Analysis on the Evaluation of Airport Intelligence Level and Its Obstacle Diagnosis Based on DPSIR-TOPSIS Model

Combined with the actual situation of smart airport construction, five listed airports in China are used as research objects, and based on the Driving Force-Pressure-State-Impact-Response (DPSIR) conceptual model, 24 indicators were selected to form the evaluation system. The Analytic Hierarchy Proc...

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Bibliographic Details
Published in:Wireless communications and mobile computing 2022-05, Vol.2022, p.1-10
Main Authors: He, Hang, Ding, Haining, Liu, Shuyue, Li, Shanshan
Format: Article
Language:English
Subjects:
Airport construction
Airports
Analytic hierarchy process
Barriers
Civil aviation
Construction
Coordination models
Coupling
Economic development
Entropy (statistics)
Environmental protection
Fixed assets
GDP
Gross Domestic Product
Indicators
Intelligence
Optimization
Passengers
Propaganda
R&D
Regional development
Research & development
Research methodology
Revenue
Smart cities
Subsystems
Transportation services
Travel time
Weighting methods
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Summary:Combined with the actual situation of smart airport construction, five listed airports in China are used as research objects, and based on the Driving Force-Pressure-State-Impact-Response (DPSIR) conceptual model, 24 indicators were selected to form the evaluation system. The Analytic Hierarchy Process (AHP) method and entropy weight method were used to assign comprehensive weights to the indicators, and then, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method was introduced to evaluate the level of intelligence, combined with the coupling coordination model to analyze the relationship between the two subsystems, by introducing the obstacle model to diagnose and analyze the influencing factors; finally, based on the analysis results, optimization suggestions are provided for the airport intelligence level. The results show that the intelligence level of each airport is between high (IV) and average (II). The pairwise coupling degree of each subsystem is higher than 0.91 and presents a benign coupling. The airport intelligence level is mainly hindered by the proportion of nonaviation revenue, the average travel time of passengers, and the regional fiscal revenue growth rate. The research results are of great significance to the construction of smart airport and the development of regional economy and transportation.
ISSN:1530-8669
1530-8677
DOI:10.1155/2022/4848105