Measuring Passenger Satisfaction Evolution with Scheduled Services
The case study examines the impact of scheduled services on passenger satisfaction within the 7th Avenue Minibus-Taxi Association in Mitchells Plain, showcasing a strategic approach to transform taxi associations. The evolution is measured through surveys conducted before and during the pilot, with an emphasis on methodology, questionnaire design, and quality control. The study aims to provide insights into the perception shift among passengers following the introduction of scheduled services.
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Presentation Transcript
specialists in strategy & complex change processes MEASURING THE EVOLUTION OF PASSENGER SATISFACTION FOLLOWING THE INTRODUCTION OF SCHEDULED SERVICES: THE CASE OF THE 7TH AVENUE MINIBUS-TAXI ASSOCIATION IN MITCHELLS PLAIN S. SADDIER, N. MCLACHLAN, D. DASS 10 July 2019
BACKGROUND CoCT SATC 2018 Presentation
THE TOC PROGRAM Designed and supported by the City of Cape Town Four taxi association of Mitchells Plain Business model improvements to transform taxi associations into Transport Operating Companies that will: own all operating licenses; employ drivers and staff; own and manage their fleet; be eligible for contracting by the City. First step: mutualising revenue and optimising operations On 10 January, 7th Ave Taxi Association rolled out scheduled services (with fixed routes and set timetables) Research question: how did passengers perceive this evolution?
APPROACH Two surveys were organized: Before the pilot (n = 732) During the pilot (n = 693) Same methodology and questionnaire for comparability Passengers surveyed at the rank while waiting for a vehicle Second survey more difficult to implement (10 days vs. 7 for the first) Surveyors recruited by the Association and trained by the Consultant
QUESTIONNAIRE AND APP Questionnaire designed to be administered in < 3 minutes Available in English and Afrikaans Three group of questions: Demographics of respondent Trip characteristics Satisfaction with service Use of smartphones to record responses QuickTapSurvey app for offline survey administration Multiple-choice questions only to simplify data processing (with one open-ended question at the end) Data uploaded daily at end of shift
QUALITY CONTROL PROCESS Daily quality control of metadata: GPS coordinates of surveyor Comparison of responses across surveyors Number of responses Survey start and end times Average duration per questionnaire Monday 15.10.2018 Surveyor A Surveyor B Surveyor C Surveyor D Surveyor E Satisfaction score General satisfaction Waiting times Pick up & drop off point Fare Conduct of crew Comfort of vehicle Safety (i.e. road safety) Security (personal) Male pass. surveyed Female pass. surveyed 3,3 3,7 3,4 2,7 3,3 3,5 3,1 3,5 13 16 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a 3,1 3,8 3,7 3,5 3,2 3,4 3,6 3,5 5 23 3,3 3,3 3,9 2,7 3,7 3,3 3 3,4 9 19 4,8 4,6 4,5 3,1 2,4 4,7 4,7 4,7 12 18 One dot = one response to the survey Example of anomalies in scoring and gender distribution (data discarded) Example of spatial anomalies detected in yellow (confirmed to be instances of GPS inaccuracy) 6 PASSENGER SATISFACTION SURVEY
DEMOGRAPHICS OF RESPONDENTS Gender of respondents Age group 450 50% 45% 400 40% 350 35% 300 30% 250 25% 200 20% 150 15% 100 10% 50 5% 0 0% female male Under 21 21-30 31-45 46+ Before the pilot During the trial Before the pilot During the pilot More female than male passengers (as observed in previous surveys) Slight variations between survey likely caused by differences in work hours and surveyors team composition These characteristics are used as control variables to check that changes in satisfaction levels result from the implementation of the new system (and not from a different population segment being surveyed) Occupational status of respondents unemployed student retired employed 0% 10% 20% 30% 40% 50% 60% Before the pilot During the pilot 7 PASSENGER SATISFACTION SURVEY
TRIP CHARACTERISTICS Large share of shopping trips consistent with previous research (possibly emphasized by survey hours). Some variation between the two surveys, likely resulting from differences in time of the year/month/day between the two surveys Similar distribution of intermodal trips across the two surveys (low share of rail emphasized by survey hours) Trip purpose 60% 50% 40% 30% 20% 10% 0% Work Education Shopping Social Administrative Before the pilot During the pilot Number of days per week using taxis Other modes of transport used on trip for connecting passengers 1-3 days 35% 30% 25% 20% 4-5 days 15% 10% 5% 6-7 days 0% Golden Arrow Train MyCiti Other taxi Other mode 0% 10% 20% 30% 40% 50% Before the pilot During the pilot Before the pilot During the pilot
SATISFACTION SCORES Mean score on a scale of one to five Mean score on a scale of one to five Overall satisfaction Overall satisfaction Waiting time Waiting time Pick-up/drop-off location Pick-up/drop-off location Fare Fare Conduct of the crew Conduct of the crew Comfort of vehicle Comfort of vehicle Road safety Road safety Personal security Personal security 0.0 0.0 0.5 0.5 1.0 1.0 1.5 1.5 2.0 2.0 2.5 2.5 3.0 3.0 3.5 3.5 4.0 4.0 4.5 4.5 5.0 5.0 Before the pilot Before the pilot During the pilot During the pilot
OPEN-ENDED QUESTIONS Before the pilot: What is the most important thing that should be improved in the taxi services on this route? During the pilot: What other changes would you like to see on taxi services on this route? No other changes needed 44% Comfort of vehicle 36% Journey time/itinerary 24% Attitude of crew 16% Comfort of vehicle 14% Journey time/itinerary 15% Fare 5% Fare 12% Attitude of crew 5% Safety/security 11% Safety/security 4% Other 8% Other 4% 10 PASSENGER SATISFACTION SURVEY
CONCLUSION Scheduled services = improvement for a majority of users Regression analysis confirms that improved satisfaction is associated with scheduled services Encouraging results for the TOC-formation program Change of business model also benefits the end-users Satisfaction = experience vs. expectation, likely to evolve in time How does the new system compare to the old one? worse: 2% n/a: 2% same: 2% better: 94%
Simon Saddier simon.saddier@transitec.net THANK YOU
