Transit commuting market investigation using the latent segmentation

This study employs a latent segmentation approach to investigate the commuting market, with focus on the usage of public transit. The factor–cluster analysis technique is used to systematically deal with multi-dimensional psychological statements, and then segment the whole sample into homogenous groups. A six-cluster solution is arrived, each with distinct combinations of latent factors, including attitude, perception, habit, and intention to use public transit. On account of the unique psychological profile of each segment, related measures and strategies are proposed to promote the choice of public transit for each sub-segment. The results demonstrate that individuals within different segments must be treated in different ways since their behavior are motivated by different factors.

[1]  Gabriela Beirão,et al.  Understanding attitudes towards public transport and private car: A qualitative study , 2007 .

[2]  M. Wedel,et al.  Market Segmentation: Conceptual and Methodological Foundations , 1997 .

[3]  P. Bonsall,et al.  Marketing in the bus industry: A psychological interpretation of some attitudinal and behavioural outcomes , 2007 .

[4]  H. Aarts,et al.  Habits as knowledge structures: Automaticity in goal-directed behavior , 2000 .

[5]  Peter Loukopoulos,et al.  An experimental simulation of adaptations to increased car-use costs , 2007 .

[6]  Susan L Handy,et al.  Driving by choice or necessity , 2005 .

[7]  S. Washington,et al.  Statistical and Econometric Methods for Transportation Data Analysis , 2010 .

[8]  Moshe Ben-Akiva,et al.  Attitudinal Market Segmentation Approach to Mode Choice and Ridership Forecasting: Structural Equation Modeling , 2003 .

[9]  Y. Shiftan,et al.  Transit market research using structural equation modeling and attitudinal market segmentation , 2008 .

[10]  Emily Parkany,et al.  Are Attitudes Important in Travel Choice? , 2004 .

[11]  Gabriela Beirão,et al.  Market Segmentation Analysis using Attitudes toward Transportation , 2008 .

[12]  Muhammad Faishal Ibrahim,et al.  Car ownership and attitudes towards transport modes for shopping purposes in Singapore , 2003 .

[13]  J. Urry,et al.  The New Mobilities Paradigm , 2006 .

[14]  Jillian Anable,et al.  'Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behaviour segments using attitude theory , 2005 .

[15]  J. Thøgersen.  Understanding repetitive travel mode choices in a stable context: A panel study approach , 2006 .

[16]  D. A. Hensher.  Market segmentation as a mechanism in allowing for variability of traveller behaviour , 1976 .

[17]  Sonja Haustein,et al.  Attitude-Based Target Groups to Reduce the Ecological Impact of Daily Mobility Behavior , 2010 .

[18]  Mark Wardman,et al.  Demand for rail travel to and from airports , 2002 .

[19]  Tommy Gärling,et al.  Application of attitude theory for improved predictive accuracy of stated preference methods in travel demand analysis , 2003 .

[20]  Linda Steg,et al.  SUSTAINABLE TRANSPORTATION AND QUALITY OF LIFE. , 2005 .

[21]  C. Pronello,et al.  Travellers’ profiles definition using statistical multivariate analysis of attitudinal variables , 2011 .

[22]  Tommy Gärling,et al.  Reintroducing attitude theory in travel behavior research: The validity of an interactive interview procedure to predict car use , 1998 .

[23]  P. Schmidt,et al.  Incentives, Morality, Or Habit? Predicting Students’ Car Use for University Routes With the Models of Ajzen, Schwartz, and Triandis , 2003 .

[24]  B. Mandel,et al.  The Interdependency of Airport Choice and Travel Demand , 1999 .

[25]  Ram M. Pendyala,et al.  Analysis of the Role of Traveler Attitudes and Perceptions in Explaining Mode-Choice Behavior , 1999 .

[26]  Lothlorien S. Redmond.  Identifying and Analyzing Travel-Related Attitudinal, Personality, and Lifestyle Clusters in the San Francisco Bay Area , 2000 .

[27]  Eric I. Pas,et al.  Market segmentation analysis of potential inter-city rail travelers , 1992 .

[28]  P. Green,et al.  Alternative approaches to cluster-based market segmentation , 1995 .

[29]  Kees Maat,et al.  The role of attitudes toward characteristics of bicycle commuting on the choice to cycle to work over various distances , 2011 .

[30]  T. Ryley,et al.  Air travel attitudes and behaviours: The development of environment-based segments , 2014 .

[31]  R. Mackett,et al.  The impact of new urban public transport systems: will the expectations be met? , 1998 .

[32]  D. Ragland,et al.  Bicycle commuting market analysis using attitudinal market segmentation approach , 2013 .

[33]  J. Hair.  Multivariate data analysis , 1972 .

[34]  D. McKenzie‐Mohr,et al.  Promoting Sustainable Behavior : An Introduction to Community-Based Social Marketing , 2000 .

[35]  Thomas F. Golob,et al.  Structural Equation Modeling For Travel Behavior Research , 2001 .

[36]  Satoshi Fujii,et al.  What does a one-month free bus ticket do to habitual drivers? An experimental analysis of habit and attitude change , 2003 .

[37]  Tobias Kuhnimhof,et al.  Users of transport modes and multimodal travel behavior : Steps toward understanding travelers' options and choices , 2006 .

[38]  Mette Jensen,et al.  Passion and heart in transport: a sociological analysis on transport behaviour , 1999 .

[39]  I. Ajzen.  The theory of planned behavior , 1991 .