## 2 Methodology  
The authors conducted an online survey of 510 people to investigate the effects of airport development and operations. A professional survey company was hired, and the survey data were taken from people aged 18 or older in South Korea during the period of 13-16 August 2019 through an in-house developed platform. The subjects were taken from an active panel with approximately 200,000 people. The active panel was managed by a professional survey company and place of living, job, sex, age, economic status, and education level of the active panel were considered in the panel management process, and the proportion was maintained to represent the general public of South Korea. For example, 18-29 age group, 30-39 age group, 40-49 age group, 50-59 age group, and 60 or older age group for male and female were sampled for each region in South Korea and then a weight factor was applied for each group based on the population of each group. As a sampling method, the professional allocation method was applied for each age group, and measurement variables were asked according to a 5-point Likert scale (Strongly Disagree, Disagree, Neutral, Agree, and Strongly Agree). Actual samples were taken to reach 110% of the targeted sample size, and then normality of the sample was verified. If any anomalies were found, they were replaced by another sample from the same group. Skewness and kurtosis were verified and it was found that no questions did not satisfy normality. Additional survey was conducted on which, if any, sub-factors of the 5 factors are affected the most by the airport development and operation in order to investigate the items that are most affected as well as the contributions of airport development and operations in individual surveys. The questionnaire consisted of a total of 31 latent variables and measurement variable with a 5-point Likert scale for the effects of airports on the region. Initially, more than 10 questions were devised for each factor, and a total of 31 questions were created after gathering opinions on the questions themselves from thirty persons, including five researchers, five aviation workers, five related field university professors, five airport operators, and ten non-experts. (See Table 1 for survey questions.) The study questions are intended to identify public perceptions regarding the impact of an airport on regional development, and the hypothesis to be verified is that the public perceives regional development through five different factors. The authors assumed that the perception of the general public towards the ripple effects of airports on regional benefit arises through five different factors. The hypothesis of a five-factor model (Figure 1) was verified through structural equation modeling. The five factors were reconstructed from territorial effects, aviation effects, flow effects, allocation effects, and urbanization effects, which were presented in [PERSON] et al. (2018) [19] as ripple effects of airports in their region, which mean direct and indirect effects induced from airport construction and operation. * Flow effects refer to \"regional economic benefit\" (hereafter referred to as \"R\"). * Territorial effects and urbanization effects refer to \"regional development\" (hereafter referred to as \"D\"). * Aviation effects refer to \"regional development\" (D) and \"dis-benefit to the region\" (hereafter referred to as \"B\"). * Allocation effects refer to \"increased use in air transportation\" (hereafter referred to as \"A\") and \"increased exchange with other regions\" (hereafter referred to as \"M\"). * Detailed ripple effects presented by [PERSON] et al. (2018) [19] were included in the survey. An initial structural equation that included all survey questions was constructed. Structural equation modeling is a powerful, multivariate technique and it is increasingly being used in scientific investigations to test and evaluate multivariate causal relationships.