Ge Gao
Yuling Sun
ABSTRACT
Participatory sensing refers to the sensing paradigm where human participants use personal mobile devices to generate and share data from their surroundings. It holds the promise of providing information that is otherwise challenging to access, which sets the stage for understanding and resolving various social issues. However, difficulties in engaging participants often hinder the fulfillment of this promise. The current paper presents a qualitative study in the context of dockless bikesharing, where participatory sensing constitutes a backbone of the bike status monitoring system. We conducted in-depth interviews with 30 participants. These participants came from different emergent groups who took part in filing status reports for shared bikes. Our analysis indicated close associations among participants' models of engagement, their perceived (dis)connections with the sensing data, and their situated interpretation of the incentives. Based on these findings, we propose ways to engage the commons in participatory sensing for dockless bikesharing and beyond.
- Michael Ahillen, Derlie Mateo-Babiano, and Jonathan Corcoran. 2016. Dynamics of bike sharing in Washington, DC and Brisbane, Australia: implications for policy and planning. International Journal of Sustainable Transportation 10, 5: 441--454.Google Scholar
Cross Ref
- Daniel P. Aldrich. 2017. Post-crisis Japanese nuclear policy: from top-down directives to bottom-up activism. In Japan at Nature's Edge, Ian Jared Miller, Julia Adeney Thomas and Brett L. Walker (eds.). University of Hawaii Press, Honolulu, 280--292. https://doi.org/10.1515/9780824838775-017Google ScholarCross Ref
- Paul Aoki, Allison Woodruff, Baladitya Yellapragada, and Wesley Willett. 2017. Environmental protection and agency: motivations, capacity, and goals in participatory sensing. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 3138--3150. https://doi.org/10.1145/3025453.3025667Google ScholarDigital Library
- Cédric Bach, Regina Bernhaupt, Caio D'Agostini, and Marco Winckler. 2013. Mobile applications for incident reporting systems in urban contexts: lessons learned from an empirical study. In Proceedings of the 31st European Conference on Cognitive Ergonomics (ECCE '13), Article No. 29. https://doi.org/10.1145/2501907.2501960Google ScholarDigital Library
- Mara Balestrini, Yvonne Rogers, Carolyn Hassan, Javi Creus, Martha King, and Paul Marshall. 2017. A city in common: a framework to orchestrate large-scale citizen engagement around urban issues. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 2282--2294. https://doi.org/10.1145/3025453.3025915Google ScholarDigital Library
- Fleura Bardhi and Giana M. Eckhardt. 2012. Accessbased consumption: the case of car sharing. Journal of Consumer Research 39, 4: 881-- 898. https://doi.org/10.1086/666376Google ScholarCross Ref
- Russell Belk. 2007. Why not share rather than own? The ANNALS of the American Academy of Political and Social Science 611, 1: 126--140. https://doi.org/10.1177/0002716206298483Google ScholarCross Ref
- Laurence Brothers, Jim Hollan, Jakob Nielsen, Scott Stornetta, Steve Abney, George Furnas, and Michael Littman. 1992. Supporting informal communication via ephemeral interest groups. In Proceedings of the 1992 ACM Conference on Computer-Supported Cooperative Work (CSCW '92), 84--90. http://dx.doi.org/10.1145/143457.143465Google ScholarDigital Library
- Matthias Budde, Andrea Schankin, Julien Hoffmann, Marcel Danz, Till Riedel, and Michael Beigl. 2017. Participatory sensing or participatory nonsense?: mitigating the effect of human error on data quality in citizen science. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT '17) 1, 3: 1--23. https://doi.org/10.1145/3131900Google ScholarDigital Library
- Jeff Burke, Deborah Estrin, Mark Hansen, A Parker, R.Anitha Nithya, S Reddy, and M Srivastava. 2006. Participatory sensing. In World-Sensor-Web Workshop at the 4th ACM Conference on Embedded Networked Sensor Systems (SenSys ?06).Google Scholar
- Andrew A. Campbell, Christopher R. Cherry, Megan S. Ryerson, and Xinmiao Yang. 2016. Factors influencing the choice of shared bicycles and shared electric bikes in Beijing. Transportation Research Part C: Emerging Technologies 67: 399--414. https://doi.org/10.1016/j.trc.2016.03.004Google ScholarCross Ref
- Andrew T. Campbell, Shane B. Eisenman, Nicholas D. Lane, Emiliano Miluzzo, and Ronald A. Peterson. 2006. People-centric urban sensing. In Proceedings of the 2nd Annual International Workshop on Wireless Internet (WICON '06). https://doi.org/10.1145/1234161.1234179Google ScholarDigital Library
- Mengwei Chen, Dianhai Wang, Yilin Sun, E. Owen D. Waygood, and Wentao Yang. 2018. A comparison of users' characteristics between station-based bikesharing system and free-floating bikesharing system: case study in Hangzhou, China. Transportation. https://doi.org/10.1007/s11116-0189910--7Google ScholarCross Ref
- Saskia Coulson, Mel Woods, Michelle Scott, Drew Hemment, and Mara Balestrini. 2018. Stop the noise! enhancing meaningfulness in participatory sensing with community level indicators. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS '18), 1183--1192. https://doi.org/10.1145/3196709.3196762Google ScholarDigital Library
- Tshering Dema, Margot Brereton, and Paul Roe. 2019. Designing participatory sensing with remote communities to conserve endangered species. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19), 664:1-- 664:16. https://doi.org/10.1145/3290605.3300894Google ScholarDigital Library
- Paul DeMaio. 2009. Bike-sharing: history, impacts, models of provision, and future. Journal of Public Transportation 12, 4: 41--56. https://doi.org/10.5038/2375-0901.12.4.3Google ScholarCross Ref
- Linda Deng and Landon P. Cox. 2009. LiveCompare: grocery bargain hunting through participatory sensing. In Proceedings of the 10th Workshop on Mobile Computing Systems and Applications (HotMobile '09), 4:1--4:6. https://doi.org/10.1145/1514411.1514415Google ScholarDigital Library
- Yi F. Dong, Salil Kanhere, Chun T. Chou, and Nirupama Bulusu. 2008. Automatic collection of fuel prices from a network of mobile cameras. In Distributed Computing in Sensor Systems (Lecture Notes in Computer Science), 140--156.Google Scholar
- Mingyang Du and Lin Cheng. 2018. Better understanding the characteristics and influential factors of different travel patterns in free-floating bike sharing: evidence from Nanjing, China. Sustainability 10, 4: 1-- 14.Google ScholarCross Ref
- Prabal Dutta, Paul M Aoki, Neil Kumar, Alan Mainwaring, Chris Myers, Wesley Willett, and Allison Woodruff. Common sense: participatory urban sensing using a network of handheld air quality monitors. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys ?09), 349--350.Google Scholar
- Deborah Estrin. 2010. Participatory sensing: applications and architecture. IEEE Internet Computing 14, 1: 12--42. https://doi.org/10.1109/MIC.2010.12Google ScholarDigital Library
- European Bicycle Manufactures Association. Bike Sharing in China. Retrieved September 17, 2019 from http://ebma-brussels.eu/bike-sharing-in-china/Google Scholar
- Elliot Fishman. 2016. Bikeshare: a review of recent literature. Transport Reviews 36, 1: 92--113. https://doi.org/10.1080/01441647.2015.1033036Google ScholarCross Ref
- Barney G. Glaser. 1978. Theoretical Sensitivity: Advances in the Methodology of Grounded Theory. Mill Valley, CA: Sociology Press.Google Scholar
- Jeffrey Goldman, Katie Shilton, Jeffrey Burke, Deborah Estrin, Mark Hansen, Nithya Ramanathan, Sasank Reddy, Vids Samanta, Mani Srivastava, and Ruth West. 2009. Participatory sensing: a citizenpowered approach to illuminating the patterns that shape our world. Ethics in Science and Engineering National Clearinghouse. Retrieved from https://scholarworks.umass.edu/esence/362Google Scholar
- Sarah Goodyear. The Real Story Behind the Global Bike-Share Boom. Retrieved September 17, 2019 from https://www.citylab.com/city-makersconnections/bike-shareGoogle Scholar
- Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Y. Yen, Runhe Huang, and Xingshe Zhou. 2015. Mobile crowd sensing and computing: the review of an emerging human-powered sensing paradigm. ACM Computing Surveys 48, 1: 1--31. https://doi.org/10.1145/2794400Google ScholarDigital Library
- Katharina Hellwig, Felicitas Morhart, Florent Girardin, and Mirjam Hauser. 2015. Exploring different types of sharing: a proposed segmentation of the market for ?sharing" businesses. Psychology & Marketing 32, 9: 891--906. https://doi.org/10.1002/mar.20825Google ScholarCross Ref
- Luiz Henrique C.B. Cavalcanti, Alita Pinto, Jed R. Brubaker, and Lynn S. Dombrowski. 2017. Media, meaning, and context loss in ephemeral communication platforms: a qualitative investigation on Snapchat. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17), 1934--1945. https://doi.org/10.1145/2998181.2998266Google ScholarDigital Library
- Youyang Hou and Dakuo Wang. 2017. Hacking with NPOs: collaborative analytics and broker roles in civic data hackathons. Proc. ACM Hum.-Comput. Interact. 1, CSCW: 53:1--53:16. https://doi.org/10.1145/3134688Google ScholarDigital Library
- Kuan Lun Huang, Salil S. Kanhere, and Wen Hu. 2010. Are you contributing trustworthy data?: the case for a reputation system in participatory sensing. In Proceedings of the 13th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWIM '10), 14--22. http://dx.doi.org/10.1145/1868521.1868526Google ScholarDigital Library
- Yun Huang, John Zimmerman, Anthony Tomasic, and Aaron Steinfeld. 2016. Combining contribution interactions to increase coverage in mobile participatory sensing systems. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '16), 365--376. https://doi.org/10.1145/2935334.2935387Google ScholarDigital Library
- Luis G. Jaimes, Idalides J. Vergara-Laurens, and Andrew Raij. 2015. A survey of incentive techniques for mobile crowd sensing. IEEE Internet of Things Journal 2, 5: 370--380. https://doi.org/10.1109/JIOT.2015.2409151Google ScholarCross Ref
- Ian G. Johnson, Aare Puussaar, Jennifer Manuel, and Peter Wright. 2018. Neighbourhood data: exploring the role of open data in locally devolved policymaking processes. Proc. ACM Hum.-Comput. Interact. 2, CSCW, 83:1--83:20.Google Scholar
- Sunyoung Kim, Christine Robson, Thomas Zimmerman, Jeffrey Pierce, and Eben M. Haber. 2011. Creek watch: pairing usefulness and usability for successful citizen science. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11), 2125--2134. https://doi.org/10.1145/1978942.1979251Google ScholarDigital Library
- Robert E. Kraut, Paul Resnick, Sara Kiesler, Yuqing Ren, Yan Chen, Moira Burke, Niki Kittur, John Riedl, and Joseph Konstan. 2012. Building Successful Online Communities: Evidence-Based Social Design. The MIT Press.Google ScholarDigital Library
- Nicholas D. Lane, Shane B. Eisenman, Mirco Musolesi, Emiliano Miluzzo, and Andrew T. Campbell. 2008. Urban sensing systems: opportunistic or participatory? In Proceedings of the 9th Workshop on Mobile Computing Systems and Applications (HotMobile '08), 11. https://doi.org/10.1145/1411759.1411763Google ScholarDigital Library
- Zhaoyang Liu, Yanyan Shen, and Yanmin Zhu. 2018. Where will dockless shared bikes be stacked?: parking hotspots detection in a New City. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '18), 566--575. https://doi.org/10.1145/3219819.3219920Google ScholarDigital Library
- Brian McInnis, Xiaotong (Tone) Xu, and Steven P. Dow. 2018. How features of a civic design competition influences the collective understanding of a problem. Proc. ACM Hum.-Comput. Interact. 2, CSCW: 120:1-- 120:25. https://doi.org/10.1145/3274389Google ScholarDigital Library
- Donald McMillan, Arvid Engström, Airi Lampinen, and Barry Brown. 2016. Data and the city. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16), 2933--2944. https://doi.org/10.1145/2858036.2858434Google ScholarDigital Library
- Rim Ben Messaoud, Yacine Ghamri-Doudane, and Dmitri Botvich. 2016. Preference and mobility task assignment in participatory sensing. In Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM '16), 93--101. https://doi.org/10.1145/2988287.2989165Google ScholarDigital Library
- Catherine Mloza-Banda and Bernard Scholtz. 2018. Crowdsensing for successful water resource monitoring: an analysis of citizens' intentions and motivations. In Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists (SAICSIT '18), 55--64. https://doi.org/10.1145/3278681.3278688Google ScholarDigital Library
- Mareike Möhlmann. 2015. Collaborative consumption: determinants of satisfaction and the likelihood of using a sharing economy option again. Journal of Consumer Behaviour 14, 3: 193--207. https://doi.org/10.1002/cb.1512Google ScholarCross Ref
- Osarieme Omokaro. 2012. A framework to promote user engagement in participatory sensing applications. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp '12), 548--551. https://doi.org/10.1145/2370216.2370306Google ScholarDigital Library
- Maria V. Palacin-Silva, Antti Knutas, Maria Angela Ferrario, Jari Porras, Jouni Ikonen, and Chandara Chea. 2018. The role of gamification in participatory environmental sensing: a study in the wild. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18), 221:1-- 221:13. https://doi.org/10.1145/3173574.3173795Google ScholarDigital Library
- Aare Puussaar, Ian G. Johnson, Kyle Montague, Philip James, and Peter Wright. 2018. Making open data work for civic advocacy. Proc. ACM Hum.-Comput. Interact. 2, CSCW: 143:1--143:20. https://doi.org/10.1145/3274412Google ScholarDigital Library
- Sasank Reddy, Deborah Estrin, Mark Hansen, and Mani Srivastava. 2010. Examining micro-payments for participatory sensing data collections. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing (UbiComp '10), 33--36. https://doi.org/10.1145/1864349.1864355Google ScholarDigital Library
- Francesco Restuccia, Sajal K. Das, and Jamie Payton. 2016. Incentive mechanisms for participatory sensing: survey and research challenges. ACM Trans. Sen. Netw. 12, 2: 13:1--13:40. https://doi.org/10.1145/2888398Google ScholarDigital Library
- Miriam Ricci. 2015. Bike sharing: A review of evidence on impacts and processes of implementation and operation. Research in Transportation Business & Management 15: 28--38. https://doi.org/10.1016/j.rtbm.2015.03.003Google ScholarCross Ref
- Dana Rotman, Jen Hammock, Jenny Preece, Derek Hansen, Carol Boston, Anne Bowser, and Yurong He. 2014. Motivations affecting initial and long-term participation in citizen science projects in three countries. In Proceedings of 2014 iConference, 110124. https://doi.org/10.9776/14054Google ScholarCross Ref
- Katie Shilton. 2009. Four billion little brothers?: privacy, mobile phones, and ubiquitous data collection. ACM Communication 52, 11: 48--53. https://doi.org/10.1145/1592761.1592778Google ScholarDigital Library
- Hongsuda Tangmunarunkit, Chengkang Hsieh, Brent Longstaff, S. Nolen, John Jenkins, Cameron Ketcham, Joshua Selsky, Faisal Alquaddoomi, D. George, Jinha Kang, Z. Khalapyan, J. Ooms, Nithya Ramanathan, and Deborah Estrin. 2015. Ohmage: a general and extensible end-to-end participatory sensing platform. ACM Trans. Intell. Syst. Technol. 6, 3: 38:1--38:21. https://doi.org/10.1145/2717318Google ScholarDigital Library
- Anthony Tomasic, John Zimmerman, Aaron Steinfeld, and Yun Huang. 2014. Motivating contribution in a participatory sensing system via quid-pro-quo. In Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '14), 979--988. https://doi.org/10.1145/2531602.2531705Google ScholarDigital Library
- Kathleen Tuite, Noah Snavely, Dun-yu Hsiao, Nadine Tabing, and Zoran Popovic. 2011. PhotoCity: training experts at large-scale image acquisition through a competitive game. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11), 1383--1392. https://doi.org/10.1145/1978942.1979146Google ScholarDigital Library
- Yi Wu and Dajian Zhu. 2017. Bicycle sharing based on PSS-EPR coupling model: exemplified by bicycle sharing in China. Procedia CIRP 64: 423--428. https://doi.org/10.1016/j.procir.2017.03.067Google ScholarCross Ref
- Bin Xu, Pamara Chang, Christopher L. Welker, Natalya N. Bazarova, and Dan Cosley. 2016. Automatic archiving versus default deletion: what Snapchat tells us about ephemerality in design. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW '16), 1662--1675. https://doi.org/10.1145/2818048.2819948Google ScholarDigital Library
- Ruiyun Yu, Jiannong Cao, Rui Liu, Wenyu Gao, Xingwei Wang, and Junbin Liang. 2019. Participant incentive mechanism toward quality-oriented sensing: understanding and application. ACM Trans. Sen. Netw. 15, 2: 21:1--21:25.Google ScholarDigital Library
- Bo Zhang, Zheng Song, Chi Harold Liu, Jian Ma, and Wendong Wang. 2015. An event-driven QoI-aware participatory sensing framework with energy and budget constraints. ACM Trans. Intell. Syst. Technol. 6, 3, 42:1--42:19. http://dx.doi.org/10.1145/2630074Google ScholarDigital Library
- Pengfei Zhou, Yuanqing Zheng, and Mo Li. 2012. How long to wait?: predicting bus arrival time with mobile phone based participatory sensing. In Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services (MobiSys '12), 379--392. https://doi.org/10.1145/2307636.2307671Google ScholarDigital Library
Index Terms
- Engaging the Commons in Participatory Sensing: Practice, Problems, and Promise in the Context of Dockless Bikesharing
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