Abstract

A new form of mobile payment, Quick Response (QR) code, has been a popular way of paying bus fares in China since 2017. Compared with conventional payment methods, cash or IC card, QR code shows a lot of differences in response time, recognition accuracy, and payment procedure, which significantly influences the boarding service time (BST) for passengers. However, no research has considered its efficiency. This study, therefore, tries to fill this gap and investigate its influence on BST. Sufficient ride-check data were collected, and the influence of the QR code payment method on BST was examined through a set of regression models. Passengers pay the bus fare with different payment methods as their first choice; nevertheless, when the payment fails, they may transfer among them. According to the payment choice, result, and process, we introduce the first-choice-based, the last-choice-based, and the choice-transfer-based models, respectively. The scenario with delays in calling out the QR code was considered in the choice-transfer-based model. The onboard crowdedness was regarded as a categorical variable to determine the regime of the boarding process in all models. We conduct empirical analysis in Wuhan, and this study can help to identify the influence of the QR code payment method on BST, consequently, improving bus service efficiency.

Highlights

  • In this research, the influence of the Quick Response (QR) code payment method on boarding service time (BST) is examined from three aspects: the unit service time per boarding passenger paying by QR code, the influence of failure in reading QR code, and the influence of delay in calling out QR code. e contributions of this paper are threefold: first, this study is the first research to investigate the service efficiency of the emerging QR code payment method in the bus transit system

  • We quantified the influence of the QR code payment method on BST, which explains why the efficiency of the QR code payment method is lower than that of the conventional payment methods. ird, we used the crowdedness to determine the regime of boarding processes, which differentiates the significance of independent variables under different scenarios and helps to analyze how the QR code payment method impacts on BST. e research results can provide specific guidance for related stakeholders to improve the service efficiency of the QR code payment method

  • With the popularization of mobile payment in our daily life, the QR code payment method is more and more commonly adopted in paying the transit fares. is research investigated the service efficiency of the emerging QR code payment method and studied its influence on bus BST, through a set of regression models. e crowdedness was used to determine the regime of the boarding process, and we examined the influence of three main factors of the QR code payment method, i.e., response time, failure in QR code reading, and delay in calling out QR code, on BST under different scenarios. e conclusions can be summarized from the results of the proposed models

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Summary

Introduction

The influence of the QR code payment method on BST is examined from three aspects: the unit service time per boarding passenger paying by QR code, the influence of failure in reading QR code, and the influence of delay in calling out QR code. e contributions of this paper are threefold: first, this study is the first research to investigate the service efficiency of the emerging QR code payment method in the bus transit system. Ird, we used the crowdedness to determine the regime of boarding processes, which differentiates the significance of independent variables under different scenarios and helps to analyze how the QR code payment method impacts on BST. E remainder of this paper is organized as follows: in Section 2, we review the existing studies on bus BST at stops; in Section 3, we model the payment processes of boarding passengers and analyze the potential influence of QR code payment method on BST, and dependent and independent variables are determined for regression analysis; in Section 4, the numerical analysis in different regimes is presented; and Section 5 summarizes the main findings of the study and provides guidance for improving the service efficiency of the QR code payment method

Methods
Results
Conclusion

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