Conference Paper

Usage patterns and impacts of a mobility flat rate traced with a Smartphone App

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... The overall high WTP for bundles may not be unreasonable and was observed in Switzerland before. In an experiment, the national train company (SBB) offered a mobility package called "SBB Greenclass" (a price bundle) 6 (Becker et al., 2018). Greenclass included a 1st class GA travelcard, a BMW i3, park and ride, car-sharing, bicycle-sharing, and vouchers for taxi journeys (total value of CHF 250). ...
Technological innovations in recent decades have led to a further decrease in transport costs. As a result, global passenger transport, which is a primary enabler of increased globalisation, is at an all-time high. This has led to interconnectedness of states, organisations and people on a scale never seen before. While this development has many positive sides, such as increased overall prosperity, the transportation sector is also a significant source of greenhouse gas emissions and thus a primary driver of climate change. In parallel, digital transformation is leaving its mark on the transport sector. It is a principal driver of future transport directions, including automated driving, passenger drones and the autonomous delivery of goods. More subtly, today's transport system is already being transformed. New business models that rely on tight digital integration of services have started to appear and new mobility services such as ride sourcing, (e-)bike sharing and e-scooter sharing have been introduced in many cities around the world. Specifically, two developments connected to digital transformation have driven the emergence of new mobility services and have increased analysts' ability to study the transportation system. First, as a consequence of the high market penetration of smartphones, there is a direct interface between most individuals and mobility providers. This allows for the comprehensive personalisation of services: the location of the customer, information about capacities of transport networks and complementary information (such as weather data) can be taken into account when a service is offered. Second, the cost and effort required to obtain data on individuals, including their location, has decreased, enabling this information to be used to inform the design of transport policies. This thesis presents three contributions that are to a great extent driven by the global trends of digital transformation and subsequent personalisation. Two contributions are part of the broad topic of new mobility services, which are likely to shape future (urban) transport systems: Mobility as a Service (MaaS) bundles and electric bicycle-sharing systems. A wide array of shared and highly integrated services may contribute to a decrease in emissions and have the potential to ease the tension between increasing mobility and mitigating the environmental burden of the transport system. The third contribution assumes a more global perspective and examines one of the primary determinants of daily commuting patterns: choice of residential location relative to an individual's work location. A personal network survey was conducted to study the effects of proximity to personal contacts on residential location choice and its connection to commuting. The first contribution of the thesis shows that MaaS bundles may indeed be an attractive option for a certain share of the population. However, the results also suggest that not all services are viewed as complementary by potential customers. Including non-complementary services may decrease the propensity of customers to choose a particular bundle. Operators should thus carefully target bundles to potential customers. The second contribution analyses free-floating e-bike sharing. Free-floating (e-)bike-sharing services are often part of MaaS bundles and provide the flexibility that traditional public transportation sometimes lacks. This chapter shows that free-floating e-bike sharing is part of an ongoing evolution of bicycle-sharing systems. The competitive position of e-bike sharing compared to traditional modes of urban transportation is also examined. Drivers of e-bike-sharing demand are analyzed and it is shown that population, workplace density and proximity to central locations are among the most important drivers of demand. Transferability of the models to new areas is also analysed and discussed. The question of how personal networks affect residential location choice is answered using data from a personal network survey that was collected as part of this thesis. It is shown that personal networks are an important factor and ignoring them may lead to an overestimation of commute time in analyses of residential location choice. Partial compensation of longer commutes may be achieved through higher access to individual social capital that is provided by proximity to personal contacts. This potentially affects transport policies aimed at reducing time spent commuting.
... The overall high WTP for bundles may not be unreasonable and was observed in Switzerland before. In an experiment, the national train company (SBB) offered a mobility package called SBB Greenclass (a price bundle) 7 (Becker et al., 2018). Greenclass included a 1st class GA travelcard, a BMW i3, park and ride, car sharing, bicycle-sharing, and vouchers for taxi journeys (total value of CHF 250). ...
Novel approaches to service bundling in the passenger transportation market are enabled by technology driven innovations and give rise to so called Mobility as a Service (MaaS) concepts. These approaches promise to increase the accessibility of existing public transportation services, possibly decrease car ownership rates and lower the environmental burden of the transportation system. However, the potential effects of comprehensive service bundles in the passenger transportation market are still largely unclear. In a competitive market, the potential success of MaaS bundles follows consumer valuation of the bundles as compared to valuation of stand-alone services. Thus, the difference between the bundle and sum-of-parts willingness to pay (WTP) is an indicator for the valuation of the bundling itself (which includes service integration valuation) and effects the competitiveness of the service bundles. In this study, several discrete choice experiments were conducted to indirectly estimate consumers' WTP for stand-alone transportation services and service bundles. The results indicate that public transportation, car sharing, and park and ride services are valuated significantly higher when offered in a bundle instead of as a stand-alone service. Bicycle-sharing, electrical bicycle (e-bike) sharing and taxi services are valuated lower. Potential consumers also exhibit a high WTP for a smartphone application that integrates the services and manages ticketing and payment. Consequently, subscription-based pure bundles for all transportation modes may not be the optimal strategy for mobility providers. Instead, it may be better to bundle public transportation with car sharing and park and ride to exploit the higher WTP and offer (electric) bicycle-sharing and taxi services on a pay-per-use basis. In this way, profitability of a public transportation system could be increased.
GPS based campaigns have been hailed as an alternative to transportation surveys that promise relatively high accuracy at a relatively low burden on the participants and fewer forgotten trips. However they still necessitate the recruitment of participants and are thus potentially biased and certainly not encompassing significant parts of the population. Given the high penetration of mobile phones, passive tracking by telephone providers would alleviate those two shortcomings at the cost of reduced sampling frequency and positional accuracy. The trade-off in quality has not yet been quantified and therefore recommendations on sensible thresholds are not yet available. In this study therefore, instead of presenting yet another method for mode of transport classification, we therefore compare the performance of existing mode detection schemes under deteriorating sampling rates and positional accuracies. As a possibility to compensate for the deteriorating signal we also calculate features from users’ positional histories that could be beneficial if their behaviour is repetitive. The evaluation is not only based on pointwise accuracy, but includes quality measures that pertain to trips as a whole. We find that the necessary accuracy and sampling rate for applications will depend on whether the information of whole trajectories can be used, or whether only the current information is available. The former being relevant to ex-post analyses while the latter situation appears more frequently in near-time analyses. For segmentwise classification, there is no major impact on the quality of the classification by the tested levels of spatial accuracies as long as the sampling intervals can be kept at or below a minute, whereas for point based classification the sampling interval should be between 30 s and a minute and increasing spatial accuracy always improves the classification.
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Fast advances in autonomous driving technology trigger the question of suitable operational models for future autonomous vehicles. A key determinant of such operational models’ viability is the competitiveness of their cost structures. Using a comprehensive analysis of the respective cost structures, this research shows that public transportation (in its current form) will only remain economically competitive where demand can be bundled to larger units. In particular, this applies to dense urban areas, where public transportation can be offered at lower prices than autonomous taxis (even if pooled) and private cars. Wherever substantial bundling is not possible, shared and pooled vehicles serve travel demand more efficiently. Yet, in contrast to current wisdom, shared fleets may not be the most efficient alternative. Higher costs and more effort for vehicle cleaning could change the equation. Moreover, the results suggest that a substantial share of vehicles may remain in private possession and use due to their low variable costs. Even more than today, high fixed costs of private vehicles will continue to be accepted, given the various benefits of a private mobility robot.
Free-floating car-sharing has been one of the latest innovations in the car-sharing market. It allows its customers to locate available vehicles via a smartphone app and reserve them for a short time prior to their rental. Because it is available for point-to-point trips, free-floating car-sharing is not only an alternative to private cars, but also to public transportation. Using spatial regression and conditional logit analysis of original transaction data of a free-floating car-sharing scheme in Switzerland, this research shows that free-floating car-sharing is mainly used for discretionary trips, for which only substantially inferior public transportation alternatives are available. In contrast to station-based car-sharing, it does not rely on high-quality local public transportation access, but bridges gaps in the existing public transportation network.
Individual travel behavior is to a large extent shaped by the respective portfolio of available mobility tools such as cars, season-tickets or a car-sharing membership. However, the choices of different mobility tools are interdependent and are also affected by individual attitudes. This paper presents an approach to jointly model the choice of four different mobility tools – including car-sharing. Using data from the Swiss transportation micro census of 2005 and 2010, it is shown that car-sharing is used as a supplement to a public transportation-oriented lifestyle, but is also used by car owners. The results further indicate that personal attitudes have a substantial effect on the choice of mobility tools and should therefore be accounted for when modeling such decisions.
The concept of Mobility as a Service or MaaS has been proposed as feasible way to achieve more sustainable transport. One example of such a service is UbiGo, a broker service for everyday urban travel developed and evaluated within the Go:Smart project in Gothenburg, Sweden. This paper presents evidence of travel behavior and related changes from a six-month field operational test (FOT), during which 195 participants tested the new service. Based on participant questionnaires, interviews, and travel diaries, change-enabling service attributes are identified, including the ‘transportation smorgasbord’ concept, simplicity, improved access and flexibility, and economy. Although not a service attribute per se, the FOT also enabled the trialability of new behaviors and a reevaluation of convenience. Additionally, the broader implications of the FOT findings on understanding travelers’ new choices and behaviors are discussed in terms of the future design of MaaS. Service design and demand are not independent of each other, and if a mobility service is to change behavior (i.e. achieve impact) as well as create added value, these goals need to drive design decisions and a deliberate, conscious development of service dimensions such as customization, bundling, and range of the offer. Based on the experiences gained, the authors emphasize a more holistic and flexible perspective on mobility (and design perspective on mobility services) that is focused on serving users’ needs, and that involves capitalizing on synergies between public and private actors, in order to develop the MaaS ‘offer’ and better meet the urban mobility challenge ahead.
Two years into the introduction of City CarShare in San Francisco, California, nearly 30% of members have gotten rid of one or more cars, and two-thirds stated that they opted not to purchase another car. By City CarShare's second anniversary, 6.5% of members' trips and 10% of their vehicle miles traveled were in carshare vehicles. Matched-pair comparisons with a statistical control group suggest that, over time, members have reduced their total vehicular travel. Because carshare vehicles tended to be small and fuel-efficient, per capita gasoline consumption and greenhouse gas emissions among members also appeared to go down. Suppressed travel likely reflected a combination of influences: reduced car ownership, more judicious and selective use of cars for particular trip purposes, and multiple-occupant carshare trips. Carsharing, however, has also enhanced mobility and allowed members to reach more destinations in and around San Francisco conveniently and to do so more quickly. Because it widens mobility choices and offers a resourceful form of automobility, carsharing is a welcome addition to the urban transportation sector in cities such as San Francisco.
Many consumer choice situations are characterized by the simultaneous demand for multiple alternatives that are imperfect substitutes for one another. A simple and parsimonious multiple discrete-continuous extreme value (MDCEV) econometric approach to handle such multiple discreteness was formulated by Bhat (2005) [Bhat, C.R., 2005. A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions. Transportation Research Part B 39(8), 679–707]. within the broader Kuhn–Tucker (KT) multiple discrete-continuous economic consumer demand model of Wales and Woodland (1983) [Wales, T.J., and Woodland, A.D., 1983. Estimation of consumer demand systems with binding non-negativity constraints. Journal of Econometrics 21(3), 263–85]. This paper examines several issues associated with the MDCEV model and other extant KT multiple discrete-continuous models. Specifically, the paper proposes a new utility function form that enables clarity in the role of each parameter in the utility specification, presents identification considerations associated with both the utility functional form as well as the stochastic nature of the utility specification, extends the MDCEV model to the case of price variation across goods and to general error covariance structures, discusses the relationship between earlier KT-based multiple discrete-continuous models, and illustrates the many technical nuances and identification considerations of the multiple discrete-continuous model structure through empirical examples. The paper also highlights the technical problems associated with the stochastic specification used in the KT-based multiple discrete-continuous models formulated in recent Environmental Economics papers.
Several consumer demand choices are characterized by the choice of multiple alternatives simultaneously. An example of such a choice situation in activity-travel analysis is the type of discretionary (or leisure) activity to participate in and the duration of time investment of the participation. In this context, within a given temporal period (say a day or a week), an individual may decide to participate in multiple types of activities (for example, in-home social activities, out-of-home social activities, in-home recreational activities, out-of-home recreational activities, and out-of-home non-maintenance shopping activities).
Stated Preference Design for Exploring Demand for
  • M Matyas
  • K Kamargianni
Matyas, M. and K. Kamargianni (2017) Stated Preference Design for Exploring Demand for "Mobility as a Service" Plans, paper presented at the 5 th International Choice Modelling Conference, Cape Town.