Supporting Air Transport Policies Using Big Data Analytics: A Descriptive Approach Based Emerging Trend Analysis

Abstract

Qualitative research methods based on literature review or expert judgement have been used to find core issues, analyze emerging trends and discover promising areas for the future. Deriving results from large amounts of information under this approach is both costly and time consuming. Besides, there is a risk that the results may be influenced by the subjective opinion of experts. In order to make up for such weaknesses, the analysis paradigm for choosing future emerging trend is undergoing a shift toward mplementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The hange used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and the promising areas for the future from research papers pertaining to overall aviation areas through text mining method, which is one of the big data analysis techniques. This study has limitations in that its analysis for retrieving the aviation-related core issues and promising fields was restricted to research papers containing the keyword "aviation." However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and emerging trends regarding the promising areas for the future in the aviation industry through the application of a big data-based descriptive approach.

Enhancing the democratic nature of voting processes within decentralized autonomous organizations

“…decision rights, accountability and incentives (Beck et al, 2018); governance problems and solutions, the typical DAO technologies and their related areas (Liu et al, 2021); the main platforms allowing the design of DAOs, and visualization tools for DAOs, as well as the authors' own visualization tool (El Faqir et al, 2020); the use of blockchain and DAOs in education (Filip ci c, 2022); the pros and cons of DAOs with a focus on its use in the nonprofit sector (Chao et al, 2022); various frameworks that can be used for the development of DAOs (Halvai and Chaudhry, 2023); the potential and challenges faced by DAOs, with an emphasis on decentralized governance and disintermediation (Bellavitis et al, 2023); legal implications of DAOs (Despotovi c et al, 2023); or trends and potential future research directions regarding DAOs emerging from the analysis of tweets and posts on Reddit (Park et al, 2023). In addition, Kondova and Barba (2019) highlighted the potential of DAO for the enforcement of the transparent governance principle, but encouraged caution regarding this innovation, considering the early stage of the technology.…”