Vera Lúcia Costa

Abstract

Abstract
The proliferation of new technologies is revolutionizing the public transport sector, allowing Operators to replace complex and expensive infrastructures by travellers' mobile devices and online management channels and platforms. This paper aims to present the Seamless Mobility platform, a disruptive solution based on these new channels, which main goal is to facilitate and promote public transport usage for travellers, as well as reducing operational costs for public transport companies. The Seamless Mobility platform integrates three main components: (i) mobile payments, (ii) route planner, and (iii) social network. The payment component is based on the pay-as-you-go concept with check-in and check-out requiring the reading of the corresponding QR Code station. The route planner combines information from published schedules with real-time information to identify the nearest stops, the next departures, or the best route for a scheduled trip. The social network component allows real time sharing among travellers of public transport information, related to several aspects of the service (e.g. noise, skilfulness of drivers). To test the concept, a mobile application, called OneRide, was developed. This application was tested by users in real environment, in the city of Porto, Portugal. The results show that users considered the system extremely useful, since it is more convenient than traditional systems. It was also clear that users valued the integration of additional and complementary services with mobile payments, such as information about their journey, maps and schedules. Regarding the social component some users found it difficult to understand the concept, but once they understood they considered it very useful. The use of the QR Codes to perform the payment has shown to be one of the main challenges to be addressed, since lighting conditions, position and distance to the QR Code influences the reading process. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
Nowadays, mobile phones are ubiquitous systems of our society. Nevertheless, the adoption of this technology to perform mobile payments, namely in public transport, was only implemented in a few number of transport networks. Thus, this paper aims to understand which are the main factors that may influence the adoption of mobile payments in public transport. For this purpose, a survey was applied to different groups of population. The study was conducted on the public transport networks of a medium-sized metropolitan area (Oporto-Portugal) and of a big-sized metropolitan area (Beijing-China). The evaluation results of the current services of purchase and validation of public transport tickets almost never show significant statistical differences (p>0.05) for the traditional variables used by the literature. This is particularly true for age. Nevertheless, some mobility factors can sometimes play an important role in the assessment of ticketing systems. Moreover, although the high differences between the ticketing systems in both cities, Chinese and Portuguese have a similar opinion about the systems implemented in their cities. Still, Chinese reveal a higher motivation to adopt the new ticketing system. In general, such system is greatly accepted by the respondents and the potential market is expected to be high (30-68%). Although this technology cannot replace the traditional systems, it can contribute to increasing the overall efficiency of the transport networks. The improvement of the passengers' appraisal, the reduction of operational and the maintenance costs of transport operators are the network impacts most expected. Convenience and time saving are the main advantages mentioned while questions about privacy, interaction and reliability are stated as the main concerns to adopt it. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
The application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users. Comparative Approaches to Using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis.

Abstract