Public Transit Customer Satisfaction Dimensions Discovery from Online Reviews

Abstract

Online user-generated content provides a valuable source for identifying dimensions of services. This study proposes a framework for extracting the dimensions of consumer satisfaction of public transportation services using unsupervised latent Dirichlet allocation model. A pilot study was performed on 17,747 online user reviews collected from 1452 public transportation agencies (including streetcar, light rail, heavy rail, boat, and aerial tram) in the United States over 8 years. The proposed approach is able to identify a few dimensions that were not discussed in the previous literature. This research also provides an alternative method to collectively gather users’ feedback and efficiently pre-process textual data related to transit customer satisfaction.

Keywords

Public Transportation / User Comments / Text Mining / LDA Model / Customer Satisfaction

References

[1] Lai W-T, Chen C-F. Behavioral intentions of public transit passengers: the roles of service quality, perceived value, satisfaction and involvement. Transp Policy, 2011, 18(2): 318-325

[2] Olsen SO. Repurchase loyalty: the role of involvement and satisfaction. Psychol Mark, 2007, 24(4): 315-341

[3] Coffel K (1995) Customer satisfaction index for the mass transit industry. TRANSIT-IDEA Program Project Final Report 10

[4] Hill N, Brierley J, MacDougall R. How to measure customer satisfaction, 2003, Aldershot: Gower Publishing, Ltd.

[5] Eboli L, Mazzulla G. A new customer satisfaction index for evaluating transit service quality. J Public Transp, 2009, 12(3): 2

[6] Nathanail E. Measuring the quality of service for passengers on the hellenic railways. Transp Res Part A, 2008, 42(1): 48-66.

[7] Cervero R, Wachs M. An answer to the transit crisis: the case for distance-based fares. J Contemp Stud, 1982, 5(2): 59-70.

[8] Goodwin PB. A review of new demand elasticities with special reference to short and long run effects of price changes. J Transp Econ Policy, 1992, 26: 155-169.

[9] Andreassen TW. (Dis) satisfaction with public services: the case of public transportation. J Serv Mark, 1995, 9(5): 30-41

[10] Perone JS, Volinski JM (2003) Fare, free, or something in between? Free Fares

[11] Cervero R. Transit pricing research. Transportation, 1990, 17(2): 117-139

[12] Wall G, McDonald M. Improving bus service quality and information in winchester. Transp Policy, 2007, 14(2): 165-179

[13] Friman M, Fellesson M. Service supply and customer satisfaction in public transportation: the quality paradox. J Public Transp, 2009, 12(4): 4

[14] Metropolitan Transportation Authority (MTA) (2014) Customer satisfaction survey subway report

[15] Daganzo CF. Structure of competitive transit networks. Transp Res Part B, 2010, 44(4): 434-446

[16] Woldeamanuel MG, Cyganski R (2011) Factors affecting travellers’s satisfaction with accessibility to public transportation. In Proceedings European transport conference

[17] Turner BA. Causes of disaster: sloppy management. Br J Manag, 1994, 5(3): 215-219

[18] Roberts H, Retting R, Webb T, Colleary A, Turner B, Wang X, Toussaint R, Simpson G, White C (2015) Improving safety culture in public transportation

[19] Lundberg ULF. Urban commuting: crowdedness and catecholamine excretion. J Hum Stress, 1976, 2(3): 26-32

[20] Litman T. Valuing transit service quality improvements. J Public Transp, 2008, 11(2): 3

[21] Cantwell M, Caulfield B, Mahony MO. Examining the factors that impact public transport commuting satisfaction. J Public Transp, 2009, 12(2): 1

[22] Olio LD, Ibeas I, Cecin P. The quality of service desired by public transport users. Transp Policy, 2011, 18(1): 217-227

[23] Aranguren M, Tonnelat S. Emotional transactions in the paris subway: combining naturalistic videotaping, objective facial coding and sequential analysis in the study of nonverbal emotional behavior. J Nonverbal Behav, 2014, 38(4): 495-521

[24] Charles E (2010) Text mining and topic models. Lecture notes

[25] Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. J Mach Learn Res, 2003, 3: 993-1022.