Market segmentation analysis for airport access mode choice modeling with mixed logit

Accessing airports can be considered as a crucial issue since passengers need not miss their flights. This issue makes the mode choice to access the airports important to study on and develop policies regarding it. Many studies show destination type as domestic or international affects the airport access mode choice, along with other factors. In this study, we investigate the effect of destination type of mode choice using mixed logit, using market segmentation approach. Market segmentation regarding destination type as domestic or international is a first in airport access mode choice modeling. Revealed-preference data was collected by face-to-face passenger surveys at Ataturk International Airport in Istanbul, Turkey, in 2015. We did market segmentation analysis for Multinomial Logit (MNL) and Mixed Logit (ML) models. When MNL and ML models were compared, it was observed that ML was superior to MNL. Further, results of market segmentation analysis revealed that using segmented models produced more accurate results than using the pooled model; both in MNL and ML. This finding was also supported by the value of time estimates; there were significant differences between domestic and international travel markets in terms of airport access mode choice. These results showed that different transportation policies may be introduced for domestic and international traveler segments, which also were explained.     

A study on passengers' airport choice behavior using hybrid choice model: A case study of Seoul metropolitan area,South Korea

Improving explanatory power is significantly important to understand variables that affect attitudes and perceptions in the decision process. This paper estimates not only tangible attributes but also intangible perceptions and attitudes using a hybrid-choice model to study air passengers' flight choice behavior. The empirical study was conducted for the choice behavior of air passengers at Seoul Metropolitan Area, South Korea. The analysis uses a two-level Nested Logit model in order to examine which factors have more effect on passengers’ choice of airport and airline simultaneously by using airport and airline choice attributes. The study also estimated the parameters in the equations relating the latent variable by using Structural Equation Model (SEM). The results indicate that the models with latent variables have improved Goodness-of-Fit when compared to classical discrete choice models and effectively capture psychological factors that affect choice behavior of passengers.     

A model for time of day and mode choice using error components logit

The severity of road congestion not only depends on the relation between traffic volumes and network capacity, but also on the distribution of car traffic among different time periods during the day. A new error components logit model for the joint choice of time of day and mode is presented, estimated on stated preference data for car and train travellers in The Netherlands. The results indicate that time of day choice in The Netherlands is sensitive to changes in peak travel time and cost and that policies that increase these peak attributes will lead to peak spreading.     

A study on travelers' transport mode choice behavior using the mixed logit model: A case study of the Seoul-Jeju route

This study is to analyze passengers' choice of the mode of transportation when air transportation is in competition with high speed rail (HSR). The Seoul-Jeju route analyzed as an empirical case study, in which the construction of an undersea tunnel to connect Seoul and Jeju city by HSR has been considered. The study also included two new variables, ‘safety of transportation’ and ‘availability of duty free shopping’ in addition to traditional transport choice variables such as travel time, travel costs and frequency of service to reflect special characteristics of the market. As data gathering tools, SP techniques and mixed logit model, for analytical methodology, were utilized. The authors found that the goodness of fit of the models was improved with new variables. The models also showed that the characteristics of business passengers and leisure passengers in choosing the mode of transportation were different. Business passengers were apt to choose a safety secured mode of transportation regardless of fare while leisure passengers preferred to use duty free shops more than business passengers.     

Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey

This study examines transit mode choice preferences of New Jersey commuters traveling to New York City (NYC) with the objective of assisting trans-Hudson ferry service planning on the basis of variables significantly affecting mode choice. A stated preference survey was conducted to collect data from a total of 2134 respondents who commute from northern New Jersey to NYC. A mixed multinomial logit model (MMLM) with random coefficients was used to analyze the data. The study considered the choice between four transit modes—ferry, PATH train, bus, and commuter rail—all of which can be used to cross the Hudson River to travel from New Jersey to NYC. Essential model results are presented for all four modes, but detailed results are discussed for only the ferry, PATH, and bus modes. Model results indicate that commuters' choices are affected not only by travel time and cost for the segment of the journey that crosses the Hudson River, but also reliability and comfort during that segment, number of access modes required by the journey, and travel time and cost of trips from home to stations/terminals before crossing the river. The results also show that commuters' attachment to the modes they currently use serves as a barrier to switching to other modes. The most important takeaway from this research for transit service planning is that there is a need to consider the attributes of both individual trip segments as well as entire journeys between commuters' home and work when exploring changes to transit service characteristics.     

Choice behavior of tourism destination and travel mode: A case study of local residents in Hangzhou,China

The social and economic growth as result of promoting the rapid development of tourism in China has brought tremendous pressure on the urban transportation systems. Research of travel behavior concerning the characteristics of tourists has provided effective information for transportation planning. Due to different city plans, public transportation system design, car parking design and management, etc., the local situation in developed countries differs from the counterpart in China. However, little research has studied the factors influencing the choice of travel destinations in tourism. The research aims to study the tourism destination and mode choice behavior of tourists and provides suggestions to improve tourism transportation service system. An online questionnaire survey is used to collect data including the travel characteristics and personal attributes of local tourists in different holidays in Hangzhou, China. A multinomial logit model is constructed with the trip destination set as the dependent variable. Results show that age, residential type, car ownership, companion type and holiday length have a significant impact on destination choice. To determine what influences modal choice for such trips, a second logit model is established with travel mode set as the dependent variable with the explanatory variables of age, gender, companion type, car ownership, holiday length and travel destination found to be significant. The results demonstrated that people aged 26 to 44 prefer suburban areas, and they are the main group driving to their travel destination. Public transport use frequency decreases when the destination is located outside of the main tourist area. Finally, suggestions have been proposed to mitigate the congestion and parking problem based on model analysis from the perspective of the bus line setting, transfer improvements, and the policy to limit cars, respectively.     

Home-end and activity-end preferences for access to and egress from train stations in the Copenhagen region

Increasing public transport use with the aim of improving the sustainability of cities should focus not only on enhancing level and quality of the service offered, but also on understanding determinants of the choice of access and egress modes to and from the railway network. This study analyzes the difference in preferences at the home-end and activity-end for travelers who have chosen train as their main travel mode while investigating the effect of policy variables such as car parking availability, bicycle parking availability and type, and bicycle on train possibility. Specifically, this study analyzes the choices between five transport modes (i.e., “walk,” “bicycle,” “car driver,” “car passenger,” “bus”) for 2921 home-end and 3658 activity-end trips. Joint mixed logit models are specified and estimated to account for heteroscedasticity and correlation across alternative modes as well as taste heterogeneity across travelers. Model estimates and pseudo-elasticities uncover the importance of travel time and underline how the improvement of walkability, bikeability, and bus service would contribute significantly to the increase in the probability of choosing sustainable modes to and from train stations. Moreover, model results emphasize the role of bicycle parking in terms of the sheer number of spaces to be increased as well as covered places to be offered at the activity end, de facto giving the possibility to leave a bicycle at that end during the night. Lastly, model results show that it is a matter of not only time and trip characteristics, but also traveler characteristics, occupation, and purpose.     

Willingness to pay for safety improvements in passenger air travel

The risk of being involved in an airplane accident is largely ignored in air passengers’ choice models. The reason presumably is that it is hard to operationalize, because objective safety indicators often involve extremely low probabilities that are hard to grasp and interpret by passengers. In this paper, we propose an operationalization that is based on the perception of safety, which is easy to understand and resonates that perceptions often influence decisions stronger than objective variables. We conceptualize that passengers form a safety perception score of a particular flight based on their perception of airline and route attributes and that this score in turn is traded-off against other flight attributes, such as ticket costs, to arrive at a flight choice. In line with this conceptualization, two stated preference experiments are conducted. In a first experiment, combinations of airline and route attributes are evaluated in terms of safety that is captured on a rating scale. In a second experiment, safety perception is treated as an attribute and traded-off against other flight attributes to arrive at a flight choice. The paper presents the results of a regression and a Panel Mixed Logit model estimated from responses obtained from a convenience sample of 161 air passengers recruited in the Netherlands. The results of both models are then combined to calculate the willingness to pay values for improvements made to a range of airline and route attributes, taking into account socio-demographic variables and psychological traits. As expected, the results indicate that the willingness to pay for improving safety decreases with higher initial safety levels.     

Latent class models of international air carrier choice

This paper uses a market segmentation approach to identify airline passengers’ potential segments and preferences toward international air carriers. The modeling approaches consist of the stated preference method and the latent class model. The stated choice experiments were designed based on service attributes in the international airline choice context. Empirical data was collected from airline passengers who have flown from Taipei to Tokyo or from Taipei to Hong Kong. The latent class model accommodating preference heterogeneity outperforms the multinomial logit model as indication of a better approach to analyze airline choice behavior. The latent class model with individual socioeconomic and trip characteristics in segment membership functions also improved model fit relative to the corresponding latent class model without individual characteristics. The values of willingness to pay for service attribute improvements vary across international air routes and segments. Passengers are willing to pay more for better service quality. In order to develop effective marketing and operational strategies for the international air travel market, this study highlights the importance of exploring airline choice behaviors by routes and segments.     

Analysis of mobility impacts of the high speed Rome-Naples rail link using withinday dynamic mode service choice models

The decrease in travel times, the better quality of the supplied services and the improved accessibility are the main factors of success of High Speed Rail links.In this paper, evidence of the impacts of the High Speed Rail line between Rome and Naples in Italy will be provided on the basis of a survey which was carried out in March 2008.A Revealed Preference (RP) survey was undertaken by Trenitalia (the Commercial Division of Italian railways) and three different questionnaires were prepared to be submitted to car users, Intercity train users and High Speed train users. They all have in common questions concerning the socioeconomic characteristics of the users, questions related to the existence of possible time constraints for the trip undertaken and questions concerning previous travel choices.Data from Trenitalia highlighted that the use of car and of Intercity trains had almost remained unchanged during the few years of operation of the High Speed service. However, a generated demand was derived from the use of this High Speed Rail link and this means that the introduction of the High Speed service between Rome and Naples probably had impacts, as excepted, on mobility choices (i.e. increase in trip frequency, new trips never done before, etc.). Data gathered were used first of all to understand this phenomenon and then to estimate a mode choice model to reproduce/forecast modal share. Specifically the choice between car and rail was modelled through a schedule based approach and with a Nested Logit model with the “train” utility function including late and early penalties.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

Public bike system pricing and usage in Taipei

Although widely implemented, public bike systems (PBSs) are facing a conflict between system usage and sustainable financing. The relationships between PBS pricing and usage must be clarified to formulate solutions for the conflict. This research used the Taipei PBS, YouBike, as a case study. A stated preference survey was conducted on metro passengers, and a binary logit model was applied to analyze the pricing effects of PBS on passengers’ choice of using PBS as their transfer mode. A latent class model was also used to identify segment-specific preferences. The empirical data show that whether commuters used PBS as a transfer mode was highly dependent on the basic fee and basic period, but not on the variable fee after the basic period; the basic fee mattered to a commuter's choice more than the basic period; irregular PBS users were more sensitive to the basic fee than regular PBS users; and regular PBS users were more sensitive to the basic period than irregular PBS users. The current results broaden the understanding of how PBS pricing affects its usage and illustrate a pricing policy analysis for YouBike that considers sustainable financing and system usage.     

Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice

Modeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of correctly measured variables. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.     

Consumer willingness to pay for in-flight service and comfort levels: A choice experiment

In the competitive aviation market as a result of the emergence of low cost carriers, charter airlines have had to reconsider their approach to service provision. Specifically, the reduction in service and comfort levels offered by the low cost airlines provides charter carriers with an opportunity to differentiate their product based on the quality of the offering. To consider this strategic option we employ an on-line choice experiment to examine consumer choices with respect to the bundle of services on offer when deciding to purchase a flight. With these data we use the Bayesian methods to estimate a mixed logit specification. Our results reveal that in principle passengers are willing to pay a relatively large amount for enhanced service quality.     

高速铁路柔性时刻表编制研究

随着新兴信息技术与交通的不断融合发展,需求响应型交通已成为未来交通发展的新模式,而柔性时刻表编制问题是决定这一新模式能否在高速铁路应用的关键问题之一。基于旅客预约条件下的需求响应型高速铁路柔性时刻表编制问题,提出完全柔性和部分柔性2种编制模式,构建同时考虑列车开行收益和旅客平均偏差时间的双层优化模型,设计模拟退火算法求解,以厦深高速铁路为例进行案例分析。研究结果表明,柔性时刻表编制模型求解得出的时刻表能够较好地匹配旅客预约的出行时间,有效满足旅客预约需求,提高运营收益,对未来需求响应型高速铁路具有一定参考价值。     

The role of schedule delays on passengers’ choice of access modes: A case study of Japan’s international hub airports

We empirically study passenger modal-choice behavior to access an international hub airport, by using stated preference (SP) data and by constructing a binomial logit model. We found that passenger modal choice is affected by the service level of the access modes: travel time, travel cost, waiting time, and delay cost. The results also indicate that if passengers choose access mode in advance they consider service frequency: departure timing from home, and the arrival timing at the airport. Moreover, our results indicate that travelers’ willingness to pay for saving time differs by time of a day. They are apt to pay more in the morning than in the afternoon. These outcomes must contribute to improve the access flight service from local to hub airports to handle the needs of passengers.     

麦加轻轨列车运行模式分析与优化研究

麦加轻轨是中铁建建设并运营的首条海外铁路,由于服务对象为朝觐客流,其列车运行模式较为独特。通过研究麦加轻轨的5种运行模式(A—E),分析其运营效果,提出麦加轻轨列车运行模式的优化方法。重点针对朝觐期间的运行模式E,以发车间隔、运营成本、车底数为约束,以乘客候车时间最短为目标构建了不同客流分布下的行车间隔优化模型,并针对不同集中度的客流分布计算得出最优方案。研究显示,相比既有的行车间隔保持不变的方案,采用优化后的差异化行车间隔方案可以在不增加运营成本的情况下缩减乘客平均候车时间,客流集中趋势越高,优化效果越好,客流高集中趋势下(标准差19.9%)最多可节省候车时间13.2%。研究结果对降低麦加轻轨运营成本、提高乘客服务水平具有现实意义。     

Analysis of ground access modes choice King Khaled International Airport, Riyadh, Saudi Arabia

Airports are vital to the transportation system because air travel is the fastest means of transporting people and goods around the world. Airports also connect aviation systems with other modes of transportation.As a result, access modes to airports are critical to the aviation system, and studying air passenger decisions regarding mode choice is an essential part of airport management and system planning.Though there has been systematic analysis of car use to access airports, there has been less systematic attention to the use of the public transport system, especially the taxi service. The aim of this study is to identify King Khaled International Airport (KKIA) access mode characteristics and users, which has not been investigated previously concentrating on the mix between car and taxi using data collected specifically for this research.More than half (55.5%) of the travelers surveyed arrived at KKIA by private car; taxi and limousine passengers accounted for 42.2% of the sample. The Saudi Public Transit Company (SAPTCO), transported only 2.3% of the air passengers surveyed. These results are similar to findings for an airport in the United States and very different from findings for an airports in the East (e.g., Hong Kong).A binary logit model was developed to evaluate the access mode choice. It was found that income, luggage, travel access time, and nationality significantly affect mode choice.Results provide insight for improved planning of access to KKIA.     

Homogeneous service with heterogeneous products: Relationships among airline ticket fares and purchase fences

A fare table derived from homogeneous service is essential for revenue management applications in the airline industry. Restrictions or so-called fences are usually regarded as a useful tool to differentiate homogeneous seat service. Nevertheless, the relationships among fares and fences are not yet clear. This study aims to investigate passengers’ preferences on the choice of ticket alternatives describing by fares and fences and using Taiwan domestic air travel as an example. Regarding the attributes that an airline ticket may be attached such as departure time, booking time, ticket validity, changing fee, refund and fare, stated preference questionnaires are developed with multiple hypothetical scenarios for respondents to select in the experiment. 398 valid samples are collected for the logit model analysis. With the use of mixed logit model to accommodate both passengers’ heterogeneity and also the issue of relevant alternatives in the experiment, the results show statistical significance of all applied attributes with correct signs. In addition, passengers possess different attitudes on the fence of booking time, ticket validity, changing fee, and fare. Willingness-to-pay of each fence is further calculated to ultimately generate a fare table based on the combination of fences for practice use.     

京沪400km/h高速铁路列车竞争力影响探析

新时代人民对于美好生活的需要已经从单一趋向多元,铁路客运需求将呈现多样化、差异化和个性化,对铁路客运产品在速度、价格和服务质量等方面都提出更高的要求。以铁路大提速运输市场份额提升和高速铁路列车客运量增长为切入点,分析列车速度与市场份额、旅客运量之间的关系,剖析高速铁路列车市场竞争力影响,构建Logit离散数学模型。以京沪高速铁路为例,探讨400km/h高速铁路列车运量预测,研究提出400km/h高速铁路列车可以扩大客流吸引范围,增加铁路客运量,提升高速铁路旅客市场竞争力。