Romanko, Oleksii

English

This thesis investigates the implications of modern ICT technologies on private sector firms, assessing both the direct impacts on productivity and the indirect advantages such as companies’ resilience in response to the Covid pandemic. The primary technology measure is the use of cloud computing but the thesis also examines how technologically skilled labour intensifies the effect of innovative technologies.The first part of the thesis concentrates on measuring the cloud adoption at scale using web-based information that is publicly available and covering a considerable number of private enterprises across the UK. We used web scraping techniques and analysis of the Internet infrastructure, using Domain Names Service (DNS) metadata about companies in their Internet records, to infer if they use cloud-related technologies. We complement the data with financial statistics from the Financial Analysis Made Easy (FAME) dataset. We performed a statistical analysis of these data using panel regressions and propensity score matching models to relate the usage of the cloud to the difference in productivity between companies. Both models show significant positive impacts of cloud technologies on the productivity of firms in the long run. However, we find a negative impact of the technology on productivity in the year of adoption, most likely due to implementation and coordination costs, but a positive return for every further year of cloud usage. The productivity impacts are greater for smaller firms, reflecting that cloud is a relatively inexpensive way of accessing digital technologies compared to the previous ICT technologies.Moreover, the successful adoption of technologies is likely reliant on the availability and quality of complementary skills. We found online job postings to be a reliable source of intelligence about skills trends. We performed work on understanding the skills content of jobs through reviewing skills ontologies and their role in building data extraction tools. We proceeded with a practical study by performing web scraping of the most popular online job postings platforms in the UK in 2019. We show how this data can be mined and used as an addition to official labour market statistics.Our final goal was to study how the usage of cloud computing technologies and the hiring of skilled labour impacted firms’ resilience to economic crises, focusing on companies’ behaviour during the Covid-19 disruption. We used text analytics modelling and natural language processing tools to mine Covid-related information from companies’ websites and categorize their response to the Covid pandemic into several groups based on the nature of their response. As measures of technological readiness, we used the indicators of cloud usage and skills data from job posting platforms described above, together with financial information from FAME. We performed before-after analysis showing that companies who used cloud and skilled labour were able to better react to Covid disruption. We extended the analysis by estimating responses both by firm size and industry. Although the effect of technological readiness is heterogeneous, technological readiness appears to be an important predictor of Covid resilience.In conclusion, this thesis outlines the usage of innovative tools and data sources for modern economic measurement and shows that such timely data can enhance and complement micro-level statistics to increase the understanding of economic processes

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Technology and firm performance: evidence from online data sources

https://kclpure.kcl.ac.uk/portal/files/232191981/2023_Romanko_Oleksii_1863476_ethesis.pdf

Technology and firm performance: evidence from online data sources

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