The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - Jan.-Mar. (2013 vol.12)
pp: 18-25
ABSTRACT
This review of IT-based services offered in public transportation focuses on the passenger's perspective. The authors suggest new directions for future services, stressing the need to develop frameworks for assessing service quality and customer satisfaction.
INDEX TERMS
ubiquitous computing, customer satisfaction, traffic information systems, transportation, customer satisfaction, pervasive technology, telematics, IT-based services, public transportation, passenger perspective, future services, service quality assessment, Vehicles, Real-time systems, Ubiquitous computing, Mobile handsets, IEEE 802.11 Standards, Social network services, Intelligent transportation systems, Urban areas, Informatics, Rail transportation, Transportation, urban informatics, information technology, public transport, intelligent transportation systems, advanced public transportation systems, pervasive computing
CITATION
T. D. Camacho, M. Foth, A. Rakotonirainy, "Pervasive Technology and Public Transport: Opportunities Beyond Telematics", IEEE Pervasive Computing, vol.12, no. 1, pp. 18-25, Jan.-Mar. 2013, doi:10.1109/MPRV.2012.61
REFERENCES
1. K.W. Watkins et al., “Where Is My Bus? Impact of Mobile Real-Time Information on the Perceived and Actual Wait Time of Transit Riders,” Transportation Research Part A: Policy and Practice, vol. 45, no. 8, 2011, pp. 839–848.
2. L. Tang and P. Thakuriah, “Ridership Effects of Real-Time Bus Information System: A Case Study in the City of Chicago,” Transportation Research Part C: Emerging Technologies, vol. 22, 2012, pp. 146–161.
3. M.-P. Pelletier, M. Trépanier, and C. Morency, “Smart Card Data Use in Public Transit: A Literature Review,” Transportation Research Part C: Emerging Technologies, vol. 19, no. 4, 2011, pp. 557–568.
4. A. Aguiléra, C. Guillot, and A. Rallet, “Mobile ICTs and Physical Mobility: Review and Research Agenda,” Transportation Research Part A: Policy and Practice, vol. 46, no. 4, 2012, pp. 664–672.
5. L.A. Fischer and J.P. Schwieterman, Who Rides Curbside Buses? A Passengers Survey of Discount Curbside Bus Services in Six Eastern and Midwestern Cities, tech. report, Chaddick Inst. for Metropolitan Development, DePaul University, 2011.
6. T. Evens et al., “Forecasting Broadband Internet Adoption on Trains in Belgium,” Telematics and Informatics, vol. 27, no. 1, 2010, pp. 10–20.
7. Transit Cooperative Research Program, Use of Social Media in Public Transportation, tech. report, Transportation Research Board of the Nat'l Academies, 2012.
8. P. Zito et al., “The Effect of Advanced Traveler Information Systems on Public Transport Demand and Its Uncertainty,” Transportmetrica, vol. 7, no. 1, 2011, pp. 31–43.
9. K. Dziekan and K. Kottenhoff, “Dynamic At-Stop Real-Time Information Displays for Public Transport: Effects on Customers,” Transportation Research Part A: Policy and Practice, vol. 41, no. 6, 2007, pp. 489–501.
10. B. Ferris and K. Watkins, OneBusAway: A Transit Traveler Information System, Lecture Notes of the Inst. for Computer Sciences, Social Informatics and Telecomm. Eng., vol. 35, Springer, 2010, pp. 92–106.
11. J. Zimmerman et al., “Field Trial of Tiramisu: Crowd-Sourcing Bus Arrival Times to Spur Co-Design,” Proc. 2011 Ann. Conf. Human Factors in Computing Systems (CHI 11), ACM, 2011, pp. 1677–1686.
12. J.D. Nelson and C. Mulley, “The Impact of the Application of New Technology on Public Transport Service Provision and the Passenger Experience: A Focus on Implementation in Australia,” to appear in Research in Transportation Economics, 2012.
13. G. Lyons and R. Harman, “The UK Public Transport Industry and Provision of Multi-Modal Traveler Information,” Int'l J. Transport Management, vol. 1, no. 1, 2002, pp. 1–13.
14. L. Zhang et al., “Traveler Information Tool with Integrated Real-Time Transit Information and Multimodal Trip Planning,” Transportation Research Record: J. Transportation Research Board, vol. 2215, no. 1, 2011, pp. 1–10.
15. Y.-J. Chang et al., “Anomaly Detection to Increase Commuter Safety for Individuals with Cognitive Impairments,” J. Developmental and Physical Disabilities, vol. 24, 2012, pp. 9–17; doi: 10.1007/s10882.011-9251-3.
16. I. Politis et al., “Evaluation of a Bus Passenger Information System from the Users' Point of View in the City of Thessaloniki, Greece,” Research in Transportation Economics, vol. 29, no. 1, 2010, pp. 249–255.
17. I. Ceapa, C. Smith, and L. Capra, “Avoiding the Crowds: Understanding Tube Station Congestion Patterns From Trip Data,” Proc. ACM SIGKDD Int'l Workshop on Urban Computing (UrbComp 12), ACM, 2012, pp. 134–141.
18. J. Preston and G. Wall, Meeting Rail Passenger User Needs: The Role of Information Technologies, tech. report, Transportation Research Group, Univ. of Southampton, 2006.
19. J.P. Schwieterman, L.A. Fischer, and M. Schulz, Staying Connected en Route: The Growing Use of Tablets and Other Portable Electronic Devices on Intercity Buses, Trains and Planes, tech. report, Chaddick Inst. for Metropolitan Development, DePaul University, 2012.
20. T. Litman, The Future Isn't What It Used to Be: Changing Trends and their Implications for Transportation Planning, tech. report, Victoria Transport Policy Inst., 2012.
21. C.S. Lee and L. Ma, “News Sharing in Social Media: The Effect of Gratifications and Prior Experience,” Computers in Human Behavior, vol. 28, no. 2, 2012, pp. 331–339.
22. M. Foth and R. Schroeter, “Enhancing the Experience of Public Transport Users with Urban Screens and Mobile Applications,” Proc. 14th Int'l Academic MindTrek Conf.: Envisioning Future Media Environments (MindTrek 10), ACM, 2010, pp. 33–40.
23. S. Kanhere, “Participatory Sensing: Crowd-Sourcing Data from Mobile Smartphones in Urban Spaces,” Proc. 12th IEEE Int'l Conf. Mobile Data Management (MDM 11), vol. 2, IEEE CS, 2011, pp. 3–6.
24. J. Zhang et al., “Data-Driven Intelligent Transportation Systems: A Survey,” IEEE Trans. Intelligent Transportation Systems, vol. 12, no. 4, 2011, pp. 1624–1639.
25. W.-T. Lai and C.-F. Chen, “Behavioral Intentions of Public Transit Passengers—The Roles of Service Quality, Perceived Value, Satisfaction and Involvement,” Transport Policy, vol. 18, no. 2, 2011, pp. 318–325.
17 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool