This paper investigates the effect of technology adoption on the performance of companies in China. We utilize text-mining techniques to extract information from the annual reports of Chinese A-share listed companies, and particularly, we construct measures of adoption of big data-related technologies based on the occurrences of big-data-related keywords. In conjunction with other company and provincial data, we explore the growth trend, determinants of big-data technology adoption, and the impact of big-data applications on the performance of companies and discuss the possible mechanism for achieving these effects. First, companies with lower tangible assets, higher GDP per capita, or more colleges in their regions are more likely to use big data technology. Second, instrumental variable regression with industry-fixed effects shows that the industry characteristics and nature of the company occasionally limit the positive effects of big data applications. Third, heterogeneity analysis suggests that Big data applications contribute to firm net profit more significantly in the financial and manufacturing industries, and non-state-owned companies.