Introduction
Motivation
Research gaps
Aim and scope of the study
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Do personal goals of older adults affect their shopping trip mode choice?
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To what degree and how do sociodemographic and built environmental factors affect shopping trip mode choice of older adults?
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Does the use of different spatial units of analysis (activity space models versus the commonly used 500-m buffer) affect the results we obtain regarding the effects of built environment?
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Does the shape of activity space and activity dispersion of older adults affect their transportation mode choice?
Methodology
Data collection procedure
Data analysis
Spatial units of analysis
Built environmental measures
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Intersection density was calculated as the share of intersections of three or more road segments per the spatial unit of analysis in question (buffer, IHR, IREM), as suggested by Frank et al. (2007). The data was drawn from the Digiroad 2017 dataset maintained by the Finnish Transport Agency. Digiroad is a national database which contains precise and accurate data on the location of all roads and streets in Finland as well as their most important physical features. The Finnish Transport Agency maintains and updates the data in the Digiroad system.
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Residential density was calculated as the ratio of the number of dwelling units to the surface area devoted to residential land use within each spatial unit of analysis in question. The residential density measure was drawn from SeutuCD 2014 building dataset (point data) which is a regional dataset provided by Helsinki Region Environmental Services Authority HSY and from the CORINE 2012 land cover dataset (raster data) that is provided for research use by Finnish environment institute. SeutuCD is an extensive collection of GIS data, which compiles the most essential register and map data sets related to the planning of the HMA. Helsinki Region Environmental Services Authority produces and provides SeutuCD data. CORINE is a 25 × 25 m raster dataset that provides information on land cover. The data of CORINE 2012 has been produced as a part of the European Gioland 2012 project by Finnish Environment Institute.
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Commercial floor area ratio was calculated as the gross commercial floor area per commercial land use. The data was drawn from SeutuCD 2014 and the Corine 2012 land cover dataset.
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Land use mix: The land use mix measure considered four land use types: residential, commercial, traffic and green space land uses. Previous studies have also considered entertainment, office, and institutional land uses (Frank et al. 2005, 2010). In this study, we adopted above mentioned land-use categories for this measure for two reasons: the availability of the data sets and because they were determined to provide the best possible correspondence to the actual built environment in the study area. The land use mix measure was calculated as follows:where H is the land use mix score, pi is the proportion of land use i among all land-use classes, and n is the number of land-use types.$$H = - 1 \left( {\mathop \sum \limits_{i = 1}^{n} pi * \ln \left( {pi} \right)} \right) \text{ / }\ln \left( n \right)$$
Personal goals within the sample population
Personal goal | Proportion of variance explained (%) | Cronbach’s alpha | The measurement indicators | Factor loadings |
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1. Physical activity and sports | 33 | 0.725 | Everyday physical activities (e.g., walking, biking) | 0.834 |
Sports or dance hobby | 0.682 | |||
Maintaining health and functional capacity of the body | 0.501 | |||
2. Caring for others | 10 | 0.701 | Health and wellbeing of others | 0.794 |
Taking care of relatives | 0.696 | |||
Relationships | 0.503 | |||
3. Manage on one’s own | 10 | 0.577 | Independent living, the preservation of an independent lifestyle | 0.530 |
Managing own financial issues and/or assets | 0.505 | |||
Maintaining memory capacities | 0.486 | |||
4. Cultural and social affairs | 9 | 0.553 | Cultural activities | 0.627 |
Politics and social affairs | 0.444 | |||
Social activities (i.e., clubs, voluntary work) | 0.381 |
Mode choice modelling framework
Dependent variable |
Mode choice for shopping trips Nominal variable including Walk, Bike, Transit, and Car (base mode) alternatives |
Built environmental factors (see “Built environmental measures” section for details) |
Walkability index Continuous variable measured for three different spatial units of analysis Green space percentage continuous variable measured for three different spatial units of analysis |
Activity space measures |
Elongation Continuous variable measured for IREM and IHR spatial units of analysis Centricity Categorical variable including three categories: 1. Monocentric (base category), 2. Bicentric, 3. Polycentric |
Latent factors (see “Personal goals within the sample population” section for details) |
12 Measurement indicators for 4 personal goals Ordinal variables on a scale from 0 to 6 |
Travel factors |
Travel time of alternative X (hour) Continuous variable. Travel time was estimated for each alternative mode based on the average speed of that alternative in HMA on the shortest route from home to the reported shopping place. Shortest route was found using network analyst toolbox in ArcMap. The transportation mode indicated by the participant for visiting each shopping place was taken into consideration while choosing the shortest path. The average speeds for Walking (5 km/h), Biking (17 km/h), and Car (50 km/h) were obtained from Helsinki Region Transport office (HSL). The average speed for public transport (33.4 km/h) was adopted from Salonen and Toivonen (2013). An average waiting time of 9 min based on the same reference (Salonen and Toivonen 2013) was added to the travel time by public transport |
Travel cost of alternative X (EURO) Continuous variable. Travel cost was estimated for Car and transit modes. For Car, it was estimated based on the shortest distance from home to the reported shopping place, and the price of gasoline at the year survey was conducted in HMA. Unfortunately, information on transit pass ownership was not available in the dataset. Cost of transit was, therefore, supposed to be the same for all respondents and equal to the cost of a one-way transit ticket. |
Frequency of visit to the shopping place per month Continuous variable calculated based on reported frequency per week. |
Respondent socioeconomic factors |
Gender: categorical variable Dummy variable.1. Male (base), 2. Female |
Age: categorical variable Dummy variable. 1. Less than 65 (base), 2. 65–75 |
Housing type Categorical variable. 1. Apartment, 2. Detached/terraced house (base) |
Education Ordinal variable on a scale from 1 to 4 (basic education to graduate degree) |
Income Ordinal variable on a scale from 1 to 5 (less than 2000 to more than 8000 euro) |
Retired dummy variable 0. No, 1. Yes |
Household structure Categorical variable. 1. Single no children (Base), 2. Single with children, 3. Couple no children, 4. Couple with children, 5. Other |
Having pets Dummy variable. 0. No, 1. Yes |
Having grand children Dummy variable. 0. No, 1. Yes |
Exercise regularly Dummy variable. 0. No, 1. Yes |
Doing regular hobbies Dummy variable. 0. No, 1. Yes |
Stated overall health Ordinal variable on a scale from 1 to 5 |
Results and discussion
Variable | IREM | IHR | 500 m buffer | |||||||||||||||
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Transit | Bike | Walk | Transit | Bike | Walk | Transit | Bike | Walk | ||||||||||
Coef. | p value | Coef. | p value | Coef. | p value | Coef. | p value | Coef. | p value | Coef. | p value | Coef. | p value | Coef. | p value | Coef. | p value | |
Alternative specific constanta | 3.16 | 0.11 | − 6.96 | 0.01 | 2.76 | 0.04 | 2.54 | 0.18 | − 8.24 | 0.00 | 2.21 | 0.09 | 2.54 | 0.15 | − 7.76 | 0.02 | 1.54 | 0.07 |
Travel factors | ||||||||||||||||||
Travel time (hour) | − 7.29 | 0.02 | − 7.29 | 0.02 | − 7.29 | 0.02 | − 7.59 | 0.01 | − 7.59 | 0.01 | − 7.59 | 0.01 | − 7.50 | 0.01 | − 7.50 | 0.01 | − 7.50 | 0.01 |
Travel cost (euro) | − 0.82 | 0.07 | – | – | – | – | − 0.96 | 0.03 | – | – | – | – | − 0.94 | 0.02 | – | – | – | – |
Frequency of visit per month | – | – | – | – | 0.07 | 0.01 | – | – | – | – | 0.07 | 0.00 | – | – | – | – | 0.08 | 0.00 |
Socio-demographics | ||||||||||||||||||
Income | − 0.69 | 0.02 | – | – | − 0.61 | 0.01 | − 0.67 | 0.02 | – | – | − 0.69 | 0.00 | − 0.60 | 0.04 | – | – | − 0.63 | 0.01 |
Having a pet | – | – | – | – | 0.57 | 0.06 | – | – | – | – | 0.57 | 0.08 | – | – | – | – | 0.67 | 0.08 |
Living in an apartment | 1.80 | 0.00 | 1.80 | 0.00 | 1.80 | 0.00 | 1.98 | 0.00 | 1.98 | 0.00 | 1.98 | 0.00 | 2.09 | 0.00 | 2.09 | 0.00 | 2.09 | 0.00 |
Built environmental factors | ||||||||||||||||||
Green (%) | – | – | – | – | – | – | – | – | – | – | – | – | – | – | 0.04 | 0.03 | – | – |
Walkability Index | – | – | – | – | 0.18 | 0.03 | 0.15 | 0.01 | 0.13 | 0.08 | – | – | – | – | 0.18 | 0.10 | – | – |
Activity space measures | ||||||||||||||||||
Elongation of activity space | – | – | – | – | − 0.40 | 0.00 | – | – | – | – | – | – | – | – | – | – | – | – |
Polycentric activity space | 0.66 | 0.10 | – | – | – | – | 0.72 | 0.08 | – | – | – | – | – | – | – | – | – | – |
Personal goals | ||||||||||||||||||
Physical activity and sports | – | – | 1.43 | 0.03 | – | – | – | – | 1.23 | 0.06 | – | – | – | – | 1.16 | 0.09 | – | – |
Caring for others | − 0.52 | 0.09 | – | – | − 0.44 | 0.07 | − 0.52 | 0.10 | – | – | − 0.50 | 0.04 | − 0.62 | 0.10 | – | – | − 0.50 | 0.03 |
Cultural and social affairs | 2.93 | 0.02 | – | – | 1.92 | 0.02 | 2.80 | 0.02 | – | – | 2.03 | 0.02 | 1.96 | 0.01 | – | – | 1.19 | 0.04 |
Model statistics | ||||||||||||||||||
Sample size | 607 | 607 | 607 | |||||||||||||||
Initial log likelihood | − 4218.498 | − 4218.498 | − 4218.498 | |||||||||||||||
Final log likelihood | − 2476.258 | − 2483.476 | − 2488.913 | |||||||||||||||
Rho square | 0.413 | 0.412 | 0.410 | |||||||||||||||
Rho square bar | 0.408 | 0.407 | 0.405 |
Personal goal | Variables | IREM | IHR | 500 m Buffer | |||
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parameter estimate | p value | parameter estimate | p value | parameter estimate | p value | ||
Physical activity and sports | Education | − 0.21 | 0.09 | − 0.19 | 0.03 | − 0.22 | 0.01 |
Female | 0.35 | 0.01 | 0.41 | 0.01 | 0.38 | 0.01 | |
Income | 0.13 | 0.04 | 0.15 | 0.05 | 0.20 | 0.03 | |
Overall health | 0.34 | 0.07 | 0.34 | 0.01 | 0.36 | 0.01 | |
exercise regularly | 0.74 | 0.00 | 0.76 | 0.00 | 0.68 | 0.00 | |
Green (%) | 0.1 | 0.03 | 0.13 | 0.07 | – | – | |
Caring for others | Education | − 0.28 | 0.00 | − 0.28 | 0.00 | − 0.29 | 0.00 |
Female | 0.30 | 0.04 | 0.33 | 0.03 | 0.38 | 0.05 | |
Income | 0.15 | 0.05 | 0.16 | 0.06 | 0.16 | 0.04 | |
Having grandchildren | 0.65 | 0.00 | 0.65 | 0.00 | 0.58 | 0.00 | |
Retired | 0.22 | 0.08 | 0.20 | 0.08 | 0.26 | 0.08 | |
Hobby regularly | 0.31 | 0.07 | 0.29 | 0.08 | 0.35 | 0.02 | |
Couple with Children | 0.38 | 0.03 | 0.37 | 0.03 | 0.46 | 0.01 | |
Cultural and social affairs | Female | 0.73 | 0.00 | 0.71 | 0.00 | 0.75 | 0.00 |
Having pets | − 0.21 | 0.07 | − 0.21 | 0.09 | − 0.36 | 0.07 | |
Polycentric activity space | 0.06 | 0.09 | 0.06 | 0.09 | – | – |
Personal goal | Indicators | IREM | IHR | 500 m Buffer | |||
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parameter estimate | p value | parameter estimate | p value | parameter estimate | p value | ||
Physical activity and sports | Everyday physical activities (e.g., walking, biking) | 1a | – | 1 | – | 1 | – |
Sports or dance hobby | 1.32 | 0.00 | 1.41 | 0.00 | 1.41 | 0.00 | |
Maintaining health and functional capacity of the body | 0.485 | 0.00 | 0.532 | 0.00 | 0.517 | 0.00 | |
Caring for others | Health and wellbeing of others | 1 | – | 1 | – | 1 | – |
Taking care of relatives | 1.46 | 0.00 | 1.58 | 0.00 | 1.56 | 0.00 | |
Relationships | 0.757 | 0.00 | 0.788 | 0.00 | 0.789 | 0.00 | |
Cultural and social affairs | Cultural activities | 1 | – | 1 | – | 1 | – |
Politics and social affairs | 0.907 | 0.00 | 0.770 | 0.00 | 0.767 | 0.00 | |
Social activities (i.e., clubs, voluntary work) | 0.384 | 0.00 | 0.494 | 0.00 | 0.562 | 0.00 |