Environmental benefits of bike sharing: A big data-based analysis

Applied Energy

Volumn 220, Issue , 2018, Pages 296-301

  Zhang, Yongping ^a   Mi, Zhifu ^b  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Air pollution; Big data; Bike sharing; Carbon emissions; Energy consumption; Sharing economy

Indexed keywords

AIR POLLUTION; BICYCLES; BIG DATA; CARBON DIOXIDE; ENERGY UTILIZATION; NITROGEN OXIDES; POPULATION STATISTICS;

BIKE SHARING; CARBON EMISSIONS; ENERGY USE; ENVIRONMENTAL BENEFITS; NOX EMISSIONS; POPULATION DENSITIES; REDUCE ENERGY CONSUMPTION; SHARING ECONOMY;

DATA SHARING;

ATMOSPHERIC POLLUTION; CARBON EMISSION; DATA ASSIMILATION; ENERGY USE; NITROGEN OXIDES; PETROLEUM; POPULATION DENSITY; TRANSPORTATION PLANNING;

CHINA; SHANGHAI;

EID: 85044599823     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2018.03.101     Document Type: Article

References (42)

1. O'Brien, O., Cheshire, J., Batty, M., Mining bicycle sharing data for generating insights into sustainable transport systems. J Transp Geogr 34 (2014), 262–273, 10.1016/j.jtrangeo.2013.06.007.
2. Annarelli, A., Battistella, C., Nonino, F., Product service system: a conceptual framework from a systematic review. J Clean Prod 139 (2016), 1011–1032, 10.1016/J.JCLEPRO.2016.08.061.
3. Mont, O., Clarifying the concept of product–service system. J Clean Prod 10 (2002), 237–245, 10.1016/S0959-6526(01)00039-7.
4. Piscicelli, L., Cooper, T., Fisher, T., The role of values in collaborative consumption: insights from a product-service system for lending and borrowing in the UK. J Clean Prod 97 (2015), 21–29, 10.1016/J.JCLEPRO.2014.07.032.
5. Caulfield, B., O'Mahony, M., Brazil, W., Weldon, P., Examining usage patterns of a bike-sharing scheme in a medium sized city. Transp Res Part A Policy Pract 100 (2017), 152–161, 10.1016/j.tra.2017.04.023.
6. Martens, K., Promoting bike-and-ride: the Dutch experience. Transp Res Part A Policy Pract 41 (2007), 326–338, 10.1016/J.TRA.2006.09.010.
7. Mont, O., Institutionalisation of sustainable consumption patterns based on shared use. Ecol Econ 50 (2004), 135–153, 10.1016/J.ECOLECON.2004.03.030.
8. Médard de Chardon, C., Caruso, G., Estimating bike-share trips using station level data. Transp Res Part B Methodol 78 (2015), 260–279, 10.1016/j.trb.2015.05.003.
9. Pfrommer, J., Warrington, J., Schildbach, G., Morari, M., Dynamic vehicle redistribution and online price incentives in shared mobility systems. IEEE Trans Intell Transp Syst 15 (2014), 1567–1578, 10.1109/TITS.2014.2303986.
10. Forma, I.A., Raviv, T., Tzur, M., A 3-step math heuristic for the static repositioning problem in bike-sharing systems. Transp Res Part B Methodol 71 (2015), 230–247, 10.1016/j.trb.2014.10.003.
11. Pal, A., Zhang, Y., Free-floating bike sharing: solving real-life large-scale static rebalancing problems. Transp Res Part C Emerg Technol 80 (2017), 92–116, 10.1016/j.trc.2017.03.016.
12. Wood, J., Slingsby, A., Dykes, J., Visualizing the dynamics of London's bicycle hire scheme. Cartogr Int J Geogr Inf Geovisualization 46 (2011), 239–251, 10.3138/carto.46.4.239.
13. Zaltz Austwick, M., O'Brien, O., Strano, E., Viana, M., The structure of spatial networks and communities in bicycle sharing systems. PLoS One, 8, 2013, e74685, 10.1371/journal.pone.0074685.
14. Beecham, R., Wood, J., Bowerman, A., Studying commuting behaviours using collaborative visual analytics. Comput Environ Urban Syst 47 (2014), 5–15, 10.1016/j.compenvurbsys.2013.10.007.
15. Bachand-Marleau, J., Lee, B., El-Geneidy, A., Better understanding of factors influencing likelihood of using shared bicycle systems and frequency of use. Transp Res Rec J Transp Res Board 2314 (2012), 66–71, 10.3141/2314-09.
16. El-Assi, W., Salah Mahmoud, M., Nurul Habib, K., Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto. Transportation (Amst) 44 (2017), 589–613, 10.1007/s11116-015-9669-z.
17. Faghih-Imani, A., Eluru, N., El-Geneidy, A.M., Rabbat, M., Haq, U., How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal. J Transp Geogr 41 (2014), 306–314, 10.1016/j.jtrangeo.2014.01.013.
18. Ogilvie, F., Goodman, A., Inequalities in usage of a public bicycle sharing scheme: socio-demographic predictors of uptake and usage of the London (UK) cycle hire scheme. Prev Med (Baltim) 55 (2012), 40–45, 10.1016/j.ypmed.2012.05.002.
19. Buck, D., Buehler, R., Happ, P., Rawls, B., Chung, P., Borecki, N., Are bikeshare users different from regular cyclists?. Transp. Res. Rec. J. Transp. Res. Board 2387 (2013), 112–119, 10.3141/2387-13.
20. Buehler, R., Determinants of bicycle commuting in the Washington, DC region: the role of bicycle parking, cyclist showers, and free car parking at work. Transp Res Part D Transp Environ 17 (2012), 525–531, 10.1016/j.trd.2012.06.003.
21. Fuller, D., Gauvin, L., Kestens, Y., Daniel, M., Fournier, M., Morency, P., et al. Use of a new public bicycle share program in Montreal, Canada. Am J Prev Med 41 (2011), 80–83, 10.1016/j.amepre.2011.03.002.
22. Habib, K.N., Mann, J., Mahmoud, M., Weiss, A., Synopsis of bicycle demand in the City of Toronto: investigating the effects of perception, consciousness and comfortability on the purpose of biking and bike ownership. Transp Res Part A Policy Pract 70 (2014), 67–80, 10.1016/j.tra.2014.09.012.
23. Chen, M., Wang, D., Sun, Y., Liu, C., Bai, Z., Service evaluation of public bicycle scheme from a user perspective. Transp Res Rec J Transp Res Board 2634 (2017), 28–34, 10.3141/2634-04.
24. Shaheen, S., Zhang, H., Martin, E., Guzman, S., China's Hangzhou Public Bicycle. Transp Res Rec J Transp Res Board 2247 (2011), 33–41, 10.3141/2247-05.
25. Zhang, Y., Thomas, T., Brussel, M., van Maarseveen, M., Exploring the impact of built environment factors on the use of public bikes at bike stations: case study in Zhongshan, China. J Transp Geogr 58 (2017), 59–70, 10.1016/j.jtrangeo.2016.11.014.
26. Zhang, L., Zhang, J., Duan, Z.Y., Bryde, D., Sustainable bike-sharing systems: characteristics and commonalities across cases in urban China. J Clean Prod 97 (2015), 124–133, 10.1016/j.jclepro.2014.04.006.
27. DeMaio, P., Bike-sharing: history, impacts, models of provision, and future. J Public Transp 12 (2009), 41–56, 10.1016/0965-8564(93)90040-R.
28. Shaheen, S., Cohen, A., Martin, E., Public Bikesharing in North America. Transp Res Rec J Transp Res Board 2387 (2013), 83–92, 10.3141/2387-10.
29. The Centre for Sharing Economy. The Research Report on Bike-sharing Employment; 2017.
30. Bao J, He T, Ruan S, Li Y, Zheng Y. Planning Bike Lanes based on Sharing-Bikes’ Trajectories. In: Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining - KDD ’17. ACM Press, New York, New York, USA; 2017. p. 1377–1386. doi:10.1145/3097983.3098056.
31. National Bureau of Statistics, China Statistical Yearbook 2017. 2017, China Statistics Press, Beijing.
32. Xinmin Evening News. 1.5 millions: Shanghai is facing a rapid increase of sharing bikes. Xinmin Evening News; 2017.
33. Mobike. About Mobike; 2017. URL: < https://mobike.com/uk/about>.
34. Sohu Financial. The market share of Mobike is approaching 60%; 2017. URL: < http://business.sohu.com/20170517/n493354558.shtml>.
35. Hornsby, K., Egenhofer, M.J., Modeling moving objects over multiple granularities. Ann Math Artif Intell 36 (2002), 177–194.
36. Zheng Y, Zhang L, Xie X, Ma W-Y. Mining interesting locations and travel sequences from GPS trajectories. In: Proceedings of the 18th international conference on World Wide Web - WWW ’09. ACM Press, New York, New York, USA; 2009. p. 791. doi: 10.1145/1526709.1526816.
37. Mi, Z., Meng, J., Guan, D., Shan, Y., Song, M., Wei, Y.-M., et al. Chinese CO2 emission flows have reversed since the global financial crisis. Nat Commun, 8, 2017, 1712, 10.1038/s41467-017-01820-w.
38. Yu, B., Ma, Y., Xue, M., Tang, B., Wang, B., Yan, J., et al. Environmental benefits from ridesharing: a case of Beijing. Appl Energy 191 (2017), 141–152, 10.1016/j.apenergy.2017.01.052.
39. Mi, Z., Zhang, Y., Guan, D., Shan, Y., Liu, Z., Cong, R., et al. Consumption-based emission accounting for Chinese cities. Appl Energy 184 (2016), 1073–1081, 10.1016/j.apenergy.2016.06.094.
40. Mi, Z., Meng, J., Guan, D., Shan, Y., Liu, Z., Wang, Y., et al. Pattern changes in determinants of Chinese emissions. Environ Res Lett, 12, 2017, 74003, 10.1088/1748-9326/aa69cf.
41. Mi, Z., Wei, Y.M., Wang, B., Meng, J., Liu, Z., Shan, Y., et al. Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030. J Clean Prod 142 (2017), 2227–2236, 10.1016/j.jclepro.2016.11.055.
42. Zheng Y, Li Q, Chen Y, Xie X, Ma W-Y. Understanding mobility based on GPS data. In: Proceedings of the 10th international conference on ubiquitous computing. ACM; 2008. p. 312–21.