu, Z., Zhao, L., Zhu, D., Li, X., Qiang, N., Shen, D., Liu, T., & Ge, B. (2023). Summary of ChatGPT-related research and perspective towards the future of large language models. Meta-Radiology, 1(2), 100017. https://doi.org/10.1016/j.metrad.2023.100017
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.2019.04.008
Moussa, F., Delhoumi, E., & Ouda, O. B. (2017). Stock return and volatility reactions to information demand and supply. Research in International Business and Finance, 39, 54–67. https://doi.org/10.1016/j.ribaf.2016.07.016
Naumer, H.-J., & Yurtoglu, B. (2022). It is not only what you say, but how you say it: ESG, corporate news, and the impact on CDS spreads. Global Finance Journal, 52, 100571. https://doi.org/10.1016/j.gfj.2020.100571
Olanrewaju, A.-S. T., Hossain, M. A., Whiteside, N., & Mercieca, P. (2020). Social media and entrepreneurship research: A literature review. International Journal of Information Management, 50, 90–110. https://doi.org/10.1016/j.ijinfomgt.2019.05.011
Reboredo, J. C., & Ugolini, A. (2018). The impact of Twitter sentiment on renewable energy stocks. Energy Economics, 76, 153–169. https://doi.org/10.1016/j.eneco.2018.10.014
Saridakis, G., Lai, Y., Mohammed, A.-M., & Hansen, J. M. (2018). Industry characteristics, stages of E-commerce communications, and entrepreneurs and SMEs revenue growth. Technological Forecasting and Social Change, 128, 56–66. https://doi.org/10.1016/j.techfore.2017.10.017
SCImago. (n. d.). SJR – SCImago Journal & Country Rank [Portal]. Retrieved September 1, 2023, from https://www.scimagojr.com
Smith, C., Smith, J. B., & Shaw, E. (2017). Embracing digital networks: Entrepreneurs’ social capital online. Journal of Business Venturing, 32(1), 18–34. https://doi.org/10.1016/j.jbusvent.2016.10.003
Umar, Z., Gubareva, M., Yousaf, I., & Ali, S. (2021). A tale of company fundamentals vs sentiment driven pricing: The case of GameStop. Journal of Behavioral and Experimental Finance, 30, 100501. https://doi.org/10.1016/j.jbef.2021.100501
Uzunoğlu, E., & Misci Kip, S. (2014). Brand communication through digital influencers: Leveraging blogger engagement. International Journal of Information Management, 34(5), 592–602. https://doi.org/10.1016/j.ijinfomgt.2014.04.007
Walker, C. B. (2016). The direction of media influence: Real-estate news and the stock market. Journal of Behavioral and Experimental Finance, 10, 20–31. https://doi.org/10.1016/j.jbef.2016.02.001
Wardati, N. K., & Er, M. (2019). The impact of social media usage on the sales process in small and medium enterprises (SMEs): A systematic literature review. Procedia Computer Science, 161, 976–983. https://doi.org/10.1016/j.procs.2019.11.207
Yang, X., Zhu, Y., & Cheng, T. Y. (2020). How the individual investors took on big data: The effect of panic from the internet stock message boards on stock price crash. Pacific-Basin Finance Journal, 59, 101245. https://doi.org/10.1016/j.pacfin.2019.101245
Yost, E., Zhang, T., & Qi, R. (2021). The power of engagement: Understanding active social media engagement and the impact on sales in the hospitality industry. Journal of Hospitality and Tourism Management, 46, 83–95. https://doi.org/10.1016/ j.jhtm.2020.10.008
Yu, X., Yuan, C., Kim, J., & Wang, S. (2021). A new form of brand experience in online social networks: An empirical analysis. Journal of Business Research, 130, 426–435. https://doi.org/10.1016/j.jbusres.2020.02.011
Zhang, N., Guo, X., Zhang, L., & He, L. (2021). How to repair public trust effectively: Research on enterprise online public opinion crisis response. Electronic Commerce Research and Applications, 49, 101077. https://doi.org/10.1016/j.elerap.2021.101077
Zhang, W., Wang, P., & Li, Y. (2021). Do messages on online stock forums spur firm productivity? Pacific-Basin Finance Journal, 68, 101609. https://doi.org/10.1016/j.pacfin.2021.101609
Zu, X., Diao, X., & Meng, Z. (2019). The impact of social media input intensity on firm performance: Evidence from Sina Weibo. Physica A: Statistical Mechanics and Its Applications, 536, 122556. https://doi.org/10.1016/j.physa.2019.122556
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Jun 29, 2024
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Naidanov, I. (2024). The Effects of Social Media Content on a Firm’s Book-Based and Market-Based Performance: Literature Review. Journal of Telecommunications and the Digital Economy, 12(2), 41–56. https://doi.org/10.18080/jtde.v12n2.920
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Digital Economy & Society
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