| Summary: | 碩士 === 國立高雄科技大學 === 航運管理系 === 107 === The global air passenger traffic was predicted will grow at a positive rate of 4.5% per year from 2012 to 2042, and the number of passengers will double from 2012 to 2034. In recent years, the opening of the fourth smart terminal of Changi Airport, and the “Full Automation” Fifth Terminal, which is currently being planned for construction. The rapid development of the Internet of Things, big data and artificial intelligence has made more and more airports become smarter. Based on the above, we can know that passenger volume will continue grow in the future, and it is necessary to set up automated facilities to cope with high passenger traffic. After reviewing the literature, we found that different airports have different degrees of intelligence, and some intelligent facilities and services have not been provided yet. Also there is no standard for measuring airport intelligence now. Therefore, this study will construct a rating model to measure the intelligence of airports.
First we drafted the airport intelligent evaluation index structure by the expert interviews were revised and determined. We issued the first expert questionnaire and used the fuzzy Delphi method to shave the less important evaluation scale, and obtained the four evaluations of "Smart Management", "Smart Airside Operation" and "Smart Energy Conservation and Environmental Protection" covering 12 evaluation projects and 47 evaluation details. Then we issued the second round expert questionnaire and used the Analytic Hierarchy Process to calculate the weights of each index, and the evaluation facet “passenger smart service” has the highest weight, the weight value is 0.354, the top three items in the overall weight ranking are 「Smart Operational Services」、「Tower Airport traffic control Intelligence」、「Smart Landside Security Management」. After establishing the airport intelligence evaluation method, the simulation application analysis was carried out at the Taiwan International Airport. Compare the performance of the three international airports in each of the appraisal projects and details to assess the degree of intelligence of each airport and provide the facets and projects that should be improved.
This study constructs an objective and comprehensive airport intelligence evaluation framework. The weights of each evaluation facet, project and detail are analyzed and the scores of each item are calculated more accurately. The constructed evaluation model is analyzed by using airport examples to obtain the current status of how smart the three international airports are.
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