Assessing Importance and Satisfaction Judgments of Intermodal Work Commuters with Electronic Survey Methodology, MTI Report WP 12-01

Recent advances in multivariate methodology provide an opportunity to further the assessment of service offerings in public transportation for work commuting. We offer methodologies that are alternative to direct rating scale and have advantages in the quality and precision of measurement. The alternative of methodology for adaptive conjoint analysis for the measurement of the importance of attributes in service offering is implemented. Rasch scaling methodology is used for the measurement of satisfaction with these attributes. Advantages that these methodologies introduce for assessment of the respective constructs and use of the assessment are discussed. In a first study, the conjoint derived weights were shown to have predictive capabilities in applications to respondent distributions of a fixed total budget to improve overall service offerings. Results with the Rasch model indicate that the attribute measures are reliable and can adequately constitute a composite measure of satisfaction. The Rasch items were also shown to provide a basis to discriminate between privately owned vehicles (POVs) and public transport commuters. Dissatisfaction with uncertainty in travel time and income level of respondents were the best predictors of POV commuting

Managerial Segmentation of Service Offerings in Work Commuting, MTI Report WP 12-02

Methodology to efficiently segment markets for public transportation offerings has been introduced and exemplified in an application to an urban travel corridor in which high tech companies predominate. The principal objective has been to introduce and apply multivariate methodology to efficiently identify segments of work commuters and their demographic identifiers. A set of attributes in terms of which service offerings could be defined was derived from background studies and focus groups of work commuters in the county. Adaptive choice conjoint analysis was used to derive the importance weights of these attributes in available service offering to these commuters. A two-stage clustering procedure was then used to explore the grouping of individual’s subsets into homogeneous sub-groups of the sample. These subsets are commonly a basis for differentiation in service offerings that can increase total ridership in public transportation while approximating cost neutrality in service delivery. Recursive partitioning identified interactions between demographic predictors that significantly contributed to the discrimination of segments in demographics. Implementation of the results is discussed

Costs of Interchange: A Review of the Literature.

Interchange within mode influences the demand for that mode through the effect it has on time spent waiting, time spent transferring between vehicles and the inconvenience and risks involved, whilst interchange between modes has additional implications in terms of information provision, through ticketing and co-ordination. The valuation and behavioural impact of each of these factors will vary with an individual’s socio-economic and trip characteristics as well as with the precise features of the interchange. A reduction in the costs of interchange brought about by an improvement to any of the above factors will lead to increasingly ‘seamless journeys’ and such benefits which must be quantified. Indeed, this issue has been identified as an area of key importance in the Government’s Transport White Paper (DETR, 1998a) which states: Quick and easy interchange is essential to compete with the convenience of car use. This message was reiterated by the draft guidance for Local Transport Plans (DETR, 1998b), which called for: more through-ticketing, better connections and co-ordination of services, wider availability of information and improved waiting facilities. Rather than being perceived simply as a barrier to travel, quality interchange is now also being regarded as an opportunity to create new journey opportunities. A recent report on the subject of interchange (Colin Buchanan and Partners, 1998) claimed that : It will become more sensible and economic to base public transport networks around the concept of interchange rather than the alternative of trying to avoid it. whilst in response to the diffuse travel patterns made possible by increased car availability, CIT (1998) commented: people should readily be able to complete a myriad of journeys by changing services (and modes) if a through facility is not available. Ease of interchange should be something we take for granted. Regardless of the precise direction in which transport policy and public transport provision develop, practical constraints and the fact that the most heavily trafficked routes tend to have through services places limitations on the extent to which the need to interchange can be reduced whilst no matter how fully integrated different modes of transport are the need to transfer between them cannot be removed. In contrast, the need to change would inevitably increase with the adoption of a practice of building networks around interchange to create new journey opportunities. However, there is considerable scope to improve existing interchange situations or to design new ones which impose minimum costs. Although previous empirical research has focused on the need to interchange or not, and this remains important, it is essential that research is also directed at improvements which facilitate interchange.The aims of this study, as set out in the terms of reference, are centred around the demand side response to interchange rather than the technical supply side issues relating to improving interchange and integration which have been covered in other studies (Colin Buchanan and Partners, 1998; CIT, 1998). The objectives are: to explore the extent to which the reality and perception of interchange deters public transport use, absolutely and in relation to other deterrents to investigate how public transport users perceive interchange; how they make choices and trade-offs in travel cost and time and the influence of interchange attributes (e.g. information, through ticketing) on those choices to assess which components of interchange act as the greatest deterrent to travel to investigate the extent to which interchange penalties vary according to journey purpose, distance and time of travel (or other factors)

Inferring transportation modes from GPS trajectories using a convolutional neural network

Identifying the distribution of users' transportation modes is an essential part of travel demand analysis and transportation planning. With the advent of ubiquitous GPS-enabled devices (e.g., a smartphone), a cost-effective approach for inferring commuters' mobility mode(s) is to leverage their GPS trajectories. A majority of studies have proposed mode inference models based on hand-crafted features and traditional machine learning algorithms. However, manual features engender some major drawbacks including vulnerability to traffic and environmental conditions as well as possessing human's bias in creating efficient features. One way to overcome these issues is by utilizing Convolutional Neural Network (CNN) schemes that are capable of automatically driving high-level features from the raw input. Accordingly, in this paper, we take advantage of CNN architectures so as to predict travel modes based on only raw GPS trajectories, where the modes are labeled as walk, bike, bus, driving, and train. Our key contribution is designing the layout of the CNN's input layer in such a way that not only is adaptable with the CNN schemes but represents fundamental motion characteristics of a moving object including speed, acceleration, jerk, and bearing rate. Furthermore, we ameliorate the quality of GPS logs through several data preprocessing steps. Using the clean input layer, a variety of CNN configurations are evaluated to achieve the best CNN architecture. The highest accuracy of 84.8% has been achieved through the ensemble of the best CNN configuration. In this research, we contrast our methodology with traditional machine learning algorithms as well as the seminal and most related studies to demonstrate the superiority of our framework.Comment: 12 pages, 3 figures, 7 tables, Transportation Research Part C: Emerging Technologie

Travellers' profiles definition using statistical multivariate analysis of attitudinal variables

This paper aims at presenting a set of travellers' typologies using attributes characterizing people's attitude, through an Exploratory Factor Analysis (EFA), and a subsequent cluster analysis (CA), based on the obtained latent constructs. The final goal is to contribute to deepen the knowledge on market segmentation in order to define more people-oriented transport policies, focusing on a medium size Italian city, Alessandria. Six factors have been defined on which the k-means cluster analysis has been applied finding four travellers' profiles. Results confirm certain hypothesis from behavioural psychological theories. Attitude-behaviour relationships loosen when habits, consolidated in time, do intervene; moreover in small-medium urban context, as opposed to large and dense cities, insufficient transport supply does not favour the use of alternative modes to the motor vehicle, if not to the cost of a great loss in efficiency. In fact, the study shows how significant constraints such as necessity, time saving, and low transport supply (mainly designed around students going to school) are in determining a behavioural change, so that the ‘‘right general attitudes'' are not sufficient to obtain a real modal shift. This leads to expect opportunistic behaviours, even within a overall positive attitude towards the environment. Actually, that overall positive attitude is not enough to prompt consistent behaviour unless a marked self-control and strong motivation are present. These two features seem to be missing in the interviewed sample of population, unlike what emerges from other studies undertaken in Northern Europe. The geographic location most likely plays a significant role in such a difference. Indeed, cultural background and the prevailing habits of the population may well explain the ‘‘slackening'' of the bond between moral norms and behaviour, and the subsequent search for surrogates (e.g. the high willingness to pay for environmental protection) to justify the unwillingness to forgo the private vehicle on behalf of more sustainable modes. Finally, our study seems to prove that education could play a key role in transport policy formulation but, moreover, in social policy, as individuals more akin to modal shift are those showing higher levels of instructio

Will they take this offer? A machine learning price elasticity model for predicting upselling acceptance of premium airline seating

Employing customer information from one of the world's largest airline companies, we develop a price elasticity model (PREM) using machine learning to identify customers likely to purchase an upgrade offer from economy to premium class and predict a customer's acceptable price range. A simulation of 64.3 million flight bookings and 14.1 million email offers over three years mirroring actual data indicates that PREM implementation results in approximately 1.12 million (7.94%) fewer non-relevant customer email messages, a predicted increase of 72,200 (37.2%) offers accepted, and an estimated $72.2 million (37.2%) of increased revenue. Our results illustrate the potential of automated pricing information and targeting marketing messages for upselling acceptance. We also identified three customer segments: (1) Never Upgrades are those who never take the upgrade offer, (2) Upgrade Lovers are those who generally upgrade, and (3) Upgrade Lover Lookalikes have no historical record but fit the profile of those that tend to upgrade. We discuss the implications for airline companies and related travel and tourism industries.© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

From Automobiles to Alternatives: Applying Attitude Theory and Information Technologies to Increase Shuttle Use at Rocky Mountain National Park

This thesis examines potential strategies for increasing voluntary shuttle use at Rocky Mountain National Park (ROMO) and the gateway community of Estes Park, Colorado. The first chapter of this two-part study evaluates the impact of a pilot intelligent transportation system (ITS) on visitor awareness and use of shuttles during the summer of 2011. Two forms of ITS, dynamic message signs (DMS) and highway advisory radio (HAR), were evaluated. Specifically, the ITS was meant to influence day-visitors to park at a new park-and-ride lot just east of Estes Park where they could then board a connector shuttle and transfer to any of four shuttle routes servicing the town and park. Surveys were administered onboard the park-and-ride shuttle (N = 68) and at two locations in downtown Estes Park (N = 490). Our analysis revealed that the DMS contributed to increased awareness of the shuttles. However, the HAR did not contribute substantially to awareness or use of the visitor shuttles. Our analysis offers additional recommendations for increasing voluntary shuttle use, such as providing direct routes between the park-and-ride and popular park attractions. The results of this study demonstrate the utility of ITS as a transportation management tool in a national park setting, but also highlight the importance of selecting appropriate technologies that meet the needs of park visitors. The second chapter explores strategies for optimizing the use of ITS by applying the theory of planned behavior (Ajzen, 1991) to identify the beliefs that inform choice of travel mode among ROMO and Estes Park visitors. Using results of a mail survey (N = 222), the theory of planned behavior was applied to the prediction of intention and use of visitor shuttles. Perceived behavioral control was found to have a significant influence on intention to use shuttles. Past experience with park shuttles was tested as an additional predictor of behavior and shown to significantly improve the prediction of shuttle use. Past experience with public transit was also added to the model, but with no significant contribution, thereby demonstrating the inherent difference between travel behaviors in everyday settings as opposed to recreation settings. These results were then coupled with segmentation analysis to identify unique segments of visitors. The segments were statistically similar in terms of demographic characteristics, yet heterogeneous in their attitudes, subjective norms, and perceived control regarding shuttle use. Of the three segments identified, Bus Backers were found to hold the most positive beliefs about shuttles and Potential Mode-shifters were identified as the segment offering the most potential for mode change due to their neutral attitudes and beliefs. Strategies were identified to maintain and improve use of shuttles among these segments. Our study broadens the application of segmentation analysis to transportation in a park setting and demonstrates its important contribution

Customizing the promotion strategies of integrated air-bus service based on passenger satisfaction

The integrated air-bus service expands the catchment area and alleviates congestion of regional airports. To gain further insights into the unexplored potential attributes of the integrated service that generate passenger satisfaction, this paper utilizes a two-stage analysis approach to identify the key promotion factors for passengers from different constituents. Based on the survey data collected in Nanjing Lukou International Airport, this paper 1) uses k-means clustering to categorize respondents into four groups. 2) Combines the gradient boosting decision tree and impact asymmetry analysis to identify the attributes that have nonlinear influences on the overall service satisfaction for each group respectively. Results suggest that the timetable of the airport bus is critical for all passenger groups. Interestingly, there are noticeable differences in passenger satisfaction with the accessibility, cost affordability, comfort, reliability, and integration of the integrated service, providing the basis for customizing service promotion strategies among different passenger groups and airports.</p