The current difficult situation in the world caused by the spread of the COVID-19 virus has led to the development of problems in many branches of the economy. However, it has significantly affected transport, which on the one hand, is the bloodstream of the economy and, on the other hand, creates a threat for virus infection. Thus, in various countries, different mobility-related restrictions during pandemic policies around the world have been introduced. What is more, plans for initiatives after lockdown have also started to appear. Moreover, not have only cities introduced appropriate management policies, but companies have also started providing logistics services, especially those offering new mobility solutions. We found a literature and research gap indicating the recording or combination of the different types of business practices and innovations used worldwide in new mobility companies in the case of a pandemic situation. Therefore, this article is dedicated to the business innovations that appear in the new mobility industry during the COVID-19 pandemic in connection to post-pandemic transportation plans in Asia, Europe, and America. In this work, we conducted two-level research based on the desk research and expert research methodologies. From the business point of view, the results show that car-sharing systems (most organizational practices) and ride-sharing services (most safety practices) have most adapted their business models to pandemic changes. In turn, bike-sharing services have implemented the fewest business practices and innovations. From the urban transport systems point of view, the results show that European authorities have proposed the most plans and practice projects for new mobility after the pandemic compared to Asia and America. The obtained results indicate, however, that business practices do not coincide with the authorities’ plans for transport after the pandemic. Moreover, the results show a lack of complementarity between the developed practices and a reluctance to create open innovations in the new mobility industry. The article supports the management of new mobility systems in times of pandemic and in post-COVID reality.
Nowadays, the concept of new mobility solutions like shared mobility systems is becoming more and more popular in current transport systems. The next technological step will be the idea of replacing traditional vehicles with autonomous ones. Because autonomous vehicles are a new concept in the automotive market, we dedicated this article to the idea of using autonomous vehicles as a part of car-sharing systems in intelligent, urban transport systems. The research herein is focused on the economic aspects of using autonomous vehicles in comparison to the classic car fleet available in car-sharing systems and to vehicles that belong to individual owners. We present our method for appropriate fleet selection based on the Delphi method and the calculations made through a scientific experiment performed based on Hartley’s plan. The results indicate the relation of travel parameters (including vehicle type) to the total cost of travel in urban transport systems. We also present the main terms related to autonomous vehicles. This article provides support for people who want to deepen knowledge about autonomous vehicles and new mobility solutions used in urban transport systems.
Due to the development of the shared economy, increasingly more shared mobility providers have launched services based on the use of electric vehicles. The increasing growth of electric shared mobility services has produced various types of problems that do not occur (or occur with a limited effect) under conventional shared mobility systems. This increase in electric shared mobility problems has led to many effects, including limitations of the system zones or going out of business. To avoid difficulties in the functioning of electric shared mobility systems, various scientific studies have been undertaken to model and optimize the operation of these systems. Modeling and optimization mainly relate to one category of the system—for example, only to bike sharing. However, to understand the system of electric shared mobility holistically, there is a need to define the criteria generally as stimulants or destimulants. Based on these assumptions, we conducted research on the identification of factors influencing the development of electric shared mobility services. We conducted our own expert research based on the Social Network Analysis method. The aim of this study was to determine the factors that influence the development or recession of services in the entire electric shared mobility market in reference to selected stakeholders. The obtained results indicate a non-standard approach to the modeling and optimization of electric shared mobility services. This study could be used as support for creating electric shared mobility models and could also be helpful for service providers or local mobility managers through the developed recommendations.
The global spread of the COVID-19 virus has led to difficulties in many branches of the economy, including significant effects on the urban transport industry. Thus, countries around the world have introduced different mobility policies during the pandemic. Due to government restrictions and the changed behaviors of transport users, companies providing modern urban mobility solutions were forced to introduce new business practices to their services. These practices are also apparent in the context of the electric shared mobility industry. Although many aspects and problems of electric shared mobility have been addressed in scientific research, pandemic scenarios have not been taken into account. Noticing this research gap, we aimed to update a previously developed model of factors that influence the operation of electric shared mobility by incorporating aspects related to the COVID-19 pandemic and its impact on this industry. This article aims to identify the main factors influencing the electric shared mobility industry during the COVID-19 and post-lockdown periods, together with their operation areas and the involved stakeholders. The research was carried out on the basis of expert interviews, social network analysis (SNA), and the use of the R environment. The article also presents sustainable transport management recommendations for cities and transport service operators, which can be implemented after a lockdown caused by an epidemic. The results in this paper can be used to support transport modeling and the creation of new policies, business models, and sustainable development recommendations. The contents will also be helpful to researchers worldwide in preparing literature reviews for articles related to sustainable management in the COVID-19 pandemic reality.
The article was dedicated to the topic of energy consumption of driving cars equipped with an electric motor. Due to the emerging demands for the excessive use of energy by vehicles (including car-sharing system vehicles), the authors carried out research to determine factors that affect the energy consumption. Due to the occurrence of a research gap related to the lack of reliable scientific information regarding real electricity consumption by vehicles used in car-sharing systems, the authors attempted to determine these values based on the proposed research experiment. The purpose of the research was to identify factors that increase energy consumption while driving in the case of car-sharing systems and developing recommendations for users of car-sharing systems and system operators in relation to energy consumption. Based on data received from car-sharing system operators and to their demands that users move cars uneconomically and use too much energy, the authors performed a scientific experiment based on Hartley’s plan. The authors made journeys with electric cars from car-sharing (measurements) in order to compare real consumption with data obtained from operators. As a result, the authors developed a list of factors that negatively affect the energy consumption of electric vehicles from car-sharing systems. As conclusion, a number of recommendations were developed for car-sharing system operators on how to manage their systems to reduce excessive energy consumption in electric vehicles.
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