Trading in this digital era is done online. If previously stock trading was synonymous with investors continuously observing stock price movements, now automatic orders can be made which is more practical. However, automatic orders also contain risks, such as system failures or errors which can also cause losses for investors. We would like to investigate these issues in order to determine the variables that affect investors’ use of automatic order placement from the perspective of DeLone-McLean and Technology Acceptance Model, which is new and became the novelty of our research. Our type of Research is done using numbers. We employ primary data that we collected by sending out surveys to respondents. Our respondents are investors who use automatic orders for online stock trading transactions. Our data analysis technique uses partial least squares modeling using structural equations. The findings of our study indicate that investors’ use of automated orders is significantly influenced by system quality, service quality, perceived usefulness, and perceived ease of use, but information quality has no discernible impact.

Link: DeLone-McLean and Technology Acceptance Model in Investors Use of Automated Order Online Trading