Presentation on theme: "Dimensions in Elderly Mobility Behaviour as a Basis for Target Group Specific Mobility Services Sonja Haustein ILS – Institut für Landes- und Stadtentwicklungsforschung."— Presentation transcript:
Dimensions in Elderly Mobility Behaviour as a Basis for Target Group Specific Mobility Services Sonja Haustein ILS – Institut für Landes- und Stadtentwicklungsforschung GmbH Ruhr-Universität Bochum (RUB) Marcel Hunecke RUB, Germany Herbert Kemming ILS, Germany
2 / 19 Outline Background Segmentation approach Description of the segments of the elderly Target group specific measures Conclusions
3 / 19 Background populations of western world are aging by 2030 almost every third European will be 60 years or older (United Nations, 2007) affects almost every aspect of our lives incl. transport sector today mobility rates and car use of the elderly are smaller than the ones of younger individuals but mobility rates and private car use of older people expected to increase due to lifestyle changes and growing car availability decreasing number of captive riders of public transport negative environmental and safety implications e.g. Rosenbloom (2001). Sustainability and automobility among the elderly: an international assessment. Transportation, 28(4), 375-408.
4 / 19 Consequences measures required that offer more environmentally- friendly alternatives to the private car, still meeting mobility and accessibility needs mobility needs and requirements of the elderly have been research in the last years (e.g. EU projects MOBILATE, SIZE) but most results refer to the whole group of the elderly however seniors are a heterogeneous group with differentiating life styles, needs and requirements 1 need for a more differentiated approach 1 BASt & DVR (2000). More road safety for senior citizens. European Conference, 2-4 May, 2000, Cologne. Bremerhaven: Wirtschaftsverlag NW.
Segmentation approaches of the elderly Käser, 2004Hildebrandt, 2003Kirchmair, 2005Jansen et al., 2001 Segmen- tation according to: variety and frequency of activities socio- demographic and household variables (e.g. age, driving license) life-style variables (e.g. consumer behaviour, leisure time activities) life-style variables (leisure time activities, TV programme, furnishing) Groups / Types Group I (17,7%): low variety and frequency Group II (50,0%): medium variety, small-high frequency Group III (30,5%): high variety, medium- high frequency Group IV (0,5%): low variety, high frequency Workers (11%) Mobile widows (29%) Granny flats (4%) Mobility impaired (12%) Affluent males (39%) Disabled drivers (5%) Demanding consumption- oriented (22%) Conservative wollowers (15%) Expense-oriented innovators (11%) Economical solitaries (11%) Risk-avers traditionals (19%) Sensation- seeking Actives (22%) Indifferent Type (34%) Sensation- seeking Type (19%) Intellectual Type (18%) Refusing Type (15%) Calm life style type (14%) 5 / 19
6 / 19 Evaluation of different approaches different kind of segmentation approaches have specific pros and cons and are relevant for different fields of application 1 not applied for the group of seniors until now: segmentation approach that regards mobility-related attitudes advantages 1 : higher relation to mobility behaviour than life styles and socio-demographic types offer better starting points for interventions than behaviour based and socio-demographic approaches 1 Hunecke, Haustein, Böhler, & Grischkat (in press). An attitude based target group approach to reduce the ecological impact of daily mobility behavior. Environment & Behavior.
7 / 19 Data base 1 standardised interviews 557 individuals (51% m., 49% f.) aged 60-80 three district types in three big German cities: city-centre, city border, suburban district face-to-face interviews (~one hour) content mobility behaviour to explain mobility behaviour: mobility-related attitudes, norms socio-demographic data infrastructural data 1 Sub-sample of data form research project MOBILANZ supported by Federal Ministry of Education and Research (cf. Hunecke, Haustein, Grischkat, & Böhler, Journal of Environmental Psychology, 27, 277-292.
8 / 19 1. step: factor analysis to develop reliable scales 2. step: regression analyses to identify the most important determinants of mobility behaviour of the elderly 3. step: cluster analyses to identify segments of elderly based on the most relevant determinants of mobility behaviour Segmentation process
9 / 19 Scale (number of items) Descriptionα1α1 Car orientation (7 Items) Symbolic-affective evaluation of the car / driving (autonomy, excitement, privacy): Driving a car means freedom to me..80 Bicycle orientation (4) Symbolic-affective evaluation of the bicycle / cycling (autonomy, excitement): By bike I can get anywhere..77 Public transport control (5) Evaluation of the ability to use public transportation: Using public transportation instead of the private car is easy for me if I want to..80 Public transport excitement (2) Evaluation of public transport in terms of excitement and recreation: For me using public transportation is relaxing..58 Ecological norm (4) Moral obligation (personal norm) and social pressure (social norm) to use environmentally friendly modes of transport: For environmental reasons I feel obliged to leave the car unused in everyday life as often as possible..67 Weather resistance (2) Willingness to use the bicycle in bad weather conditions: I dont like riding my bike when the weather is chilly. (reversed).70 Perceived mobility needs (2) People's perceptions of mobility-related consequences of their personal living circumstances: I have to be mobile all the time to meet my obligations..84 Psychological scales 1 Conbachs α First step: Development of reliable scales
Regression analyses (2 out of 5) 10 / 19 PredictorsDistance travelledPercentage trips by car City centre-.09* Driving license.13*.11* Number of cars.14*.23*** Age-.18*** Partner in household.10* Partner in different household (LAT).12* Employed.13* Ecological norm-.12* Public transport control-.32*** Weather resistance-.18*** Perceives mobility needs.16*.12** R2R2.21.50 Second step:Identification of relevant determinants of mobility behaviour
Regression analyses (2 out of 5) 11 / 19 PredictorsDistance travelledPercentage trips by car City centre-.09* Driving license.13*.11* Number of cars.14*.23*** Age-.18*** Partner in household.10* Partner in different household (living apart together).12* Employed.13* Ecological norm-.12* Public transport control-.32*** Weather resistance-.18*** Perceives mobility needs.16*.12** R2R2.21.50 Second step:Identification of relevant determinants of mobility behaviour
Cluster centres 12 / 19 Third step: Identification of segments of the elderly
Distance travelled and leisure time activities 15 / 19
16 / 19 Overview of segments characteristics Mobile Car- Oriented Restricted Mobiles Self- Determined Mobiles Pragmatic PT- Oriented Bicycle- Oriented Eco-friendly PT-Oriented Mobility behaviour Car+++0---- Public transport ----+-++ Bicycle ----0++- Foot --+++ + Distance travelled ++--0 0- Leisure time activ. 0--+-++ Mobility-related attitudes / norms PT control -- +++++ PT excitement ----00++ Bicycle orientation 0--+0++0 Ecological norm ----00++ PMN ++----0+ Weather resistance ----0++- Sociodemo- grahic data, accessibility Age -+-++-0 Income ++--0-0 Number of cars ++00-0-- Season ticket --00+0++
17 / 19 Target group specific measures Mobile Car- Oriented Restricted Mobiles Self- Determined Mobiles Pragmatic PT- Oriented Bicycle- Oriented Eco-friendly PT-Oriented promotion of good (= fast) railway connections X test tickets for public transport X trainings for public transport use X escort service for public transport use X cheap ticket without any extras XX off-peak and first class ticket options X better bicycle carriage facilities X public awareness campaigns with ecological arguments XXX support of current behaviour: positive feedback about contribution to climate protection XX
Conclusions Mobility management for the elderly has to recognise the heterogeneous requirements and attitudes of this group. The presented approach defines relevant subgroups, which can serve as target groups for specific measures. Segments mobility behaviour cannot be explained by socio- demographic and infrastructural differences alone but also requires the consideration of mobility-related attitudes. Car availability is not necessarily required for a high amount of leisure time mobility if access to PT is available: three segments with the highest amount of leisure time activities show above average shares of eco-friendly modes (foot, bike, or public transport); none of them uses the car above-average good public transport service can help to enhance mobility of older people and contribute to a high quality of life 18 / 19
Thanks for your attention! Sonja Haustein ILS – Institut für Landes- und Stadtentwicklungsforschung GmbH email@example.com http://www.ils.nrw.de/ Ruhr-Universität Bochum Workgroup for Environmental and Cognitive Psychology firstname.lastname@example.org http://eco.psy.ruhr-uni-bochum.de/