Streamlining the Selection Phase of Systematic Literature Reviews (SLRs) Using AI-Enabled GPT-4 Assistant API
This tool addresses the problem of managing the escalating volume of academic literature for researchers, particularly in fields like management and economics, though it is incremental as it applies an existing AI model to a specific task.
This study tackled the challenge of efficiently selecting articles for Systematic Literature Reviews (SLRs) by introducing an AI tool using GPT-4, which significantly accelerates the time-consuming selection process across academic disciplines.
The escalating volume of academic literature presents a formidable challenge in staying updated with the newest research developments. Addressing this, this study introduces a pioneering AI-based tool, configured specifically to streamline the efficiency of the article selection phase in Systematic Literature Reviews (SLRs). Utilizing the robust capabilities of OpenAI's GPT-4 Assistant API, the tool successfully homogenizes the article selection process across a broad array of academic disciplines. Implemented through a tripartite approach consisting of data preparation, AI-mediated article assessment, and structured result presentation, this tool significantly accelerates the time-consuming task of literature reviews. Importantly, this tool could be highly beneficial in fields such as management and economics, where the SLR process involves substantial human judgment. The adoption of a standard GPT model can substantially reduce potential biases and enhance the speed and precision of the SLR selection phase. This not only amplifies researcher productivity and accuracy but also denotes a considerable stride forward in the way academic research is conducted amidst the surging body of scholarly publications.