<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/10013027" mdate="2023-03-31 00:00:00"> <author>Evisa Mitrou and Nicholas Tsitsianis and Supriya Shinde</author> <title>An Empirical Investigation of Big Data Analytics The Financial Performance of Users versus Vendors</title> <pages>179 - 191</pages> <year>2023</year> <volume>17</volume> <number>3</number> <journal>International Journal of Economics and Management Engineering</journal> <ee>https://publications.waset.org/pdf/10013027</ee> <url>https://publications.waset.org/vol/195</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDAvendors (businesstobusiness) and BDAclients (businesstocustomer). We distinguish between the five BDAtechnologies (bigdataasaservice (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDAtechnologies affect the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDAclients and BDAvendors. Our study also explores the effect of the COVID19 pandemic on business continuity for both BDAvendors and BDAclients.</abstract> <index>Open Science Index 195, 2023</index> </article>