Contemporary Issues in the Ethics of Data Analytics in Ride-Hailing Service

Contemporary Issues in the Ethics of Data Analytics in Ride-Hailing Service

Victor Chang (International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China), Yujie Shi (International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China) and Xuemin Li (International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China)
Copyright: © 2019 |Pages: 14
DOI: 10.4018/IJoSE.2019070105
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Big data technology has brought about the establishment of transportation network companies (TNCs), such as Uber in the USA, and Didi in China, who provide the ride hailing services (RHS's) which allows the individuals to act as independent contractors serving customers via a smartphone app. The RHS system installed gigantic databases which can store enormous data and its equipment can collect various kinds of data at any time. Additionally, data analysis technologies in TNCs such as behavioral analysis, heatmap optimization surge pricing and the automatic order assignment mechanisms, can make the RHS more efficient. However, along with achievements big data technology offers, we are struggling towards the ethical problems, including privacy, inequity and safety.
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1. Introduction

New big data technology primarily is in the form of computing power and widespread access to the Internet through computers and mobile phone devices. Many services can generate data, whose analysis has played important roles, such as analysis of patterns and correlations can be used to interpret meanings behind the scene (Mai, 2015). There are five characteristics of big data called 5V: volume, variety, velocity, variability, veracity. Volume means that the value and potential information of the considered data can be determined by the size of data. Variety means the diversity of data. Velocity means the speed of capturing data. Variability means that the process to deal with data can be impeded due to the inconsistency of the data set. Veracity means the quality of data. A suitable example is as follows. The traditional taxi service requires drivers to drive around the streets to find potential passengers according to their intuition and the adoption of beckon-to-stop model, an order-taking oriented approach. The previous way is pretty time-wasting and high-cost for drivers, and it is not effective for customers, for example, if passengers want to take a taxi, but there is no taxi around, they have to wait or walk for a long distance to take a car. In this case, the application of electronic devices and high-end networking technology can turn the traditional taxi patterns into predictable movements, eventually this can be similar to forecasted automation (Zhou et al., 2016). To make this happen, an online provider system for ride hailing service (RHS) can be used. It can play the role of matchmaker, broker or intermediary between the potential passengers and the “third party” private drivers (Ng, 2016). All services and systems should be integrated, so that it is convenient to use and get things done. Similar to smart phones today, each smart phone can provide different functions beyond just calling and receiving phone calls. While the technology has advanced, this phenomenon of getting integrated product and services is unavoidable and more common to happen.

In general, an online provider system for RHS involves three parties: drivers, a service provider (SP) and riders corresponding to driver mobile terminal, terminal processing server, and passenger mobile terminal, as shown in the Figure1 respectively (Pham et al., 2017). Explanations for each component and how RHS can function is described as follows. Both drivers and passengers can download the smartphone apps, GPS and Network communication technology are used to collect and transmit data to support the service. There are databases, network communication module and trade processing module in terminal processing server (Ng, 2016). The gigantic database contains all the information of participants, and the information is delivered and received by the communication module in the drivers’ and passengers’ apps. The passengers will generate an order according to his location delivered to the online transportation platform, and the platform will find a suitable driver for him, who is nearby. Meanwhile, the trade processing module is responsible for the trading connection between drivers and passengers (Chen et al., 2017). The collaboration of these parts makes the complete system run efficiently. Functionality of this system is useful and convenient since it allows users to get a private car at anywhere and anytime with lower costs than taxis via their smart phone apps. The RHS can serve users the purpose of convenience to get private cars with lower costs. However, there are some ethical concerns for the RHS system. Millions of personal information can be obtained without any legal restrictions and with very low cost. This means that service providers and drivers know details of their customers. They can sell to any third parties under certain ways to cover their identities and responsibilities from legal bidding. Private drivers and companies can get more revenues and sources of income by providing these services. In some countries such as China, drivers need to have a separate application authorized by the local government in order to be on the list.

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