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final final copy of BIKE SHARE IN SAN JOSE

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BIKE SHARE IN SAN JOSE: WHO WILL USE IT, HOW MUCH MONEY PEOPLE WILL
PAY FOR IT, AND WHAT THEY WILL USE IT FOR
Kenneth An...
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In the Bay Area, 36.4% of Greenhouse gases come from transportation, thus
significantly contributing to global ...
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States faces air pollution, Global Warming and Climate Change from greenhouse gas emissions,
and an oil dependency that ...
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final final copy of BIKE SHARE IN SAN JOSE

  1. 1. 1 BIKE SHARE IN SAN JOSE: WHO WILL USE IT, HOW MUCH MONEY PEOPLE WILL PAY FOR IT, AND WHAT THEY WILL USE IT FOR Kenneth Antonio Rosales Environmental Studies 198: Senior Seminar December 13, 2011
  2. 2. 2 ABSTRACT In the Bay Area, 36.4% of Greenhouse gases come from transportation, thus significantly contributing to global climate change. In response to this issue, the cities of San Francisco, Redwood City, Palo Alto, Mountain View, and San Jose will implement a pilot Bike Share program funded by the Metropolitan Commission, Bay Area Air Quality Management District, and Valley Transportation Authority in the summer of 2012. One hundred and fifteen (115) surveys were conducted throughout the principal areas where the Bike Share program kiosk stations will be disseminated to find out if a significant correlation between participants' age and their willingness to pay exists. The average age and willingness to pay, information about whether survey participants will use Bike Share or not, why they wouldn’t use Bike Share, and what they would use Bike Share for were also acquired. No significant correlations between people’s age and willingness to pay were found because of an imbalanced distribution of young people over older individuals surveyed. However, most people who would use Bike Share would use it to run errands, and those who would not use Bike Share would rather use another mode of transportation. Most survey participants would use Bike Share at Diridon Station over any other area, and would on average, pay much more compared to Washington D.C. or Boston, Massachusetts’ Bike Share Programs . Therefore, San Jose’s Bike Share vendor can make their prices more expensive to provide innovative public education and outreach programs in terms of safety and training or can fund their maintenance, vandalism, and theft costs with ease. However, the Bike Share should be a non-profit organization that survives through low costs from in-kind sponsorships, subsidies, subscriptions, and local affiliates. INTRODUCTION Motivation The United States of America is plagued with air quality issues, traffic congestion, and inadequate land use by reason of insufficient private and governmental actions, and the lack of citizen demands for change in transportation reform. For example, in 1923 General Motors (GM) and several other motor transit companies such as Greyhound, Rex Finance, and Omnibus Corporation to name a few bought out electric street car systems in the entire country (Snell 2010). By 1950, GM had converted 900 electric street car systems to single occupancy vehicles (SOV) and motorized bus systems from coast to coast (Snell, 2010). Six years later, President Eisenhower signed the Federal Highway Aid Act of 1956 to expand highway systems across the country and in turn increased the use of SOV’s at an unimaginable level (Weingroff 1996). The United States has now exhausted most of its own supply of petroleum, imports over 70% of its oil, consumes over 25% of the world supply of gasoline, pumps over 85 million barrels a day, but only withholds 2.5% of the world’s reserves (Gerston, 2009). Consequently, the United
  3. 3. 3 States faces air pollution, Global Warming and Climate Change from greenhouse gas emissions, and an oil dependency that all simultaneously adversely affects the contemporary daily lives of individuals and the sustainability for future generations (EPA, 2011) The Environmental Protection Agency releases information about national air pollutants released on an annual basis to the public. In 1999, transportation accounted for 27.6% of particulate matter (pm2) released into the air (EPA, 2011). Based off the EPA’s study on analyzing different pollutants, averages of 1.794 parts per million (ppm) of carbon monoxide from 388 different site visits, 0.00966 ppm of nitrogen oxide from 230 different sites visited, and 0.0028 ppm from 480 different sites visited were all emitted (EPA, 2011). It must be stated that 95% of non-work related trips are used by car and are linked to health concerns (Freeman, 2010). Other pollutants listed are sulfur and toxic air pollutants such as benzene, carbonyl sulfide, and chloroform out of the188 different regulated chemicals dispersed. Sulfur dioxide is connected to premature death, respiratory, and cardiovascular disease, and nitrogen dioxide is linked to photochemical smog that disturbs various cities in the summer and consequently causes asthma attacks (Logan). Asthma, birth defects, cancer, chronic obstructive pulmonary disorder, and negative cardiovascular and neurological effects come from the combustion of fossil fuels (Nazelle et. Al, 2011). Transportation also contributes to the release of greenhouse gases (GHGs). About one- third of greenhouse gases come from transportation and in 2008, the U.S. emitted slightly less than 7 billon metric tons of greenhouse gases (EPA, 2011). In the Bay Area, 36.4% of Greenhouse gases come from transportation alone (BAAQMD, 2010). Obesity is also an issue that has arisen in the United States and beyond. The U.S. Center for Disease Control and Prevention (2004) published an increase of obesity among adults (Gerston 2009, 72). The amount of obese adults increased from 14% in 1980 to 32.9% in 2004 (Gerston 2009, 72). Obesity is also linked to serious health concerns such as Type-2 diabetes, heart disease, hypertension, congestive heart failure, premature death, and pregnancy issues. This may be correlated to the fact that 95% of non-related work trips are used by car (Freeman, 2010). Over the last 25 years, global, social, and economic growth has also had a great impact with the demand of journeys in large urban areas, ensuing and increasing the use of the car (dell ‘Ollio 2011, 1). Currently, 50% of the world lives in urban areas, but is projected to increase to 70%, thus a decrease of urban sprawl dwellers (Nazelle, 2011 767). Therefore issues in the United States also reflect the world and vice versa through globalization. The World Health Organization has recently suggested that 2.8 million deaths come from overweight and obesity issues (Nazelle, 2011). Physical inactivity is responsible for 2.8 million deaths a year (Nazelle, 2011). The population mostly impacted by these issues is the suburbanite populace. Studies have shown that suburbanites “suffer more from hypertension and other chronic diseases” (Nazelle 2011, 769). However, bicycling as a transportation alternative can be a great solution to reduce air pollutants and greenhouse gas emissions because it emits none other than an individual’s steam. Communities that have great pedestrian and bicycle infrastructure, parks, and high density are interrelated with neighborhoods that are physically active and thus have a “healthier weight
  4. 4. 4 status and better mental health” (Nazelle, 2011). In the United States, bicycle trips have increased from 1,272 (millions) annual bike trips in 1977 to 4,081 bike trips [millions] (Pucher et.al, 2011). While 1% of total trips are made by the bike in the United States, the entire country must emulate cities like Copenhagen, Denmark where “as nearly 38% of all transportation trips in Copenhagen are done by bike” (Pucher et.al, 2011; Streetfilms, 2010). Also, the United States needs to emulate countries like Germany who have greater trips by public transport, foot, and bikes fourfold than the United States, and drive 25% less than United States citizens (Buehler 2010, 644). Furthermore, 27% of all trips including business and non-business related trips in the Netherlands are made by the bicycle and similarly, 12% in Germany (Martens, 2006; DeMaio and Gifford 2004, 5). In medium-sized cities, bicycle trips increases at a whopping 35% (Martens 2006, 327). Increased physical activity has further and evidently suggested that it develops major health benefits such as the enhanced fitness levels within the adult population (Titze, et.al. 2008,252) A bicycle dependent society may lead to a lifestyle that is car-free and increase the competitiveness of environmentally sound modes of transportation such as public transport and walking (Martens 2006, 326). Background Bike Share programs can be of tremendous aid by promoting bicycle use, connecting people to public transit stations, reducing energy use, decreasing congestion and consequently giving access to public transportation corridors, and shrinking the emissions of air pollutants and greenhouse gases (Martens, 2006). In addition, the launch of a public bicycle sharing program enables the augment in the use of personal bike use in the long run, and could reduce over one million car trips per year and decrease carbon-dioxide emissions larger than 3.5 million pounds on an annual basis per municipality (Dossett 2008, 6). Public Bike Sharing programs can be the cornerstone of a transcending movement to a bike-oriented society in the United States (Dossett 2008, 6). Bike Share is a program that is distinguishable to bike rental services. To utilize Bike Share, an individual has to purchase a pass at an available station or through the internet (dell ‘Ollio 2011). Passes for Bike Share vary from system to system. Some Bike Share initiatives may have daily, weekly, monthly, and annual passes available to sell and some may mix and match the different time scales of passes (dell ‘Ollio 2011). After the purchase of a pass, the first 30 minutes of use of a shared bike is free (the pass is still purchased so it is not technically free). After the first 30 minutes expires, a “penalty” charge is placed in the user’s account (Dossett 2008). An incrementing charge is imposed after every thirty minutes and eventually the charge increment is capped. The automated electronic and solar powered system continues to charge the user after every thirty minutes of use at the capped price until the shared bike is returned to a station (Dossett 2008). History Bike Share systems has existed for about 43 years since 1968 and has been plagued with theft, liability issues, and lack of demand (dell ‘Olio 2010, 90; DeMaio and Gifford 2004, 3). However, Bike Share programs have gone through an absolute overhaul than what it used to be. When Bike Share first launched in Amsterdamn, The Netherlands, regular bikes colored in white were supplied to the public without permanent pick-up and drop off points, were
  5. 5. 5 subsequently stolen, and the entire system failed within days (dell ‘Olio 2010, 90; DeMaio and Gifford 2004, 3). In the next generation of Bike Sharing, Copenhagen, Denmark launched its program called the Bycyklen with pick up and returning stations and a coin deposit system that still exists today. The Bycyklen encountered numerous theft issues; however, the third wave of Bike Share was heavily influenced by Copenhagen’s work and therefore gave rise to Smart Bikes. The Smart Bike program utilizes electronic bike or rack locks, credit cards, magnetic stripe cards, or smartcards, and telecommunication systems (dell ‘Olio 2010, 90; DeMaio and Gifford 2004, 3). More recently, Bike Share programs have people subscribe for daily passes at a respective station with the use of a credit or debit card. Passes or special card keys that require longer periods of usage such as weekly or annual passes are subscribed for online. The Smart Bikes program transformed itself over three generations and has generated results of improvement. Theft and problems with liability have been dealt with in a similar fashion with many Bike Share programs in the United States. Minneapolis, Minnesota, Washington D.C., and Boston Massachusetts all require that any theft or accident be reported immediately to the local police station and/or to their Bike Share vendor depending on the situation and city laws (Capital Bikeshare 2011; Hubway 2011; Nice Ride MN2011). Users may be charged for a loss or theft of a bike, depending on the notification and facts behind a person’s story. Since a person is held responsible of following all street laws once acquiring a bicycle, a person who gets in an accident must return the bicycle at a docking station or contact the vendor varying under the circumstance a person goes through (Capital Bikeshare 2011; Hubway 2011; Nice Ride MN 2011).Currently, Minnestoa’s Nice Ride spends $99,400 in replacing bicycle units from theft and vandalism from an annual replacement rate of five percent (Dossett 2008, 44). Therefore, safety is usually made apparent from the Bike Share vendor to its customers by encouraging them to wear helmets and to take bicycle training classes about road rules. Generally, helmets are for sale near Bike Share stations. Additionally in terms of theft, the Smart Bikes are made with puncture proof tires, a rigid frame, illuminating colors, require unique disassembly components, and unusual dimensions to stand out from other bicycles [Figure 1] (DeMaio and Gifford 2004, 10).
  6. 6. 6 Figure 1 Bike Share Bicycle depicted in VTA’s Bike Share Pilot Project PHASE 1 Implementation Plan Bike Share in the bay area The Bay Area is in development of a Bike Share program led by the Bay Area Air Quality Management District (BAAQMD) and is going to launch its pilot program next summer in June to last only one year until the final implementation plans go through (Cuenco, 2011; Wenzinger, 2011; Zenobi, 2011). About 1,000 bikes will be available in the whole region of three counties: San Francisco, Santa Clara, and San Mateo. In the County of Santa Clara, San Jose, Mountain View, and Palo Alto will have bikes, and in San Mateo, only Redwood City will have bikes (Cuenco, 2011; Wenzinger, 2011; Zenobi, 2011). About 100 bikes will be given to each city (Cuenco, 2011; Wenzinger, 2011; Zenobi, 2011). The Safe Roots to Transit Regional Measure 2 has extracted one dollar from bridge toll increases to go into the Bike Share program via the Valley Transportation Authority (VTA) in the Santa Clara County (Cuenco, 2011; Wenzinger, 2011; Zenobi, 2011). VTA controlled the Bike Share program until the Metropolitan Transportation Commission stepped in along with the BAAQMD due to a federal grant from Federal Transportation Dollars (Cuenco, 2011; Wenzinger, 2011; Zenobi, 2011). The total amount of money for the entire program will be 7.9 million dollars (Cuenco, 2011; Wenzinger, 2011; Zenobi, 2011; San Francisco Chronicle 2011). The Valley Transportation Authority (VTA) provides San Jose public transit services and is in charge of finding a Bike Share vendor for pricing and locations of the bikes and stations (aka pods or kioks) respectively. Furthermore, the cities of San Jose, Mountain View, Redwood City, Palo Alto, and San Francisco will receive about 100 bicycles each and 10 to 12 stations will be available for Bike Share within a 1 to 3 mile radius from a main public transit station. VTA’s Bike Share Pilot Project PHASE 1 Implementation Plan states that “priority areas considered for potential pod sites include the downtowns, universities (if located in either San Jose or Palo Alto) and City Halls” ( 2010, 7). However, the exact locations and prices are unkown. Bike Share programs are supposed to have a high demand in order for it to be successful. Even though bicycle use in the United States is low, it is still growing. It had risen from 0.6% to 0.9% within the years 1977 to 1995, and is now at 1% (Pucher et.al, 2011). The area of this study was in San Jose, California since it is one of the Bay Area cities that received funding for the pilot Bike Share Program that will launch in the summer of 2012 (Pucher et.al, 2011). However, according to the United Stated Census, San Jose’s population is 945,942 and has a low population density of 5,256.2 people per square mile. San Jose’s General Plan: Envision 2040 shows that 1.2% of commuter trips are made by bicycle and San Jose’s Bike Plan 2020 states that 1% of all trips in San Jose are made by bicycles, just like the national percentage. San Jose is known for its wide spread of single-family homes and car friendly infrastructure, but in order to survive, Bike Share Programs need demand, infrastructure, facilities, safety, profitability or surplus revenues, and multi-modal connectivity (DeMaio and Gifford 2004, 10). Bike Share programs are inclusively a good start to reduce vehicle miles traveled (VOTs). For example, the Twin-Cities in Minnesota have started a successful Bike Share program that focuses on high density areas in which to connect the public to public transportation (Dossett 2008).
  7. 7. 7 Objective of study • To evaluate whether there was a significant correlation between people’s ages and their willingness to pay for daily, weekly, monthly, and annual passes San Jose’s Bike Share pilot program will provide. • To find quantitative and qualitative measures as to why, why not, and what people would use the Bike Share program to ultimately determine where stations should be placed. METHODS Study Design The design of this study is to evaluate whether there is a significant correlation between people’s ages and their willingness to pay for San Jose’s Bike Share pilot program (figure 2). Qualitative meaures such as why or why not people would use the Bike Share program were also analyzed. By 2012, 10 to 12 stations will be available for bikeshare within a 1 to 3 mile radius from the Diridon Station located at Santa Clara and Montgomery St (VTA 2011, 7). The Valley Transportation Authority (VTA) provides San Jose public transit services and is in charge of finding a Bike Share vendor for pricing and locations of the bikes and stations (aka pods or kiosks) respectively. VTA’s Bike Share Pilot Project PHASE 1 Implementation Plan states that “priority areas considered for potential pod sites include the downtowns, universities (if located in either San Jose or Palo Alto) and City Halls” ( 2010, 7). However, the exact locations and prices are unkown. Therefore, three different cities’s bikeshare programs such as Boston Massachusettes’s Hubway Bike Share, Washington D.C.’s Capital Bike Share, and Minneapolis Minesota’s Nice Ride Bike Share have been analyzed for pricing.Exactly 115 out of 120 surveys in five different regions were conducted. Within the three regions, 40 surveys were carried out (figure 3). Every region had four subregions in which 10 surveys were filled out.
  8. 8. 8 Figure 2 Diagram of the broad approach to this study: The affect of bikeshare demand by finding the correlation of age and prices Figure 3 Regional Survey Map with three regions. Within each region are sub-region that will have 10 surveys conducted, thus every region will have 40 suvery conducted, for a total of 120 surveys. Each participant will be surveyed in a manner that will result in both qualitative and quantitative measurements in each region. . The qualitative measurements and quantitative measurements will be calculated in Microsoft Excel and Systat . The calculations of the raw data collected from the surveys will produce results in diagrams, graphs, and charts that will visually aid audiences. The results will lead to analytical conclusions and recommendations of the study.
  9. 9. 9 Data Collection The exact locations of the bikeshare stations are currently unkown. The pilot program for the Bay Area wide bikeshare project will launch in either June or July next summer of 2012 (Wenzinger, 2011). The prices for the pilot program is also in its developmental phases. Patrick E. Wenzinger, the Administrative Analyst Strategic Incentive Division for the Bay Area Air Quality District projects that the Bike Share program extending from the san Francisco County, San Mateo County, and all the way down to Santa Clara County will emulate Boston, Massachusette’s Bike Share paying/pricing system, where the first 30 minutes of utilization will be free. To keep the program a “sharing” system rather than “renting,” an ascending fee will be imposed on the user after each 30 minute increments are up after the first “free” 30 minutes. The VTA Implementation Plan Phase 1 mentions that the Bike Share stations will most likely be placed near station areas (Diridon Station), city government (San JoseCity Hall), and universities (San Jose State University). With 120 surveys printed out, a clipboard, and multiple pens, the three different regions illustrated in figure 3 were visited. Survey participants were randomly selected based off of flipping a coin to a group or in range of the survey area. If the flipped coin landed on heads, then that result would be “yes” or affirmatively approving whether the individual(s) would be surveyed. However, if the coin were to land on tails, then it would result to “no” and the next individual(s) in range would be be potentially surveyed (figure 4). Prior to filling out surveys, participants were educated on how Bike Share systems work. Once the randomly slected people were given surveys, they were allowed to answer all questions freely. Although participants were given a range within the questions about their willingess to pay, it was verbally stated to them that they were free to go beyond the range. The ranges only served as an indicator to show that the price’s range can be as low as free to significantly expensive based off their personal opinion.
  10. 10. 10 Figure 4 a copy of the survey handed out to randomly selected participants. The first region that was surveyed was the Diridon Station located on West Santa Clara Street and Cahill Street in San Jose, California from 12pm to 6pm on Thursday, October 20th , 2011 during commute and non-commuting hours (figure 5). The four sub-regions visited in order were: the bus stop area as the first, the first and second train tracks (Caltrain, Altamont Commuter Express, and Amtrak) as the second sub-region, the third and fourth train tracks (also Caltrain, Altamont Commuter Express, and Amtrak) as the third sub-region, and the Valley Transporation Authority lightrail tracks as the fourth survey set (sub-region).
  11. 11. 11 Figure 5 The figure shows the sub-regions of Region 1: Diridon Station The second region was located at San Jose City Hall, 200 E. Santa Clara Street, San Jose California and conducted at 5:30 pm on Tuesday, October 18th , 2011 during commuting hours (figure 6). The sub-regions in the City Hall region were also divided into four sub-regions, the streets that surround City Hall. Fourth Street as the first survey sub-region, Santa Clara Street as the second, San Fernando Street as the third, and 6th Street as the fourth. The third survey region was San Jose State University, 1 Washington Square San Jose, California at 5:30 p.m. on Wednesday October 20th , 2011 during commute hours. Broken up into four sub-regions, the first survey area was on 4th Street, the second on San Fernando Street , the third on San Salvador Street, and the fourth on 10th Street (Figure 6).
  12. 12. 12 Figure 6 This figure shows Regions 2 and 3 and its sub-regions of surveys conducted Within each survey, people were asked if they would use Bike Share; why or why they would not use it; how much they are willing to pay for a daily, weekly, monthly, and annual passes; and finally their age. Participants were free to answer the questions however they wanted. For example, if they stated they did not want to use the program, but felt like it was a great idea and wished to hypothetically fill out their willingess to pay questions, then they were granted to do so. Furthermore, if the surveyed individual wished to fill in a price beyond the range listed, then they were allowed to do so. If a applicant wished not to answer certain questions, they did not have to.
  13. 13. 13 Data Analysis After all 120 surveys were collected, a quantitative analysis in the form of a linear regression analyis was conducted. Using Microsoft Excel 2007 and Systat 13, a visual demonstration was produced to observe whether there was a significant correlation between two continuous variables: age and the prices people were willing to pay for Bike Share. Qualitiative measurements were also conducted with the aid of Microsoft Excel 2007 and Systat 13. Several graphs were created based on the type of paying methods they were asked in the survey. The r- square (R2) to find a line of best fit was specifically looked for in the linear regression analysis. The R2 is used as a prediction measurement and in a scatter plot, the better the line of best fit is (when plots fit on the line), the more a person can make a prediction about a relationship. The p- values were evaluated in which it allowed the determination of whether there was a significant linear correlation between the continuous variables. A p-value less than .05 indicated whether something was considered significant. An R2 between .5 and 1 was considered to be a good value to indicate that the plots on a graph were closer to the line of best fit. Averages of age and willingness to pay at large and by regions were calculated for quantitative purposes and chi- square test of associations were also evaluated for both qualitative and quantitative measures such as the reasons why people would use Bike Share or not at large or by its region,. Furthermore, people’s age in relation to Bike Share use, and age distribution by region respectively were part of the qualitative measurements. The actual cost of Bike Share was calculated through Microsoft Excel 2007 by finding the average costs of Boston, Massachusetts, Minneapolis/Saint Paul, Minnesota, and Washington D.C.’s prices (figure 7).
  14. 14. 14 Washington D.C.- http://www.capitalbikeshare.com/pricing Minneapolis, MN/St.Paul- https://secure.niceridemn.org/map/ Boston, MA -https://secure.niceridemn.org/map/ Figure 7 Price scheme for Washington D.C., Minneapolis/Saint Paul Minnesota, and Boston, Massachusetts Hypotheses 1) The older a person is, the less they are willing to use Bike Share. 2) The younger a person is, the more they are willing to use Bike Share. 3) The younger a person is, the more they are likely to pay lower prices for Bike Share. 4) The older the person is, the more they are likely to pay higher prices for Bike Share. 5) People who would not use Bike Share would tend to not use it because they would rather drive. 6) People who would use Bike Share would use it for recreational purposes. Null hypothesis: 7) The older a person is, the more they are willing to use Bike Share. 8) The younger a person is, the less they are willing to use Bike Share. 9) The younger a person is, the more they are likely to pay higher prices for Bike Share. 10) The older the person is, the more they are likely to pay lower prices for Bike Share. 11) People who would not use Bike Share would tend to use it because they would rather not drive. 12) People who would use Bike Share would, on average, would not use it for recreational purposes.
  15. 15. 15 RESULTS Regression Analysis: Age vs. Willingness to Pay The regression analysis performed between people’s willingness to pay and their age showed no significant correlations (figures 1-4). All p-values resulted in scores over .05 and all squared multiple R numbers were well below 0.5. In order of daily, weekly, monthly, and annual passes, the p-values resulted in 0.309, 0.099, 0.570, and 0.082(figures 7-10). For the squared multiple R in the same order the values were 0.006, 0.042, 0.045, and 0.002. The actual costs of Bike Share from daily to annual passes were: $5.67, $13.50, $27.50, and $73.33. p-Value 0.309 Figure 8 Regression Analysis, the estimate line shows a negative correlation between daily passes and age. The older a person is, the less they are willing to pay. However, there is no significant correlation between age and the willingness to pay for a Bike Share pass due to its p- value of .309. There are also many plots missing on the estimate line and several outlying plots such as the 22 year old willing to pay $35 for a daily pass. The R squared value is 0.0064, thus giving no prediction of future outcomes. y = -0.0315x + 5.071 R² = 0.0064 0 5 10 15 20 25 30 35 40 0 20 40 60 80 D A I L Y P A S S AGE Bike Share: Age vs Daily Pass Actual Cost Linear (Bike Share: Age vs Daily Pass) Linear (Actual Cost ) Bike Share: Age vs Daily Pass
  16. 16. 16 p-Value 0.099 Figure 9 Regression Analysis, the estimate line shows a negative correlation between daily passes and age. The older a person is, the less they are willing to pay. There is no significant correlation between age and the willingness to pay for a Bike Share weekly pass due to its p- value of 0.099. However, 0.099 indicates a trend. There are also many plots missing on the estimate line and several outlying plots such as the 22 year old willing to pay over $100 for a weekly pass. The R squared value is 0.042, thus giving no prediction of future outcomes. y = -0.308x + 26.83 R² = 0.042 0 20 40 60 80 100 120 0 20 40 60 80 W E E K L Y P A S S AGE Bike Share: Age vs Weekly Pass Actual Cost Linear (Bike Share: Age vs Weekly Pass) Linear (Actual Cost) Bike Share: Age vs Weekly Pass
  17. 17. 17 p-Value 0.570 Figure 10 Regression Analysis, the estimate line shows a negative correlation between daily passes and age. The older a person is, the less they are willing to pay. There is no significant correlation between age and the willingness to pay for a Bike Share weekly pass due to its p- value of 0.570. There are also many plots missing on the estimate line and several outlying plots such as the 57 year old willing to pay over $250 for a monthly pass. The R squared value is 0.0045, thus giving no prediction of future outcomes. y = -0.3112x + 63.876 R² = 0.0045 0 50 100 150 200 250 300 0 20 40 60 80 M O N T H L Y P A S S AGE Bike Share: Age vs Monthly Pass Actual Cost Linear (Bike Share: Age vs Monthly Pass) Linear (Actual Cost) Bike Share: Age vs Monthly Pass
  18. 18. 18 p-Value 0.082 Figure 11 Regression Analysis, the estimate line shows a negative correlation between annual passes and age. The older a person is, the more they are willing to pay. However, there is no significant correlation between age and the willingness to pay for a Bike Share pass due to its p- value of .082. The p-value for this result indicates an even stronger trend than the weekly pass. There are many plots missing on the estimate line and thus outlying plots such as the 62 year old willing to pay over $500. The R2 is 0.001, thus showing no significant correlation between age and willingness to pay for a daily pass and the fact that plots are far away from the line of best fit fives no prediction model. Bike Share Use Although there were no significant correlations between age and the willingness to pay, several other figures had arisen. The number of people surveyed, 115, are almost exactly split in half in either using Bike Share or not. The number of people who chose to use it was 58 persons while 57 chose not to (Table 1). y = -0.390x + 150.3 R² = 0.001 0 100 200 300 400 500 600 0 20 40 60 80 A N N U A L P A S S AGE Bike Share: Age vs Annual Pass Actual Cost Linear (Bike Share: Age vs Annual Pass) Linear (Actual Cost) Bike Share: Age vs Annual Pass
  19. 19. 19 People Who Would Either Use Bike Share or Not Yes No 58 57 Total: 115 Figure 12 Preference of using Bike Share or not was split right down the middle. However, more people preferred to use Bike Share by one score, 58 to 57. Calculated Averages The average willingness to pay for a daily pass is $6.44, $28.43 for a weekly pass, $88.62 for a monthly pass, and $227.29 for an annual pass (table 1). The average age of all participants was 29.44. 0 50 Yes No P e o p l e Would You Use Bike Share? Bike Share Use Bike Share Use
  20. 20. 20 Table 1 All the averages put together from all regions and the averages in each region for the willingness to pay and the ages for all the survey participants are found here. Qualitative Measurements The reasons for using Bike Share or not were split into five main categories, two for using Bike Share and three for not using Bike Share. The first two main reasons for using Bike Share were either for errands or for leisure. The three main reasons for not using Bike Share were because the participant neither can use, will not, or would rather use something else other than Bike Share. Just as there are categories for the reasons to use Bike Share or not, there are subdivisions within those categories as well. The following subcategories made up the sum of the leisure category: 1) Sports 2) Recreation 3) Kids 4) Exercise 5) Friends or family 6) Trails The following subcategories made up the sum of the errands category: 1) Get around Downtown 2) Practice 3) Work related 4) Transit stations
  21. 21. 21 5) Shopping 6) Save gas 7) Safety 8) School 9) Home 10) Library 11) Convenience 12) Everything important 13) Emergencies 14) Hassle The following subcategories made up the sum of people who said they cannot use Bike Share because: 1) Does not know how 2) Too lazy 3) Exhausted 4) Disabilities 5) Does not bike 6) Poor 7) No, kids The following subcategories made up the sum of people who said they will not use Bike Share because: 1) Already Owns long board 2) Already owns bike 3) Theft 4) Accidents 5) Maintenance 6) No need The following subcategories made up the sum of people who said they rather: 1) Own bike 2) Use public transportation 3) Walk 4) Drive 5) Not because only within walking/driving range 6) Not use because hardly travels 7) Not use it because lives nearby 8) Use something else because a non San Jose resident 9) Not because not near public transportation
  22. 22. 22 Leisure and errands Most of the participants who would use Bike Share for reasons of leisure came from San Jose State University. However, the case is different when it comes to errands. Diridon Station carried most of the reasons for errands. There were nine reasons for Bike Share leisure uses in San Jose State University (SJSU) while City Hall and Diridon Station resulted in four (table 2). For reasons of errands, Diridon Station had 26 reasons while City Hall had 25, and SJSU produced 19 reasons (table 3). Table 2 Number of reasons to use Bike Share for leisure by region Table 3 Number of reasons to use Bike Share for errands by region Errands(rows) by Region(columns) Number of Reasons Diridon City Hall SJS U Total 0 3 1 6 10 1 11 8 11 30 2 6 7 1 14 3 1 1 2 4 Total 21 17 20 58 Cannot, will not, and rather not People who did not want to use Bike Share centered at San Jose City Hall. Eight reasons for people who cannot use Bike Share at City Hall outnumbered the five reasons produced from both San Jose State University and Diridon Station. In the same order, but for people who will not use Bike Share for their own reasoning numbered at 14 at City Hall, six for SJSU, and five at Diridon Station. For reasons of rather using some other mode of transportation over Bike Share, City Hall again outnumbers other regions by generating 15 reasons, 13 reasons at SJSU, and nine reasons at Diridon Station. Leisure (rows) by Region(columns) Number of Reasons Diridon Station City Hall SJS U Total 0 17 13 12 42 1 3 3 7 13 2 1 1 1 3 Total 21 17 20 58
  23. 23. 23 Table 4 Number of reasons people cannot use Bike Share by region Cannot Use (rows) by Region (columns) Number of Reasons Diridon Station City Hall SJSU Total 0 9 15 15 39 1 5 8 5 18 Total 14 23 20 57 Table 5 Number of reasons people will not to use Bike Share by region Will Not Use(rows) by Region (columns) Number of Reasons Diridon Station City Hall SJSU Total 0 11 9 14 34 1 2 14 6 22 3 1 0 0 1 Total 14 23 20 57 Table 6 Number of reasons people would rather use something else by region. Rather Use Something Else(rows) by Region (columns) Number of Reasons Diridon Station City Hall SJSU Total 0 6 10 10 26 1 7 11 8 26 2 1 2 1 4 3 0 0 1 1 Total 14 23 20 57 Furthermore on Age and Bike Share Use There are more people who were the ages of 18 through 27 than 28 through 76. Ages 18 through 27 had at least four people who had been surveyed and the rest of the ages were either one, two , or three (tables 7 and 8). While San Jose State University had the youngest population, Diridon Station had the oldest and City Hall was in the middle (table 8). Most people said they would use Bike Share at Dirdon Station (21 scores) as opposed to City Hall which is the exact opposite (23 scores). People near San Jose State University were neutral, with 20 saying yes and 20 saying no about using Bike Share (table 9).
  24. 24. 24 Table 7 This table shows the distribution of age (rows) and whether the individual would like to use Bike Share or not. Age (rows) by Bike Share Use (columns) Age No Yes Total 18 6 4 10 19 2 5 7 20 2 4 6 21 3 6 9 22 7 3 10 23 3 2 5 24 4 5 9 25 2 3 5 26 4 5 9 27 2 2 4 28 0 2 2 29 1 2 3 30 3 0 3 31 1 1 2 32 0 1 1 33 1 2 3 34 1 0 1 35 2 1 3 37 0 1 1 38 0 1 1 40 0 1 1 41 1 1 2 42 1 0 1 43 0 1 1 45 3 0 3 47 1 0 1 50 1 0 1 51 1 1 2 52 1 0 1 55 1 0 1 57 0 1 1 58 1 0 1 60 0 1 1 61 0 1 1 71 0 1 1 75 1 0 1 76 1 0 1 Total 57 58 115
  25. 25. 25 Table 8 This table shows the distribution of age within each region of surveys conducted. Age (rows) by Region (columns) Diridon StationCity HallSJSUTotal 18 2 2 6 10 19 1 2 4 7 20 2 1 3 6 21 3 4 2 9 22 3 3 4 10 23 0 2 3 5 24 2 4 3 9 25 0 2 3 5 26 1 5 3 9 27 3 0 1 4 28 2 0 0 2 29 2 0 1 3 30 0 1 2 3 31 1 1 0 2 32 1 0 0 1 33 1 2 0 3 34 0 1 0 1 35 1 0 2 3 37 1 0 0 1 38 0 0 1 1 40 1 0 0 1 41 0 1 1 2 42 0 1 0 1 43 0 1 0 1 45 1 2 0 3 47 1 0 0 1 50 0 1 0 1 51 1 1 0 2 52 0 0 1 1 55 0 1 0 1 57 1 0 0 1 58 1 0 0 1 60 1 0 0 1 61 0 1 0 1 71 1 0 0 1 75 0 1 0 1 76 1 0 0 1 Total 35 40 40 115
  26. 26. 26 Table 9 People who would either use or not use Bike Share are split up in the three regions of survey collection. Region (rows) by Bike Share Use (columns) Region No Yes Total Diridon 14 21 35 City Hall 23 17 40 SJSU 20 20 40 Total 57 58 115 DISCUSSION In response to the hypotheses proposed: 1) The older a person is, the less they are willing to use Bike Share. 2) The younger a person is, the more they are willing to use Bike Share. The results to this research suggested that these hypotheses are true; however, there was an imbalance of the number of older people surveyed. 3) The younger a person is, the more they are likely to pay higher prices for Bike Share. 4) The older the person is, the more they are likely to pay higher prices for Bike Share. This section of hypotheses was rather surprising. All parties were willing to pay higher prices than the actual cost. However, again, a larger sample size is needed to make a better judgment because for weekly and annual passes, a trend is evident and the line of best fit is negative, thus indicating that older people would prefer to pay lower passes. 5) People who would not use Bike Share would tend to not use it because they would rather drive. 6) People who would use Bike Share would use it for recreational purposes. Both of these hypotheses are true, however, many people did not want to use Bike Share because they would rather own their own bike, would rather take public transit, or would rather walk or drive because their mandatory daily trips require long distances to use a car or they are so close to their destination that they would rather walk. Many reasons such as not being able to walk, laziness or exhaustion were made apparent. Also, people stated that they will not use Bike Share because they are afraid hypothesis did not support the bigger picture of the outcome the results gave. The sum of multiple reasons as to whether someone would use Bike Share or not was calculated because there were great similarities within all the types of responses survey participants had. The regression analyses between age and willingness to pay were all considered insignificant because of their p-values. Therefore, it was surprising that there was no perceptible significant correlation between the two. However, a trend was indicated between age and willingness to pay for weekly and annual passes due to their p-values, 0.099 and 0.082 respectively were close to reaching 0.05. While the study’s age distribution was unequal and in
  27. 27. 27 favor of the younger populace, it is also interesting that both young and old individuals would pay relatively high prices for Bike Share regardless of region in comparison to prices in cities like Montreal, Boston, and Washington D.C have adopted. On average, the actual cost for weekly, monthly, and annual passes resulted in $13.50, $27.50 and $73.33 respectively while San Jose urbanites on average were willing to pay $28.43, $88.62, and $227.29 for the same exact passes. CONCLUSION/RECOMMENDATIONS As mentioned earlier, a larger sample size was needed. As dell ‘Ollio 2011 produced in Implementing bike-sharing systems, up to 768 people were surveyed, level of income, frequency of journey and gender were part of the analysis. Dell ‘Ollio, 2011 conducted a multiple step survey that included a survey to target households who would use a bicycle in any type of trip at least one of five times a week, then a follow up telephone survey would be implemented to find out the details. Although dell’Ollio 2011 only targeted bicyclers, it is still important to find out how many people would not use Bike Share, find out why they do not use it, and use the results to strengthen a program. For example, a bicycle riding educational workshop provided by the Bike Share vendor for people who do not know how to ride a bicycle would be an example of further pushing a Bike Share program to progression because of acquired knowledge of such studies that included why people would not use Bike Share. Nonetheless, finding out income brackets, gender, and the frequency of people’s journeys are essential and should be included in further analyses of implementing Bike Share systems. Most of all, larger sample sizes is vital to gain accurate data that represents the entire population. These results indicate that the San Jose survey participants are willing to pay about double, triple, and quadruple the amount of the actual cost for daily, weekly, monthly and annual passes correspondingly. San Jose Bike Share vendor can potentially increase its price to gain more revenue to support educational programs for safety, distribute helmets, student discounts, system maintenance, theft, infrastructure, vandalism, and potential liabilities. The San Jose Bike Share program is mostly supported by a young population with an elevated price for willingness to pay. It would be reasonable to place Bike Share stations near the beginning and end of residential areas, local shops, transit corridors, schools, and work areas, but not near public parking areas, bike rental and bike shops, skateboard shops, car dealerships, and bike racks due to the fact that most people who would not use Bike Share would rather use another mode of transportation or own a bike themselves. The Bay Area Air Quality Management District, the Valley Transportation Authority, and the Metropolitan Transportation Commission have all been looking at the City of Minneapolis/Saint Paul as an example to pursue the non-profit sector to be the Bike Share vendor. Dossett, B., Munger, J., & Bono, K. (2008) recommends non-profit organizations as vendors because the system they set in motion in Minneapolis/ Saint Paul function at low costs due to the utilization of public subsidies, and private in-kind sponsorships from local contractors and employees. Furthermore, the non-profit sector is obliged to sell subscriptions and must please its customers in order to continue its business. Assuming that the prices will reflect what other cities have done, the analyses of results indicate that San Jose Bike Share may be a success because people are willing to pay more than what may be put in place.
  28. 28. 28 The results produced in this study suggest that San Jose urbanites are willing to pay high costs for a Bike Share program. Therefore, San Jose’s Bike Share vendor may be able to afford improvement costs of its own system while still maintaining a low cost and affordable program. San Jose needs to actively support programs like Bike Share in order to take advantage of any benefit such as its relatively level, flat land and its increasing demand in bicycle use. Addressing the reduction of greenhouse gases, toxicity, and energy usage, and the promotion of a healthy lifestyle through biking are essential in a low dense city like San Jose that is constituted as a car- oriented place. The assumption that cheap oil will live forever has come to an end as global petroleum reserves dwindle in a world that excessively demands it. Mitigation measures must take place to reduce immense environmental impacts. Bike Share may be a promising foundation of the transition from a car demanding society to one that relies on alternative transportation.
  29. 29. 29 Figures 1. Envision 2040 San Jose and VTA Implementation Plan Bike Share Bicycle…………………………………………………………………………………..Cover 2. Figure 1 VTA Implementation Plan Bike Share Bicycle ....…………………………….. 5 3. Figure 2 Study Design ……….. ……………………………………………………8 4. Figure 3 Regional Survey Map…………………..……………………………….. 8 5. Figure 4 Copy of Survey………………………………………………………….. 10 6. Figure 5 Sub-Regional Map of Diridon Station….……………………………….. 11 7. Figure 6 Sub-Regional Map of San Jose City Hall and San Jose State University..12 8. Figure 7 Price Scheme of other Bike Share Vendors………..……………………. 14 9. Figure 8 Bike Share: Age vs. Daily Pass……………………...……………………15 10. Figure 9 Bike Share: Age vs. Weekly Pass ………………………………………...16 11. Figure 10 Bike Share: Age vs. Monthly Pass……………………………………... 17 12. Figure 11 Bike Share: Age vs. Annual Pass………………………………………. 18 13. Figure 12 Bike Share Use……………………..…………………………………... 19 14. Table 1 Age and Willingness to Pay Averages……………………………………..20 15. Table 2 Number of Leisure Reasons to Use Bike Share…………………………....22 16. Figure 3 Number of Errands Reasons to Use Bike Share by Region.…………… …22 17. Table 4 Number of Reasons People Cannot Use Bike Share by Region …………...23 18. Table 5 Number of Reasons People Will Not Use Bike Share by Region .…………23 19. Table 6 Number of Reasons People Rather Not Use Bike Share by Region ….……23 20. Table 7Age by rows and Bike Share Use by Columns….…………………………..24 21. Table 8 Age by Region ……………………………………………………………..25 22. Table 9 Bike Share Use by Region………………………………………………….26
  30. 30. 30 REFERENCES "American Fact Finder ." U.S. Census Bureau. http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml (accessed December 11, 2011). "Bay Area Air Pollution Summaries” Bay Area Air Quality Management District. http://www.baaqmd.gov/~/media/Files/Communications%20and%20Outreach/Annual% 20Bay%20Area%20Air%20Quality%20Summaries/pollsum09.ashx (accessed September 9, 2011). "Bike Plan 2020." City of San Jose Transportation Department. http://www.sanjoseca.gov/transportation/bikeped/supportFiles/bikeped/2010/BikePlan/Bi ke_Plan_2020,_Complete_Document.pdf (accessed December 12, 2011). Buehler, R. "Determinants of transport mode choice: a comparison of Germany and the USA." Journal of Transport Geography 19 (2010), www.elsevier.com/locate/jtrangeo (accessed September 9, 2011). "Climate Change." Environmental Protection Agency. http://www.epa.gov/climatechange/basicinfo.html#emissions (accessed September 9, 2011). "Capital Bike Share." http://www.capitalbikeshare.com/ (accessed September 1st, 2011). Cuenco, A. Valley Transportation Authority. (personal communication, September 1, 2011). "Currently Designated Nonattainment Areas for all Criteria Pollutants Environmental Protection Agency. http://epa.gov/oaqps001/greenbk/ancl.html (accessed September 9, 2011).
  31. 31. 31 DeMaio, P and J Gifford. "Will Smart Bikes Succeed as Public Transportation in the United States?." Journal of Public Transportation 7 (2004): 1-15. Dossett, B., Munger, J., & Bono, K. (2008). Non‐profit business plan for twin cities Bike Share system. The City of Minneapolis Community Planning and Economic Development Department, Public, 1-49. "Draft Envision San Jose 2040 Goals, Policies, & Actions Circulation Section." City of San Jose Planning Division. http://www.sanjoseca.gov/planning/gp_update/documents/Transportation_Goals_and_Pol icies_6-7-10TF_000.pdf (accessed December 12, 2011). Freeman, D. (2010). Changing employee parking and eco pass policies at san josé state university. 1-89. "Data Tables." Environmental Protection Agency. http://www.epa.gov/air/airtrends/aqtrnd99/pdfs/Appena.pdf (accessed September 9, 2011). dell, L., Ibeas, A., & Moura, J. L. (2011). Implementing bike-sharing systems. Intitution of Civil engineers, 164(ME2), 89-101. Gerston, L. (2009). Confronting reality. (pp. 1-207). Dubuque: Kendall Hunt. Gordon, R. "Bike-sharing project expected to begin next year." San Fracnsico Chronicle , October 27, 2010, Collections section, http://articles.sfgate.com/2010-10- 27/news/24223536_1_bike-sharing-car-sharing-programs-timothy-papandreou (accessed September 1st, 2011). "Hubway." http://www.thehubway.com/ (accessed September 1st, 2011). Logan, Michael. “Coal Should Not Be The Energy Of The Future. EJ3010502207 ” Opposing Viewpoints: Coal. Web. (2008).
  32. 32. 32 Martens, K. (2007). Promoting bike-and-ride: the dutch experience. Transportation Research Part A, 41, 326-338. Nazelle, Audrey, M.J Nieuwenhuijsen and J.P Anton'. "Improving health through policies that promote active travel: A review of evidence to support integrated health impact assessment." Environment International 37 (2011), www.elsevi e r.com/locate/envint (accessed September 9, 2011). "Nice Ride MN." https://www.niceridemn.org/ (accessed September 1st, 2011). Pucher, J, R Buehler and M Seinin. "Bicycling renaissance in North America? An update and re- appraisal of cycling trends and policies." Transportation Research Part A 45 (2011), sciencedirect.com (accessed September 9, 2011). Wenzinger, P. Bay Area Air Quality Management District. (personal communication, September 16, 2011). Snell, B. (n.d.). The streetcar conspiracy how general motors deliberately destroyed public transit. Retrieved from http://webcache.googleusercontent.com/search?q=cache:5gyumw8qPXMJ:www.lovearth .net/gmdeliberatelydestroyed.htm+When+GM+buys+out+Los+Angeles+public+ transportation%3F&cd=2&hl=en&ct=clnk&gl=us&client=firefox-a Streetfilms. “Cycling Copenhagen, Through North American Eyes.” http://www.streetfilms.org/cycling-copenhagen-through-north-american-eyes/ (accessed August 5, 2011). "Source Inventory of Bay Area Greenhouse Gas Emissions” Bay Area Air Quality Management District. http://www.baaqmd.gov/~/media/Files/Planning%20and%20Research/Emission% 20Inventory/regionalinventory2007_2_10.ashx (accessed September 9, 2011). Titze, S., Stronegger, W. J., Janschitz, S., & Oja, P. (2008). Association of built-environment,
  33. 33. 33 social-environment and personal factors with bicycling as a mode of transportation among austrian city dwellers. Preventive Medicine, 47, 252-259. Valley Transportation Authority, (2010). Bike Share Pilot Project Phase 1 Implementation Plan Draft . Zenobi, E. San Jose State University Associated Students: Transportation Solutions. (personal communication, September, 1, 2011).

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