TITLE:
Complexity Analysis on the Influence Factors of the Flight Delay Risk Based on SNA
AUTHORS:
Yueyao Wang, Yun Li
KEYWORDS:
Airport, Flight Delay, Risk Governance, Social Network Analysis
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.8 No.5,
May
13,
2020
ABSTRACT: Flight delay is the major emergency faced during in the process of flight
production guarantee in civil aviation transportation industry, which will
cause significant impact on the normal operation of large airports, and the
comprehensive management on how to reduce the risk of flight delay has been
conducted. Reducing the probability of delay events and its consequences is an
important issue and research topics in the emergency management of civil
aviation transportation industry. However, large airports are typical complex
transportation infrastructure owing to the characteristics of many
participation units, complex process, external environmental factors and so on,
which decides that the risk factors to trigger flight delay have the
characteristics of concealment and diversity, and causes the influence on how
to identify the risk factors of flight delay comprehensively and
systematically. Secondly, the risk factors of flight delay are interrelated and
interweaved for living, which have the typical complexity features and pose the
challenges on how to understand the generative mechanism of airport flight
delay events and design the risk factors to eliminate and control flight delay
events. This paper conducts the in-depth research and analysis of the generative
mechanism and law of flight delay events and puts forward design method of
flight risk management strategy according to systematic thinking through the
in-depth investigation on the flight production guarantee process of Shenzhen
Bao’an International Airport (Shenzhen Airport) for the existing problems of the
existing flight delay management. Firstly, the analysis on flight production
process of Shenzhen Airport based on the theoretical framework of
society-ecology-technology is conducted, and it comprehensively uses the web
crawler and Delphi method through mixed data collection method. It
systematically identifies the risk factors of flight delay and the correlation
between risk factors based on the collection of multiple source data of flight
delay to form the deep understanding of the generative mechanism of flight
delay. In addition, it innovatively uses the social network analysis method to
conduct modelling for the risk factors of flight delay and their correlation
and carries out analysis on the complexity to put forward risk control strategy
from integrity level. The research work of this paper helps the airport
management units to have scientific understanding on risk factors of flight
delay and their relationship, in order to provide theoretical basis for the
scientific design of risk control measures.