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Investigating Impact of Crowdsourcing on Transit Ridership
A. Taniguchi et al. / Journal of Transport & Health 3 (2016) S62–S78
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places have low probabilities of cardiac arrest occurrence and defibrillators in such places are not used. Public transport nodes in Japan are quite crowded because public transportation is the main travel mode of commuting; and interventions towards such places are efficient. http://dx.doi.org/10.1016/j.jth.2016.05.004
P02 Investigating Impact of Crowdsourcing on Transit Ridership Shailesh Chandra 1, Parth Thakkar 2, Neel Pandya 1, Ajay Zalavadia 1 1 2
California State University, Long Beach, Long Beach, CA, USA Texas A&M University Health Science Center, Austin, TX, USA
Abstract Background: Several research studies show that frequent walking to public transit improves physical activity. In this research, transit ridership is treated as the surrogate of physical activity. Thus, Los Angeles (LA) Metro's light rail transit (LRT) ridership changes are investigated vis-à-vis monthly retweets (as crowdsourcing information) by Metro's Twitter followers. Although LA Metro's twitter account has close to fifty thousand direct followers, there are several indirect followers or beneficiaries of tweets shared by direct followers. In essence, when the direct followers retweet or forward information shared by LA Metro about delays and service disruptions on a LRT line, crowdsourcing of information occurs. Therefore, based on the crowdsourced information both the direct as well as indirect followers of LA Metro decide or readjust their travel plans in order to ride or to avoid a particular transit line. Our literature survey shows that this work is a first of its kind in investigating impact of crowdsourcing on potential impact on public transit ridership. Methods: A comparative analysis has been carried out by compiling retweets from LA Metro's twitter webpage and the ridership data for seven LRT lines operated by LA Metro - Orange, Silver, Red, Blue, Expo, Green and Gold. The ridership data were collected from LA Metro's website. Since this research commenced in December 2015 and is to considered as an ongoing research, the ridership data collected so far are for those available for three consecutive months of October, November and December in 2015. A total of 1076 tweets as crowdsourced retweets related to delays and service disruptions of LRT were from direct followers of LA Metro. These retweets were correlated with probable impact on ridership of LRT lines. Results: The number of crowdsourced retweets and the monthly percentage ridership change for all seven LRT lines were examined as two variables for correlation using IBM SPSS Statistical package. Our results indicate a statistically significant strong positive correlation between the two variables (with Pearson's r ¼ 0.791, n ¼ 7, p ¼ 0.034) for the month of November. Blue Line transit riders were found to be potentially the most influenced while Expo Line, Green Line and Gold Line transit riders were potentially the least influenced by their transit specific retweets. Conclusions: From preliminary data analysis in this ongoing research (scheduled to conclude in April 2016), crowdsourcing retweets and transit ridership could potentially be correlated. http://dx.doi.org/10.1016/j.jth.2016.05.005
P03 Can Promoting Use of Public Transportation Improve People's Health? -Analysis Focusing on Relationship Among Health, Lifestyle and Transportation Habit y Cross-Regional DataYusuke Kanda 1, Ayako Taniguchi 2, Satoshi Fujii 1, Takeru Mori 3 1
Kyoto University, Japan University of Tsukuba, Risk Engineering, Japan 3 NTT Facilities, Inc., Japan 2
Abstract Background: It is often said that lifestyle is quite important for better health. Especially, improvement of physical activity level brings better effects on individual's health condition. Non-car transportation use such as walk, bicycle, and public transportation provides more
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places have low probabilities of cardiac arrest occurrence and defibrillators in such places are not used. Public transport nodes in Japan are quite crowded because public transportation is the main travel mode of commuting; and interventions towards such places are efficient. http://dx.doi.org/10.1016/j.jth.2016.05.004
P02 Investigating Impact of Crowdsourcing on Transit Ridership Shailesh Chandra 1, Parth Thakkar 2, Neel Pandya 1, Ajay Zalavadia 1 1 2
California State University, Long Beach, Long Beach, CA, USA Texas A&M University Health Science Center, Austin, TX, USA
Abstract Background: Several research studies show that frequent walking to public transit improves physical activity. In this research, transit ridership is treated as the surrogate of physical activity. Thus, Los Angeles (LA) Metro's light rail transit (LRT) ridership changes are investigated vis-à-vis monthly retweets (as crowdsourcing information) by Metro's Twitter followers. Although LA Metro's twitter account has close to fifty thousand direct followers, there are several indirect followers or beneficiaries of tweets shared by direct followers. In essence, when the direct followers retweet or forward information shared by LA Metro about delays and service disruptions on a LRT line, crowdsourcing of information occurs. Therefore, based on the crowdsourced information both the direct as well as indirect followers of LA Metro decide or readjust their travel plans in order to ride or to avoid a particular transit line. Our literature survey shows that this work is a first of its kind in investigating impact of crowdsourcing on potential impact on public transit ridership. Methods: A comparative analysis has been carried out by compiling retweets from LA Metro's twitter webpage and the ridership data for seven LRT lines operated by LA Metro - Orange, Silver, Red, Blue, Expo, Green and Gold. The ridership data were collected from LA Metro's website. Since this research commenced in December 2015 and is to considered as an ongoing research, the ridership data collected so far are for those available for three consecutive months of October, November and December in 2015. A total of 1076 tweets as crowdsourced retweets related to delays and service disruptions of LRT were from direct followers of LA Metro. These retweets were correlated with probable impact on ridership of LRT lines. Results: The number of crowdsourced retweets and the monthly percentage ridership change for all seven LRT lines were examined as two variables for correlation using IBM SPSS Statistical package. Our results indicate a statistically significant strong positive correlation between the two variables (with Pearson's r ¼ 0.791, n ¼ 7, p ¼ 0.034) for the month of November. Blue Line transit riders were found to be potentially the most influenced while Expo Line, Green Line and Gold Line transit riders were potentially the least influenced by their transit specific retweets. Conclusions: From preliminary data analysis in this ongoing research (scheduled to conclude in April 2016), crowdsourcing retweets and transit ridership could potentially be correlated. http://dx.doi.org/10.1016/j.jth.2016.05.005
P03 Can Promoting Use of Public Transportation Improve People's Health? -Analysis Focusing on Relationship Among Health, Lifestyle and Transportation Habit y Cross-Regional DataYusuke Kanda 1, Ayako Taniguchi 2, Satoshi Fujii 1, Takeru Mori 3 1
Kyoto University, Japan University of Tsukuba, Risk Engineering, Japan 3 NTT Facilities, Inc., Japan 2
Abstract Background: It is often said that lifestyle is quite important for better health. Especially, improvement of physical activity level brings better effects on individual's health condition. Non-car transportation use such as walk, bicycle, and public transportation provides more