Venture capital funds are active investors in technology-based firms in Taiwan. However, there is very little evidence on the influence of VC funds’ investments in the investee firms. This study examines the relations between venture-backing and two issues, earnings management and value relevance, in the technology-based industry. For the issue of the relationship between venture-backing and earnings management, four hypotheses are derived to test the above connections. Three different proxies of earnings management are employed to conduct this analysis: cross-sectional modified Jones model, performance-matched modified Jones model and unexpected accounts receivable model. Empirical evidence shows that there is a negative association between venture-backing and abnormal accruals. Specifically, age of VC funds, percentage of VC funds’ shareholdings on investee firms, and VC funds invested by the government are negatively related with abnormal accruals in most of analyses. These findings indicate that VC funds in Taiwan provide monitoring functions on financial reporting of their invstee firms. For the issue of value relevance of venture-backing information, five hypotheses are derived to test the above connections. Ohlson (1995) model is used for the examination. Empirical evidence shows that venture-backing information is value relevant in the TSE market, but not in the OTC market. The sufficiency of financial information has an impact on value relevance of venture capital information. Value relevance of venture-backing information in the TSE market increases with VC funds’ investments and VC funds’ government investments, but not with VC funds’ age in most of analyses. These findings indicate that investors treat venture-backing information as value-relevant information only in the TSE market, but not in the OTC market. In addition, several tests are performed to determine the sensitivity of the results to a potential selection bias in the research design. The results of this analysis are mixed. Therefore, this paper cannot rule out selection bias as a potential alternative explanation for the findings.