Commuting Connections: Carpooling and Cyberspace

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Presented by: Kalina Soltys, Ron Buliung and Catherine Habel
Presented at: ACT Canada 2008 TDM Summit, Halifax, October 2008

Published in: Automotive
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  • 49% (46%) of respondents have matched through the system; 28% (16%) have formed carpools and 24% (14%) are actually carpooling; and 38% (42%) are still waiting for matches.
  • Commuting Connections: Carpooling and Cyberspace

    1. 1. Commuting Connections: Carpooling and Cyberspace
    2. 2. <ul><li>Presented at the Association for Commuter Transportation </li></ul><ul><li>TDM Summit, Halifax, October 21, 2008 </li></ul><ul><li>by: </li></ul><ul><li>Catherine Habel </li></ul><ul><li>Program Coordinator, Smart Commute </li></ul><ul><li>Metrolinx </li></ul><ul><li>Co-authors: </li></ul><ul><li>Kalina Soltys </li></ul><ul><li>Master’s Candidate </li></ul><ul><li>University of Toronto at Mississauga </li></ul><ul><li>Ron Buliung </li></ul><ul><li>Professor, Department of Geography </li></ul><ul><li>University of Toronto at Mississauga </li></ul>
    3. 3. Outline <ul><li>Background </li></ul><ul><li>Research Partnership </li></ul><ul><li>Research Objectives </li></ul><ul><li>Literature Review </li></ul><ul><li>Methodology </li></ul><ul><li>Findings </li></ul><ul><li>Conclusions </li></ul>
    4. 4. Background – Smart Commute
    5. 5. Background – Carpool Zone <ul><li>Online ridematching service </li></ul><ul><li>Administered and paid for by Metrolinx </li></ul><ul><li>Open and free of charge to the public </li></ul><ul><li>Promoted by ten TMAs at GTHA employers </li></ul>
    6. 7. Research Partnership <ul><li>University of Toronto at Mississauga (UTM) Department of Geography </li></ul><ul><li>Since 2006 with Smart Commute Association, Smart Commute Mississauga and Peel Region </li></ul><ul><li>2008 data-sharing agreement between Metrolinx & UTM </li></ul><ul><li>Centre for excellence – commuting research in Canada </li></ul>
    7. 8. Research Partnership (cont.) <ul><li>Resources </li></ul><ul><ul><li>in-kind time </li></ul></ul><ul><ul><li>Assistant Professor, UTM </li></ul></ul><ul><ul><ul><li>Directing research </li></ul></ul></ul><ul><ul><ul><li>Coordinating funding proposals </li></ul></ul></ul><ul><ul><li>Undergraduate/graduate student, UTM </li></ul></ul><ul><ul><li>Program Coordinator, Smart Commute </li></ul></ul><ul><ul><ul><li>Conducting CPZ satisfaction survey </li></ul></ul></ul><ul><ul><ul><li>Compiling database </li></ul></ul></ul><ul><ul><ul><li>Reviewing draft reports </li></ul></ul></ul><ul><ul><li>Data extraction capabilities, Pathway Intelligence </li></ul></ul>
    8. 9. Research Partnership (cont.) <ul><li>Benefits: </li></ul><ul><ul><li>Building capacity for TDM </li></ul></ul><ul><ul><li>Practical application for student research </li></ul></ul><ul><ul><li>In-depth analysis of data set </li></ul></ul><ul><ul><li>New knowledge of carpool behaviour </li></ul></ul><ul><ul><li>Canadian example </li></ul></ul><ul><ul><li>Policy direction </li></ul></ul><ul><ul><li>Smart Commute profiled during Geography Week </li></ul></ul><ul><ul><li>Guest lecture at UTM </li></ul></ul>
    9. 10. Research Objectives <ul><li>Model determinants in forming a successful carpool </li></ul><ul><li>Explore gender differences in carpooling attitudes and behaviours </li></ul><ul><li>Evaluate the performance of Carpool Zone and provide recommendations for the refinement and extension of the program </li></ul><ul><li>Inform Smart Commute policies and programming </li></ul>
    10. 11. Research Objectives (cont.) <ul><li>How do socio-demographic, economic, attitudinal, and spatial factors influence carpool formation and use? </li></ul><ul><li>How can we leverage the power and flexibility of other systems (e.g., Internet) to do a better job in the task of moving people? </li></ul>
    11. 12. Literature Review <ul><li>Existing thoughts about differences in levels of mobility and commuting patterns </li></ul><ul><li>Literature on gender and travel behaviour </li></ul><ul><li>Literature on the use of ICT to improve urban mobility </li></ul>
    12. 13. Methodology – Survey <ul><li>Yearly survey a component of SC monitoring and evaluation framework, fall 2007 </li></ul><ul><li>Individualized link e-mailed to all registered users </li></ul><ul><li>Incentive provided – draw for iPod Touch </li></ul><ul><li>Reminder (319 additional responses) </li></ul><ul><li>Responses associated with profile information </li></ul><ul><li>Excel database extracted, identifiers removed, data provided to UTM </li></ul><ul><li>Follow up questions and clarifications </li></ul>
    13. 14. Methodology – Questionnaire <ul><li>22 questions, multiple choice or one answer </li></ul><ul><li>Reasons for interest in carpooling </li></ul><ul><li>Usage level (carpooling, waiting for better matches, etc.) </li></ul><ul><li>Ratings of Carpool Zone features and services </li></ul><ul><li>Ease of use and extent of feature usage </li></ul><ul><li>Communication between users </li></ul><ul><li>Follow up (testimonials and further input) </li></ul><ul><li>Recommendation </li></ul><ul><li>Open comment field </li></ul>
    14. 15. Methodology – Profile Information <ul><li>Home postal code </li></ul><ul><li>Gender </li></ul><ul><li>Age </li></ul><ul><li>Household car ownership </li></ul><ul><li>Commute mode </li></ul><ul><li>Length of trip (time) </li></ul><ul><li>Language </li></ul><ul><li>Community characteristic urban/suburban and median income by FSA (inferred) </li></ul>
    15. 16. Methodology – UTM Modelling <ul><li>Exploratory/descriptive analysis of motivations, current commuting behaviour, and performance. </li></ul><ul><li>Logistic regression analysis of the likelihood of successfully forming and using a Carpool Zone- enabled carpool. </li></ul>
    16. 17. Methodology – Challenges <ul><li>Researchers would have preferred more demographic information e.g.: </li></ul><ul><ul><li>Education level, individual and household income, occupation </li></ul></ul><ul><ul><li>SC does not ask these questions for privacy reasons </li></ul></ul><ul><li>Destination information </li></ul><ul><ul><li>Weren’t able to provide this with the first data set, however, trip information has since been extracted and provided to UTM – findings should be available by the end of this year </li></ul></ul>
    17. 18. Findings – Descriptive Analysis <ul><li>1,425 respondents (25% response rate) </li></ul><ul><li>89% of respondents are satisfied with the service overall </li></ul><ul><li>Of those who formed carpools through the system, 84% were satisfied with the quality of the carpools. </li></ul><ul><li>87% of respondents would definitely or likely recommend Carpool Zone to their friends and colleagues. </li></ul>
    18. 19. Findings – Descriptive Analysis Gender Distribution of Survey Respondents
    19. 20. Findings – Descriptive Analysis Age Distribution of Survey Respondents
    20. 21. Findings – Descriptive Analysis U = 122,657.00, p > 0.10
    21. 22. Findings – Descriptive Analysis x 2 = 22.316, p < 0.001
    22. 23. Findings – Descriptive Analysis x 2 = 39.243, p < 0.001
    23. 24. Findings – Descriptive Analysis 24% have started carpooling Legend: JR-just registered WM-waiting for match WBM-waiting for better match WR-waiting on response FWOS-formed without starting FS-formed and started DO-dropped out OTH-other
    24. 26. Findings – Predictive Model <ul><li>Regression analysis - independent variables: </li></ul><ul><ul><li>Demographics </li></ul></ul><ul><ul><li>Spatial </li></ul></ul><ul><ul><li>Motivations </li></ul></ul><ul><ul><li>Current commute mode </li></ul></ul>
    25. 27. Findings – Demographic <ul><li>More females (13%) in carpools than males (11%) </li></ul><ul><li>Gender has greatest explanatory effect: </li></ul><ul><ul><li>female respondents are 1.3 times more likely to be carpooling </li></ul></ul><ul><li>Age and inferred median income insignificant </li></ul><ul><li>Demographic information “parsimonious”, further research required </li></ul>
    26. 28. Findings – Spatial <ul><li>Matching potential close to home (significant within 1 km buffer zone) </li></ul><ul><li>Addition of one match within 1 km of residence increases the odds of forming a carpool by 4-21% </li></ul><ul><li>Increase of matches within broader market (> 3 km) doesn’t appear to increase rate of carpooling </li></ul><ul><li>Distance from carpool lot, urban v. suburban and place of residence don’t appear to be significant </li></ul><ul><li>More research being conducted to include trip-end variables into analysis </li></ul>
    27. 29. Findings – Motivations <ul><li>Environment and cost had similar effects but weren’t considered significant </li></ul><ul><li>Desire to use an HOV lane was the only significant motivational factor that explained carpool formation and use </li></ul><ul><ul><li>associated with saving time </li></ul></ul><ul><ul><li>almost two times more likely to form a carpool than concern for the environment </li></ul></ul>
    28. 30. Findings – Current Commute Mode <ul><li>Transit commuters 40% less likely to form a carpool than SOV commuters </li></ul><ul><li>Passengers 1.8 times more likely to form a carpool than SOV commuters </li></ul><ul><li>Insufficient evidence with respect to active commuters </li></ul>
    29. 31. Conclusions <ul><li>Utility in considering residential-based marketing </li></ul><ul><li>Urban density (home) = more carpools </li></ul><ul><li>Accessibility to potential matches near the home is associated with carpool formation </li></ul><ul><li>Potentially important role of HOV lanes (even more than carpool lots) </li></ul>
    30. 32. Conclusions (cont.) <ul><li>Making connections…: </li></ul><ul><ul><li>with academic institutions and researchers keen to contribute knowledge to our field </li></ul></ul><ul><ul><li>with the next generation of TDM practitioners </li></ul></ul><ul><ul><li>by looking at the Canadian context </li></ul></ul><ul><ul><li>between the various factors that influence commuter behaviour </li></ul></ul>
    31. 33. Thank You Catherine Habel Smart Commute, Metrolinx catherine@smartcommute.ca, (416) 874-5934

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