NICE RIDE MINNESOTA PROGRAM EVALUATION
Minneapolis-St. Paul Bike Share System
Prepared by:
Jessica Schoner1 Greg Lindsey2 David Levinson1
1Department of Civil, Environmental, and Geo- Engineering 2Humphrey School of Public Affairs University of Minnesota
Submitted to: CENTERFOR PREVENTION AT BLUE CROSSAND BLUE SHIELDOF MINNESOTA NICE RIDE MINNESOTA
May 2015
Contents
1 Introduction1 1.1 Minneapolis-St. Paul Bike Share System Study Objectives...... 1 1.2 Study Purpose and Goals...... 1 1.3 Structure of Report...... 1
2 Approach and Methods3 2.1 Analysis of Nice Ride electronic trip and member records...... 3 2.2 Survey of Nice Ride members...... 3 2.3 Secondary analyses of related databases (Census, TBI, etc.)...... 4
3 Effects on individual physical activity7
4 Effects on rates of cycling within general population 11 4.1 Spillover effects on non-member cycling...... 11 4.2 Diffusion effects on expanding membership...... 14
5 Effects on broader culture of active living 17
Appendices
A IRB A-1
B Minneapolis Survey Instrument B-1 B.1 Survey...... B-1 B.2 Recruiting email...... B-24
C Minneapolis Survey Data Report C-1
D Preliminary Minneapolis Survey Findings D-1 E Bike Walk Twin Cities 2013 Count Report E-1
F Minneapolis Supplemental Models F-1 F.1 Supplemental Innovation Diffusion/Membership Descriptive Statistics...... F-1 F.2 Supplemental Innovation Diffusion/Membership Models...... F-3
ii List of Figures
2.1 Geocoded Nice Ride Subscriber Addresses...... 4
3.1 Self-reported changes in exercising, bicycling, walking, and noticing other cyclists relative to before joining Nice Ride...... 8 3.2 Percent of bicycle trips made by Nice Ride (versus personal bicycle) in a typical month with good weather...... 9 3.3 Percent of respondents who have used Nice Ride for different trip purposes....9
5.1 Perceptions of Nice Ride having made bicycling more popular in Minneapolis... 17 5.2 Average reported bicyclist and driver comfort level by infrastructure type..... 18 5.3 Average reported bicyclist and driver comfort level by infrastructure type and per- cent of bike trips made by Nice Ride...... 19 iv List of Tables
2.1 Summary of Minneapolis Evaluation Data Sources...... 5
4.1 Descriptive Statistics for General Population Model Variables...... 12 4.2 Regression of tbot...... 13 4.3 Descriptive Statistics for Innovation Diffusion Model Variables...... 15 4.4 OLS Regression Model of Membership Growth - Pooled...... 16 4.5 Effects of Pooled Model 2 Independent Variables on New Membership...... 16
F.1 Descriptive Statistics for Innovation Diffusion Model Variables - By Year..... F-1 F.2 Descriptive Statistics for Innovation Diffusion Model Variables - Pooled Model.. F-2 F.3 OLS Regression Model of Membership Growth - By Year...... F-3 F.4 OLS Regression Model of Membership Growth - Pooled...... F-4 vi Chapter 1
Introduction
1.1 Minneapolis-St. Paul Bike Share System Study Objectives
The Nice Ride Minnesota bike share system in Minneapolis and St. Paul has completed five seasons of operation. Ridership has increased steadily from the first season (about 100,000 trips) through 2013 (over 300,000 trips). What effects have implementing and expanding the system had on total physical activity levels of people who use Nice Ride? Have rates of all types of bicycling and the broader culture of active living changed in response to Nice Ride’s highly visible presence? This study aims to evaluate the effects of Nice Ride in the Minneapolis–St. Paul Metropolitan Area (Twin Cities) on both its own user base and the community at large.
1.2 Study Purpose and Goals
Three key questions have been identified for the Minneapolis evaluation.
1. What are the effects of the Nice Ride bike share system on individual physical activity?
2. What are the effects of the Nice Ride bike share system on rates of cycling within the general population?
3. What are the effects of the Nice Ride bike share system on the broader culture of active living?
1.3 Structure of Report
The report is structured as follows. Chapter2 describes the approach, methods, and data sources used in the evaluation. Chapters3,4, and5 describe the results, corresponding to each of the three principal goals identified in Section 1.2.
1 2 Chapter 2
Approach and Methods
2.1 Analysis of Nice Ride electronic trip and member records
Nice Ride Minnesota provided a database of subscribers and trips taken on the Nice Ride bike share system. The origin station, destination station, start time, end time, and subscriber ID are electron- ically recorded for every trip. The subscriber database contains the date joined, age, geographic location, gender, and subscription type. Figure 2.1 shows the geocoded approximate locations of Nice Ride’s past and present subscribers. These data were analyzed from a “diffusion of innovation” framework using a lagged variable model of membership growth within a census block group as a function of past membership levels in the block group and network growth (new stations) in the block group, along with an indicator of the year or overall system growth.
2.2 Survey of Nice Ride members
A survey instrument was developed based on past Nice Ride surveys and current evaluation and re- search needs. It received a Category 2 exemption from the Institutional Research Board (IRB) (Ap- pendixA). The instrument contained questions about the respondents use of Nice Ride, perceptions of family and acquaintance use of bicycling and Nice Ride, self-reported travel diary sample, and other attitude and socio-economic questions. The full instrument is available in Appendix B.1. Nice Ride Minnesota sent a customized URL via email to their mailing list of current and former subscribers on Tuesday, November 4th, 2014. The URL linked responses to the electronic trip records for each subscriber. As an incentive for completing the survey, respondents were eligible to enter a drawing for one of ten $50 gift card prizes. A copy of the email used to administer the survey is available in Appendix B.2. 1024 subscribers participated in the survey. The travel diary portion at the end of the survey was very long, so only 580 (57%) respondents “completed” the survey including this portion.
3 Figure 2.1: Geocoded Nice Ride Subscriber Addresses
However, response rates on the main (non-diary) portion of the survey are better, with 67% of respondents completing at least 80% of the questions. Response rates for individual questions vary, with over 80% of questions having at least 768 (75%) responses. Over half the sample (56%) recorded at least two trips in the travel diary. 74% of respondents took the survey on the day it was administered, and 95% took it within the first week. The preliminary survey findings presented in the November meeting are available in Ap- pendixD. A summary report generated by the online survey package for all the non-diary, non-text survey responses is included in AppendixC.
2.3 Secondary analyses of related databases (Census, TBI, etc.)
Data about bicycling and bike share use in Minneapolis and Saint Paul were collected from sev- eral sources, summarized in Table 2.1. The US Census and American Community Survey (ACS) provide the most consistent measures of rates of bicycle commuting across geographies within the
4 Table 2.1: Summary of Minneapolis Evaluation Data Sources
Source Year(s) Units Measurement Nice Ride MN 2010 - 2013 Trip Origin, destination, start/end times, subscriber ID Subscriber Trips, billing address, membership status, age, gender UMN Evaluation 2014 Nice Ride subscriber Survey Responses NR & UMN 2012 Subscriber Member survey responses linked to ID US Census 2000, SF3 Census P030: Means of transportation to tract work for workers 16 years and over ACS 2006 - 2012, 1yr Census B08301: Means of transportation 2007 - 2012, 3yr∗ tract to work 2009 - 2012, 5yr∗ ∗Multi-year estimates end in the year specified. E.g., 2009 5-year estimates span 2005-2009. BWTC 2007-2013 Location Bike/ped counts with Nice Ride bike tally Met Council 2011 Household TBI Survey Responses (for control) & UMN
United States over time. The Census Bureau commuting question only asks about a single mode used most frequently over the previous week, so it undercounts part-time bicyclists. ACS estimates are administered on a rolling basis for 1-, 3-, and 5-year periods. The 2000 census was adminis- tered on April 1st, so comparisons between the 2000 census and ACS should be made cautiously. US Census and ACS data are available at the block group or census tract level, depending on the measure. For finer levels of aggregation, only 5-year estimates are available. Previous survey and count results are available from University of Minnesota (UMN), Bike Walk Twin Cities (BWTC), and the Metropolitan Council. BWTC bike count data include a tally of Nice Ride bikes observed in addition to the total number of bicyclists observed. The Metropolitan Council administers a travel behavior inventory (TBI) every decade, which includes travel diaries for all members of households that participate. Data from the 2011 TBI were provided by the Metropolitan Council to explore effects of Nice Ride on cycling among non-Nice Ride subscribers (general population). Each household record contains the number of trips made by all members of the household, the number of bicycle trips, sociodemographic characteristics, and a set of spatial measures around the household (e.g., population density and availability of bicycle infrastructure near the home).
5 General Population Bicycling Model explores household participation in and frequency of bi- cycling, as a function of proximity to Nice Ride infrastructure and activity. It uses data from the TBI as dependent variable. Households near Nice Ride stations, particularly Nice Ride stations with high levels of use, are hypothesized to have both higher rates of participation in cycling (de- fined as any household member making at least one trip by bicycle) and frequency of bicycle trips than households not near Nice Ride stations.
6 Chapter 3
Effects on individual physical activity
About half of all respondents (49.9%) characterize their frequency of using Nice Ride as “Once a week” or greater. Nice Ride subscribers self-reported having increased their levels of bicycling and physical activity in general since starting to use Nice Ride. Figure 3.1 shows that over 40%1 of 2 respondents feel they get more exercise than before joining Nice Ride, and a full /3 of the sample bicycles more often. Most respondents (59%) indicated that they walk about the same amount as before, and only 18% felt that they walk less now, so Nice Ride does not appear to be replacing or squeezing out other healthy activities. Additionally, 44% of the sample reported a decrease in how much they drive. In a typical month with good weather, the average self-reported share of bicycle trips that are made using Nice Ride (versus a personal bicycle) is 59.2% (SD 39.7%), but this measure masks more nuanced trends. The distribution of cycling trips between Nice Ride and personal bicycles appears to be bimodal (Figure 3.2), with 60% of the sample using one or the other almost exclusively. 31% of respondents use Nice Ride exclusively, and another 4% almost exclusively (90- 99% of trips). 25% of respondents primarily use a personal bicycle, with Nice Ride comprising 10% or less of their bicycle trips. For the remaining 40% of respondents, Nice Ride and traditional cycling appear to be complements. 15% and 17% use either Nice Ride or a personal bicycle (respectively) for 11-40% of their bike trips, and 8% use the two modes about equally (40-60% Nice Ride). A similar question about Nice Ride versus personal bicycles asked about behavior over the past 7 days (also shown in Figure 3.2). However, due to the timing of the survey, only about 9% of respondents had actually bicycled within the past 7 days. Among this sub-sample, given weather conditions and the Nice Ride season end the day prior to survey distribution, the average percent of Nice Ride bike trips was lower (44.0%, SD 30.5%), and fewer respondents (8%) used Nice Ride for at least 90% of their bike trips.
1Unless otherwise specified, percentages are based on responses to an individual question. E.g., 1,002 people responded to the question about overall frequency of using Nice Ride, and 500 of them (49.9%) reported values of 1-4 (“Daily” through “Once a week”). The number of responses for each question are included in AppendixC.
7 Figure 3.1: Self-reported changes in exercising, bicycling, walking, and noticing other cyclists relative to before joining Nice Ride
Respondents use Nice Ride for a variety of trip purposes (Figure 3.3). Over 60% of respondents have used Nice Ride to go to a restaurant (64%), for personal errands (60%), or to go for a bike ride with no particular destination (60%). More than half the sample also reported having used Nice Ride for entertainment, including bars, night clubs, spectator sports, theater, etc., and to go to work. Two categories explicitly ask about trips for which the purpose is physical activity: “To go for a bike ride (e.g., no particular destination)” and “Recreation (e.g., gym, park, to play a sport)”. Combined, 35% of respondents have used Nice Ride for both activities (not shown), and 74% of respondents have used Nice Ride for at least one of these physical activity purposes (Figure 3.3).
8 Figure 3.2: Percent of bicycle trips made by Nice Ride (versus personal bicycle) in a typical month with good weather
Figure 3.3: Percent of respondents who have used Nice Ride for different trip purposes
9 10 Chapter 4
Effects on rates of cycling within general population
This research objective was approached from two perspectives: spillover effects of Nice Ride’s presence on general population cycling, and effects of Nice Ride on recruiting new Nice Ride members.
4.1 Spillover effects on non-member cycling
Statistical models of household propensity to bicycle are used to look for evidence about whether Nice Ride is associated with spillover effects on traditional bicycling. Three model approaches are used: (1) binary logistic regression to model household participation in bicycling, (2) negative binomial regression to model frequency of bicycle trips at the household level, and (3a & 3b) zero-inflated negative binomial regression to jointly estimate participation and frequency. The research team selected the number of Nice Ride trips starting or ending within 400m as the key variable of interest. We hypothesized that Nice Ride’s visibility is the causal mechanism behind a potential spillover effect. Trip activity at a station implies both visibility of the station itself and visibility of bicyclists using Nice Ride on the streets around the station, whereas a simple measure of stations near the household is an incomplete measure of visibility. Due to multicollinearity between Nice Ride measures, it was inappropriate to use multiple Nice Ride station and trip activity measures in the same model. Table 4.2 shows the results of a model of household bicycling as a function of nearby Nice Ride bike share infrastructure and activity. The binary logistic regression of participation in cycling has the highest Pseudo-R2, at 0.0810. Although McFadden Pseudo-R2 does not have the same interpretation as R2 in linear regression, this still indicates that bicycling is not well explained by this set of variables. The α parameter is
significant in Models 2, 3a, and 3b, suggesting that the dependent variable hrb is over-dispersed
11 Table 4.1: Descriptive Statistics for General Population Model Variables
Variable N Mean SD Min Max Dependent Variables h 1 Binary: Household participation in cycling 1,941 0.12 0.33 0.00 1.00 b0 hrb Number of household bike trips 1,941 0.40 1.34 0.00 12.00 Nice Ride Variable
1 sod Number of Nice Ride trips within 400m (1,000’s) 1,941 0.86 2.46 0.00 15.34 Other Built Environment Variables ek Population density within 400m (people per acre) 1,941 14.31 7.80 0.58 49.32 el Km of bike lanes within 400m 1,941 0.20 0.46 0.00 2.88 ep Km of bike trails within 400m 1,941 0.11 0.23 0.00 1.82 Other Household Variables
2 hr Number of trips by any mode 1,941 7.81 5.36 1.00 37.00 hw Number of workers 1,941 1.04 0.81 0.00 4.00 h 1 Binary: Student(s) 1,941 0.22 0.42 0.00 1.00 u0 h 1 Binary: Child(ren) under 6 1,941 0.08 0.28 0.00 1.00 c0 1 2010 Nice Ride system data 2 Sample restricted to Minneapolis households that made at least one trip
12 Table 4.2: Regression of tbot
Binary Logit Negative binomial Zero-inflated Negative Binomial Model 1 Model 2 Model 3a Model 3b Coef SE Coef SE Coef SE Coef SE
Participation sod -0.045 0.041 -0.051 0.042 ∗∗∗ ∗∗∗ ek 0.047 0.010 0.045 0.010 ∗∗∗ ∗∗∗ hr 0.076 0.014 0.067 0.015 ∗∗∗ ∗∗∗ hw 0.392 0.098 0.453 0.104 ∗ h 1 0.313 0.175 0.282 0.182 u0 h 1 0.006 0.233 0.063 0.248 c0 el -0.180 0.197 -0.185 0.205 ∗∗ ∗∗ ep 0.606 0.302 0.741 0.332 13 Constant -3.897∗∗∗ 0.244 -1.734∗∗∗ 0.093 -3.714∗∗∗ 0.256
Frequency sod -0.026 0.040 0.015 0.028 0.022 0.025 ∗∗∗ ∗∗ ek 0.050 0.012 0.020 0.008 0.010 0.007 ∗∗∗ ∗∗∗ ∗∗∗ hr 0.123 0.021 0.053 0.011 0.044 0.010 ∗ ∗∗ hw 0.227 0.123 -0.076 0.082 -0.183 0.075 h 1 0.334 0.218 0.171 0.123 0.134 0.117 u0 h 1 -0.222 0.318 -0.165 0.166 -0.192 0.162 c0 el -0.104 0.236 0.014 0.157 0.007 0.146 ep 0.277 0.394 -0.213 0.239 -0.351 0.237 Constant -3.206∗∗∗ 0.293 0.156 0.263 0.657∗∗∗ 0.188 LN(α) 2.369∗∗∗ 0.096 -1.392∗∗∗ 0.343 -1.754∗∗∗ 0.328 McFadden Pseudo-R2 0.0810 0.0353 0.0220 0.0650 ∗∗∗p < 0.01 ∗∗p < 0.05 ∗p < 0.1 and negative binomial regression is appropriate (shown in Table 4.2). Additionally, a Vuong test comparing the zero-inflated models to standard negative binomial regression is significant at the p¡0.01 level (not shown). The variable of interest, the number of Nice Ride trips starting and ending near a household
(sod), is not significant in any of the models. This analysis does not find evidence of a spillover effect of Nice Ride on household participation in and frequency of bicycling. Additional models using the number of stations within 400 meters instead of trip activity were also insignificant. Several other variables were significant in the models, however. Population density was pos- itive and significant in all four models (participation equation only in 3b). Bike paths or trails within 400 meters of home was positively associated with participation in cycling (Models 1 and 3b). Additionally, the household structure (number of workers, the presence of students, and over- all number of trips made) were associated with participation and frequency.
4.2 Diffusion effects on expanding membership
Table 4.3 summarizes the variables used to model Nice Ride membership growth. The dependent variable is the net change in membership in a census block group from the
previous year to the current year, per 1,000 residents (∆mt0→t1,i). The explanatory variables are the base membership in the previous year per 1,000 residents (mt0,i), the change in number of 2 stations within the block group from the previous year to current year per km (∆st0→t1,i), and an indicator of the year or overall system growth. The first model in Table 4.4 uses binary variables to indicate 2012 and 2013 cases, with 2011
as the base year (t1). The second uses a system growth variable to differentiate between years
(∆St0→t1,I ). This variable is the measure of new stations added to the system in that year. For example, there were 65 stations in 2010, and 116 stations in 2011, so the system growth variable for 2011 is 116 − 65 = 51. Table4.4 show the results of a set of membership growth regression models with data pooled across the 2011, 2012, and 2013 seasons. AppendixF contains an alternate analysis with separate regressions by season. The R2 for both models are approximately 0.07, meaning that 7% of the change in block group Nice Ride membership per 1,000 residents can be explained by system growth (new stations) and membership growth nearby. All variables in both models are significant. The coefficients for subscribers and increase in stations are nearly identical between the two pooled models. Table 4.5 shows the elasticities of each variable with other variables held at their means for Pooled Model 2. A 1% increase in the base year’s members per 1,000 residents is associated with 0.1 additional new members in the following season, suggesting a modest spillover effect of membership on future membership. The elasticities show that the systemwide growth variable has largest effect on
14 Table 4.3: Descriptive Statistics for Innovation Diffusion Model Variables
Variable N Mean SD Min Max Main Explanatory Variables
∆mt0→t1,i Net subscribers per 1,000 residents 4,119 0.558 2.974 -30.362 62.201 from t0 to t1 for block group i
mt0,i Subscribers per 1,000 residents 4,119 1.548 4.713 0.000 78.947 in t0 for block group i 2 ∆st0→t1,i Net stations per km 4,119 0.062 0.866 -23.021 23.021 from t0 to t1 for block group i System and Year Variables
∆St0→t1,I Net stations 4,119 35.000 11.432 25.000 51.000 from t0 to t1 for entire system I t1 = 2011 2011 binary indicator (base case in model) t1 = 2012 2012 binary indicator t1 = 2013 2013 binary indicator membership growth at the block group level, with a 1% change in the number of new stations across the system added associated with an almost 4$ change in membership growth, or 2.2 additional new members in a block group. With the systemwide new station variable held at its mean, each 1% increase in stations per kilometer in a block group is associated with 0.02 additional new members.
15 Table 4.4: OLS Regression Model of Membership Growth - Pooled
Pooled Model 1 Pooled Model 2 Coef SE Coef SE Subscribers per 1000 residents 0.061∗∗∗ 0.010 0.061∗∗∗ 0.010 Increase in stations per km2 0.300∗∗∗ 0.052 0.300∗∗∗ 0.052 2012 season -1.353∗∗∗ 0.110 2013 season -1.681∗∗∗ 0.111 New stations for the season 0.064∗∗∗ 0.004 Constant 1.456∗∗∗ 0.078 -1.781∗∗∗ 0.149 R2 0.0714 0.0713 ∗∗∗ Significant at p < 0.01 ∗∗ Significant at p < 0.05 ∗ Significant at p < 0.1 ∗∗∗p < 0.01 ∗∗p < 0.05 ∗p < 0.1
Table 4.5: Effects of Pooled Model 2 Independent Variables on New Membership
%∆ in new members Number of new members per 1,000 residents per 1,000 residents (ey/ex)(dy/ex) 1%∆ in subscribers per 1,000 0.170 0.095 residents in the block group 1%∆ in stations per km2 0.033 0.019 in the block group 1%∆ in new stations for the 3.990 2.226 whole season/system Elasticities calculated with all other variables held at means
16 Chapter 5
Effects on broader culture of active living
Respondents were asked to indicate the extent to which they agree or disagree with a series of statements, on a 100-point slider scale. An overwhelming majority of respondents agreed with the statement, “Nice Ride has made bicycling in the Twin Cities more popular”. The average score was 79.7 (SD 18.25). Figure 5.1 shows that 36% of respondents scored between 91 and 100, indicating strong agreement.
Figure 5.1: Perceptions of Nice Ride having made bicycling more popular in Minneapolis
Respondents were asked about their comfort level with various types of bicycle infrastructure, both while cycling and while driving near cyclists. In general, both when cycling and driving
17 near cyclists, subscribers preferred infrastructure that separated them from fast-moving auto traffic (Figure 5.2).
Figure 5.2: Average reported bicyclist and driver comfort level by infrastructure type
Figure 5.3 shows the average comfort level while bicycling for each type of infrastructure, grouped by whether the respondent predominately uses their own personal bicycle (90% of the time or more), predominately Nice Ride (90% of the time or more), or uses a mix of both (11- 89% of trips by either type). While comfort level for paths, bike lanes, and residential streets are nearly identical between groups, they varied in their responses for city streets with no dedicated infrastructure. People who use a personal bicycle for ≥90% of their bicycle trips self-reported higher levels of comfort on city streets than people who make relatively more Nice Ride trips. Predominately Nice Ride users (≥90% of trips) reported the lowest comfort levels on city streets without infrastructure. A plurality of the sample (35% - Figure 3.2) falls into this predominately Nice Ride group. The difference in comfort levels bicycling on city streets with no dedicated infrastructure sug- gests that Nice Ride is reaching the “interested but concerned” or “potential cyclist” population. Figure 5.3: Average reported bicyclist and driver comfort level by infrastructure type and percent of bike trips made by Nice Ride
Appendices
Appendix A
IRB
A-1 1408E53171 - PI Levinson - IRB - Exempt Study Notification
Subject: 1408E53171 - PI Levinson - IRB - Exempt Study Notification From: [email protected] Date: Mon, 24 Nov 2014 10:43:25 -0600 (CST) To: [email protected]
TO : [email protected], [email protected], [email protected], [email protected],
The IRB: Human Subjects Committee determined that the referenced study is exempt from review under federal guidelines 45 CFR Part 46.101(b) category #2 SURVEYS/INTERVIEWS; STANDARDIZED EDUCATIONAL TESTS; OBSERVATION OF PUBLIC BEHAVIOR.
Study Number: 1408E53171
Principal Investigator: David Levinson
Title(s): Nice Ride Minnesota Program Evaluation
This e-mail confirmation is your official University of Minnesota HRPP notification of exemption from full committee review. You will not receive a hard copy or letter.
This secure electronic notification between password protected authentications has been deemed by the University of Minnesota to constitute a legal signature.
The study number above is assigned to your research. That number and the title of your study must be used in all communication with the IRB office.
Research that involves observation can be approved under this category without obtaining consent.
SURVEY OR INTERVIEW RESEARCH APPROVED AS EXEMPT UNDER THIS CATEGORY IS LIMITED TO ADULT SUBJECTS.
This exemption is valid for five years from the date of this correspondence and will be filed inactive at that time. You will receive a notification prior to inactivation. If this research will extend beyond five years, you must submit a new application to the IRB before the study?s expiration date.
Upon receipt of this email, you may begin your research. If you have questions, please call the IRB office at (612) 626-5654.
You may go to the View Completed section of eResearch Central at http://eresearch.umn.edu/ to view further details on your study.
The IRB wishes you success with this research.
We value your feedback. We have created a short survey that will only take a couple of minutes to complete. The questions are basic, but your responses will provide us with insight regarding what we do well and areas that may need improvement. Thanks in advance for completing the survey. http://tinyurl.com/exempt-survey
A-2 1 of 1 2/6/15, 10:02 07AM Appendix B
Minneapolis Survey Instrument
B.1 Survey
B-1 Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Consent Form
Dear Nice Ride Member:
Welcome to the Nice Ride Active Living Survey!
You are invited to help Nice Ride, the University of Minnesota, and the Center for Prevention at Blue Cross and Blue Shield of Minnesota learn about active living and travel in the Twin Cities.
About the survey
Nice Ride Minnesota, the University of Minnesota, and Blue Cross and Blue Shield of Minnesota are conducting a survey to better understand personal travel and active living.
Your response to this survey will help Nice Ride better understand travel and activity needs among Nice Ride members and Twin Cities area residents and visitors.
Who can participate
ALL current and former Nice Ride subscribers who are at least 18 years old are invited to participate. In addition, anyone age 18 and older who has used a Nice Ride bicycle or has an interest in bicycling is welcome to participate.
Voluntary and confidential participation
Your participation in this survey is completely voluntary. Your responses will be kept completely confidential. Reports will present information in aggregate form so that no survey participant may be identified.
The survey takes about 30 minutes to complete. You may skip any questions that you do not wish to answer, and you may quit the survey at any time.
Prize for completion
To thank you for your participation, every person who completes this survey may enter into a drawing for one of 10 $50 gift card prizes.
Winners will be selected randomly from all survey respondents who enter before the deadline on November 14, 2014.
If you wish to enter the drawing, you will be invited to enter your name and e-mail address at the end of the survey. Please complete your survey before November 14, 2014 to be entered into the drawing.
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Contact and More Information
If you have any questions about the study, please contact Jessica Schoner, the University of Minnesota research assistant managing survey distribution, at [email protected].
Thank you very much for participating in this study!
Sincerely,
Dr. David Levinson, University of Minnesota Dr. Greg Lindsey, University of Minnesota
Survey Consent and Eligibility
Do you wish to take the survey?
I have read the consent and information letter (above) and agree to take the survey.
I do not wish to take the survey.
Are you at least 18 years old?
Yes
No
Nice Ride Use
How would you characterize your frequency of using Nice Ride bikes?
Daily
4 to 6 times a week
2 to 3 times a week
Once a week
2 to 3 times a month
Once a month
Less than once a month
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Have you used Nice Ride within the past 7 days?
Yes
No
Have you made any other bicycle trips within the past 7 days? E.g., using a personal bicycle.
Yes
No
Have you ever used Nice Ride to get to any of the following destinations? Check all that apply.
Work
School
Business meeting
Grocery store or other shopping
Restaurant or cafe
Entertainment or night life (e.g., bar, night club, spectator sport, theater)
Personal errands (e.g., post office, library, medical appointment, visiting friends or relatives)
Recreation (e.g., gym, park, to play a sport)
To go for a bike ride (e.g., no particular destination)
What type(s) of Nice Ride memberships have you ever used? Check all that apply, including discounted memberships or free promotional coupons.
Annual
30-day pay-as-you-go
Month-to-month (discontinued)
Day pass
I use another person's membership (e.g., employer or business subscription)
I have never used Nice Ride
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Think about the first time you used Nice Ride. Which type of membership did you use?
Please specify:
» Annual » 30-day pay-as-you-go » Month-to-month (discontinued) » Day pass » I use another person's membership (e.g., employer or business subscription) » I have never used Nice Ride
Think about the first time you used Nice Ride. What did you pay for this membership?
Full price
Student price
Free promotional or trial membership
What type is your current membership now?
I do not have a current membership
Other (specify):
What did you pay for your current membership?
Full price
Student price
Free promotional or trial membership
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Do you plan to continue your current membership when your free promotion or trial ends?
I will purchase an annual membership
I will purchase a 30-day Pay-as-you-go membership
I will purchase day passes when I want to use Nice Ride
I do not plan to purchase a membership
Your Experience with Bicycles
In a typical month with good weather, on average, what percentage of your bicycle trips are made using a Nice Ride bicycle versus a personal bicycle?
0%: 100%: All of my bicycle trips are usually All of my bicycle trips are usually made on a personal bicycle made on a Nice Ride bicycle
0 10 20 30 40 50 60 70 80 90 100
Over the past 7 days, on average, what percentage of your bicycle trips were made using a Nice Ride bicycle versus a personal bicycle?
0%: 100%: All of my bicycle trips were made All of my bicycle trips were made on a personal bicycle on a Nice Ride bicycle
0 10 20 30 40 50 60 70 80 90 100
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When you are riding a bicycle (including Nice Ride), how comfortable do you feel biking in each of these situations?
Very Somewhat Somewhat Very uncomfortable uncomfortable comfortable comfortable
0 10 20 30 40 50 60 70 80 90 100
On a separate path or trail (e.g., Midtown Greenway)
On a quiet residential street
In a bicycle lane
On a city street with no dedicated infrastructure
When you are driving a car, how comfortable do you feel sharing the road with a bicyclist (including Nice Ride) in each of these situations?
Very Somewhat Somewhat Very uncomfortable uncomfortable comfortable comfortable
0 10 20 30 40 50 60 70 80 90 100
On a quiet residential street
In a bicycle lane next to your lane
On a city street with no dedicated infrastructure
Your Experience with Nice Ride
6 of 22 B-7 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Please answer the following questions about your changes in travel and activity compared to before you became a Nice Ride member.
A little more A lot less now A little less now About the same now A lot more now How much exercise do you get now, compared to
before you joined Nice Ride? How much do you bicycle now, compared to before you joined Nice Ride? How much do you walk now, compared to before you joined Nice Ride? How much do you drive now, compared to before you joined Nice Ride? Whenever you are driving a car, how often do you observe people bicycling
now, compared to before you became a Nice Ride member?
7 of 22 B-8 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Based on your experiences with Nice Ride, to what extent do you agree with each of the following statements?
Strongly Disagree Disagree Agree Strongly Agree
0 10 20 30 40 50 60 70 80 90 100
Nice Ride helps make exercise part of my daily routine
Nice Ride is fun to use
I already have a bike, so I do not use Nice Ride
Nice Ride has made bicycling in the Twin Cities more popular
I do not feel safe biking on streets, so I do not use Nice Ride
I save money by using Nice Ride
Nice Ride station locations are not convenient for me
I am not interested in bicycling or using Nice Ride
Using Nice Ride is doing something good for the environment
Nice Ride costs too
8 of 22 B-9 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Bicycling and Nice Ride Among Peers
Before you became a Nice Ride member, what percentage of these groups of people did you ever observe using a personal bicycle in the Twin Cities before you became a Nice Ride member?
%
0 10 20 30 40 50 60 70 80 90 100
Coworkers
Neighbors
People in your household
Other people you know
During the time since you joined Nice Ride, what percentage of these groups of people have you ever observed using a personal bicycle in the Twin Cities?
%
0 10 20 30 40 50 60 70 80 90 100
Coworkers
Neighbors
People in your household
Other people you know
9 of 22 B-10 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
In the past month, what percentage of these groups of people have you ever observed using a personal bicycle in the Twin Cities?
%
0 10 20 30 40 50 60 70 80 90 100
Coworkers
Neighbors
People in your household
Other people you know
Before you became a Nice Ride member, what percentage of these groups of people did you ever observe using a Nice Ride bicycle in the Twin Cities before you became a Nice Ride member?
%
0 10 20 30 40 50 60 70 80 90 100
Coworkers
Neighbors
People in your household
Other people you know
10 of 22 B-11 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Since the time when you joined Nice Ride, what percentage of these groups of people have you ever observed using a Nice Ride bicycle in the Twin Cities?
%
0 10 20 30 40 50 60 70 80 90 100
Coworkers
Neighbors
People in your household
Other people you know
In the past month, what percentage of these groups of people have you ever observed using a Nice Ride bicycle in the Twin Cities?
%
0 10 20 30 40 50 60 70 80 90 100
Coworkers
Neighbors
People in your household
Other people you know
About You
11 of 22 B-12 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
In what year were you born?
What is the highest level of school you have completed or the highest degree you have received?
Some grade school or high school Bachelor's degree High school diploma or equivalent (GED) Master's degree Some college (no degree) Professional degree Associates degree or technical degree/certificate Doctoral degree
What is your current employment status?
Full time Not employed Part time Retired
Are you a student?
Yes, full-time
Yes, part-time
No
What is your approximate annual household income?
What language(s) do you primarily speak at home? (Check all that apply)
English Somali
Spanish Other
Hmong Prefer not to answer
12 of 22 B-13 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
What is your gender?
Male
Female
Other
Prefer not to answer
About Your Household
Do you live in the Twin Cities?
Yes
No
How long have you lived at your current address?
Years
Months
How many working bicycles does your household have?
How many working automobiles does your household have?
Including yourself if applicable, how many people in your household are licensed drivers?
13 of 22 B-14 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Describe your level of access to your personal automobiles:
I have access any time I want
I have access if I plan for it
I rarely have access
Please describe the vehicle you use most frequently
Make
Model
Year
How many children under the age of 18 are in your household, in the following ages:
Younger than 6 0
6 to 11 years old 0
12 to 15 years old 0
16 to 17 years old 0
Total 0
Including yourself, how many adults in your household are:
18 to 24 years old 0
25 to 29 years old 0
30 to 39 years old 0
40 to 49 years old 0
50 to 59 years old 0
60 to 69 years old 0
Age 70 or greater 0
Total 0
Household, Continued
14 of 22 B-15 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
What level of responsibility do you have for the children under age 18 in your household?
I am their primary caretaker
I share responsibilities equally with another adult
Someone else is their primary caretaker
I have no responsibilities for them (e.g., non-related roommate)
Think about the other adults in your household age 18 or older (excluding yourself).
Over the past 7 days, did any adults in your household (excluding yourself) do any of the following activities for at least 30 minutes in one day?
Yes No Bike (using Nice Ride) Bike (using a personal or
non-Nice Ride bicycle) Walk
Do you have a mobile or cellular phone?
Yes
No
What kind of mobile or cellular phone do you currently have?
Regular cell phone
Smart phone
What type of smart phone do you use?
Android
Apple iPhone
Blackberry
Windows
Other
15 of 22 B-16 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
In what year did you buy your current cell phone?
In what year did you acquire your first cell phone?
In what year did you acquire your first smart phone?
Trip Diary 2
This section asks about all of the trips you made yesterday, by any mode of travel. Please recall your trips from yesterday as best you can.
Please complete this diary even if you did not bicycle or use Nice Ride yesterday. Your honest response helps us understand people's overall travel needs and active living.
We aggregate the data for analyzing, and the details of your travel diary are never shared.
For this study, a "trip" is defined as a one-way segment of travel between two places where you stopped for any specific reason, even if the stop was very brief (e.g., quick stops for coffee or gas, dropping off or picking up someone, or a drive thru window). Waiting for travel (e.g., traffic jam, waiting for the bus, etc.) do not count as stops.
Trip Example 1: "I drove from home to work. Along the way, I dropped my child off at school and got coffee from a drive thru window." This counts as three separate trips: One from home to the child's school, a second from school to the drive thru restaurant, and a third from the drive thru to work.
Trip Example 2: "I walked from home to a bus stop, waited for the bus, and rode the bus to the library." This counts as one trip from home to the library because waiting for the bus is part of travel, not a deliberate stop.
16 of 22 B-17 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Trip Example 3: "I biked around the lake just for fun, with no specific stops. I started and ended my trip at home." This counts as one trip from home to home, assuming this person made no other stops (e.g., stopped for coffee along the way).
Where were you at 6:00 AM?
Give Location 1 a name:
Street address or street and nearest cross street
City
State
Zipcode
What was your primary activity at this location?
Did you leave this location at all for the rest of the day?
Yes
No
What time did you leave this location?
Departure Time AM/PM HH:MM AM PM
Block 11
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Including yourself, how many of your household members were on this trip?
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What type(s) of transportation did you use after you left this location?
Please check all that apply (up to three modes). For example, if you drove to a parking lot in Downtown Minneapolis and then rode a Nice Ride bicycle to Target Field, select both "Personal auto" and "Nice Ride bicycle".
Commuter rail (Northstar Personal auto Walk Dial-a-ride or private bus train) Car share (e.g., Car2Go, Personal bicycle School bus Other Hourcar, or Zipcar) Not applicable - Didn't Public bus Nice Ride bicycle Traditional taxi leave Light rail (Blue Line or Skateboard or scooter Uber or Lyft taxi Green Line)
Were you the driver or passenger?
Driver
Passenger
Please indicate whether any of the household members accompanying you on this trip (excluding yourself) were in the following age ranges.
Age 0 to 5
Age 7 to 11
Age 12 to 15
Age 16 to 17
Adults ages 18 and over
Approximately how far did you travel from your starting location to your destination?
Enter either miles or blocks.
Miles
Blocks
18 of 22 B-19 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
What time did you arrive at your destination?
HH HH:MM AM PM
Did you have to pay for parking at your destination?
Yes, I paid for parking for this trip
Yes, I used a long-term parking pass that I paid for previously
Yes, but my employer or someone else paid
No
If you had used a private auto for this trip instead of how you actually traveled, would you have had to pay for parking at your destination?
Yes
No
I don't know
19 of 22 B-20 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
What was your destination?
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A new location
Please describe your destination.
Give this location a name
Street address or street and nearest cross street
City
State
Zipcode
20 of 22 B-21 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
What was your primary activity at your destination?
Did you leave this location at all for the rest of the day?
Yes
No
What time did you leave this location?
Departure Time AM/PM HH:MM AM PM
Prize drawing2
Is there anything else you would like to share about bicycling, Nice Ride, or active living in general?
Do you have any feedback on this survey?
To thank you for your participation, every person who completes the survey has the option to be entered into a drawing for one of 10 $50 gift card prizes. Winners will be selected randomly from all survey respondents who enter.
If you wish to enter the drawing, you will be invited to enter your name and e-mail address on the next page. Entering the drawing is optional.
21 of 22 B-22 10/28/14, 8:15 56AM Qualtrics Survey Software https://umn.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrin...
Would you like to enter the drawing for one of 10 $50 gift card prizes?
Yes, please enter me into the drawing. (Provide contact information on the next page)
No, I do not wish to enter. Please submit my survey now.
To enter the prize drawing, please enter your contact information. This information is only used to contact the prize winners.
First name
E-mail address
Phone number
Survey Powered By Qualtrics
22 of 22 B-23 10/28/14, 8:15 56AM B.2 Recruiting email University of Minnesota Nice Ride Active Living Survey
Subject: University of Minnesota Nice Ride Active Living Survey From: Nice Ride Minnesota
U of M Active Living Survey View this email in your browser
Dear Nice Ride Member: You are invited to help Nice Ride, the University of Minnesota, and the Center for Prevention at Blue Cross and Blue Shield of Minnesota learn about active living and travel in the Twin Cities.
To take take part in the survey, follow this link: https://umn.qualtrics.com/SE/?SID=SV_cBeTaHsw81vfAm9&bike=T6C7YAFELV
About the survey Nice Ride Minnesota, the University of Minnesota, and Blue Cross and Blue Shield of Minnesota are conducting a survey to better understand personal travel and active living. Your response to this survey will help Nice Ride better understand travel and activity needs among Nice Ride members and Twin Cities area residents and visitors.
Who can participate ALL current and former Nice Ride subscribers who are at least 18 years old are invited to participate. In addition, anyone age 18 and older who has used a Nice Ride bicycle or has an interest in bicycling is welcome to participate.
Voluntary and confidential participation Your participation in this survey is completely voluntary. Your responses will be kept completely confidential. Reports will present information in aggregate form so that no survey participant may be identified.
B-25 1 of 2 2/6/15, 10:21 31AM University of Minnesota Nice Ride Active Living Survey
The survey takes about 30 minutes to complete. You may skip any questions that you do not wish to answer, and you may quit the survey at any time.
Prize for completion To thank you for your participation, every person who completes this survey may enter into a drawing for one of 10 $50 gift card prizes.
Winners will be selected randomly from all survey respondents who enter before the deadline on November 14, 2014. If you wish to enter the drawing, you will be invited to enter your name and e-mail address at the end of the survey. Please complete your survey before November 14, 2014 to be entered into the drawing.
Contact and More Information If you have any questions about the study, please contact Jessica Schoner, the University of Minnesota research assistant managing survey distribution, at [email protected].
Thank you very much for participating in this study!
Sincerely, Dr. David Levinson, University of Minnesota Dr. Greg Lindsey, University of Minnesota
You are receiving this email as a member of Nice Ride Minnesota
Our mailing address is: Nice Ride Minnesota 2701 36th Ave S Minneapolis, MN 55406
Add us to your address book
unsubscribe from this list
B-26 2 of 2 2/6/15, 10:21 31AM Appendix C
Minneapolis Survey Data Report
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6 8 0 5 3 5 5 1 8 1 7 7 e ...... 4 9 . . . g 1 8 4 3 2 7 7 8 5 9 9 7 a 8 5 5 8 8 2 2 3 1 7 r e v A e u l 0 0 0 0 0 0 0 0 0 0 0 0 a 0 0 0 0 0 0 0 0 0 0 0 0 ...... V 0 0 0 0 0 0 0 0 0 0 0 0 x 0 0 0 0 0 0 0 0 0 0 0 0 a 1 1 1 1 1 1 1 1 1 1 1 1 M e u l 0 0 0 0 0 0 0 0 0 0 0 0 a 0 0 0 0 0 0 0 0 0 0 0 0 V ......
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5 4 1 7 d r 2 2 4 2 a d n a t S e u l a V 9 9 5 1
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C-18 s e s n 5 4 2 7 o 3 5 6 2 p 5 5 5 6 s e R n o i t a i v e 5 6 0 5 2 9 3 4 D . . . .
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i t e M i s C e h n t i f w o T e e g h t a e t n u n i l e 0 0 0 0 a e c 0 0 0 0 l r V . . . .
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0 0 0 0 x u 1 1 1 1 a o y M e v a h e l p o e e u p l f 0 0 0 0 a o 0 0 0 0
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i t e i s C e h n t i f w o T e e g h t a t n n i e e c l r c d e l y p c o
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C-21 % % % % % % % % % 4 6 0 0 2 7 5 6 4 2 1 e s n 2 4 7 o 9 9 6 9 6 2 5 0 9 p e 1 5 3 4 7 3 2 7 9 1 4 7 s u l 3 8 3 1 8 9 e . . . a 7 5 1 1 R V r a B t s e h g i h e h t r o d e t e l e p t a m c o i f c i t r e ) e v c D a / h E e
e G u r ( o g l t y e o n l d o e o l l h o a a c v h c s i i c u n s h )
q f h g e i e c o
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a n
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C-22 % % % % % 9 1 7 3 7 1 e 4 5 4 8 u l 3 5 7 1 4 9 . . . a 7 1 0 0 V e s n 2 8 o 6 6 4 3 9 p 8 5 2 6 7 s e R r a B ? s u t a t s t n e m y o l p m e d t e n y e o l r r r e e p e u d m m m c i w i e t l n t e r r
s t i l a o t t r u l t i n s t o e a o u o e a A y i F P N R T s
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o t D p e a e s u h c d e u l i r e l t c a W a a R s n # 1 2 3 4
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i n x a a . a r t n t a i a e a t o 2 S M M M V S T 2
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o e e o e a a A i Y Y N T s v u n e o o y D p e
e s e u c d e u l r i r e l t c a A a a R s n # 1 2 3
i V d n l V t a
i n x a a . a r t n t a i a e a t o 3 S M M M V S T 2
C-24 24. What is your approximate annual household income?
# Answer Bar Response %
1 Less than $5,000 20 3% 2 $5,000 but less than $10,000 4 1% 3 $10,000 but less than $15,000 16 2% 4 $15,000 but less than $20,000 14 2% 5 $20,000 but less than $25,000 21 3%
6 $25,000 but less than $30,000 19 3% 7 $30,000 but less than $35,000 32 4% 8 $35,000 but less than $40,000 28 4% 9 $40,000 but less than $45,000 29 4% 10 $45,000 but less than $50,000 24 3% 11 $50,000 but less than $60,000 58 8%
12 $60,000 but less than $75,000 77 10% 13 $75,000 but less than $100,000 112 15% 14 $100,000 but less than $125,000 102 14% 15 $125,000 but less than $150,000 49 7% 16 $150,000 but less than $200,000 69 9%
17 $200,000 but less than $250,000 23 3%
18 $250,000 or more 37 5%
Total 734
Statistic Value
Min Value 1
Max Value 18 Mean 11.77 Variance 16.81
Standard Deviation 4.10 Total Responses 734
C-25 25. What language(s) do you primarily speak at home? (Check all that apply)
# Answer Bar Response %
1 English 773 97% 2 Spanish 18 2% 3 Hmong 4 1% 4 Somali 3 0% 5 Other 32 4%
6 Prefer not to answer 3 0%
Other
portuguese Marathi Hindi Persian Arabic Hindi
Vietnamese
German italian French French
Arabic
Korean Italian Dutch Mandarain
French, German Dutch german
Telugu, Tamil Swedish Mandarin
German German
Vietnamese Italian Russian
Japanese French, german Ojibwe
Statistic Value
Min Value 1
Max Value 6 Total Responses 794
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o t D p e a e s u h c d e u l i r e l t c a W a a R s n
i V d n l # 1 2 3 4 V t a
i n x a a . a r t n t a i a e a t o 6 S M M M V S T 2
C-27 % % % 7 3 9 e 3 3 8 2 u l 0 0 1 1 2 8 . . . a 7 1 0 0 V e s n 6 2 o 6 5 8 p 2 7 7 s e R r a B ? s e i t i C n i w T r e e h w t l
s a n s t n i n o e o o i A e s t Y N T v e a i i l s
v n u e o o D p y e
e s u c d e o u l i r e l t c a # 1 2 D a a R s n
i V d n l V t a
i n x a a . a r t n t a i a e a t o 7 S M M M V S T 2
C-28 e 5 u l 7 a 7 V ? s s e r d d a t n . e ) r r s u h t c
n r o u o m y
+ t a 2
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s a u r e o a y y e (
) Y e s ( ) 7 v a .
s 3 a l . 3 h h e s t ) 9 3
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e ( e 0 t y 7 n l H 5 i R d 6 s a 7 % a % % 1 i l i l 9 : o t : : % p : h d h h x a . c a g t t t t n t s t i e a e i v D s 5 5 9 o 8 S R D A S M 1 2 M 7 9 M T 2
C-29 e 8 u l 7 a 7 V ? e v a h d l o h e s u o h r u o y s e o d s e l c y c i b g n i k r o . w l
e s y c e n x s a E n 1 m o 1 3 1 n
i p : : :
0 w 2 s e e e d : c o l : l l i e i i i e e 0 t n l H i R d 4 s 3 % a % % 0 i i l 3 : o t : : % : h d h h x a . c a g t t t t n t t i e a e v D s 5 5 9 o 9 S R A S M 1 2 M 7 9 M T 2
C-30 e 8 u l 7 a 7 V ? e v a h d l o h e s u o h r u o y s e o d s e l i b o m o t u a g n i k r o . w l
e s y c e n x s a E n m o 1 2 4 n
i p : : :
0 w 1 s e e e d : c o l : l l i e i i i e e 0 t n l H i R d 8 s 2 % a % % 0 i i l 3 : o t : : % : h d h h x a . c a g t t t t n t t i e a e v D s 5 5 9 o 0 S R A S M 1 2 M 7 9 M T 3
C-31 e 5 u l 7 a 7 V e r a d l o h e s u o h r u o y n i e l p o e p y n a m w o h
, e l b a c i l p p a f i f l e s r u . l o e s y
? c e g s x s r n E n i e o d v 1 2 5 n i i p u : : : r 0 l 2 s e e e d d : c c l : l l i e i i i e e t n n d l I i R d 7 s 2 % a % % e 0 i i l 1 : o t : s : % : h d h h x a . c a g t t t t n n t t i e a e v D s 5 5 9 o e 1 S c R A S M 1 2 M 7 9 M T i 3 l
C-32 % % % % 2 9 9 7 1 e 7 2 4 0 u l 3 4 6 1 3 7 . . . e a 7 1 0 0 s V n 6 4 0 o 0 5 4 7 p 7 5 1 7 s e R r a B : s e l i b o m o t u a l a n o s r e p r u o t y
n o a t t
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s y t y l
w e e e l a e i e v v s s r a v t b a a n n i a e o r h h r o A c I I I T D p e s e s u c d e e u l i r e l t c a D a a R s n
i V d n l V t a
i # 1 2 3 n x a a . a r t n t a i a e a t o 2 S M M M V S T 3
C-33 n o i t a i v e 1 5 1 1 D 4 3 3 2 . . . . d 0 0 0 0 r a d n a t S e u l a V
0 8 7 3 e 1 0 0 0 . . . . g 0 0 0 0 a r e v A e u l a 0 0 0 0 V 0 0 0 0 . . . . x 4 3 3 2 a M e h t n i
, d l o h e s e u u l o 0 0 0 0 a h 0 0 0 0
V . . . . r 0 0 0 0 u n i o y M n i e r a
8 1 f o e g a e h t r e d n u
d d l l n d l o o e 6 r
o s s d n r r l s i a r a a h h a e e t c y y e
r r y y 5 7 e e n 1 1 1 : g a w s 1 n o o s t t m e u
o n t g o 2 6 w A a Y 6 1 1 o g H n i w . # 1 2 3 4 o l 3 l o 3 f
C-34 n o i t a i v e 0 1 7 5 4 0 9 D 7 0 7 6 6 4 1
...... d 0 1 0 0 0 0 0 r a d n a t S e u l a V
7 8 8 1 3 3 2 e 2 3 4 3 3 1 0 ...... g 0 0 0 0 0 0 0 a r e v A e u l 0 a 0 0 0 0 0 0 0 0 . 0 0 0 0 0 V ......
0 6 4 4 2 2 2 x 2 a M : e r e a
u l d l 0 0 0 0 0 0 0 a o 0 0 0 0 0 0 0 V ...... h 0 0 0 0 0 0 0 n e i s M u o h r u o y n i s t l u d a y n a m w o r d d d d d d h l l l l l l
e , t o o o o o o f l a s s s s s s e r r r r r r e s r a a a a a a r g e e e e e e u r y y y y y y o
r o y 4 9 9 9 9 9
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Appendix D
Preliminary Minneapolis Survey Findings
D-1 Nice Ride Evaluation Project Meeting - 11/24/2014 1 of 7
Preliminary Twin Cities Survey Results Response rate!
• 1012 responses to the survey email • 576 “finished” surveys (meaning the respondent clicked “submit”), but many more submitted enough data to be usable • Response rates on questions before the diary are generally pretty high (650-950) • Diary has not been analyzed for completeness yet. Over half the sample (55%) reported at least two trips. Survey Highlights! Self-reported frequency of using Nice Ride (N=990)!
Daily 3.8%
4-6 times per week 13.8%
2-3 times per week 18.6%
Once per week 13.5%
2-3 times per month 22.8%
Once per month 10.0%
Less than once per month 17.4%
0% 7.5% 15% 22.5% 30% Percent of sample
D-2 Nice Ride Evaluation Project Meeting - 11/24/2014 2 of 7
Type of first subscription (N=958)!
1-year membership 44.1%
30-day Pay as you go membership 16.4%
24-hour pass 29.9%
30-day pass 9.7%
0% 12.5% 25% 37.5% 50% Percent of sample Nice Ride as a share of all bicycling (N=934)!
0 to 9% 20.8%
10 to 19% 8.1%
20 to 29% 6.9%
30 to 39% 4.8%
40 to 49% 2.4%
50 to 59% 5.4%
60 to 69% 3.1% (versusapersonal bike) 70 to 79% 3.4% inatypical month with good weather 80 to 89% 6.9% Percentbikeof tripsmade using Nice Ride
90 to 100% 38.3%
0% 10% 20% 30% 40% Percent of sample
D-3 Nice Ride Evaluation Project Meeting - 11/24/2014 3 of 7
Comfort level on infrastructure (N=876-939)!
Biking Driving near bicyclists
93 Multiuse paths
77 Bike lane 79
89 Quiet street 81
51 City street 55
0 25 50 75 100 Average score on a scale from Very uncomfortable (0) to Very comfortable (100) Sliders started in a default position of 0. If the respondent did not move the slider at all, it was recorded as missing data. For this chart, if the respondent skipped 1/4 biking questions or 1/3 driving questions, the missing response was imputed as 0. If the respondent skipped 2 or more questions in a section (biking or driving), all of their responses for that section were set to missing.
D-4 Nice Ride Evaluation Project Meeting - 11/24/2014 4 of 7
How much do you ___ now, compared to before you joined Nice Ride? (N=886-907)!
Exercise 3.5
Bike 3.9
Walk 3.1
Drive 2.5
Observe bicyclists while driving 3.8
1 2 3 4 5 Average score on a scale of A lot less (1), A little less (2), About the same (3), A little more (4), A lot more (5)
D-5 Nice Ride Evaluation Project Meeting - 11/24/2014 5 of 7
Experience with Nice Ride statements (N=614-898)!
Good for environment 84
Fun to use 82
Convenient to use 81
Made biking more popular 80
Makes exercise routine 59
Save money 54
Inconvenient stations 38
Already have bike 28
Costs too much 27
Don't feel safe 16
Not interested 10
Don't understand 8
0 25 50 75 100 Average score on a scale from Strongly Disagree (0) to Strongly Agree (100)
D-6 Nice Ride Evaluation Project Meeting - 11/24/2014 6 of 7
Observations of other biking !
What percent of these people have you observed using a personal bicycle? (N=629-783) 60% Before you joined Since you joined In the past month 56%
50% 50% 45%
41% 38% 35% 30% 31% 28% 28% 27% 24% 24%
15% Avg. pct. of peopleof pct. in group observed biking Avg. 0% Coworkers Neighbors Household Others
What percent of these people have you observed using Nice Ride? (N=476-624) 60% Before you joined Since you joined In the past month
45% 48%
37% 30%
26%
19% 19% 21% 15% 18% 19% 15% 16% 13% 14%
Avg. pct of peopleof pct in group observed using NR Avg. 0% Coworkers Neighbors Household Others
D-7 Nice Ride Evaluation Project Meeting - 11/24/2014 7 of 7
Cell phone ownership and type!
Nice Ride sample United States* 60%
57%
45%
37%
30% 31% 30% 28%
15%
10% Percentcellof phone subscribers in sample orin USstudy 0% 2% 2% 2% 1% 0% 0% Regular phone Android iPhone Blackberry Windows Other *United States cell phone data from comScore (http://www.comscore.com/Insights/Market- Rankings/comScore-Reports-September-2014-US-Smartphone-Subscriber-Market-Share)
D-8 Appendix E
Bike Walk Twin Cities 2013 Count Report
E-1 Bike Walk Twin Cities 2013 Count Report
Issued December 12, 2013
a program of transit for livable communities Executive Summary This annual report, the 2013 Bike Walk Twin Cities Pedestrian and Bicycle Count Report, provides a detailed view of bicycling and walking at benchmark locations across the Twin Cities. This ongoing to develop a more complete picture of overall travel behavior in our communities. collection of annual data about nonmotorized traffic supplements existing data on motorized traffic key findings
1. Rates of bicycling and walking Annual counts at 43 benchmark locations in the Twin Cities metro indicate that bicycling increased 78 percent and walking 16 percent between 2007 and 2013. Overall, active transportation (bicycling and walking together) rose by 45 percent from 2007 to 2013. Between 2012 and 2013, bicycling increased 13 percent, walking decreased 6 percent, and active transportation increased 4 at locations encompassing a broad range of street types and facilities and representing all areas ofpercent. Minneapolis The findings and several are based adjacent on manual communities. 2-hour Thecounts 2013 conducted counts are by thespecially-trained highest ever recorded volunteers for bicycle trips, and the second highest ever recorded for pedestrian trips (down slightly from the record high of 2012).
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 1
E-2 2. Impact of new facilities 2013 key findings Count locations with new facilities (new bike lanes summary* or other improvements) showed higher increases in bicycling than locations without improvements. Trails
2007-2013 connections saw the greatest increases in bicycle where extensions were built to improve network Bicyclists: +78% to facilities improvements and more related to major destinations.use. Increased Count pedestrian data continue traffic seems to demonstrate less related Pedestrians: +16% that fewer bicyclists ride on sidewalks when there is Nonmotorized: +45% a dedicated bicycling facility available. This has safety
for pedestrians and making bicyclists more visible and 2012-2013 predictablebenefits for toall motorists.road users, making sidewalks clearer
Bicyclists: +13% 3. Mode share Pedestrians: -6% Nonmotorized: +4% Bridges provide a unique opportunity for the study of modes in a network. A comparison of motorized and *Based on data from 43 benchmark movement and the proportion of traffic using different locations. nonmotorized traffic on bridges over the Mississippi River shows that the nonmotorized share of traffic ranges from 11-26 percent and averages 16 percent. 4. Gender The data show that the rate of increase in bicycling and walking has been similar for men and
Thewomen. gender The difference gender split, for averagingwalking is 29 percent female bicyclists from 2008-2013 (with a range of not27-32 as percent),pronounced, remains with roughlyan average the of same as it was in 2008, when gender data collection began. 45 percent women pedestrians from 2008 to 2013.
5. Seasonality In addition to annual counts, BWTC locations since 2008. The monthly has conducted monthly counts at six 2013, while absolute numbers of bicyclistscount data are indicate much lowerthat from in winter 2008- months, bicycling increased at a higher rate in winter than in summer months.
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 2
E-3 I. Introduction that since 2007 bicycling has increased by 78 percent and walking by 16 percent. Since 2007, total Bike Walk Twin Cities counts of bicycle and pedestrian traffic at 43 benchmark locations reveal percent, walking declined by 6 percent, and nonmotorized trips increased by 4 percent. non-motorized trips have increased by 46 percent. From 2012 to 2013, bicycling increased by 13 as well as counts conducted by the City of Minneapolis, both of which show that trips made by walkingThe dramatic and bicycling increases have are neverconsistent been with higher. the findings of the American Community Survey (ACS)
Since 2007, 7 of the 43 benchmark locations have more than doubled in the amount of observed bicycle traffic. Over that same period, 5 of the 43 benchmark locations have seen more than double Citythe amount of Minneapolis of pedestrian show tentraffic. additional There likely such arelocations, many otherof which locations eight have that areimproved not part facilities. of this count Not surprisingly,program where the non-motorized locations that have travel shown has more the greatest than doubled. increases For ininstance, bicycling counts are along conducted corridors by the that have been improved for bicycling or where trail extensions have been made to fill network gaps. downtownIn terms of Minneapolis.pedestrian traffic, the greatest increases in walking are in places where new destinations have been built: for example, near the new Twins Stadium and other recent developments in bicyclists riding on sidewalks, which is inherently dangerous both for bicyclists and pedestrians. Investments in new bike facilities have had the additional benefit of greatly reducing the rate of
Pedestrian, Bike, and Total Non‐motorized Traffic in the Minneapolis NTP Study Area September, 4‐6pm Counts 2007‐2013 16000
14000
12000
10000 Bike Pedestrian 8000 Non‐motorized
6000
4000
2000
0 2007 2008 2009 2010 2011 2012 2013
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 3
E-4 locations with increases greater than 100%, 2007-2013
Bicycling Name | Count location | Percentage
1. Bridge 9 | Loc. 3 | 546% 2. Cedar Lake Trail, under I-94 | Loc. 43 | 388% 3. 42nd St. E, east of Minnehaha | Loc. 25 | 285% 4. Cedar Lake Trail at Royalston with new extension | Loc. 70 | 278% 5. Loring Bikeway Bridge | Loc. 74 | 167% 6. 26th Ave. N, east of Penn | Loc. 15 | 114% 7. Midtown Greenway, west of Hennepin Ave. | Loc. 42 | 106%
Walking Name | Count location | Percentage
1. Sabo Bridge & 28th St. crossing Hiawatha | Loc. 27 & 28 | 255% 2. Cedar Lake Trail at Royalston with new extension | Loc. 70 | 203% 3. Loring Bikeway Bridge | Loc. 74 | 200% 4. Glenwood Ave., west of Royalston Ave. | Loc. 38 | 177% 5. 26th Ave. N, east of Penn | Loc. 15 | 160% 6. U of M Transitway, east of 25th Ave. SE | Loc. 5 | 113%
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 4
E-5 II. Facilities Analysis bicycling
Locations with new bikeway facilities showed higher increases in bicycling than locations without
Lyndale Ave. N. south of Broadway, averaged nearly the same when neither had bike lanes. In 2009, theimprovements. 7th Street location For example, had 13 two bicyclists locations in thein north two hour Minneapolis, count period, 7th Street while N. the over Lyndale I-94 andlocation had 12. After bike lanes were added in 2012, the 7th Street location doubled to 26 and was up to 33 in 2013. Meanwhile the Lyndale location (still without bike lanes) recorded only 10 in 2012 and 11 bicyclists in 2013.
Trails where new extensions were built to complete network connections saw perhaps the greatest increases in bicycle use. For example, bicycling increased by 53 percent from 2012 to 2013 at nearBridge downtown, 9 along the bicycling Dinkytown increased Greenway, 278 percentwhich was from completed 2007 to 2013. in August This 2013. route Frominto downtown 2007 to 2013, bicycling increased 546 percent at the Bridge 9 location. Along the Cedar Lake Trail extension benchmark count locations.) was completed in 2011. (The Cedar Lake Trail extension was not a BWTC project, but is one of the
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 5
E-6 Total Bicyclists at Locations with Improved Facilities, 2007‐2013
250
200
150
Bicyclists, 2007 100 Bicyclists, 2013
50
0
walking
scarcity of counts conducted in areas where major pedestrian improvements (e.g. new sidewalks) Facility improvement did not correlate as highly with increased walking. This may be due to a
Royalston,were made. near In addition, the Twins increased Stadium, pedestrian saw a 177 traffic percent seems increase less relatedfrom 2007 to facilities to 2013. improvements and more related to major destinations. For instance, the count location Glenwood Avenue, west of Some of the improvements for bicyclists resulted in an improved environment for lane conversions with bike lanes) have been pedestrians. For instance, “road diets” (4-3 crashes (and all other crash types) by simplifyingfound to significantly the roadway decrease and reducing car-pedestrian what ais buffer known zone as the for “multiple pedestrians. threat” BWTC pervasive funding andwith encouragement 4-lane roadways. resulted Bike lanes in road also diets provide at the following locations: Riverside Ave.,
Douglas10th Ave. Drive, SE, Franklin and Marshall Ave. Bridge, Ave. 27th Ave. SE, Fremont Ave. N., parts of Glenwood Ave.,
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 6
E-7 sidewalks of bicycles riding on the sidewalk. BWTC 2013 count data again show a high incidence of sidewalk An especially salient count finding demonstrates that bike lanes significantly reduce the incidence do not feel safe on the roadway, a high percentage will use the sidewalk. Yet, research shows that riding on thestreets sidewalk with high may traffic actually volumes be more and dangerous no dedicated for cyclists space for than bicyclists. the roadway When and cyclists also problematic for pedestrians. BWTC observations indicate fewer sidewalk riders at locations with designated facilities for bicyclists. The data demonstrate that improvements in the design of the built environment encourage safer behavior.
% Sidewalk Bicyclists at Locations with Facilities Improvement, 2008‐2013
80%
70%
60%
50%
40%
30%
20% 10% % Sidewalk Riding, 2013 0% % Sidewalk Riding, 2008
Total Sidewalk Total Bicyclists % Sidewalk 2013 5 worst locations without facilities, 2013 Bicyclists
18 Lyndale Ave N, south of Broadway 11 2 18% 24 Franklin Ave, west of Nicollet 76 21 28% 37 Hennepin Ave, north of 28th St 53 16 30% 81 Cedar Ave, South of Riverside Ave 79 20 25% 536 University Ave, west of Prior 49 32 65%
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 7
E-8 100% 12% locations with new bicycle facilities showing both increases in bicycle use average rate of sidewalk riding and decreases in sidewalk riding at 32 benchmark locations
(This excludes all count locations along bike paths as well as bridge locations where off-street paths, e.g., the East and West River Parkways, route bicyclists directly onto the sidewalks: Ford Parkway, Lake Street, Franklin Avenue, 65% and Hennepin Avenue bridges.) highest rate of sidewalk riding, on University Avenue in Saint Paul 8% versus 24% the rate of bicycles riding on sidewalks at locations with on-street bicycle facilities (8 percent) versus at locations without facilities (24 percent)
(As above, this does not include off-street paths or locations where off- street facilities feed directly onto bridge sidewalks.)
On Central Ave., sharrows (aka shared lane markings) were added just north of Lowry Ave. in 2012.Two of While the locations these markings with high have sidewalk reduced riding the incidence rates (see of next sidewalk page) haveriding existing (down bicyclefrom a highfacilities. of 78 percent in 2010) sharrows do not appear to be as effective in encouraging bicyclists to use the street as do bike lanes, where cyclists have their own dedicated space on the roadway. This is much less important when motorized traffic is light, as in the case of E. 42nd Street or Bryant Ave., south Inof Lakethe case Street. of 26th Sharrows Street in N., these surface low-traffic conditions locations may play tend a roleto be in highly the choice effective. to ride on the sidewalk instead of the street. The bike lanes on 26th Street are riddled with potholes. When the street was in much better shape in 2008, sidewalk riding was 21 percent. Counters have also noted that the bike lanes themselves are often ignored by motorists, who have continued to use them for parking their cars with little fear of enforcement over the years.
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 8
E-9 locations with least bicycle-riding on sidewalks in 2013
Name | Count location | Percentage
1. Bryant Ave., north of Lake St. | Loc. 149 | 1.5% 2. Como Ave., west of Raymond | Loc. 535 | 1.9% 3. 15th Ave. SE, north of University Ave. SE | Loc. 1 | 2.1% 4. 10th Ave. Bridge over Mississippi River | Loc. 7 | 3.4% 5. Summit Ave., east of Western | Loc. 541 | 4.0% locations with rates of bicycle-riding on sidewalks of 25% or greater
Name | Count location | Percentage
1. University Ave., west of Prior | Loc. 6 | 65% 2. Central Ave. NE, north of Lowry Ave. | Loc. 21 | 50% 3. Lyndale Ave. S, north of Franklin | Loc. 29 | 47% 4. 26th St. N, east of Penn Ave. N | Loc. 15 | 40% 5. Hennepin Ave., north of 28th St. | Loc. 37 | 30% 6. Franklin Ave., west of Nicollet | Loc. 24 | 29% 7. Cedar Ave., south of Riverside Ave. | Loc. 81 | 25%
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 9
E-10 III. Network Effects One of the outcomes of the BWTC federal Nonmotorized Transportation Pilot Program is the expansion of the network of routes in the Twin Cities. BWTC infrastructure investments sought to fill gaps in the existing network of off-street trails and to greatly increase the on-street routes tobetween 3rd and off-street 4th Streets paths. South. An exampleThe network of a network of new routes gap that is shown was filled in orange is the connectionin the map frombelow. the LRT trail into downtown Minneapolis, with a new segment of bike path extending from 11th Avenue following question in mind: do new facilities attract new users, or simply encourage current walkers and/orIn order bicyclists to measure to switchthe impact to a differentof the expanded route? network, BWTC analyzed the count data with the
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 10
E-11 By conducting counts along several distinct corridors that lead to many of the same destinations, and by having representative counts throughout an entire system, we can begin to answer this question. The following analysis demonstrates that observation at as many points as possible is critical for understanding a network, and network effect. Too few data points may result in a skewed understanding of real trends.
The Sabo Bridge and 28th Street crossing Hiawatha: Because of their two locations are considered as a pair.proximity, Before it the is essential Sabo Bridge that wasthese built, crossing Hiawatha at 28th Street (at grade) was the only option to continue on the Midtown Greenway. With the new Sabo Bridge, a second option was introduced. In 2007 were 220 at grade crossings—a 6 percent decrease. But when combined with the observed 573 bridge crossings,(before the we bridge can document was built) a there total wereincrease 235 along at-grade this crossings corridor ofin 237a two percent. hour period. It appears In 2013 the newthere bridge has helped to encourage new users.
Bicycling Rates on the Sabo Bridge versus crossing at grade, 2007-2013 900
800
700
600
500
400
300 28th St E (Greenway) crossing Hiawatha 200
100 Sabo Bridge
0 2007 2008 2009 2010 2011 2012 2013
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 11
E-12 The Loring Bikeway Bridge and Lyndale Avenue Looking at the two locations over time, it is clear that the Loring Bikeway Bridge is moving some bicyclists from Lyndale Avenue up onto the bridge (presumably: This is a good commuters example usingof network the Bryant offset. Ave. Bike Boulevard). Like the Sabo Bridge, the Loring Bikeway Bridge is attracting new users. This average annual increase in ridership on the bridge is greater than the average annual decrease in ridershipis indicated at bythe the Lyndale slopes location. of the trendlines If cyclists that were fit simply the data-points moving from for eachone tolocation. the other, That the is, slopes the would be much more similar.
This graphic shows that while more bicyclists are diverting to the Loring Bikeway Bridge, there is facilities do, in fact, attract new users. also a net increase in bicycle traffic. The same is true on the Sabo Bridge. This is to say that good
Bicycling Rates on Loring Bikeway Bridge versus Lyndale Ave, 2008-2013 350
300
250
200 y = 17.5x
150 Total
100 Loring Bikeway Bridge
y = -9.2 50 Lyndale Ave S, north of Franklin ‐ 2008 2009 2010 2011 2012 2013
The new Dinkytown Greenway and increases on Bridge 9: Two locations where there were increases of 56 percent and 38 percent, respectively. Much of this increase likely is due to the August 2013significant opening increases of the newlyin bicycling completed from 2012Dinkytown to 2013 Greenway, are the U which of M Transitway connects these and twoBridge locations 9, with via along the Greenway and these connecting locations as more people discover this new trail. This is an off-street trail along a rail corridor. It will be interesting to see how much more growth occurs another example of the network effect.
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 12
E-13 IV. Bridges and Mode Share Bridges provide a unique opportunity for the study of movement and the proportions of users in a network. This is because there are no alternative routes around or over geographic boundaries might decide to use one route or another for various reasons. Bridges control for this variation. such as rivers. Traffic must concentrate on these routes, whereas in other parts of a network a user
Bike and Pedestrian Mode Share, 2013 30%
25%
20%
15% % Pedestrians 10% % Bicyclists
5%
0% Plymouth Ave Hennepin Ave 10th Ave. Franklin Ave Lake Street Ford Parkway Bridge Bridge bridge over Bridge Bridge Bridge Mississippi River
The following analysis of bridges over the Mississippi
area.River Lookingis used to at understand these comparisons, mode-share—the we get a better share of motorized and nonmotorized traffic—in the study can contribute to a transportation network. This is one of theunderstanding questions posed of the by extent the legislation to which biking enabling and the walking federal Nonmotorized Transportation Pilot Program.
Average Daily Trips (AADT) from the City of Minneapolis toFor nonmotorized this analysis, wedata—Estimated compared motorized Daily Trips data—Annual (EDT) from the annual bicycling and walking counts.
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 13
E-14 mode share on bridges
Bridge Location Bicycles Pedestrians Motor Vehicles
Plymouth Avenue 7% 11% 82% Hennepin Avenue 6% 7% 87% 10th Avenue 10% 8% 82% Franklin Avenue 15% 11% 74% Lake Street 10% 5% 85% Ford Parkway 7% 4% 89%
Overall 9% 7% 84%
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 14
E-15 V. Gender
Within the larger results showing increased bicycling and walking from 2007 to 2013, data show that the rate of increase has been locations where women similar for men and women. The gender bicyclists are more than 35% remains roughly the same as it was in 2008, in 2013 split, of 28-32 percent female bicyclists, made. The average across the count years Name | Count location | Percentage isthe 29 first percent year genderwomen observations cyclists. The genderwere difference for walking is not as pronounced, with an average of 45 percent women 1. Larpenteur Ave., east of Cleveland Loc. 902 | 44% walking from 2008 to 2013. 2. Pelham Blvd., north of Otis| 42%* Additionally, just as a proportional 3. 20th Ave., south of I-94 | Loc. 2 | 41% analysis of mode share may be best 4. Lake St. Bridge | Loc. 32 | 39% bridges, so too is a proportional analysis 5. E. 42nd St., east of Minnehaha Ave. executed through an analysis of a city’s Loc. 25 | 37% appropriate with a bridge analysis. 6. Polk St. NE, north of Lowry | 37%* of the gender make-up of bicyclists 7. Franklin Ave. Bridge | Loc. 26 | 36% In looking at this data from the 6 bridge locations, the female share is similar to 8. Plymouth Ave. Bridge | Loc. 19 | 36% what was observed at the 43 benchmark locations across the NTP study area. *new count location in 2013
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 15
E-16 % Women Bicyclists, 6 Bridge Locations, Minneapolis 40% 35% 30% 25% 20% % Women Bicyclists 15% 10% 5% 0% 2008 2009 2010 2011 2012 2013
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E-17 VI. The Minnesota Factors: Weather & Seasonality weather
Each year counts have been conducted the second week of September, beginning on a Tuesday, consistent with a national protocol/methodology. By doing duplicate counts (two or more counts for a given location) on several different days, and sometimes into the following week, we have been able to document that some days tend to have higher number of bicyclists than others. Almost will dissuade some people from biking to work on that particular day, and hence, even if the temperaturesalways the fluctuations are ideal andappear there to isbe not weather a cloud related. in the skyAn early by afternoon, rain in the there morning, may be for fewer instance, cyclists counted than another day where it did not rain in the morning. a weather adjustment, through a linear regression model. This report does not utilize the model, whichBWTC is stillworking in development. with the Volpe However Center itat should the US beDOT noted to create that most a model of the that counts attempts for this to calculate report were conducted on Tuesday, September 10, 2013, when rain fell during the morning hours. Duplicate counts at 8 different locations show that the following day had, on average, 12 percent higher bicycle volumes, but lower walk volumes. This may be indicative that some cyclists switch to may switch to bicycling. walking when weather is less than ideal, and when weather is perceived to be “nicer,” some walkers
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E-18 seasonal variation
More important, perhaps, than the weather variation during the annual bicycling during the colder season. Incounts, addition is the to significantour annual decline counts in conducted every September, monthly monthlycounts have count been data conducted indicate that,at six while absolutelocations numbers since February of bicyclists 2009. areThe lower during winter months, bicycling years at a higher rate than in summer monthsin winter during increased the same over thetime last period. five
Monthly Count Location Averages: September, 2009-2013 versus January 2010-2013
250
y = 5x 200
150
100 September y = 14x Averages January Averages
50 Linear (September Averages) Linear (January Averages) 0 2009 2010 2011 2012 2013
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 18
E-19 VII. Annual Count Effort When the Nonmotorized Transportation Pilot (NTP) Program was authorized by Congress in
December, 2005, the stated goal was to “determine the extent to which bicycling and walking could become part of the transportation solution.” The four pilot communities (Marin County, CA, beganSheboygan conducting County, counts WI, City in of2007 Columbia, as part MO,of this and Congressional Minneapolis-Saint mandate Paul, to MN) measure all agreed the overall to conduct impactcounts atof keythe pilot“benchmark” program. locations: Counts conducted locations bycounted BWTC on have an annualalso been basis. used Bike to measure Walk Twin the Cities impact bike lanes, etc.) are the most effective in encouraging increased walking and bicycling. of project-specific investments in an attempt to determine which types of facilities (new sidewalks,
The Volunteer Effort By the 330 Numbers…. total volunteer hours in 2013, including observations, training, and transport to and from locations.
This equals more than two months of work for a single person, or ~$8800 of value, based on the average Minneapolis salary (indeed.com). 132 hours counting in 2013, including all redundant counts 60 66 This is 3.3 work weeks. total volunteers for observations BWTC count in 2013 in 2013
1233 hours counting for observations from 2007 to 2013
This equals 61.7 work weeks or 15.4 months or 1.3 years of counting alone. This does not include training or transport.
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E-20 changes in methodology
Because of the nature of the NTP pilot program, we are always innovating. That is true today and was true in 2007 and 2008. Our current dataset is based on observations that started in September 2007. At that time, as an organization we were concerned with bicyclist safety, which meant that count locations focused on intersection movements. After that and since, we have focused on approach, we changed our methodology, in 2008 and afterward, from monitoring intersection movementsunderstanding to observingtotal bike andbicyclists pedestrian and pedestrians traffic across crossing the NTP a screen area. Because line. In 2008,of this we change also startedin recording gender observations. To understand total trends, we can use intersection observations to deduce the number of bicyclists and pedestrians that crossed a screen line on one of the legs, but we cannot speculate on the variables that we also started tracking as of 2008, such as gender. As such, some of the data and charting capture trends or changes from 2007, while some are limited to 2008 and subsequent years.
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E-21 new benchmark locations
BWTC is dedicated to continuing to support the nonmotorized community in the metro area added four new benchmark locations in anticipation of improvements to these corridors. The fourby expanding locations ourare: data collection effort to respond to local needs and new projects. In 2013, we
• Pelham Blvd., north of Otis Ave., Saint Paul (neighborhood effort to add bicycle facilities ) • Polk St. NE, north of Lowry Ave., Minneapolis (bicycle boulevard project to open in 2014) • 8th Ave. NE, west of Marshall Ave., Minneapolis (neighborhood effort to add bicycle facilities) • Dinkytown Greenway, Minneapolis (opened in August 2013)
This new baseline data will help us continue to measure how improvements or changes in infrastructure impact rates of bicycling and walking.
Total Total Total Non- New 2013 Count Locations Bicyclists Pedestrians Motorized 83 Polk St NE, north of Lowry 27 26 53 84 8th Ave NE, west of Marshall St 58 35 93 589 Pelham Blvd, north of Otis 50 20 70 85 Dinkytown Greenway, under University Ave SE 110 10 120
Since 2007, comprehensive, strategic investments made by the Bike Walk Twin Cities federal Nonmotorized
network for bicycling and walking, adding more than 75 milesTransportation of new bikeways Pilot Program and sidewalks. have greatly BWTC expanded also provided the
SPOKESstart-up bike/walkand expansion connect funds in forthe Nice Seward Ride neighborhood Minnesota of Minneapolis,bike sharing, forand the the University Community of PartnersMinnesota Bike Bike Library Center, at Cycles for Change. BWTC investments have also included planning studies, community outreach and education, and
the measurement efforts reflected in this report. To date, advisorythe infrastructure bike lanes, investments leading pedestrian have included interval several signals, “firsts” and for Minnesota: bicycle boulevards, bicycle traffic signals, While there are still investments being made through this pilot“bicycles program may use(11 fullremaining lane” signage projects in yetstrategic to be completed),locations. 2013 counts reveal that the investments made to date have
in Minneapolis and surrounding communities. had a significant impact in increasing walking and bicycling
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E-22 Appendix ID # 27/28 BWTC Total Non-Motorized Count 2007-2012 3 Como Ave, west of Raymond Ave 535 3 University Ave, west of Prior 536 4 Summit Ave, east of Western 541 0 SW LRT Trail, east of Beltline Blvd 901 0 Larpenteur Ave, east of Cleveland 902 1Central Ave NE, north of Lowry 21 2Bloomington Ave over Hwy 62 22 0Fillmore St NE, south of Broadway 20 Plymouth Ave Bridge 19 4Franklin Ave, west of Nicollet 24 62nd St N, south of Plymouth Ave 16 526th Ave N, east of Penn 15 LRT Trail, west of 11th Ave S 11 3Washington Ave S, Over I-35W 13 3Portland Ave over Hwy 62 23 8Lyndale Ave N, south of Broadway 18 7th St N, over I-94 17 542nd St E, east of Minnehaha 25 9Lyndale Ave S, north of Franklin 29 6Franklin Ave Bridge 26 0Portland Ave S, north of 28th St 30 2Lake Street Bridge 32 4Ford Parkway Bridge 34 7Hennepin Ave, north of 28th St 37 9Cedar Lake Trail, west of Kennilworth Trail 39 Glenwood Ave, west of Royalston Ave 38 2Midtown Greenway, west of Hennepin Ave 42 3Cedar Lake Trail, under I-394 43 41st St S, West of 3rd Ave S 64 0Cedar Lake Trail at Royalston with new trail extension 70 4Loring bikeway Bridge 74 5Lyndale Ave, north of Loring Bikeway Bridge 75 2Riverside Ave, East of Cedar Ave 82 1Cedar Ave, South of Riverside Ave 81 15th Ave SE north of University 1 20th Ave, south of I-94 2 Bridge 9 3 Riverside Ave, over I-94 6 U of M Transitway, East 25th Ave SE 5 10th Ave. bridge over Mississippi River 7 Hennepin Ave Bridge 9 Sabo Bridge and 28th St crossing Hiawatha Location 005 1,6 12,224 12,76910,045 0720 0921 0121 2013 2012 2011 2010 2009 2008 2007 1,843 349 367 145 483 273 247 111 256 278 334 273 356 143 231 505 377 203 162 267 113 284 327 122 216 336 7 5 7 5 7 168 172 154 178 156 175 4 4 0 3 0 347 406 332 304 347 247 4 9 0 3 2 670 820 632 708 797 246 71 99 60 36 38 64 32 51 47 87 71 81 41 1,888 383 214 143 134 386 646 316 385 300 130 328 432 198 368 431 411 290 117 673 277 129 244 342 105 354 382 149 110 274 449 53 83 86 38 52 38 78 53
106
12,029 1,980 395 171 161 124 419 476 348 151 281 244 100 315 474 120 266 411 347 334 645 284 141 162 137 359 360 505 151 231 408 44 73 69 38 39 39 97 88 47 409 14,063 14,009 1,935 330 158 186 145 371 629 321 125 259 238 320 456 162 180 440 458 192 606 262 163 147 126 409 323 634 117 184 382 89 68 82 3563 27 48 90 45 2,627 394 194 182 139 408 713 323 114 279 259 115 286 529 187 283 488 415 254 659 362 115 607 157 345 365 561 132 290 317 44 38 94 33 39 35 93 96 40 2,912 345 176 198 136 352 661 234 104 125 276 328 121 183 544 129 320 546 198 407 400 643 438 454 187 325 349 480 157 592 60 27 4785 35 98 89 78 39 14654 2656 332 287 234 162 355 406 653 272 279 280 362 235 463 204 441 832 279 198 348 440 709 571 185 607 343 190 403 487 103 283 445 51 84 41 66 57 98 28 70 75 40 ∆ 2007-2013 230% 238% 128% 181% 274% 168% ‐ 24% ‐ 11% ‐ 16% ‐ 31% ‐ 15% 44% 98% 64% 42% 49% 35% 11% 21% 53% 37% 13% 60% 47% 39% 43% 24% 90% 88% 64% 21% 51% 49% 31% 32% ‐ 5% ‐ 3% ‐ 8% ‐ 2% 7% 6% 2% 46% ∆ 2012-2013 144% 100% ‐ 15% ‐ 19% ‐ 66% ‐ 78% ‐ 15% ‐ 15% ‐ 19% ‐ 13% ‐ 14% ‐ 25% 45% 33% 19% 74% 21% 15% 67% 28% 58% 24% 10% 10% 30% 89% 34% 15% 16% 80% ‐ 9% ‐ 4% ‐ 1% ‐ 1% ‐ 4% 1% 4% 0% 2% 6% 1% 3% 4%
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E-23 ID # 72 Sabo Bridge and 28th St crossing Hiawatha 27/28 0 Larpenteur Ave, east of Cleveland 902 0 SW LRT Trail, east of Beltline Blvd 901 4 Summit Ave, east of Western 541 3 University Ave, west of Prior 536 3 Como Ave, west of Raymond Ave 535 2Riverside Ave, East of Cedar Ave 82 1Cedar Ave, South of Riverside Ave 81 5Lyndale Ave, north of Loring Bikeway Bridge 75 4Loring bikeway Bridge 74 0Cedar Lake Trail at Royalston with new trail extension 70 41st St S, West of 3rd Ave S 64 2Midtown Greenway, west of Hennepin Ave 42 3Cedar Lake Trail, under I-394 43 9Cedar Lake Trail, west of Kennilworth Trail 39 8Glenwood Ave, west of Royalston Ave 38 Portland Ave S, north of 28th St 30 7Hennepin Ave, north of 28th St 37 2Lake Street Bridge 32 9Lyndale Ave S, north of Franklin 29 4Ford Parkway Bridge 34 6Franklin Ave Bridge 26 542nd St E, east of Minnehaha 25 4Franklin Ave, west of Nicollet 24 3Portland Ave over Hwy 62 23 2Bloomington Ave over Hwy 62 22 1Central Ave NE, north of Lowry 21 0Fillmore St NE, south of Broadway 20 9Plymouth Ave Bridge 19 8Lyndale Ave N, south of Broadway 18 77th St N, over I-94 17 62nd St N, south of Plymouth Ave 16 526th Ave N, east of Penn 15 Hiawatha LRT Trail, south of 11th Ave 11 3Washington Ave S, Over I-35W 13 Hennepin Ave Bridge 9 10th Ave. bridge over Mississippi River 7 Riverside Ave, over I-94 6 U of M Transitway, East 25th Ave SE 5 Bridge 9 3 20th Ave, south of I-94 2 15th Ave SE north of University 1 BWTC Bike Count 2007-2013 Location oas499 ,6 682 644 ,9 7,793 7,890 6,434 6,802 7,264 4,929 Totals 0720 0921 0121 2013 2012 2011 2010 2009 2008 2007 276 176 153 306 201 122 235 113 153 280 212 234 197 116 128 200 514 2 333 229 18 9 1217958 38 10892 45 69 47 34 9 10479 4 14394 14 58 22 40 40 31 13 18 45 60 26 769 57 107 382 233 234 597 244 186 142 234 290 771297 178327 232 195 221 598 27 84 55 69 99 46 41 36 88 34 61 55 48 20 23 65 77 87
364 103 259 130 154 564 287 260 119 204 311 684 315 131 237 223 151 117 214 633 7 0 7 322 379 307 279 27 62 97 51 55 44 70 40 91 27 68 25 61 66 33 12 13 23 55 68 55 573 85 59 75 338 102 175 223 120 137 547 147 239 122 114 311 118 583314 117305 210 166 179 585 24 62 40 78 63 51 77 19 77 10 64 54 59 20 11 36 90 3 13773 8 267 122 165 256 149 568 305 597 195 104 776 206 372 148 351 127348 218 173 229 787 24 69 67 70 47 52 62 20 91 17 27 68 40 17 14 53 78 9 637 507 157 258 183 423 404 572 293 204 381 326 153 366 204 182 108 194 862 70 38 26 84 41 42 51 27 49 79 85 27 94 25 20 44 10 26 18 50 79
7678% 8786 631 793 394 125 150 333 8 167% 184 8 278% 580 3 338% 534 388 105 211 330 166 352 110 336 140 351 207 251 6 546% 168 4 -27% 147 866 27 9-16% 49 53 79 69 51 3-33% 53 2285% 52 76 32 58 76 44 1-16% 11 33 4114% 14 63 94 ∆ 2007-2013 106% 237% 53% 43% 58% 39% 63% 76% 89% 47% 93% 50% 38% 18% 77% 66% 32% 44% 45% 93% 89% 40% 47% 83% 39% 21% 50% 57% 96% 68% -7% 5% ∆ 2012-2013 13% 156% 190% 100% -22% -24% -13% -19% -22% -24% 49% 20% 26% 55% 29% 37% 32% 32% 10% 33% 95% 24% 93% 28% 51% 10% 27% 26% 19% 38% 56% -4% -8% -4% 4% 1% 4% 3% 8% 0% 4% 1% 0%
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 23
E-24 ID # 72 Sabo Bridge and 28th St crossing Hiawatha 27/28 0 Larpenteur Ave, east of Cleveland 902 0 SW LRT Trail, east of Beltline Blvd 901 Summit Ave, east of Western 541 3 Como Ave, west of Raymond Ave 535 3 University Ave, west of Prior 536 7Hennepin Ave, north of 28th St 37 2Riverside Ave, East of Cedar Ave 82 9Plymouth Ave Bridge 19 1Cedar Ave, South of Riverside Ave 81 Loring bikeway Bridge 74 Cedar Lake Trail at Royalston with new trail extension 70 1st St S, West of 3rd Ave S 64 Cedar Lake Trail, under I-394 43 Cedar Lake Trail, west of Kennilworth Trail 39 Glenwood Ave, west of Royalston Ave 38 Ford Parkway Bridge 34 5Lyndale Ave, north of Loring Bikeway Bridge 75 62nd St N, south of Plymouth Ave 16 8Lyndale Ave N, south of Broadway 18 26th Ave N, east of Penn 15 2Midtown Greenway, west of Hennepin Ave 42 Lake Street Bridge 32 1Central Ave NE, north of Lowry 21 Fillmore St NE, south of Broadway 20 7th St N, over I-94 17 Washington Ave S, Over I-35W 13 2Bloomington Ave over Hwy 62 22 9Lyndale Ave S, north of Franklin 29 0Portland Ave S, north of 28th St 30 6Franklin Ave Bridge 26 42nd St E, east of Minnehaha 25 Portland Ave over Hwy 62 23 1Hiawatha LRT Trail, south of 11th Ave 11 4Franklin Ave, west of Nicollet 24 15th Ave SE north of University 1 Bridge 9 3 U of M Transitway, east 25th Ave SE 5 Riverside Ave, over I-94 6 10th Ave. bridge over Mississippi River 7 20th Ave, south of I-94 2 Hennepin Ave Bridge 9 BWTC Pedestrian Count 2007-2013 Location oas5,116 Totals
,0 5,422 5,505
0720 0921 0121 2013 2012 2011 2010 2009 2008 2007 1,329 136 235 239 426119 166 170 232 140 122 249 189 149 1 7139 795 87 95 103 87 118 11 23 60 8130 84 91 7153 23 98 20 76 19 25 66 29 3716 49 45 39 17 18 9 2 4
1,290 153 274 285 307134 141 109 110 207 186 261 135 154 212 162 319 26 26 67 94 8391 46 26 10 7676 21 15 28 22 55 42 56 19 57 18 14 6 5
10 100
5,595
1,347 128 408 100 304 277 100 101 128 150 196 282 159 196 176 181 239 24 20 44 62 97 24 47 26 88 81 57 14 26 12 29 11 12 54 10 56 13 25 8 7
,1 6,270 6,119
1,350 459 331 381 129 100 114142 198 267 142 161 161 151 324 49 21 8228 44 66 77 2345 74 5955 27 15 44 30 29 85 20 55 17 25 6 4
1,840 168 396 275 353 116 109 100152 182 255 178 190 168 165 365 44 16 27 50 77 5759 65 85 39 6241 68 62 16 39 11 15 57 60 22 27 8 4 9
2050 337 196 323 274 116 149 165 107 107 123 104 218 148 234 151 295 33 26 13 37 85 73 34 47 94 31 71 91 71 35 21 44 16 68 16 57 96 4 7 8
9916% 5919 1790 158 337 264 147 295 111 132 130 116 111 148 330 203 185 302 170 26 39 13 26 51 68 37 50 73 27 78 52 70 35 65 24 38 66 36 68 18 6 7 8 9 ∆ 2007-2013 177% 255% 203% 200% 160% 113% -44% -15% -43% -54% -40% -26% -31% -23% -17% -22% -22% -13% -52% -59% -44% 16% 12% 43% 10% 46% 44% 45% 76% 10% 73% 87% 35% 57% 42% 24% 47% 74% 21% -6% -9% 7% ∆ 2012-2013 116% 125% 125% -6% -40% -30% -41% -22% -33% -13% -12% -23% -39% -14% -51% -49% -13% -56% -13% -91% 79% 18% 63% 10% 50% 14% 25% 68% 23% 19% 14% -4% -1% -3% 0% 4% 9% 6% 1% 7% 0% 0% 2%
Count reports from previous years, with past results, key findings, and additional background information and materials, are available at www.bikewalktwincities.org.
Bike Walk Twin Cities | A Program of Transit for Livable Communities | 2013 Count Report | December 2013 | Page 24
E-25
Appendix F
Minneapolis Supplemental Models
F.1 Supplemental Innovation Diffusion/Membership Descrip- tive Statistics
Table F.1: Descriptive Statistics for Innovation Diffusion Model Variables - By Year
N Mean SD Min Max 2011 Model
∆M10→11 Change in subscribers per 1,000 residents 1,373 1.52 4.15 -1.38 62.20 M10 Previous year subscribers per 1,000 residents 1,373 0.46 1.36 0.00 18.34 2 ∆S10→11 Change in stations per km 1,373 0.11 0.77 -9.18 7.58 2012 Model
∆M11→12 Change in subscribers per 1,000 residents 1,373 0.24 1.78 -8.67 24.49 M11 Previous year subscribers per 1,000 residents 1,373 1.97 5.29 0.00 73.37 2 ∆S11→12 Change in stations per km 1,373 0.06 0.98 -7.58 23.02 2013 Model
∆M12→13 Change in subscribers per 1,000 residents 1,373 -0.08 2.18 -30.36 30.16 M12 Previous year subscribers per 1,000 residents 1,373 2.21 5.92 0.00 78.95 2 ∆S12→13 Change in stations per km 1,373 0.02 0.83 -23.02 8.51
F-1 Table F.2: Descriptive Statistics for Innovation Diffusion Model Variables - Pooled Model
Variable N Mean SD Min Max Main Explanatory Variables
∆mt0→t1,i Net subscribers per 1,000 residents 4,119 0.558 2.974 -30.362 62.201 from t0 to t1 for block group i mt0,i Subscribers per 1,000 residents 4,119 1.548 4.713 0.000 78.947 in t0 for block group i 2 ∆st0→t1,i Net stations per km 4,119 0.062 0.866 -23.021 23.021 from t0 to t1 for block group i System and Season Variables
∆St0→t1,I Net stations 4,119 35.000 11.432 25.000 51.000 from t0 to t1 for entire system I t1 = 2011 2011 binary indicator (base case in model) t1 = 2012 2012 binary indicator t1 = 2013 2013 binary indicator F.2 Supplemental Innovation Diffusion/Membership Models
Table F.3 and Table F.4 show results of a set of regressions modeling growth in Nice Ride mem- bership. The dependent variable is the net change in membership in a census block group from the previous year to the current year. The explanatory variables are the base membership in the previous year, and the change in number of stations within the block group from the previous year to current year. Table F.3 contains separate models for each year of data: 2011, 2012, and 2013. The model name refers to the “current” year in each model. So the dependent variable for the 2011 model is the net change in membership from 2010 to 2011.
Table F.3: OLS Regression Model of Membership Growth - By Year
2011 Model 2012 Model 2013 Model Coef SE Coef SE Coef SE Subscribers per 1000 residents 2.373∗∗∗ 0.051 0.065∗∗∗ 0.009 -0.065∗∗∗ 0.010 Increase in stations per square km 0.435∗∗∗ 0.090 0.266∗∗∗ 0.048 0.042 0.070 Constant 0.385∗∗∗ 0.073 0.098∗∗ 0.050 0.058 0.062 R2 0.6202 0.0647 0.0315 ∗∗∗ Significant at p < 0.01 ∗∗ Significant at p < 0.05 ∗ Significant at p < 0.1
Table F.4 contains two models with data from all years pooled, with additional explanatory variables to distinguish years. The first uses binary variables to indicate 2012 and 2013 cases, with 2011 as the base year. The second uses a system growth variable to differentiate between years. This variable is the measure of new stations added to the system in that year. For example, there were 65 stations in 2010, and 116 stations in 2011, so the system growth variable for 2011 is 116 − 65 = 51. Table F.4: OLS Regression Model of Membership Growth - Pooled
Pooled Model 1 Pooled Model 2 Coef SE Coef SE Subscribers per 1000 residents 0.061∗∗∗ 0.010 0.061∗∗∗ 0.010 Increase in stations per square km 0.300∗∗∗ 0.052 0.300∗∗∗ 0.052 2012 season -1.353∗∗∗ 0.110 2013 season -1.681∗∗∗ 0.111 New stations for the season 0.064∗∗∗ 0.004 Constant 1.456∗∗∗ 0.078 -1.781∗∗∗ 0.149 R2 0.0714 0.0713 ∗∗∗ Significant at p < 0.01 ∗∗ Significant at p < 0.05 ∗ Significant at p < 0.1