Factors influencing companies’ implementation of big data analytics

Given the doubling of the total amount of data that occurs every two years, and also the low cost of processing and storing data, for companies becomes important to implement big data analytics as a tool that provides a competitive advantage. The question arises: why, given the availability of free software, some companies have not been able to implement these technologies? In order to answer this question, we expanded the unified theory of acceptance and use of technology, adapted to the conditions of big data analytics, by adding two variables to it: reluctance to use and calculated risk. Using the degree of implementation of these technologies, we divided the companies into those that use and those that do not use big data analytics (BDA). The structural models were evaluated using the partial least squares (PLS) method. The results show that the importance of a good infrastructure outweighs the difficulties that companies face in implementing it. And while companies that plan to use big data expect good results, current users rate their performance more frugal.