Major cities in developing countries are increasingly becoming motorized. Thus, effective solutions to address the negative impacts that come with rising car-ownership are needed as part of an overall travel demand management strategy. In developed and emerging economies, shared-mobility in the form of car-sharing is becoming popular as potentially low-cost and environmentally sustainable alternative to car-ownership. Yet, our understanding of car-sharing adoption and diffusion factors in developing countries is limited. In this study, we fill this gap by examining car-sharing adoption intentions among young adults aged between 18 and 35 years in Ghana, Sub-Saharan Africa. Using structural equation modelling, we model car-sharing adoption intentions based on a framework that integrates individuals’ perception of the benefits of car-sharing, attitudes towards the environment and technology, trust of stewardship in car-sharing, perception of innovativeness of car-sharing, travel expectations and socio-demographic factors. We found that pro-technology and pro-environmental attitudes correlate positively with perceived benefits of car-sharing. Perceived benefits of car-sharing, in turn, has the largest predictive effect on intentions to car-share. Other factors, including individuals’ previous experience using Uber on-demand taxi services, gender, education, driver’s licensure and expectation of comfortable and fast travel options, all predict car-sharing adoption intentions. While there exists an interest in both station-based and free-floating car-sharing services, more of the would-be users favour the latter than the former. Also, majority of the potential adopters (62%) would join a car-sharing service within the first 1 year of its introduction. An important finding is that dissatisfaction with existing public transit services underpins car-sharing intentions, implying that relying on car-sharing alone to meet travel needs, without a holistic strategy of providing quality and affordable public transit services, could lead to unsustainable outcomes.

Autonomous cars controlled by an artificial intelligence are increasingly being integrated in the transport portfolio of cities, with strong repercussions for the design and sustainability of the built environment. This paper sheds light on the urban transition to autonomous transport, in a threefold manner. First, we advance a theoretical framework to understand the diffusion of autonomous cars in cities, on the basis of three interconnected factors: social attitudes, technological innovation and urban politics. Second, we draw upon an in-depth survey conducted in Dublin (1,233 respondents), to provide empirical evidence of (a) the public interest in autonomous cars and the intention to use them once available, (b) the fears and concerns that individuals have regarding autonomous vehicles and (c) how people intend to employ this new form of transport. Third, we use the empirics generated via the survey as a stepping stone to discuss possible urban futures, focusing on the changes in urban design and sustainability that the transition to autonomous transport is likely to trigger. Interpreting the data through the lens of smart and neoliberal urbanism, we picture a complex urban geography characterized by shared and private autonomous vehicles, human drivers and artificial intelligences overlapping and competing for urban spaces.

Artificial intelligence (AI) is becoming part of the everyday. During this transition, people’s intention to use AI technologies is still unclear and emotions such as fear are influencing it. In this paper, we focus on autonomous cars to first verify empirically the extent to which people fear AI and then examine the impact that fear has on their intention to use AI-driven vehicles. Our research is based on a systematic survey and it reveals that while individuals are largely afraid of cars that are driven by AI, they are nonetheless willing to adopt this technology as soon as possible. To explain this tension, we extend our analysis beyond just fear and show that people also believe that AI-driven cars will generate many individual, urban and global benefits. Subsequently, we employ our empirical findings as the foundations of a theoretical framework meant to illustrate the main factors that people ponder when they consider the use of AI tech. In addition to offering a comprehensive theoretical framework for the study of AI technology acceptance, this paper provides a nuanced understanding of the tension that exists between the fear and adoption of AI, capturing what exactly people fear and intend to do.

Land use–transport interaction modeling: A review of the literature and future research directions

Retrospective understanding of the magnitude and pace of urban expansion is necessary for effective growth management in metropolitan regions. The objective of this paper is to quantify the spatial–temporal patterns of urban expansion in the Greater Kumasi Sub-Region (GKSR)—a functional region comprising eight administrative districts in Ghana, West Africa. The analysis is based on Landsat remote sensing images from 1986, 2001 and 2014 which were classified using supervised maximum likelihood algorithm in ERDAS IMAGINE. We computed three complementary growth indexes namely; Average Annual Urban Expansion Rate, Urban Expansion Intensity Index (UEII) and Urban Expansion Differentiation Index to estimate the amount and intensity of expansion over the 28-year period. Overall, urban expansion in the GKSR has been occurring at an average annual rate of 5.6 %. Consequently, the sub-region’s built-up land increased by 313 km² from 88 km² in 1986 to 400 km² in 2014. The analysis further show that about 72 % of the total built-up land increase occurred in the last 13 years alone, with UEII value of 0.605 indicating a moderate intensity of urban expansion. Moreover, the metropolitan-core of the sub-region, being the focal point of urban development and the historical origins of expansion, accounted for more than half of the total built-up land increase over the 28-year period. Over the last decade and half however, urban expansion has spilled into the neighbouring peripheral districts, with the highest intensity and fastest rate of expansion occurring in districts located north and north east of the sub-regional core. We recommend a comprehensive regional growth management strategy grounded in effective strategic partnerships among the respective administrative districts to curb unsustainable urban expansion.