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WebWalk: walking behavior on campus

This research project investigates the relationship between path characteristics and route selection on corporate campuses, focusing on factors like pleasure, comfort, and safety. Conducted by a team from the Georgia Institute of Technology, the project aims to develop tools for conducting environmental audits, refine survey and focus group guides, and enhance our understanding of how the built environment influences pedestrian behavior. The ultimate goal is to promote healthier walking habits on campus through data-driven insights.

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WebWalk: walking behavior on campus

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  1. WebWalk:walking behavior on campus Craig Zimring, Ph.D. Georgia Institute of Technology, College of Architecture September 5, 2007 Status Update craig.zimring@coa.gatech.edu

  2. Research Purpose • How are path characteristics related to route selection on corporate campuses? • Develop tools… • Environmental Audit • Software/Database • Survey/Focus Group Guide • Develop initial understanding based on… • Pleasure • Comfort • Safety

  3. Project Staff • Research Team: • Craig M Zimring, Ph.D. • Julie Gazmararian, MPH, Ph.D. • Mahbub Rashid, Ph.D., AIA • Phillip B.Sparling, Ed.D., FACSM • Sheila Bosch, Ph.D. • Michael Herndon, M.S. • Sharon Tsepas, M. Arch • Lu Yi, M. Arch • Advisory Committee: • Jeffrey Koplan, M.D., MPH • Kenneth E. Powell, M.D. • Philippe C. Dordai, AIA

  4. Literature Review • Environmental factors can influence path choice • Path characteristics may induce people to walk further than they would otherwise • Hoogendoorn SP, Bovy 2002 • Joseph A, Zimring C, 2007 • Zimring, C et al, 2005

  5. 2 3 1 Environmental Audit: Introduction • Describes physical attributes of path segments: • Safety • Comfort • Pleasurably

  6. Environmental Audit: Genesis • Irvine-Minnesota Inventory (Boarnet, et al., 2006; Day, et al., 2005; Day, et al., 2006) • SPACES Tool (Systematic Pedestrian and Cycling Environmental Scan): University of Western Australia • Path Environment Audit Tool (Troped, et al., 2006)

  7. Environmental Audit: Introduction • Examples: • Path Material • Path Width • Presence of Benches, etc. • Presence of Food/Coffee Shops • Quality/Type of Landscape • Building Maintenance • Surveillance from Buildings • Presence of Litter • Presence of Fountains/Bridges • Presence of Shading

  8. Environmental Audit: Interrater Reliability • Interrater reliability vital • Process • Paths had wide array of characteristics • A lack of applicable standards • Measurement • Cohen’s Kappa (Cohen, 1960; Troped, et al., 2006; McGinn, et al. 2004) • K > .60 • Percent Agreement (Boarnet, et al., 2006) • P > 80% Agreement

  9. Audit Tool: Inter-rater Reliability • Version One – developed at Georgia Tech, informed by visits to other sites. • Originally Low • Examined data entry • Refined audit form • Revisited segments • Rated photographs (Picasaweb) • Revised questions • Revisited GA Tech campus • Reviewed 30 segments at Bellsouth (Atlanta, GA) • Planned trip to Kimberly-Clark campus (Roswell, GA)

  10. Environmental Audit: Tool • 28 Questions • multiple subparts • Designed to be used on every segment on site • Future versions may use hand-held electronic form • reduce data entry time • reduce possible errors

  11. Environmental Audit: Training Protocol • 52-slide PowerPoint presentation • Includes quizzes • 14-page long form (Day, et al. 2005) • Supervised rating period

  12. WebWalk Software: Introduction • PURPOSE OF THIS SOFTWARE • Based on Scalable Vector Graphics and JavaScript SVG JavaScript

  13. WebWalk Software • Initial Login • One time survey • Subsequent Logins • Path selection • Every-time survey

  14. One Time Survey • Based on IPAQ: • Physical activity • Also asks about: • Beliefs about physical activity • Demographics • Job Classification • Length of Time at Company/Campus

  15. WebWalk Software

  16. Every Time Survey • Date and Time • Intensity • Purpose of Trip • work-related • personal • combination

  17. WebWalk Software • Web-based Application • Scalable Vector Graphics (SVG) • JavaScript/PHP • Internet Explorer • MySQL Server

  18. Develop .SVG Map from Plans • Created with GIS Software • Best done from CAD plans • Can be done from overhead imagery • On-campus visit highly recommended

  19. Data Analysis • Segment Scores • Pleasure • Comfort • Safety • Both Local and Relational Scores • Correlate Scores with Route Choice

  20. Building A Building B Data Analysis: Assumptions

  21. Building A Building B Data Analysis: Assumptions No Possible Conclusion

  22. Building A Building B Data Analysis: Assumptions Possible Conclusion

  23. Data Analysis: Assumptions • “Shortest” route • Metric Shortest Distance • Lowest angular turns • Most Integrated Paths (Space Syntax) • “Shortest” route may be 1 to 3 routes • Analysis will only examine environmental characteristic causality when routes chosen are not the “shortest.”

  24. Data Analysis • Primary Analysis • Route Choice Based on: • Safety • Comfort • Pleasureability • Secondary Analysis • Route choice preferences based on demographic/job type • Differences in route choice based on time • avoiding non-shaded paths during mid-day • avoiding less safe paths early and late in day • Route choice based on different types of buildings • More leisurely routes from/to cafeteria, gym • Create weighted or modified route scores

  25. Georgia Institute of Technology • Georgia Tech • Atlanta, GA • Full time faculty, staff, graduate students • Over 30 buildings • Over 500 path segments • Final usability test in progress

  26. United Parcel Service • UPS World Headquarters • Atlanta, GA • Environmental Audit late September ‘07

  27. Sprint/Nextel Corporation • Sprint National Headquarters • Overland Park, KS • Environmental Audit late September ‘07

  28. Hypotheses/Questions • Relatively homogenous physical characteristics will play little role in route choice on Work-related trips once certain threshold levels have been reached. • Route choice on trips taken for Personal or Combination reasons will show more evidence of being influenced by path characteristics. • The presence of amenities, high quality landscaping, and other “pleasureable” factors will be highly correlated with the shortest paths between buildings; this correlation can be explained by the ability of planners and/or designers to anticipate the use of various paths.

  29. Conclusion Thank you… • Craig Zimring Georgia Tech College of Architecture • craig.zimring@coa.gatech.edu 404.894.3915

  30. References • Boarnet MG, Day K, Alfonzo M, Forsyth A, Oakes M. The Irvine-Minnesota Inventory to Measure Built Environments Reliability Tests Am J Prev Med 2006;30(2):153-159. • Cohen J. A Coefficient of Agreement for Nominal Scales, Env and Psych Meas, 1960;20(1):37-46. • Day K, Boarnet M, Alfonzo M. Irvine Minnesota Inventory for Observation of Physical Environment Features Linked to Physical Activity. Codebook. 2005. • Day K, Boarnet M, Alfonzo M, Forsyth A. The Irvine-Minnesota Inventory to Measure Built Environments Development. Am J Prev Med 2006;30(2):144-152. • Hoogendoorn SP, Bovy PHL. Pedestrian route-choice and activity scheduling theory and models. Transportation Research B 2002 • Joseph A, Zimring C. Where Active Older Adults Walk. Environment and Behavior 2007;39(1):75-105. • McGinn T, Wyer PC, Newman TB, Keitz S, Leipzig R, Guyatt G. Tips for learners of evidence-based medicine: 3. Measures of observer variability (kappa statistic). CMAJ, 2004;171(11):1369-1373. • Pikora T. Systematic Pedestrian and Cycling Environmental Scan (SPACES), Survey of the Physical Environment in Local Neighborhoods: Observer's Manual. Nedlands, Western Australia: University of Western Australia; 2002. • Troped PJ, Cromley EK, Fragala MS, Melly SJ, Hasbrouck HH, Gortmaker SL, Brownson RC. Development and Validity Testing of an Audit Tool for Trail/Path Characteristics: The Path Environment Audit Tool (PEAT). J of Phys Act and Health 2006;Sup1:S158-S175. • Zimring C, Joseph A, Nicoll GL, Tsepas S. Influences of building design and site design on physical activity: Research and intervention opportunities. Am J Prev Med 2005;28(2, Supplement 2), 186-193.

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