“Sustainability” as a Motive for Choosing Shared-Mobility Services: The Case of Polish Consumers of Uber Services

Abstract

(1) Background: Uber Technologies are currently changing the pattern of urban transport. Statista reports that in the period 2017–2019 alone, the average monthly number of active Uber users worldwide increased by 126.5%, and the average monthly number of Uber trips grew by 115%. The purpose of this article is to identify the most important motives encouraging both current and potential customers to use Uber “taxi” services. Particular attention was paid to the factor of perceiving these services as a more sustainable way of meeting transport needs. Uber creates its image specifically on the idea of sustainability. (2) Methods: The operationalization of the sustainability concept was based on three dimensions: ecological, social and economic. The CAWI (Computer-Assisted Web Interview) technique was used to collect the research data. The representative research sample covered 1003 Poles. A logistic regression model was used to analyze empirical data collected based on the survey. The data analysis used R program and the selected packages for this program. (3) Results: Among the most important motives, sustainability is the most frequently indicated. (4) Conclusions: The choices of Uber services are significantly influenced by the reasons related to two sustainability pillars—one social and one economic. The factors significantly influencing consumer decision-making processes related to the use of shared mobility services belong to the following groups of motives: sustainable development, knowledge of information and communication technologies (ICT), innovation, user convenience and savings. The findings from the study can become the basis for organizations and local authorities to undertake appropriate marketing activities to promote shared-mobility services (SMS) and support sustainable and environmentally friendly development.

Exploring the Intention to Adopt Sustainable Mobility Modes of Transport among Young University Students

“…We therefore agree with Bąk et al [ 13 ] on two issues. On the one hand, that sustainable development is one of the greatest contemporary challenges and mobility can offer great opportunities, and on the other hand, that the impact of mobility on the sustainability of cities should be analyzed in terms of three dimensions: economic (e.g., additional income and savings), social (access to services and comfort) and environmental (reduction in energy consumption, greenhouse gas emissions, traffic congestion and noise).…”

“…However, only few studies focus on its ecological branch via ecological concern or knowledge (e.g., [ 1 , 20 , 21 , 35 ]). Additionally, even scarcer are those that have investigated consumers’ perception of the ecological, social and economic impacts of mobility transport modes and their influence on consumers’ intention to use transport modes [ 13 ].…”

“…On the other hand, since the Brundtland Commission in 1987, scholars and policy professionals have focused great concern on sustainable development that must meet the needs of the present without sacrificing the ability of future generations to do the same, namely economic, social and human development, and human, environmental and ecological health [ 12 ]. However, studies on consumers’ perception of the ecological, social, and economic impacts of mobility solutions and their influence on their adoption are very scarce and limited [ 13 ]. Consequently, this paper also strives to fulfill this gap.…”

Origin-Destination prediction from Road Segment Speed Data using GraphResLSTM Model

“…Origin-Destination (OD) prediction is a pivotal aspect of urban mobility planning and intelligent transportation system (ITS), as it aids in alleviating congestion and optimizing travel efficiency during peak hours and in heavily trafficked regions [1]. Emerging transportation solutions such as customized bus, carpooling, shared mobility services, taxi dispatching, and shared parking [2][3][4][5][6] are grouped under the umbrella term Intelligent Dispatched Mobility on Demand (IDMoD). IDMoD utilizes inferred OD matrix to proactively strategize ideal travel modes for passengers, thereby substantially cutting waiting times and enhancing overall travel efficacy.…”