Assessing Transit Loyalty Sample Clauses

Assessing Transit Loyalty. The collected data through Automated Fare Collection (AFC) systems provide valuable information than can be used for different purposes. This study focusses on measuring the user’s loyalty to public service based on the data analysis from smart cards system. In order to evaluate large amounts of data, transit agencies need to have access to continuous data on the behaviors of transit users. Determining loyalty or retention rate could be useful when developing marketing strategies, fare packages, or to increase attractiveness of the system (Xxxxxxxxx et al., 2012). Previous studies have shown that the customer level of satisfaction is related to transit loyalty. Better service frequency, lower waiting and travel times, and vehicle comfort and cleanliness are usually identified as key factors for retaining customers. This paper presents the application of a discrete time hazard model using data collected for 5 years, from January 1, 2004 to December 31, 2008 of a medium-size transit authority Société de transport de l’Outaouais (STO) in Canada. The STO operates 200 buses and provide services to 240,000 people where more than 80% of the users have smart cards (Xxxxxxxxx et al., 2012). The interest of this paper was to investigate the factors that can influence the usage of smart cards by analyzing the information collected per transactions such as the starting and ending month of individual cards and frequency of monthly usage of the card. In the case that the personal information was limited, then the following attributes could be used: average zonal socio- demographic, land use, and the transportation system. Using these attributes, a model can be developed of transit smart card usage as a function of the available attributes (Xxxxxxxxx et al., 2012). A Hazard model is then the appropriate one to determine the duration of a user’s smart card. As stated in Are transit users loyal? Revelations from a hazard model based on smart card data (Xxxxxxxxx et al., 2012), the concept of the hazard model relates to the fact that the probability to continue the use of a smart card by a user, at a particular time, is conditional to the probability of not cancelling the card before the end of the time period. For this case, the study only used adults’ smart cards transactions, because they use public transportation more frequently than students as shown in Figure 6. Information was collected from more than 68,100 smart cards showing a mean average of 16.26 months. The ave...
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