# Design of Air Passenger Travel Choice Intention Prediction System Based on Deep Learning

Authors: Wei Wei; Wang Cheng
Journal: Scientific Programming
 (2022)

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## Abstract

Under the Beijing-Tianjin regional comprehensive transportation system, the flow of air passengers between multiple airports in the region is more frequent. The fundamental reason for the flow of air passengers is that there are differences in the level of service quality provided by airports and airlines in the region. Passengers’ choice intention is the consumption and purchase decision of passengers on aviation services. By constructing a Logit model, this paper analyzes the degree of influence on the travel choice intention of air passengers in the Beijing-Tianjin region from five aspects: individual passenger demographic characteristics, travel purpose, ground transportation characteristics, airport operation capacity, and airport soft power. Passengers can effectively predict the choice of air travel mode in the Beijing-Tianjin region. The results show that Beijing Capital Airport is favored by business travelers; Beijing Daxing International Airport is favored by travelers because of its fast security check-through speed; for Tianjin Binhai International Airport, the convenience of getting in and out of the airport by car and the speed of airport security check-through are two significant factors. Indicators do not affect the selection of airports; reasonable follow-up arrangements when airport flights are delayed are the only significant but negatively correlated factor; the research design results provide new ideas for the analysis of passenger travel mode selection behavior in multiple airport areas, enriching the data-driven research on transportation choices.


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## Body

## 1. Related Introduction

Since the birth of the basic theory of artificial intelligence, artificial intelligence technology and applications have developed rapidly, and machine learning is an important form of artificial intelligence. Machine learning has experienced two waves from shallow machine learning to deep learning. With the continuous development of machine theory and applications, various shallow machine learning models have been proposed one after another. Typical machine learning models include support vector machines invented by Cortes and others. At present, the main methods for airport passenger throughput include two aspects, linear prediction and nonlinear prediction. Linear-based methods include time series models, grey models. Although these methods have achieved good prediction results, they cannot reflect nonlinear trends, and the prediction accuracy needs to be improved; nonlinear-based methods include BP neural network, recurrent neural network, long short-term memory network, support vector regression, and other models; in addition, the combined model also achieved good prediction results. This type of model can fit the nonlinear relationship between input and output and has strong fault tolerance. It is also a commonly used research model for airport passenger throughput forecasting. In a word, machine learning has become one of the key research areas of artificial intelligence at present, and it is applied in many fields, including speech processing, computer vision, and natural language processing. Machine learning has also achieved good results in regression prediction. In recent years, domestic and foreign scholars have achieved certain results in the research on the travel choice intention of air passengers. Different from previous studies, this paper not only focuses on the travel choice intention of air passengers but also can more intuitively reflect the travel choice intention of air passengers after calculation based on the consumption and purchase decision-making of air services by passengers. This paper belongs to a research proposition that considers comprehensive influencing factors. It does not just focus on the travel choice intention of air passengers but also studies the choice intention of passengers through the consumption and purchasing power of air services from the side. The model selected is mainly based on the Logit model. Finally, the feasibility and effectiveness of the model are verified [1–9].


## 2. Related Theoretical Methods

A deep neural network model framework is built, as shown in Figure1. First, the transmission parameters of the data are explained, including time step, which indicates how many historical input values are used to predict future values; learning rate, which indicates the learning step size in gradient descent; input dimension, output dimension; batch size; batch number; hidden the number of neurons in the layer, the number of neurons in the GRU layer, and the number of GRU layers. The data are divided into batches before entering the neural network, and each batch is divided into time steps. The data first pass through the FIR filter layer, then enter the input layer, then pass through the hidden layer, then pass through several GRU layers for time series prediction, finally pass through the hidden layer and the output layer to output data, and train the parameters of each part of the network by comparing with the label data and BPTT propagation. During the training process, if the setting of the learning rate is too large, the loss value will oscillate around the local optimal solution. If the setting of the learning rate is too small, the convergence will be slow in the gradient descent process [10–14].Figure 1
Deep neural network model framework.


## 3. Model and Variable Selection

### 3.1. Model Selection

For the airport selection research of passenger travel, the deep neural network model and the Logit model are the most commonly used methods. The Logit model is the earliest discrete choice model, and it has gradually formed a complete discrete choice model system, such as the probit model, the NL model, and the mixed Logit model.In this paper, the standard polynomial Logit model is used to study the probability of airport selection for Beijing-Tianjin air passengers. The theoretical basis of the standard polynomial Logit model is the stochastic utility theory and the utility maximization hypothesis. Therefore, the effect function 1.1 is introduced first [15–19].(1)Tki=xkβi+εki.Among them,Tki is the utility of individual k choosing i scheme (such as choosing Beijing Daxing International Airport), xk is the set of influencing factors, such as gender, and age, βi is the generation of influencing factors in choosing the i-th scheme. The estimated parameter vector, εki, is the error term.WhenTki > Tkj (i ≠ j, i, j ∈ J, J represents the set of airports that can be selected), the individual will choose the scheme i. Therefore, the probability formula for individual k to choose plan i is 1.2.(2)Pki=PTki>Tkj,i≠j.Substituting formulas (1) into (2), and assuming that εki obeys the generalized extreme value distribution, formula (3) of the standard polynomial Logit model can be derived, that is, the probability that individual k chooses the i airport. The standard polynomial Logit model needs to assume that one item is selected as the benchmark group (this paper takes Beijing Capital International Airport as the benchmark group). The standard polynomial Logit model is not only fast and stable but also has the assumption that each airport in Beijing and Tianjin is independent and irrelevant, which is conducive to the analysis of each indicator [20].(3)Pki=eβxki∑j∈JJeβxkj.In expression (3), Pki represents the probability of choosing an airport i for air passenger k; βx represents the deterministic utility generated when choosing an airport for air passenger travel and using the influencing factors that air passengers experience when choosing an airport. The linear combination of i, j ∈ J, J represents the set of airports that can be selected.In this paper, Logit regression is performed on each influencing factor through Stata software to explore the significant degree of influence of each factor on the choice of each airport. Then, the multinomial Logit model is solved to obtain the selection probability of each individual for each airport, and then, the selected probability of each airport is summed and averaged to finally obtain the passenger occurrence probability of each airport.


### 3.2. Data Acquisition and Analysis

This paper extracts the demographic characteristics, travel purpose, ground transportation characteristics, airport operation capacity, airport soft power, and other factors that may affect the passenger’s choice behavior at the individual level of passengers and establishes a quantitative analysis model to describe the passenger’s choice behavior, as shown in Table1. By exploring the effect on choice behavior, the selected elements and dimensions contain the relevant intentions at the individual level of air tourist travel.Table 1
Variable names, categories, attributes, and definitions.
VariableVariable categoryVariable propertiesDefinitionGenderDemographic characteristicsNumeric variablesDependent variable takes a value of 1 if the gender is male; otherwise, it is 0AgeCategorical variables18–29 years old, take the value 1; 30–39 years old, take the value 2; 40–49 years old, take the value 3; 50–59 years old, take the value 4; Over 60 years old, take the value 5Whether or not to travel for leisure tourismNumeric variablesFor the dependent variable, if the passenger travels for leisure tourism, the value is 1; otherwise, 0Whether the purpose of travel is to visit relatives and friendsPurpose of travelNumeric variablesFor the passenger’s travel purpose of visiting relatives and friends, the value is 1; otherwise, 0Whether you are traveling for business purposesNumeric variablesFor the passenger, if the passenger travels for business purposes, the value is 1; otherwise, 0Access to the airport is quick and easy to get in and out of the airportGround transportation featuresCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport parking facilities are well builtCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5Check-in at the airport is easy and fastAirport operational capacityCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport has a high punctuality rate of flightsCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5Reasonable follow-up arrangements in the event of flight delays at the airportCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5Airport security passes quicklyCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport terminal environment is cleanAirport soft powerCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5There are many airport-related supporting entertainment facilitiesCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport flight information is prominently located and the information is correctCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5


#### 3.2.1. Demographic Characteristics

Based on network data and past research, it is found that women’s travel frequency is generally higher than that of men for shopping, leisure, entertainment, and other reasons, and the travel frequency of young people is generally higher than that of middle-aged and elderly people. It can be seen that demographic characteristics have a certain degree of influence on passengers’ travel choices. However, due to the protection of the individual privacy of respondents, complete demographic characteristics cannot be obtained. Therefore, extracting characteristics such as gender and age helps to explore the demographic characteristics in the Beijing-Tianjin area.


#### 3.2.2. Purpose of Travel

Combined with the economic and social construction conditions in the Beijing-Tianjin region, the purpose of travel also has an impact on travelers’ travel choices. Therefore, the vast majority of tourists choose Beijing’s two airports for business and leisure purposes. Therefore, in this paper, the purpose of travel is divided into three categories: leisure travel, visiting relatives and friends, and business office, to help explore the impact of travel purpose in the Beijing-Tianjin region on the travel choice of air passengers [21].


#### 3.2.3. Characteristics of Ground Traffic

With the development of social construction planning, the availability of ground transportation tends to be average, and airport options are basically available. Therefore, this paper focuses on the impact of ground transportation convenience on travelers’ travel choices. The convenience of entering and leaving the airport by car and the construction of airport parking lot facilities are used as two indicators to reflect the convenience of ground transportation.


#### 3.2.4. Airport Operation Capability

The impact indicators of airport operation capacity on passengers’ choice of an airport are mainly reflected in the convenience of airport procedures, the on-time rate of airport flights, the rationality of airport follow-up arrangements when flights are delayed, and the rate of airport security checks. Excellent airport operation ability can strongly attract passengers to choose. Therefore, this paper incorporates various indicators of airport operation ability into the exploration factors to explore the impact of airport operation ability on air passengers’ travel choices in the Beijing-Tianjin region.


#### 3.2.5. Airport Soft Power

Under the condition that the hard demands are basically satisfied, the soft power of the airport is the characteristic competitiveness of the airport, which can improve the passenger stickiness, enhance the travel experience of passengers, and increase the loyalty and frequency of choice. This research uses the airport environment, the number of airport supporting entertainment facilities, and the accuracy and convenience of airport flight information transmission as indicators of airport soft power to explore the impact of airport soft power on air passengers’ travel choices in the Beijing-Tianjin region [22, 23].


## 3.1. Model Selection

For the airport selection research of passenger travel, the deep neural network model and the Logit model are the most commonly used methods. The Logit model is the earliest discrete choice model, and it has gradually formed a complete discrete choice model system, such as the probit model, the NL model, and the mixed Logit model.In this paper, the standard polynomial Logit model is used to study the probability of airport selection for Beijing-Tianjin air passengers. The theoretical basis of the standard polynomial Logit model is the stochastic utility theory and the utility maximization hypothesis. Therefore, the effect function 1.1 is introduced first [15–19].(1)Tki=xkβi+εki.Among them,Tki is the utility of individual k choosing i scheme (such as choosing Beijing Daxing International Airport), xk is the set of influencing factors, such as gender, and age, βi is the generation of influencing factors in choosing the i-th scheme. The estimated parameter vector, εki, is the error term.WhenTki > Tkj (i ≠ j, i, j ∈ J, J represents the set of airports that can be selected), the individual will choose the scheme i. Therefore, the probability formula for individual k to choose plan i is 1.2.(2)Pki=PTki>Tkj,i≠j.Substituting formulas (1) into (2), and assuming that εki obeys the generalized extreme value distribution, formula (3) of the standard polynomial Logit model can be derived, that is, the probability that individual k chooses the i airport. The standard polynomial Logit model needs to assume that one item is selected as the benchmark group (this paper takes Beijing Capital International Airport as the benchmark group). The standard polynomial Logit model is not only fast and stable but also has the assumption that each airport in Beijing and Tianjin is independent and irrelevant, which is conducive to the analysis of each indicator [20].(3)Pki=eβxki∑j∈JJeβxkj.In expression (3), Pki represents the probability of choosing an airport i for air passenger k; βx represents the deterministic utility generated when choosing an airport for air passenger travel and using the influencing factors that air passengers experience when choosing an airport. The linear combination of i, j ∈ J, J represents the set of airports that can be selected.In this paper, Logit regression is performed on each influencing factor through Stata software to explore the significant degree of influence of each factor on the choice of each airport. Then, the multinomial Logit model is solved to obtain the selection probability of each individual for each airport, and then, the selected probability of each airport is summed and averaged to finally obtain the passenger occurrence probability of each airport.


## 3.2. Data Acquisition and Analysis

This paper extracts the demographic characteristics, travel purpose, ground transportation characteristics, airport operation capacity, airport soft power, and other factors that may affect the passenger’s choice behavior at the individual level of passengers and establishes a quantitative analysis model to describe the passenger’s choice behavior, as shown in Table1. By exploring the effect on choice behavior, the selected elements and dimensions contain the relevant intentions at the individual level of air tourist travel.Table 1
Variable names, categories, attributes, and definitions.
VariableVariable categoryVariable propertiesDefinitionGenderDemographic characteristicsNumeric variablesDependent variable takes a value of 1 if the gender is male; otherwise, it is 0AgeCategorical variables18–29 years old, take the value 1; 30–39 years old, take the value 2; 40–49 years old, take the value 3; 50–59 years old, take the value 4; Over 60 years old, take the value 5Whether or not to travel for leisure tourismNumeric variablesFor the dependent variable, if the passenger travels for leisure tourism, the value is 1; otherwise, 0Whether the purpose of travel is to visit relatives and friendsPurpose of travelNumeric variablesFor the passenger’s travel purpose of visiting relatives and friends, the value is 1; otherwise, 0Whether you are traveling for business purposesNumeric variablesFor the passenger, if the passenger travels for business purposes, the value is 1; otherwise, 0Access to the airport is quick and easy to get in and out of the airportGround transportation featuresCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport parking facilities are well builtCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5Check-in at the airport is easy and fastAirport operational capacityCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport has a high punctuality rate of flightsCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5Reasonable follow-up arrangements in the event of flight delays at the airportCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5Airport security passes quicklyCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport terminal environment is cleanAirport soft powerCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5There are many airport-related supporting entertainment facilitiesCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5The airport flight information is prominently located and the information is correctCategorical variablesGreat influence, take the value 1; larger influence, take the value 2; general influence, take the value 3; slightly affect, take the value 4; no effect, take the value 5


### 3.2.1. Demographic Characteristics

Based on network data and past research, it is found that women’s travel frequency is generally higher than that of men for shopping, leisure, entertainment, and other reasons, and the travel frequency of young people is generally higher than that of middle-aged and elderly people. It can be seen that demographic characteristics have a certain degree of influence on passengers’ travel choices. However, due to the protection of the individual privacy of respondents, complete demographic characteristics cannot be obtained. Therefore, extracting characteristics such as gender and age helps to explore the demographic characteristics in the Beijing-Tianjin area.


### 3.2.2. Purpose of Travel

Combined with the economic and social construction conditions in the Beijing-Tianjin region, the purpose of travel also has an impact on travelers’ travel choices. Therefore, the vast majority of tourists choose Beijing’s two airports for business and leisure purposes. Therefore, in this paper, the purpose of travel is divided into three categories: leisure travel, visiting relatives and friends, and business office, to help explore the impact of travel purpose in the Beijing-Tianjin region on the travel choice of air passengers [21].


### 3.2.3. Characteristics of Ground Traffic

With the development of social construction planning, the availability of ground transportation tends to be average, and airport options are basically available. Therefore, this paper focuses on the impact of ground transportation convenience on travelers’ travel choices. The convenience of entering and leaving the airport by car and the construction of airport parking lot facilities are used as two indicators to reflect the convenience of ground transportation.


### 3.2.4. Airport Operation Capability

The impact indicators of airport operation capacity on passengers’ choice of an airport are mainly reflected in the convenience of airport procedures, the on-time rate of airport flights, the rationality of airport follow-up arrangements when flights are delayed, and the rate of airport security checks. Excellent airport operation ability can strongly attract passengers to choose. Therefore, this paper incorporates various indicators of airport operation ability into the exploration factors to explore the impact of airport operation ability on air passengers’ travel choices in the Beijing-Tianjin region.


### 3.2.5. Airport Soft Power

Under the condition that the hard demands are basically satisfied, the soft power of the airport is the characteristic competitiveness of the airport, which can improve the passenger stickiness, enhance the travel experience of passengers, and increase the loyalty and frequency of choice. This research uses the airport environment, the number of airport supporting entertainment facilities, and the accuracy and convenience of airport flight information transmission as indicators of airport soft power to explore the impact of airport soft power on air passengers’ travel choices in the Beijing-Tianjin region [22, 23].


## 3.2.1. Demographic Characteristics

Based on network data and past research, it is found that women’s travel frequency is generally higher than that of men for shopping, leisure, entertainment, and other reasons, and the travel frequency of young people is generally higher than that of middle-aged and elderly people. It can be seen that demographic characteristics have a certain degree of influence on passengers’ travel choices. However, due to the protection of the individual privacy of respondents, complete demographic characteristics cannot be obtained. Therefore, extracting characteristics such as gender and age helps to explore the demographic characteristics in the Beijing-Tianjin area.


## 3.2.2. Purpose of Travel

Combined with the economic and social construction conditions in the Beijing-Tianjin region, the purpose of travel also has an impact on travelers’ travel choices. Therefore, the vast majority of tourists choose Beijing’s two airports for business and leisure purposes. Therefore, in this paper, the purpose of travel is divided into three categories: leisure travel, visiting relatives and friends, and business office, to help explore the impact of travel purpose in the Beijing-Tianjin region on the travel choice of air passengers [21].


## 3.2.3. Characteristics of Ground Traffic

With the development of social construction planning, the availability of ground transportation tends to be average, and airport options are basically available. Therefore, this paper focuses on the impact of ground transportation convenience on travelers’ travel choices. The convenience of entering and leaving the airport by car and the construction of airport parking lot facilities are used as two indicators to reflect the convenience of ground transportation.


## 3.2.4. Airport Operation Capability

The impact indicators of airport operation capacity on passengers’ choice of an airport are mainly reflected in the convenience of airport procedures, the on-time rate of airport flights, the rationality of airport follow-up arrangements when flights are delayed, and the rate of airport security checks. Excellent airport operation ability can strongly attract passengers to choose. Therefore, this paper incorporates various indicators of airport operation ability into the exploration factors to explore the impact of airport operation ability on air passengers’ travel choices in the Beijing-Tianjin region.


## 3.2.5. Airport Soft Power

Under the condition that the hard demands are basically satisfied, the soft power of the airport is the characteristic competitiveness of the airport, which can improve the passenger stickiness, enhance the travel experience of passengers, and increase the loyalty and frequency of choice. This research uses the airport environment, the number of airport supporting entertainment facilities, and the accuracy and convenience of airport flight information transmission as indicators of airport soft power to explore the impact of airport soft power on air passengers’ travel choices in the Beijing-Tianjin region [22, 23].


## 4. Empirical Analysis

Based on the Beijing-Tianjin regional air passenger travel choice data obtained from the questionnaire, the relevant data sources are mainly obtained through random interviews in the form of Richter scales, and Stata16.0 was used to carry out descriptive statistics, linear relationship analysis, and multiple Logit model solutions for variables. In order to make the running results clearer and more beautiful, this paper encodes the variables in the form of pinyin: gender (xb), age (nl), whether the travel purpose is for leisure travel (xxly), whether the travel purpose is to visit relatives and friends (tqfy), whether the purpose of travel is for business office (swbg), the airport is convenient and fast to travel by car (ccbj), the airport parking lot facilities are well constructed (tcch), the airport check-in procedures are convenient and fast (sxbj), and the airport flight has a high punctuality rate (zdl), reasonable follow-up arrangements when airport flights are delayed (aphl), fast airport security check (ajk), clean and tidy airport terminal environment (hj), more airport-related entertainment facilities (ylss), airport flight information is eye-catching. The information is correct (xxzq). The selection of relevant variables is mainly based on the most common variables of air travel.


### 4.1. Running Results

In order to better observe the variables, this study carried out descriptive statistics and linear relationship analysis on the variables. The descriptive statistics of the variables are shown in Table2, where the first column obs represents the observed quantity, the second column mean represents the mean, the third column Std.Dev. represents the standard deviation, the fourth column Min represents the minimum value, and the fifth column Max represents the maximum value.Table 2
Descriptive statistics for variables.
VariableObservational measurementAverage valueStandard errorMinimumMaximumGender (xb).8550.38830410.487649601Age (nl).8551.7625730.91359915Whether to travel for leisure tourism (xxly).8550.65847950.474497201Whether to visit relatives and friends for the purpose of travel (tqfy).8550.04678360.211298701Whether it is for business office purposes (swbg).8550.19181290.393957101Airport selection8551.9064331.49648919Easy and quick access to the airport (ccbj).8552.4666671.32830815The airport parking facilities are well built (tcch).8553.2748541.26584115Check-in at the airport is quick and easy (sxbj).8552.3789471.35208315Airport flights have a high punctuality rate (zdl).8552.1005851.32855115Reasonable follow-up arrangements in the event of airport flight delays (aphl).8552.2690061.34291815Airport security passes quickly (ajk).8552.5824561.297615The airport terminal is clean and tidy (hj).8552.8233921.25372115There are many airport-related supporting facilities (ylss).8553.6339181.21293615The airport flight information is prominently located and the information is correct (xxzq).8552.5111111.29927215In order to reduce the deviation of the influence of the respective variables on the dependent variable, this paper also explores whether there is a linear relationship between the respective variables and uses Stata16.0 to test the linear relationship between the variables, as shown in Table3. It can be found that the VIF values of the respective variables are all less than 3, indicating that there is no significant linear relationship between the respective variables, which proves that the subsequent Logit model regression solution value deviation is small, and the results are efficient.Table 3
Variable linear relationship test.
VariableBright1/VIFWhether the purpose of travel is to visit relatives and friends (tqfy).2.800.357124Whether it is for business office purposes (swbg).2.670.374038Airport selection2.480.403751Easy and quick access to the airport (ccbj).2.440.410381The airport parking facilities are well built (tcch).2.330.429666Check-in at the airport is quick and easy (sxbj).2.260.442728Airport flights have a high punctuality rate (zdl).2.160.463237Reasonable follow-up arrangements in the event of airport flight delays (aphl).2.150.464106Airport security passes quickly (ajk).2.000.500020The airport terminal is clean and tidy (hj).1.620.617394There are many airport-related supporting facilities (ylss).1.410.711014The airport flight information is prominently located and the information is correct (xxzq).1.280.779130Whether the purpose of travel is to visit relatives and friends (tqfy).1.100.911822Whether it is for business office purposes (swbg).1.090.916891Mean VIF1.98In this paper, the multinomial Logit model is solved, and the choice of airport for air passenger travel is taken as the dependent variable (select Beijing Capital International Airport, value 1; Beijing Daxing International Airport, value 2; Tianjin Binhai International Airport, value 3), and various indicators of factors such as demographic characteristics, travel purpose, ground traffic characteristics, airport operating capacity, and airport soft power are used as independent variables, and Stata software is used to solve the model to obtain the degree of influence of each factor on each choice, as shown in Tables4-6.Table 4
Logit model regression results for selecting Beijing Capital International Airport.
Choice 1 VariableQuasiR2 = 0.0266Regression coefficientsStandard errorWithpGender (xb).−.21656140.1562371−1.390.166Age (nl).0.08595510.08470111.010.310Whether to travel for leisure tourism (xxly).0.09694740.24201280.400.689Whether the purpose of travel is to visit relatives and friends (tqfy).0.13502240.39901090.340.735Whether it is for business office purposes (swbg).0.80021190.29296582.730.006Easy and quick access to the airport (ccbj).0.11946810.08387461.420.154The airport parking facilities are well built (tcch).−0.00717030.0733454−0.100.922Check-in at the airport is quick and easy (sxbj).0.07907510.09128780.870.386Airport flights have a high punctuality rate (zdl).−0.08268860.0863616−0.960.338Reasonable follow-up arrangements in the event of airport flight delays (aphl).0.16191730.08050462.010.044Airport security passes quickly (ajk).−0.20339710.0831281−2.450.014The airport terminal is clean and tidy (hj).−0.04403110.082426−0.530.593There are many airport-related supporting facilities (ylss).0.01931790.06829840.280.777The airport flight information is prominently located and the information is correct (xxzq).−0.08486990.0855178−0.990.321Table 5
Logit model regression results for selecting Beijing Daxing International Airport.
Choice 2QuasiR2 = 0.00775Regression coefficientsStandard errorWithpGender (xb).0.04224960.35830260.120.906Age (nl).−0.60526240.2657307−2.280.023Whether to travel for leisure tourism (xxly).−0.13463330.495872−0.270.786Whether the purpose of travel is to visit relatives and friends (tqfy).0.05493190.76016360.070.942Whether it is for business office purposes (swbg).0.05653740.5869650.100.923Easy and quick access to the airport (ccbj).−0.16976480.1847487−0.920.358The airport parking facilities are well built (tcch).0.0977630.16380260.600.551Check-in at the airport is quick and easy (sxbj).−0.08993770.2017813−0.450.656Airport flights have a high punctuality rate (zdl).0.19756620.18158751.090.277Reasonable follow-up arrangements in the event of airport flight delays (aphl).−0.04735640.1714052−0.280.782Airport security passes quickly (ajk).0.54811340.1842762.970.003The airport terminal is clean and tidy (hj).−0.29038140.1798466−1.610.106There are many airport-related supporting facilities (ylss).0.13050160.16046580.810.416The airport flight information is prominently located and the information is correct (xxzq).−20.7721410.1917859−1.000.320Table 6
Logit model regression results for selecting Tianjin Binhai International Airport.
Choice 3QuasiR2 = 0.0255Regression coefficientsStandard errorWithpGender (xb).0.04961010.19940630.250.804Age (nl).−0.0250308−0.1079822−0.230.817Whether to travel for leisure tourism (xxly).0.13353510.31574770.420.672Whether the purpose of travel is to visit relatives and friends (tqfy).0.51745010.48181681.070.283Whether it is for business office purposes(swbg).−0.48375590.3899762−1.240.215Easy and quick access to the airport (ccbj).−0.21008710.107067−1.960.050The airport parking facilities are well built (tcch).0.08220150.09157460.900.369Check-in at the airport is quick and easy (sxbj).0.0201250.11526690.170.861Airport flights have a high punctuality rate (zdl).0.08136160.11120210.730.464Reasonable follow-up arrangements in the event of airport flight delays (aphl).−0.11906370.1030323−1.160.248Airport security passes quickly (ajk).−0.20090670.1059133−1.900.058The airport terminal is clean and tidy (hj).0.06141140.1049840.580.559There are many airport-related supporting facilities (ylss).−0.01197670.0845989−0.140.887The airport flight information is prominently located and the information is correct (xxzq).0.12675820.10760921.180.239


### 4.2. Analysis of Results

It can be seen from the results in Tables4-6. The first column in Table 4 to Table 6 is each factor variable; the second column is the coefficient corresponding to each variable; the positive or negative of the coefficient is logically related to the correlation of each factor, and a positive number indicates a positive correlation; otherwise, it is A negative correlation; the importance of each factor can be obtained by the absolute value of the coefficient; the third column is the standard error of each factor; the degree of dispersion of the sample can be judged by its size; the fourth column is the corresponding value of each variable Z values; the fifth column is the standard error for each factor. This column is the P value corresponding to each variable. Usually, these two values ​​are used to judge the significance of each variable. Under the 90% confidence level, if the absolute value of z is greater than 1.645 and the P-value is less than 0.10, then the variable is selected by passengers.


#### 4.2.1. Beijing Capital International Airport

As shown in Table4, the Z-values of the three indicators are more than 1.645, and the P-values are all less than 0.10, indicating that these three indicators are important for the influence of Beijing-Tianjin Airlines passengers, and choosing Beijing Capital International Airport is significant. From the perspective of travel purpose, it can be seen that most of the passengers who choose Beijing Capital International Airport are for business and office travel purposes. From the perspective of airport operation capability, Beijing-Tianjin Airlines passengers pay great attention to the rationality of the follow-up arrangements for flight delays at Beijing Capital International Airport and the speed of security inspection. These two items will directly affect whether Beijing-Tianjin Airlines passengers choose Beijing Capital International Airport.


#### 4.2.2. Beijing Daxing International Airport

As shown in Table5, the absolute values of the Z-values of the two indicators of age and the speed of passing through the airport security check are both greater than 1.645, and the P-values are both less than 0.10, indicating that these two indicators have a high level of significance. However, the corresponding coefficient of age is −0.605, indicating that age is negatively correlated with the choice of Beijing Daxing International Airport by air passengers, which reflects that age has no profound influence on the choice of Beijing Daxing International Airport. In terms of airport operation capability, only the speed of passing the airport security check has a significant impact, which reflects the degree to which the speed of passing the airport security check has an impact on the travel choices of Beijing-Tianjin air passengers.


#### 4.2.3. Tianjin Binhai International Airport

According to Table6, the absolute value of the Z value of the two indicators of the convenience and speed of entering and leaving the airport and the speed of airport security inspection is greater than 1.645, and the P-value is less than 0.10, indicating that the two indicators have a high level of significance. The coefficient corresponding to the convenience of entering and leaving the airport by car is −0.210, and the corresponding coefficient of the airport security check passing speed is −0.200, both of which are negative numbers, indicating that these two indicators have a negative correlation with the selection of Tianjin Binhai International Airport. Tianjin Airlines passengers have little influence on the choice of Tianjin Binhai International Airport.


## 4.1. Running Results

In order to better observe the variables, this study carried out descriptive statistics and linear relationship analysis on the variables. The descriptive statistics of the variables are shown in Table2, where the first column obs represents the observed quantity, the second column mean represents the mean, the third column Std.Dev. represents the standard deviation, the fourth column Min represents the minimum value, and the fifth column Max represents the maximum value.Table 2
Descriptive statistics for variables.
VariableObservational measurementAverage valueStandard errorMinimumMaximumGender (xb).8550.38830410.487649601Age (nl).8551.7625730.91359915Whether to travel for leisure tourism (xxly).8550.65847950.474497201Whether to visit relatives and friends for the purpose of travel (tqfy).8550.04678360.211298701Whether it is for business office purposes (swbg).8550.19181290.393957101Airport selection8551.9064331.49648919Easy and quick access to the airport (ccbj).8552.4666671.32830815The airport parking facilities are well built (tcch).8553.2748541.26584115Check-in at the airport is quick and easy (sxbj).8552.3789471.35208315Airport flights have a high punctuality rate (zdl).8552.1005851.32855115Reasonable follow-up arrangements in the event of airport flight delays (aphl).8552.2690061.34291815Airport security passes quickly (ajk).8552.5824561.297615The airport terminal is clean and tidy (hj).8552.8233921.25372115There are many airport-related supporting facilities (ylss).8553.6339181.21293615The airport flight information is prominently located and the information is correct (xxzq).8552.5111111.29927215In order to reduce the deviation of the influence of the respective variables on the dependent variable, this paper also explores whether there is a linear relationship between the respective variables and uses Stata16.0 to test the linear relationship between the variables, as shown in Table3. It can be found that the VIF values of the respective variables are all less than 3, indicating that there is no significant linear relationship between the respective variables, which proves that the subsequent Logit model regression solution value deviation is small, and the results are efficient.Table 3
Variable linear relationship test.
VariableBright1/VIFWhether the purpose of travel is to visit relatives and friends (tqfy).2.800.357124Whether it is for business office purposes (swbg).2.670.374038Airport selection2.480.403751Easy and quick access to the airport (ccbj).2.440.410381The airport parking facilities are well built (tcch).2.330.429666Check-in at the airport is quick and easy (sxbj).2.260.442728Airport flights have a high punctuality rate (zdl).2.160.463237Reasonable follow-up arrangements in the event of airport flight delays (aphl).2.150.464106Airport security passes quickly (ajk).2.000.500020The airport terminal is clean and tidy (hj).1.620.617394There are many airport-related supporting facilities (ylss).1.410.711014The airport flight information is prominently located and the information is correct (xxzq).1.280.779130Whether the purpose of travel is to visit relatives and friends (tqfy).1.100.911822Whether it is for business office purposes (swbg).1.090.916891Mean VIF1.98In this paper, the multinomial Logit model is solved, and the choice of airport for air passenger travel is taken as the dependent variable (select Beijing Capital International Airport, value 1; Beijing Daxing International Airport, value 2; Tianjin Binhai International Airport, value 3), and various indicators of factors such as demographic characteristics, travel purpose, ground traffic characteristics, airport operating capacity, and airport soft power are used as independent variables, and Stata software is used to solve the model to obtain the degree of influence of each factor on each choice, as shown in Tables4-6.Table 4
Logit model regression results for selecting Beijing Capital International Airport.
Choice 1 VariableQuasiR2 = 0.0266Regression coefficientsStandard errorWithpGender (xb).−.21656140.1562371−1.390.166Age (nl).0.08595510.08470111.010.310Whether to travel for leisure tourism (xxly).0.09694740.24201280.400.689Whether the purpose of travel is to visit relatives and friends (tqfy).0.13502240.39901090.340.735Whether it is for business office purposes (swbg).0.80021190.29296582.730.006Easy and quick access to the airport (ccbj).0.11946810.08387461.420.154The airport parking facilities are well built (tcch).−0.00717030.0733454−0.100.922Check-in at the airport is quick and easy (sxbj).0.07907510.09128780.870.386Airport flights have a high punctuality rate (zdl).−0.08268860.0863616−0.960.338Reasonable follow-up arrangements in the event of airport flight delays (aphl).0.16191730.08050462.010.044Airport security passes quickly (ajk).−0.20339710.0831281−2.450.014The airport terminal is clean and tidy (hj).−0.04403110.082426−0.530.593There are many airport-related supporting facilities (ylss).0.01931790.06829840.280.777The airport flight information is prominently located and the information is correct (xxzq).−0.08486990.0855178−0.990.321Table 5
Logit model regression results for selecting Beijing Daxing International Airport.
Choice 2QuasiR2 = 0.00775Regression coefficientsStandard errorWithpGender (xb).0.04224960.35830260.120.906Age (nl).−0.60526240.2657307−2.280.023Whether to travel for leisure tourism (xxly).−0.13463330.495872−0.270.786Whether the purpose of travel is to visit relatives and friends (tqfy).0.05493190.76016360.070.942Whether it is for business office purposes (swbg).0.05653740.5869650.100.923Easy and quick access to the airport (ccbj).−0.16976480.1847487−0.920.358The airport parking facilities are well built (tcch).0.0977630.16380260.600.551Check-in at the airport is quick and easy (sxbj).−0.08993770.2017813−0.450.656Airport flights have a high punctuality rate (zdl).0.19756620.18158751.090.277Reasonable follow-up arrangements in the event of airport flight delays (aphl).−0.04735640.1714052−0.280.782Airport security passes quickly (ajk).0.54811340.1842762.970.003The airport terminal is clean and tidy (hj).−0.29038140.1798466−1.610.106There are many airport-related supporting facilities (ylss).0.13050160.16046580.810.416The airport flight information is prominently located and the information is correct (xxzq).−20.7721410.1917859−1.000.320Table 6
Logit model regression results for selecting Tianjin Binhai International Airport.
Choice 3QuasiR2 = 0.0255Regression coefficientsStandard errorWithpGender (xb).0.04961010.19940630.250.804Age (nl).−0.0250308−0.1079822−0.230.817Whether to travel for leisure tourism (xxly).0.13353510.31574770.420.672Whether the purpose of travel is to visit relatives and friends (tqfy).0.51745010.48181681.070.283Whether it is for business office purposes(swbg).−0.48375590.3899762−1.240.215Easy and quick access to the airport (ccbj).−0.21008710.107067−1.960.050The airport parking facilities are well built (tcch).0.08220150.09157460.900.369Check-in at the airport is quick and easy (sxbj).0.0201250.11526690.170.861Airport flights have a high punctuality rate (zdl).0.08136160.11120210.730.464Reasonable follow-up arrangements in the event of airport flight delays (aphl).−0.11906370.1030323−1.160.248Airport security passes quickly (ajk).−0.20090670.1059133−1.900.058The airport terminal is clean and tidy (hj).0.06141140.1049840.580.559There are many airport-related supporting facilities (ylss).−0.01197670.0845989−0.140.887The airport flight information is prominently located and the information is correct (xxzq).0.12675820.10760921.180.239


## 4.2. Analysis of Results

It can be seen from the results in Tables4-6. The first column in Table 4 to Table 6 is each factor variable; the second column is the coefficient corresponding to each variable; the positive or negative of the coefficient is logically related to the correlation of each factor, and a positive number indicates a positive correlation; otherwise, it is A negative correlation; the importance of each factor can be obtained by the absolute value of the coefficient; the third column is the standard error of each factor; the degree of dispersion of the sample can be judged by its size; the fourth column is the corresponding value of each variable Z values; the fifth column is the standard error for each factor. This column is the P value corresponding to each variable. Usually, these two values ​​are used to judge the significance of each variable. Under the 90% confidence level, if the absolute value of z is greater than 1.645 and the P-value is less than 0.10, then the variable is selected by passengers.


### 4.2.1. Beijing Capital International Airport

As shown in Table4, the Z-values of the three indicators are more than 1.645, and the P-values are all less than 0.10, indicating that these three indicators are important for the influence of Beijing-Tianjin Airlines passengers, and choosing Beijing Capital International Airport is significant. From the perspective of travel purpose, it can be seen that most of the passengers who choose Beijing Capital International Airport are for business and office travel purposes. From the perspective of airport operation capability, Beijing-Tianjin Airlines passengers pay great attention to the rationality of the follow-up arrangements for flight delays at Beijing Capital International Airport and the speed of security inspection. These two items will directly affect whether Beijing-Tianjin Airlines passengers choose Beijing Capital International Airport.


### 4.2.2. Beijing Daxing International Airport

As shown in Table5, the absolute values of the Z-values of the two indicators of age and the speed of passing through the airport security check are both greater than 1.645, and the P-values are both less than 0.10, indicating that these two indicators have a high level of significance. However, the corresponding coefficient of age is −0.605, indicating that age is negatively correlated with the choice of Beijing Daxing International Airport by air passengers, which reflects that age has no profound influence on the choice of Beijing Daxing International Airport. In terms of airport operation capability, only the speed of passing the airport security check has a significant impact, which reflects the degree to which the speed of passing the airport security check has an impact on the travel choices of Beijing-Tianjin air passengers.


### 4.2.3. Tianjin Binhai International Airport

According to Table6, the absolute value of the Z value of the two indicators of the convenience and speed of entering and leaving the airport and the speed of airport security inspection is greater than 1.645, and the P-value is less than 0.10, indicating that the two indicators have a high level of significance. The coefficient corresponding to the convenience of entering and leaving the airport by car is −0.210, and the corresponding coefficient of the airport security check passing speed is −0.200, both of which are negative numbers, indicating that these two indicators have a negative correlation with the selection of Tianjin Binhai International Airport. Tianjin Airlines passengers have little influence on the choice of Tianjin Binhai International Airport.


## 4.2.1. Beijing Capital International Airport

As shown in Table4, the Z-values of the three indicators are more than 1.645, and the P-values are all less than 0.10, indicating that these three indicators are important for the influence of Beijing-Tianjin Airlines passengers, and choosing Beijing Capital International Airport is significant. From the perspective of travel purpose, it can be seen that most of the passengers who choose Beijing Capital International Airport are for business and office travel purposes. From the perspective of airport operation capability, Beijing-Tianjin Airlines passengers pay great attention to the rationality of the follow-up arrangements for flight delays at Beijing Capital International Airport and the speed of security inspection. These two items will directly affect whether Beijing-Tianjin Airlines passengers choose Beijing Capital International Airport.


## 4.2.2. Beijing Daxing International Airport

As shown in Table5, the absolute values of the Z-values of the two indicators of age and the speed of passing through the airport security check are both greater than 1.645, and the P-values are both less than 0.10, indicating that these two indicators have a high level of significance. However, the corresponding coefficient of age is −0.605, indicating that age is negatively correlated with the choice of Beijing Daxing International Airport by air passengers, which reflects that age has no profound influence on the choice of Beijing Daxing International Airport. In terms of airport operation capability, only the speed of passing the airport security check has a significant impact, which reflects the degree to which the speed of passing the airport security check has an impact on the travel choices of Beijing-Tianjin air passengers.


## 4.2.3. Tianjin Binhai International Airport

According to Table6, the absolute value of the Z value of the two indicators of the convenience and speed of entering and leaving the airport and the speed of airport security inspection is greater than 1.645, and the P-value is less than 0.10, indicating that the two indicators have a high level of significance. The coefficient corresponding to the convenience of entering and leaving the airport by car is −0.210, and the corresponding coefficient of the airport security check passing speed is −0.200, both of which are negative numbers, indicating that these two indicators have a negative correlation with the selection of Tianjin Binhai International Airport. Tianjin Airlines passengers have little influence on the choice of Tianjin Binhai International Airport.


## 5. Conclusion

According to the analysis of the results in chapter 4.2, it can be seen that the most important factor when choosing an airport is the airport’s operational capability, especially the speed of passing through the airport security check. Efficiency needs. Therefore, the following conclusions can be drawn: (1) The airport is appropriately expanded, and the security check channel is increased. (2) Artificial intelligence to speed up the identification of dangerous goods is introduced, and the quality and efficiency of security inspections are improved. (3) Green passages are built to allow passengers without security inspection requirements to pass quickly. In this way, the travel time cost of Beijing-Tianjin Airlines passengers can be reduced, and the travel efficiency of passengers can be improved. According to the results of the model solution, it can also be concluded that the current regional airports with less passenger distribution have less influencing factors than the current Beijing-Tianjin hub airports, which indicates that if the regional airports want to attract more. There are many Beijing-Tianjin Airlines passengers while enhancing the airport’s operational strength, and they need to focus on the corresponding soft power and combine regional characteristics and passenger characteristics to implement special services to increase the travel experience of passengers, so as to improve the Beijing-Tianjin Airlines passengers’ interest in the airport. As for Beijing Capital International Airport, which is currently saturated with passengers, the first thing to consider is the passenger diversion strategy, and it will be completed jointly with Beijing Daxing International Airport and other airports in the two places. This requires the government to strengthen the air space between Beijing and Tianjin. The railway combined transport mode makes the transportation between the three places more accessible and convenient, reduces the gap between regions, and eliminates the inertial thinking of Beijing-Tianjin air passengers on previous travel choices, so as to make the allocation of air passengers between Beijing and Tianjin more convenient and reasonably average.



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*Source: 7340552-2022-03-11.xml*