In this study, researchers aimed to conduct a systematic literature review (SLR) on technological forecasting methods in the field of airplane technologies. They followed a rigorous protocol that included selecting articles based on specific inclusion and exclusion criteria, such as data sources and measures used for assessing technological performance. The selected articles were then validated for quality and relevance by an independent author.
The study filtered out 302 of the initial 327 articles, leaving a final collection of 25 articles that met the inclusion criteria. These articles were assessed for quality and relevance through a detailed validation process. The researchers employed the SLR method to comprehensively collect related research on airplane technologies in an unbiased and reliable manner.
To ensure objectivity, the researchers created a review protocol at the outset of the study and adhered to it throughout the process. They also used specific inclusion and exclusion criteria to select articles and validate their quality. The final selection of 25 articles was based on these criteria, ensuring that only relevant and high-quality studies were included in the analysis.
The study’s findings highlight the importance of using a systematic approach when conducting literature reviews. By following a rigorous protocol and adhering to specific inclusion and exclusion criteria, researchers can minimize bias and ensure an objective review of the literature. This is particularly crucial in fields like airplane technologies, where complex methods are used to forecast future developments.
In conclusion, this SLR provides a comprehensive overview of technological forecasting methods in airplane technologies. By employing a rigorous protocol and adhering to specific inclusion and exclusion criteria, the study ensures objectivity and reliability in its findings. The results demonstrate the effectiveness of the SLR method in providing a detailed understanding of complex topics in a transparent and rigorous manner.
Artificial Intelligence, Computer Science