Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content
The COVID-19 pandemic has caused many entrepreneurs and small and medium enterprises (SMEs) to adapt their business models and business strategies to the consequences caused by the pandemic. In order to identify the main innovations and technologies adopted by SMEs in the pandemic, in the present study, we used a database of 56,941 tweets related to the coronavirus to identify those that contained the hashtag #SMEs. The fnal sample was analyzed using several data-mining techniques such as sentiment analysis, topic modeling and textual analysis. The theoretical perspectives adopted in the present study were Computer-Aided Text Analysis, User-Generated Content and Natural Language Processing. The results of our analysis helped us to identify 15 topics (7 positive: Free support against Covid-19, Webinars tools, Time Optimizer and efciency, Business solutions tools, Advisors tools, Software for process support and Back-up tools; 4 negative: Government support, Payment systems, Cybersecurity problems and Customers solutions in Cloud, and and 4 neutral: Social media and e-commerce, Specialized startups software, CRMs and Finance and Big data analysis tools). The results of the present study suggest that SMEs have used a variety of digital tools and strategies to adapt to the changing market conditions brought on by the pandemic, and have been proactive in adopting new technologies to continue to operate and reach customers in a connected era. Future research should be directed towards understanding the long-term efects of these technologies and strategies on entrepreneurial growth and value creation, as well as the sustainability of SMEs in the new era based on data-driven decisions.
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.
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