Prototype business models for Mobility-as-a-Service

Mobility as a Service (MaaS) is a promising concept which aims at offering seamless mobility to end users and providing economic, societal, transport-related and environmental benefits to the cities of the future. To achieve a successful future market take-up of MaaS it is important to develop prototype business models to offer high-value bundled mobility services to customers, as well as enable the MaaS operator and the involved actors to capture value. This paper aims at investigating the business perspective of MaaS by collecting qualitative data from workshops and in-depth interviews in three European metropolitan areas: Budapest, Greater Manchester and the city of Luxembourg. The analysis of the collected data contributed to the in-depth analysis of the MaaS business ecosystem and the identification of the champions of MaaS in the three areas. Prototype business models for MaaS are developed based on the Osterwalder's canvas, to describe how MaaS operators may create, deliver, and capture value. Our findings indicate that the MaaS ecosystem comprises of public and private actors who need to cooperate and compete in order to capture value. Although noticeable deviations among the study areas are observed, mobility service providers, public transport authorities and regional authorities were commonly indicated as the key actors in a MaaS partnership. In addition, viewed as a system, enablers and barriers to MaaS are identified based on the systems’ of innovation approach. The analysis indicates that the regulatory framework of the cities, the lack of standardization and openness of the application programming interfaces and the need for transport-related investments constitute risks for the successful implementation of MaaS in the study areas. Trust between MaaS actors and cooperation in e-ticketing are key enablers in some of the study areas

Modeling cross-national differences in automated vehicle acceptance

The technology that allows fully automated driving already exists and it may gradually enter the market over the forthcoming decades. Technology assimilation and automated vehicle acceptance in different countries is of high interest to many scholars, manufacturers, and policymakers worldwide. We model the mode choice between automated vehicles and conventional cars using a mixed multinomial logit heteroskedastic error component type model. Specifically, we capture preference heterogeneity assuming a continuous distribution across individuals. Different choice scenarios, based on respondents’ reported trip, were presented to respondents from six European countries: Cyprus, Hungary, Iceland, Montenegro, Slovenia, and the UK. We found that large reservations towards automated vehicles exist in all countries with 70% conventional private car choices, and 30% automated vehicles choices. We found that men, under the age of 60, with a high income who currently use private car, are more likely to be early adopters of automated vehicles. We found significant differences in automated vehicles acceptance in different countries. Individuals from Slovenia and Cyprus show higher automated vehicles acceptance while individuals from wealthier countries, UK, and Iceland, show more reservations towards them. Nontrading mode choice behaviors, value of travel time, and differences in model parameters among the different countries are discussed

Social marketing and healthy eating : Findings from young people in Greece

This document is the Accepted Manuscript version. The final publication is available at Springer via http://dx.doi.org/10.1007/s12208-013-0112-xGreece has high rates of obesity and non-communicable diseases owing to poor dietary choices. This research provides lessons for social marketing to tackle the severe nutrition-related problems in this country by obtaining insight into the eating behaviour of young adults aged 18–23. Also, the main behavioural theories used to inform the research are critically discussed. The research was conducted in Athens. Nine focus groups with young adults from eight educational institutions were conducted and fifty-nine participants’ views towards eating habits, healthy eating and the factors that affect their food choices were explored. The study found that the participants adopted unhealthier nutritional habits after enrolment. Motivations for healthy eating were good health, appearance and psychological consequences, while barriers included lack of time, fast-food availability and taste, peer pressure, lack of knowledge and lack of family support. Participants reported lack of supportive environments when deciding on food choices. Based on the findings, recommendations about the development of the basic 4Ps of the marketing mix, as well as of a fifth P, for Policy are proposedPeer reviewe

Starlight-polarization-based tomography of the magnetized ISM: Pasiphae's line-of-sight inversion method

We present the first Bayesian method for tomographic decomposition of the plane-of-sky orientation of the magnetic field with the use of stellar polarimetry and distance. This standalone tomographic inversion method presents an important step forward in reconstructing the magnetized interstellar medium (ISM) in 3D within dusty regions. We develop a model in which the polarization signal from the magnetized and dusty ISM is described by thin layers at various distances. Our modeling makes it possible to infer the mean polarization (amplitude and orientation) induced by individual dusty clouds and to account for the turbulence-induced scatter in a generic way. We present a likelihood function that explicitly accounts for uncertainties in polarization and parallax. We develop a framework for reconstructing the magnetized ISM through the maximization of the log-likelihood using a nested sampling method. We test our Bayesian inversion method on mock data taking into account realistic uncertainties from $Gaia$ and as expected for the optical polarization survey PASIPHAE according to the currently planned observing strategy. We demonstrate that our method is effective in recovering the cloud properties as soon as the polarization induced by a cloud to its background stars is higher than $\sim 0.1\%$, for the adopted survey exposure time and level of systematic uncertainty. Our method makes it possible to recover not only the mean polarization properties but also to characterize the intrinsic scatter, thus opening ways to characterize ISM turbulence and the magnetic field strength. Finally, we apply our method to an existing dataset of starlight polarization with known line-of-sight decomposition, demonstrating agreement with previous results and an improved quantification of uncertainties in cloud properties.Comment: 28 pages, including 2 appendices, submitted to A&

Matching supply and demand in crowdshipping: A theoretical framework

The emergence of internet and smartphones had played an important role in the increase of on-demand economy. Crowdshipping (CS) is an emerging trend that is expected to reduce the externalities caused by Urban Freight Transport (UFT). However, modelling the CS services, predicting their market share and their effect in the network is not a trivial task. CS matches the demand created by freight transport companies with the available capacity offered by passengers. Currently a gap exists in the literature on models that integrate the decisions related to the supply and the choices that identify the demand and matches them in the real-time. This paper presents a theoretical methodological framework that proposes an innovative collection of preference data in order to develop choice models that identify the need willingness of commuters to crowdship. In parallel it calculates the demand and proposes the development of a real-time matching simulator for the assignment of packets to crowdshippers and then to the network