[en] This paper explores the knowledge of the concept ‘Light Rail Transit’ (LRT) in the context of implementing a Light Rail system in a (sub)-urban region. To this end, three models are estimated: a first model to explore the role of knowledge on modal choice, a second one to identify the determinants of the level of knowledge and a third model to identify the determinants of a cognitive mismatch between actual (real) knowledge and perceived knowledge. The first model (a negative binomial regression model) underlines the significant relation between knowledge of the concept LRT and modal choice. Given the lack of knowledge of the concept ‘Light Rail Transit’ revealed by the descriptive results, it is of crucial importance to raise the level of knowledge. Knowledge acquisition can be based on transit experiences and information provision. To explore how information campaigns should be constructed and which target groups should be approached, the factors influencing travelers’ knowledge and the determinants of a cognitive mismatch are identified by a Multinomial Logit Model (MNL-model) and a binary logit model. The results show that various socio-economic variables as well as socio-psychological variables are significantly influencing actual knowledge and significantly influencing a cognitive mismatch. Among these variables, employment, gender, perception of ticket price of Public Transit (PT) and expectations with regard to seat availability in the LRT-vehicle are the most influential ones.
Research center :
LEMA - Local Environment Management and Analysis Lepur : Centre de Recherche sur la Ville, le Territoire et le Milieu rural - ULiège
Disciplines :
Civil engineering Special economic topics (health, labor, transportation...)
Author, co-author :
Creemers, Lieve
Tormans, Hans
Bellemans, Tom
Janssens, Davy
Wets, Geert
Cools, Mario ; Université de Liège - ULiège > Département Argenco : Secteur A&U > Transports et mobilité
Language :
English
Title :
Knowledge of the concept Light Rail Transit: Exploring its relevance and identification of the determinants of various knowledge levels
Publication date :
2015
Journal title :
Transportation Research. Part A, Policy and Practice
Agresti A. Categorical Data Analysis 2002, John Wiley & Sons, United States. second ed.
Anable J. Complacent car addicts or aspiring environmentalists? Identifying travel behaviour segments using attitude theory. Transp. Policy 2005, 12:65-78.
Arentze T. Personalized travel information systems: a Bayesian method to learn users' personal preferences in multimodal transport networks. IEEE Trans. Intell. Transport. Syst. 2013, 14:1957-1966.
Arentze T., Molin E.J.E. Travelers' preferences in multimodal networks: design and results of a comprehensive series of choice experiments. Transport. Res. Part A: Policy Pract. 2013, 58:15-28.
Arentze T., Bos I., Molin E., Timmermans H. Internet-based travel surveys: selected evidence on response rates, sampling bias and reliability. Transportmetrica 2005, 1:193-207.
Arentze T., Timmermans H., Jorritsma P., Olde Kalter M.J., Schoenmakers A. More gray hair - but for whom? Scenario-based simulations of elderly activity travel patterns in 2020. Transportation 2008, 35:613-627.
Bamberg S., Fujii S., Friman M., Gärling T. Behaviour theory and soft transport policy measures. Transp. Policy 2011, 18:228-235.
Beale J.R., Bonsall P.W. Marketing in the bus industry: a psychological interpretation of some attitudinal and behavioral outcomes. Transport. Res. Part F: Traffic Psychol. Behav. 2007, 10:271-287.
Bhattacharjee S., Goetz A.R. Impact of light rail on traffic congestion in Denver. J. Transp. Geogr. 2012, 22:262-270.
Blythe P. Congestion charging: technical options for the delivery of future UK policy. Transport. Res. Part A: Policy Pract. 2005, 39:571-587.
Bonsall, P., Firmin, P., Beale, J. (2004). Perceptions of modal attributes: how accurate and how susceptible to change? In: Presented at the 83rd Annual Meeting of the Transportation Research Board, Washington, D.C.
Brög, W., Erl, E., Mense, N., 2002. Individualized marketing: changing travel behavior for a better environment. In: Paper Presented at the OECD Workshop: Environmentally Sustainable Transport, Berlin.
Cervero R. Built environments and mode choice: toward a normative framework. Transport. Res. Part D: Transp. Environ. 2002, 7:265-284.
Chatterjee K. Modelling the dynamics of bus use in a changing travel environment using panel data. Transportation 2011, 38:487-509.
Chen C., Chao W. Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit. Transport. Res. Part F: Traffic Psychol. Behav. 2011, 14:128-137.
Chorus C.G., Arentze T., Timmermans H.J.P. Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses. Transportation 2007, 34:625-645.
Cools M., Moons E., Janssens D., Wets G. Shifting towards environment-friendly modes: profiling travelers using Q-methodology. Transportation 2009, 36:437-453.
Cools, M., Declercq, K., Janssens, D., Wets, G., 2010. Onderzoek verplaatsingsgedrag Vlaanderen 4.2 (2009-2010): Tabellenrapport (Travel behavior research Flanders 4.2 (2009-2010): Table report). Hasselt University, Diepenbeek, Belgium.
Cools M., Brijs K., Tormans H., Moons E., Janssens D., Wets G. The socio-cognitive links between road pricing acceptability and changes in travel-behavior. Transport. Res. Part A: Policy Pract. 2011, 45:779-788.
Creemers L., Cools M., Tormans H., Lateur P.J., Janssens D., Wets G. Identifying the determinants of light rail mode choice for medium/long distance trips: results from a stated preference study. Transport. Res. Rec.: J. Transport. Res. Board 2012, 2275:30-38. (Transportation Research Board of the National Academies, Washington, D.C.).
Creemers L., Wets G., Cools M. Meteorological variation in daily travel behaviour: evidence from revealed preference data from the Netherlands. Theor. Appl. Climatol. 2014, (forthcoming). 10.1007/s00704-014-1169-0.
Cronin J.J., Hightower R. An evaluation of the role of marketing in public transit organizations. J. Public Transport. 2004, 7:17-36.
Currie G., Ahern A., Delbosc A. Exploring the drivers of light rail ridership: an empirical route level analysis of selected Australian, North American and European systems. Transportation 2011, 38:545-560.
De Lijn Regionet Limburg. Regionaal openbaar vervoer in de provincie Limburg. Conceptstreefbeeld 2002, Vervoersmaatschappij De Lijn, Mechelen, Belgium.
De Witte A., Hollevoet J., Dobruszkes F., Hubert M., Macharis C. Linking modal choice to motility: a comprehensive review. Transport. Res. Part A: Policy Pract. 2013, 49:329-341.
Dell'Olio L., Ibeas A., Dominguez A., Gonzalez F. Passenger preference analysis: light rail transit or bus versus car. Transport 2012, 27:276-285.
Diana M. From mode choice to modal diversion: a new behavioural paradigm and an application to the study of the demand for innovative transport services. Technol. Forecast. Soc. Chang. 2010, 77:429-441.
Diana M., Mokhtarian P.L. Grouping travelers on the basis of their different car and transit levels of use. Transportation 2009, 36:455-467.
Diana M., Mokhtarian P.L. Desire to change one's multimodality and its relationship to the use of different transport means. Transport. Res. Part F: Traffic Psychol. Behav. 2009, 12:107-119.
Diana M., Pronello C. Traveler segmentation strategy with nominal variables through correspondence analysis. Transp. Policy 2010, 17:183-190.
Dziekan K. Learning an Unfamiliar Public Transport System: An In-Depth Study from the User Perspective in Stockholm 2007, Royal Institute of Technology, Stockholm, Sweden.
Dziekan K. What do people know about their public transport options? Investigating the memory representations of public transport through telephone interviews in a residential area of Stockholm, Sweden. Transportation 2008, 35:519-538.
Dziekan K., Dicke-Ogenia M. Reducing uncertainty and supporting cognitive maps in travel information for public transport. World Rev. Intermodal Transport. Res. 2010, 3:73-90.
Elias W., Shiftan Y. The influence of individual's risk perception and attitudes on travel behavior. Transport. Res. Part A: Policy Pract. 2012, 46:1241-1251.
Eriksson L., Garvill J., Nordlund A.M. Interrupting habitual car use: the importance of car habit strength and moral motivation for personal car use reduction. Transport. Res. Part F: Traffic Psychol. Behav. 2008, 11:10-23.
European Environment Agency, 2012. The Contribution of Transport to Air Quality, TERM 2012: Transport Indicators Tracking Progress Towards Environmental Targets in Europe. Number 10/2012 in EEA Report, Office for Official Publications of the European Communities, Luxembourg.
Fan W., Yan Z. Factors affecting response rates of the web survey: a systematic review. Comput. Hum. Behav. 2010, 26:132-139.
Forsey D., Habib K.H., Miller E.J., Shalaby A. Evaluating the impacts of a new transit system on commuting mode choice using a GEV model estimated to revealed preference data: a case study of the VIVA system in York Region, Ontario. Transport. Res. Part A: Policy Pract. 2013, 50:1-14.
Galdames C., Tudela A., Carrasco J. Exploring the role of psychological factors in mode choice models by a latent variables approach. Transport. Res. Rec.: J. Transport. Res. Board 2011, 2230:68-74. (Transportation Research Board of the National Academies, Washington, D.C).
Gardner B., Abraham C. What drives car use? A grounded theory analysis of commuters' reasons for driving. Transport. Res. Part F: Traffic Psychol. Behav. 2007, 10:187-200.
Gatersleben B., Appleton K.M. Contemplating cycling to work: attitudes and perceptions in different stages of change. Transport. Res. Part A: Policy Pract. 2007, 41(4):302-312. 10.1016/j.tra.2006.09.002.
Gifford R., Steg L. The impact of automobile traffic on quality of life. Threats from Car Traffic to the Quality of Urban Life: Problems, Causes, and Solutions 2007, Elsevier, Amsterdam. T. Gärling, L. Steg (Eds.).
Guiliano G., Hayden S. Marketing public transport. Handbooks in Transport 2005, Pergamon Press, Oxford. D. Hensher, K.J. Button (Eds.).
Guo Z. Mind the map! The impact of transit maps on path choice in public transit. Transport. Res. Part A: Policy Pract. 2011, 45:625-639.
Habib K.M.N., Day N., Miller E.J. An investigation of commuting trip timing and mode choice in the Greater Toronto Area: application of a joint discrete-continuous model. Transport. Res. Part A: Policy Pract. 2009, 43(7):639-653. 10.1016/j.tra.2009.05.001.
Handy S.L., Xing Y., Buehler T.J. Factors associated with bicycle ownership and use: a study of 6 small U.S. cities. Transportation 2010, 37:967-985.
Hart, N., Lownes, N.E., Jackson, E., 2012. Analysis of a method for bias reduction in electronic travel surveys. In: Presented at the 91th Annual Meeting of the Transportation Research Board, Washington, D.C.
Haustein S. Mobility behavior of the elderly: an attitude-based segmentation approach for a heterogeneous target group. Transportation 2011, 39:1079-1103.
Haustein S., Hunecke M. Identifying target groups for environmentally sustainable transport: assessment of different segmentation approaches. Energy Syst. 2013, 5:197-204.
Heinen E., Maat K., Van Wee B. The role of attitudes towards characteristics of bicycle commuting on the choice to cycle to work over various distances. Transport. Res. Part D: Transp. Environ. 2011, 16:102-109.
Holgùin-Veras J., Yushimito W.F., Aros-Vera F., Reilly J. User rationality and optimal park-and-ride location under potential demand maximization. Transport. Res. Part B: Methodol. 2012, 46:949-970.
Hunecke M., Haustein S., Böhler S., Grischkat S. An attitude based target group approach to reduce the ecological impact of daily mobility behaviour. Environ. Behav. 2010, 42:3-43.
Jones, P.M., Sloman, L., 2003. Encouraging behavioural change through marketing and management: what can be achieved? In: Paper presented at the 10th International Conference on Travel Behaviour Research, Lucerne, August.
Kim S., Ulfarsson G.F. Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips. Transportation 2008, 35:723-737.
Li Z., Yang C., Wang W., Jiang G. Bicycle commuting market segmentation analysis using attitudinal factors. J. Southeast Univ. (Natural Science Edition) 2012, 42(4):784-789.
Li Z., Wang W., Yang C., Ragland D.R. Bicycle commuting market analysis using attitudinal market segmentation approach. Transport. Res. Part A: Policy Pract. 2013, 47:56-68.
Loo B.P.Y., Chen C., Chan E.T.H. Rail-based transit-oriented development: lessons from New York City and Hong Kong. Landscape Urban Plann. 2010, 97:202-212.
Loukopoulos P., Gärling T. Are car users too lazy to walk? The relationship of distance thresholds for driving to the perceived effort of walking. Transport. Res. Rec.: J. Transport. Res. Board 2005, 1926:206-211. (Transportation Research Board of the National Academies, Washington, D.C.).
Mackett R., Babalik-Sutcliffe E. New urban rail systems: a policy based technique to make them more successful. J. Transp. Geogr. 2003, 11:151-164.
Mattson J., Peterson D., Ripplinger D., Thoms W., Hough J. An assessment of demand for rural intercity transportation services in a changing environment. Transport. Res. Rec.: J. Transport. Res. Board 2010, 2145:108-114. (Transportation Research Board of the National Academies, Washington, D.C.).
Molenberghs G., Verbeke G. Models for Discrete Longitudinal Data 2005, Springer, United States.
NIS, 2010. Structure of the Population by Age and Gender. <>. http://statbel.fgov.be/nl/modules/publications/statistiques/bevolking.
Outwater M.L., Spitz G., Lobb J., Campbell M., Sana B., Pendyala R., Woodford W. Characteristics of premium transit services that affect mode choice. Transportation 2011, 38:605-623.
Páez A., Trépanier M., Morency C. Modeling isoexposure to transit users for market potential analysis. Transport. Res. Part A: Policy Pract. 2012, 46:1517-1527.
Pedersen T., Kristensson P., Friman M. Effects of critical incidents on car users' predicted satisfaction with public transport. Transport. Res. Part F: Traffic Psychol. Behav. 2011, 14:138-146.
Popuri U., Proussaloglou K., Ayvalik C., Koppelman F., Lee A. Importance of traveler attitudes in the choice of public transportation to work: findings from the regional transportation authority attitudinal survey. Transportation 2011, 38:643-661.
Pronello C., Camusso C. Travellers' profiles definition using statistical multivariate analysis of attitudinal variables. J. Transp. Geogr. 2011, 19:1294-1308.
Rose G., Ampt E. Travel blending: an Australian travel awareness initiative. Transport. Res. Part D: Transp. Environ. 2001, 6:95-110.
Rose G., Marfurt H. Travel behaviour change impacts of a major ride to work day event. Transport. Res. Part A: Policy Pract. 2007, 41:351-364.
Scherer M. Is light rail more attractive to users than bus transit? Arguments based on cognition and rational choice. Transport. Res. Rec.: J. Transport. Res. Board 2010, 2144:11-19. (Transportation Research Board of the National Academies, Washington, D.C.).
Shiftan Y., Outwater M.L., Zhou Y.S. Transit market research using structural equation modeling and attitudinal market segmentation. Transp. Policy 2008, 15:186-195.
Smith C., Spitz G. Internet access: is everyone online yet and can we survey them there?. Transport. Res. Rec.: J. Transport. Res. Board 2010, 2176:12-20. (Transportation Research Board of the National Academies, Washington, D.C.).
Sperry, B.R., Larson, S., Leucinger, D., Janowiak, S., Morgan, C.A., 2012. Design and implementation of an internet-based traveler intercept survey. In: Presented at the 91th Annual Meeting of the Transportation Research Board, Washington, D.C.
Wright K.B. Researching internet-based populations: advantages and disadvantages of online research, online questionnaire authoring software packages, and web survey services. J. Comput.-Mediated Commun. 2005, 10.
Zhang J., Arentze T., Timmermans H. A Multimodal transport network model for advanced traveler information system. J. Ubiquitous Syst. Pervasive Netw. 2012, 4:21-27.
