Conventionally, academic researchers who wish to submit their findings to a journal cannot rely on aid from a dedicated system. Instead, they need to gather their own information and analyze their own preferences and target journals. Therefore, they are unable to make the objective measurements, analysis and manuscript submission decisions which can be achieved by big data. The objective of this study is to establish a decision support system to aid academic researchers in the process of submitting manuscripts to academic journals. The four steps of Simon's model of decision-making are applied to the process of gathering intelligence, assessing cases and choosing a case from the diverse myriad of journal publications. The system then produces a list of recommended journals that match the user's criteria. Three modular subsystems: the decision factor filtering system, the manuscript submission decision support system, and the decision model verification system are integrated in this study. Descriptive statistical analysis and the analytical hierarchical process is performed on the results of expert surveys to obtain decision factor weights. Finally, the method and system are verified by using enterprise resource planning as an example.