Inviting travelers to the smorgasbord of sustainable urban transport: evidence from a MaaS field trial

A Mobility-as-a-Service (MaaS) concept, UbiGo, was implemented in Gothenburg, Sweden, and used for a 6-month period by 195 individuals in 83 households. Four participant subgroups were identified: Car shedders, Car accessors, Simplifiers, and Economizers. A qualitative analysis revealed that the subgroups had different reasons to join the service and different expectations of the change that would occur on the basis of the altered preconditions offered by the service. Previous car users reduced their use of private car and increased their use of public transport and active modes. Participants who did not have access to a privately-owned car but thought they needed one discovered that they managed well without. Other participants were reinforced in their existing behaviors but in ways they did not envisage, depending on which goals they had at the outset of the trial. Overall, the participants were also satisfied with the service, as well as with stated changes and non-changes, even if this in some cases meant more planning. Based on the empirical findings it could be argued that a service approach, such as UbiGo, has the potential to reduce the need for private car ownership, and enable people to change their mode choices and travel patterns. The potential relies however on a number of specific features of the service of which flexibility and a need- rather than a mode-based approach are key features.     

How do passengers use travel time? A case study of Shanghai–Nanjing high speed rail

Traditional travel behavior theory regards travel time as a waste. Recent studies suggest that it carries a positive utility, among other reasons for the benefit of the activities conducted while traveling. However, most studies of travel time use have focused on conventional trains in developed countries. Few have systematically examined the permeation of information and communication technology (ICT) into travel time use and the correlates of activity participation in developing countries, particularly on high speed rail (HSR). Using a survey conducted on the Shanghai–Nanjing corridor (N = 901), this study examines how HSR passengers use their travel time and explores the correlates of the different types of activities of business and non-business travelers, respectively, through multivariate probit models. We found that 96% of the respondents use ICT during their HSR journey and that most passengers spend some of their travel time on work-related activities. Moreover, items carried and advance planning as well as work-related travel attributes contribute significantly to activity participation. However, the factors affecting time use of business and non-business travelers differ. HSR service design should facilitate passenger engagement in various activities and improvement of their travel experience. A stable internet connection, adequate power sockets, and a noise-free environment will promote both work and leisure activities on the HSR.     

A hazard-based approach to modelling the effects of online shopping on intershopping duration

Despite growing prevalence of online shopping, its impacts on mobility are poorly understood. This partially results from the lack of sufficiently detailed data. In this paper we address this gap using consumer panel data, a new dataset for this context. We analyse one year long longitudinal grocery shopping purchase data from London shoppers to investigate the effects of online shopping on overall shopping activity patterns and personal trips. We characterise the temporal structure of shopping demand by means of the duration between shopping episodes using hazard-based duration models. These models have been used to study inter-shopping spells for traditional shopping in the literature, however effects of online shopping were not considered. Here, we differentiate between shopping events and shopping trips. The former refers to all types of shopping activity including both online and in-store, while the latter is restricted to physical shopping trips. Separate models were estimated for each and results suggest potential substitution effects between online and in-store in the context of grocery shopping. We find that having shopped online since the last shopping trip significantly reduces the likelihood of a physical shopping trip. We do not observe the same effect for inter-event durations. Hence, shopping online does not have a significant effect on overall shopping activity frequency, yet affects shopping trip rates. This is a key finding and suggests potential substitution between online shopping and physical trips to the store. Additional insights on which factors, including basket size and demographics, affect inter-shopping durations are also drawn.     

Change in list of a ship due to vertical shifting of a weight

When a ship gets an original list, and a weight is to be vertically shifted (or is to be suspended by a ship’s gear), two approaches for calculating the change in list of the ship have been developed as follows: the first one—for the case when the biggest list of a ship is not more than 5–6°, and the second one—when the biggest list of a ship is not more than 10–12°. These equations have been represented in dimensionless form and reviewed for different specific shapes of a ship’s sides: circle, tumblehome, and wall-sided ones. For wall-sided ships, in order to simplify the procedure of calculating the change in list, a graphical approach and corresponding nomogram has been proposed and designed. The developed method and equations can be also used for calculating the change in list of a ship when heavy-lift cargo is just suspended by the ship’s own gear during heavy-lift operations.     

Trust and safety onboard

Shipping is a high-risk industry. The aims of this conceptual paper are to build a framework showing in what way safety onboard is influenced by trust, and to identify the main obstacles to trust-building within the shipping industry. To meet these aims, a literature review and a pilot study are conducted. The study shows that interpersonal trust from employees to managers, and among seafarers, seems to be a prerequisite and an indirect factor, or mediating variable, that influence safety-related organizational outcomes positively and seems to reduce human errors. Interpersonal trust seems to be most valuable in weak situations, which means situations that are not critical and when no exact guidance or incentives to behave in a particular way are needed. An optimal level of trust exists onboard, and because of the high-risk environment, this optimal level of trust is expected to be relatively high. The main obstacles to trust within the shipping industry seem to be the dual employment practice, the physical distance between onboard, crewing agency and onshore, the reduced competence requirements, the frequent reorganization of the crew and multiculturalism. The paper contributes to the trust and to the safety literature by a new framework and to the development of 11 hypotheses on trust and safety. Finally, the paper is indicating that trust may be the missing piece in the safety puzzle.     

Revisiting port pricing; a proposal for seven port pricing principles

A review of seven large landlord port authorities around the world reveals a notable diversity of pricing structures. While port authorities increasingly act as commercial undertakings, port pricing often seems to be not driven by commercial considerations. In this paper, we argue that ports can be regarded as “business ecosystems” with multiple users. This provides a valuable perspective on pricing and raises the question of whether ports can be regarded as two-sided markets. We argue this is not the case. The business ecosystem perspective provides a basis for deducing seven pricing principles for port authorities that are detailed in the paper and illustrated with cases these principles. These pricing principles are broadly follow a direct user pays approach; capture value from “non-core” tenants; price aggressively for activities with a high strategic value; differentiate pricing based on price elasticity and connectivity improvements; maximize revenue from long-term lease agreements, price port dues competitively; critically consider differentiation of charges based on environmental performance; and finally use incentives to align interests of terminal operators and shipping lines. We conclude that the ecosystem perspective is central to the understanding of pricing decisions of port authorities and that various pricing issues deserve more attention.     

Impacts of built environment and emerging green technologies on daily transportation greenhouse gas emissions in Quebec cities: a disaggregate modeling approach

This paper aims to investigate the impact of the built environment (BE) and emerging transit and car technologies on household transport-related greenhouse gas emissions (GHGs) across three urban regions. Trip-level GHG emissions are first estimated by combining different data sources such as origin–destination (OD) surveys, vehicle fleet fuel consumption rates, and transit ridership data. BE indicators for the different urban regions are generated for each household and the impact of neighborhood typologies is derived based on these indicators. A traditional ordinary least square (OLS) regression approach is then used to investigate the direct association between the BE indicators, socio-demographics, and household GHGs. The effect of neighborhood typologies on GHGs is explored using both OLS and a simultaneous equation modeling approach. Once the best models are determined for each urban region, the potential impact of BE is determined through elasticities and compared with the impact of technological improvements. For this, various fuel efficiency scenarios are formulated and the reductions on household GHGs are determined. Once the potential impact of green transit and car technologies is determined, the results are compared to those related to BE initiatives. Among other results, it is found that BE attributes have a statistically significant effect on GHGs. However, the elasticities are very small, as reported in several previous studies. For instance, a 10 % increase in population density will result in 3.5, 1.5 and 1.4 % reduction in Montreal, Quebec and Sherbrooke, respectively. It is also important to highlight the significant variation of household GHGs among neighborhoods in the same city, variation which is much greater than among cities. In the short term, improvements on the private passenger vehicle fleet are expected to be much more significant than BE and green transit technologies. However, the combined effect of BE strategies and private-motor vehicle technological improvement would result in more significant GHGs reductions in the long term.     

Immigrant status and commute distance: an exploratory study based on the greater Golden Horseshoe

With 8.76 million residents in 2011, the population of Southern Ontario’s Greater Golden Horseshoe (GGH) has grown dramatically over the past decades, driven by net domestic in-migration and immigration. Corresponding to its growth in population, commuting distances and times within the region have grown as well. Yet, despite the number of immigrants that the region attracts on a yearly basis, there is comparatively little information on commute distances. Consequently, this paper examines commuting distance amongst immigrants in the GGH. Specifically, it evaluates commute distance by immigrant status (immigrants and native born), along with how commute distance differs by arrival cohort and ethnic and racial population groups. Results indicate that commute distance increases with increasing duration of residence, with differences by race and ethnicity.     

I can’t believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice

The number of conventionally fuelled motor vehicles in use is increasing worldwide despite warnings about finite fossil fuel and the detrimental impacts of burning such fuels. While electric vehicles, the subject of much research, generate far less emissions and offer the potential for power from renewable sources, they are yet to significantly penetrate the market. Tangible barriers such as price and vehicle range still exist, but consumer attitudes also drive behaviour. This paper examines attributes in a framework relatively new to transportation and energy policy; best–worst scaling. This method is widely considered an improvement over traditional methods of eliciting attitudes and beliefs, where respondents select attitudes they find best or worst from a set of attitudinal statements. To avoid potential endogeneity bias, we jointly model attitudes and choice for the first time with best–worst data. It is found that energy crisis, air quality and climate change concerns influence behaviour with respect to vehicle range and that travel behaviour change and forms of government incentives are needed influences on behaviour with respect to vehicle emissions. It is argued that correctly modelling attitudes reduces the error term of the vehicle choice model and provides policy makers with an improved lens for assessing behaviour. Additionally, the methods described within can easily be adapted to other policy scenarios.