Abstract
Year 2020 was challenging for companies across all sectors and regions. For many, the special circumstances brought by the Covid-19 pandemic and related counter measures led to required transformations in incumbent practices. While all sectors were impacted during 2020, manufacturing industries experienced unique challenges due to supply shortages and shutdowns of production plants. This research focuses in studying the external communications of manufacturing companies. Social media platforms have emerged as channels for company communications, and Twitter as a focal one for less than formal communication. Companies’ activity on this platform during challenging times arises as meaningful for identifying latent signals on the developments in industries. Hence, Twitter activity of 18 most traded Finnish manufacturing companies in Helsinki Stock Exchange during 2020 is studied. In total, 4 915 tweets and their contents were analyzed. Frequently used words and n-grams are reflected with the financial performance of said companies and developments of Covid-19 pandemic during that year. The overall activity is observed to somewhat correlate with the recorded Covid-19 infections, however, number of tweets was lower than in 2019. Also, activity seems to follow official statements and set preventing measures concerning the virus. Content analysis of tweets reveals that Covid-19 was frequent topic in the studied companies’ external communications. In addition, need to organize non-conventional stakeholder events emerge from the companies’ communications. However, mostly the content seems to focus on long-time strategies of the studied companies, e.g., business renewal and efforts to increase sustainability.
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References
Hilmola, O.-P., Lähdeaho, O., Henttu, V., Hilletofth, P.: Covid-19 pandemic: early implications for north european manufacturing and logistics. Sustainability 12, 8315 (2020). https://doi.org/10.3390/su12208315
Handfield, R.B., Graham, G., Burns, L.: Corona virus, tariffs, trade wars and supply chain evolutionary design. Int. J. Oper. Prod. Manag. 40(10), 1649–1660 (2020). https://doi.org/10.1108/IJOPM-03-2020-0171
Moro, S., Rita, P., Vala, B.: Predicting social media performance metrics and evaluation of the impact on brand building: a data mining approach. J. Bus. Res. 69(9), 3341–3351 (2016). https://doi.org/10.1016/j.jbusres.2016.02.010
Gao, Q., Feng, C.: Computers in human behavior branding with social media: user gratifications, usage patterns, and brand message content strategies. Comput. Hum. Behav. 63, 868–890 (2016). https://doi.org/10.1016/j.chb.2016.06.022
Chae, B.: Insights from hashtag #supplychain and Twitter analytics: considering Twitter and Twitter data for supply chain practice and research. Int. J. Prod. Econ. 165, 247–259 (2015). https://doi.org/10.1016/j.ijpe.2014.12.037
Blasi, S., Brigato, L., Sedita, S.: Eco-friendliness and fashion perceptual attributes of fashion brands: an analysis of consumers’ perceptions based on twitter data mining. J. Clean. Prod. 244, 118701 (2020). https://doi.org/10.1016/j.jclepro.2019.118701
Tamayo, S., Combes, F., Gaudron, A.: Unsupervised machine learning to analyze City Logistics through Twitter. Transp. Res. Procedia 46, 220–228 (2020). https://doi.org/10.1016/j.trpro.2020.03.184
Luo, F., Cao, G., Mulligan, K., Li, X.: Explore spatiotemporal and demographic characteristics of human mobility via Twitter: a case study of Chicago. Appl. Geogr. 70, 11–25 (2016). https://doi.org/10.1016/j.apgeog.2016.03.001
Suma, S., Mehmood, R., Albugami, N., Katib, I., Albeshri, A.: Enabling next generation logistics and planning for smarter societies. Procedia Comput. Sci. 109, 1122–1127 (2017). https://doi.org/10.1016/j.procs.2017.05.440
Wang, Z., Ye, X., Tsou, M.-H.: Spatial, temporal, and content analysis of Twitter for wildfire hazards. Nat. Hazards 83(1), 523–540 (2016). https://doi.org/10.1007/s11069-016-2329-6
Xu, Z., Liu, Y., Yen, N.Y., Mei, L.: Crowdsourcing based description of urban emergency events using social media big data. IEEE Trans. Cloud Comput. 8(2), 387–397 (2016). https://doi.org/10.1109/TCC.2016.2517638
Alalwan, A.A., Rana, N.P., Dwivedi, Y.K., Algharabat, R.: Social media in marketing: a review and analysis of the existing literature. Telematics Inform. 34(7), 1177–1190 (2017). https://doi.org/10.1016/j.tele.2017.05.008
Chew, C., Eysenbach, G.: Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PLoS ONE 5(11), 1–13 (2010). https://doi.org/10.1371/journal.pone.0014118
Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hai, M., Shah, Z.: Top concerns of tweeters during the COVID-19 pandemic: a surveillance study. J. Med. Internet Res. 22(4), e19016 (2020). https://doi.org/10.2196/19016
Confirmed corona cases in Finland (COVID-19). https://thl.fi/en/web/thlfi-en/statistics/statistical-databases/open-data/confirmed-corona-cases-in-finland-covid-19. Accessed 27 Jan 2020
Lähdeaho, O., Hilmola, O.-P.: Content analysis of Finnish manufacturing companies’ Twitter activity. In: GSOM Emerging Markets Conference-2020, pp. 272–278. St. Petersburg State University Graduate School of Management, St. Petersburg, Russia (2020)
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Lähdeaho, O., Hilmola, OP. (2021). Crisis Year 2020: Analysis of Finnish Manufacturing Companies’ Twitter Activity. In: Zimmermann, A., Howlett, R.J., Jain, L.C., Schmidt, R. (eds) Human Centred Intelligent Systems . KES-HCIS 2021. Smart Innovation, Systems and Technologies, vol 244. Springer, Singapore. https://doi.org/10.1007/978-981-16-3264-8_4
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DOI: https://doi.org/10.1007/978-981-16-3264-8_4
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