Analysis of the Influential Factors towards Adoption of Car-Sharing: A Case Study of a Megacity in a Developing Country

Abstract

Motorization has been escalating rapidly in developing countries, posing a severe challenge to sustainable urban mobility. In the past two decades, car-sharing has emerged as one of the most prominent alternatives to facilitate smart mobility solutions, thereby helping to reduce air pollution and traffic congestion. However, before its full-scale deployment, it is essential to understand the consumers’ acceptance of car-sharing systems. This study aimed to assess the public perception and acceptance of the car-sharing system through a stated preference (SP) questionnaire in the city of Lahore, Pakistan. The collected data contained detailed information on various service attributes of three alternative modes (car-sharing, private car, and taxi) in addition to the sociodemographic attributes of respondents. Data analysis and interpretation were performed using econometric models such as the Multinomial Logit Model (MNL), the Nested Logit Model (NL), and the Random Parameter Logit Model (RPL). Study findings revealed that several generic attributes such as travel time, travel cost, waiting time, and privacy were predicated as significant influential factors towards the adoption of car-sharing. Sociodemographic attributes, including age, education, monthly income, the individuals who had driver’s licenses, and frequency of travel in a week, were also found to be significant. The findings of the current study can provide valuable insights to stakeholders and transportation planners in formulating effective policies for car-sharing.

Sharing Economy

“…It also contributes to the protection of the environment, adopting sustainable consumption practices [34], and creates a tendency for the establishment of social relationships with the local community [35], positively affecting the society in this way. Safdar et al [36] argue that in the past two decades the practice of car-sharing has emerged as a solution to facilitate mobility, reducing air pollution and traffic congestion.…”

Optimal Deployment of Electric Vehicles’ Fast-Charging Stations

“…Constraint (10) defnes that EVs can only be charged in location j ∈ V if this site is chosen for accommodating a charging station. Constraint (11) stipulates that for the chosen station, a minimum one charger must be installed, with the total number of chargers not exceeding the station's capacity. If a station is not specifed within it, no chargers are deployed.…”

“…As a result, the notion of green transport is evolving, which refers to an easy, efcient, safe, low polluting, and diverse urban transport system [7][8][9]. With progressions in communication and technology, a green transport system provides one of the most efective solutions in combating air pollution, decreasing congestion, and easing the fuel crisis [10,11].…”

Analyzing Spatial Location Preference of Urban Activities with Mode-Dependent Accessibility Using Integrated Land Use–Transport Models

“…However, the literature demonstrates that these techniques have largely ignored taking into account subtle details of accessibility, such as those relating to a specific time of day or mode [17,18]. Due to rapid motorization, urbanization, and population growth, cities in developing nations face severe challenges such as traffic congestion, traffic accidents, increasing demand for land, environmental pollution, and the impact on the existing demand and supply for the transportation system, which ultimately impacts public health, city sustainability, and the country's economy [19][20][21]. Most developed countries, such as the United States and countries in Europe, have implemented integrated land use-transport models for sustainable urban planning [22,23].…”