@article{THESIS,
      recid = {5124},
      author = {Zhang, Yijing},
      title = {How Does Big-data-related Technology Adoption Affect  Listed Companies' Market Performance},
      publisher = {University of Chicago},
      school = {M.A.},
      address = {2022-12-10},
      number = {THESIS},
      abstract = {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.},
      url = {http://knowledge.uchicago.edu/record/5124},
      doi = {https://doi.org/10.6082/uchicago.5124},
}