Instant Mobility at Nomadic Workshop : Acceptability and social community for ridesharing and multimodality
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Instant Mobility at Nomadic Workshop : Acceptability and social community for ridesharing and multimodality

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Nomadic Workshop 15 November 2012, Lyon, written with Amel ATTOUR

Nomadic Workshop 15 November 2012, Lyon, written with Amel ATTOUR

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    Instant Mobility at Nomadic Workshop : Acceptability and social community for ridesharing and multimodality Instant Mobility at Nomadic Workshop : Acceptability and social community for ridesharing and multimodality Presentation Transcript

    • Acceptability and social community issuesfor ridesharing and multimodality success Nomadic Workshop, Lyon,15 November 2012 Nathalie Dubus, Orange Amel Attour, Ecole des Mines, Nancy
    • Instant Mobility and the Future of Internet Instant Mobility* project:  Context : increasing urban population, solve transportation issues, improve ecological impact and cities attractiveness  Instant Mobility is an European Project bringing together cities (Roma, Istanbul, Nice, Trondheim), solution providers and research institutes; with the aim to study and evaluate the opportunities that future internet technology may bring in urban mobility (car, bus, tramway, bike, walk for instance).* Instant Mobility is one of the use cases of the Future of Internet FI-PPP (Private Partnership Programme): http://www.fi-ppp.eu/
    • The Future of Internet Internet of Things Internet of Services Internet of People
    • Instant Mobility and the Future of Internet Aim:  to resolve the mobility issues by including all the stakeholders : multimodal travellers, car drivers and passengers, public transport operators, carriers and fleet managers, road and traffic managers.  provide to travellers and vehicles drivers a mean to plan and adjust their multi modal journey, or better find ride sharing opportunities in a dynamic way, and according to their preferences, location and the real time conditions (traffic, timetables, prices, etc.)  provide to public transport operators and the fleet managers a mean to optimize  for logistics actors: du to the e-commerce growth, a mean to organize load sharing, prevent re- delivery, use dynamic drop points, adapt the delivery to the consignee  itineraries adapted and optimized in real time as all the means of transport
    • Instant Mobility and acceptability Objectives of acceptability studies: evaluate the acceptability for a generalization of demand-driven multi-modal transportation services bases on real time and anywhere location, and advanced preferences.  in 4 cities: Nice, Istanbul, Roma, Trondheim
    • Acceptability Surveys Methodology  acceptability concerns present and future perception  Nielson framework of acceptability of a system (Kaasinen, 2005)
    • Acceptability Surveys Methodology  Factors that influences the social acceptability:
    • Acceptability Surveys Methodology  The applications was just conceptual, so we decided to test:  Technology characteristics  usability  easiness  security  confidentiality  Social factors:  intention of use and behaviour: how to find information to prepare the travel, actual pratices (mobile or GPS usage), intention of use  privacy and traceability  positiv factors
    • Acceptability Surveys Methodology  2 targets (perception of the services, the technologies and the location may be different- the mean channels of advertising the survey also)  Everyman users (travelers and drivers)  Professional drivers  several languages versions of the questionnaire available  Major topics to be tested:  real time and anywhere location  contextualization  ranking the services
    • Acceptability Surveys  An online survey, distributed in the 4 cities: via institutional web sites (Nice, Istanbul, Roma), local government web sites, transport operators web site, email to transport tickets holders in Trondheim
    • Main results of citizen target Citizen target: online survey published on Instant Mobility web site and the partners web sites (4 done, 1 to come)  Big success 3096 Number of responses 1766 1330 336 Istanbul Roma Nice Trondheim
    • Main results of citizen target A majority of persons uses its own vehicle, very light ride- sharing activity High demand for information while travelling Through web or mobile applications mainly Large use of smartphones before traditional information in stations (panels, …)
    • Their opinion on: Real-time location and previous trip recording:  >90% would accept to transmit in real time their location  more than 84% would accept trip recording  More than 50% require anonymous recording, and good privacy preservation rules Personnal preferences recording  >50% record personal preferences today  >90% would give them in the future  >70% would require easy management of their data (modify, remove, share, …)
    • Main results Which customized services are expected?  Customised information while traveling in case of issues (accident, road works …)  Optimised itinerary matching preferences  Better conditions: duration, arrival time, mean of transport  Far after: security or price Assessment?  Today >60% evaluate a service, in the future >85%  Public transportation: punctuality and frequency (>85%)  Ride-sharing: punctuality and experience of the driver (80%)  attractiv terms : simple access and easyness of the tool, possibility to evaluate anonymously
    • Detailed and econometrical analysis Find the determinants’ acceptancy of the Services of Instant Mobility
    • Location transmission and travelrecordness acceptability
    • Location transmission acceptability Travel recordness acceptability Criteria conditions of Location Criteria conditions of travel transmission acceptability recordness acceptability Privacy Privacy 13% 13% 17% 22% Anonymity Anonymity 8% 3%13% Trust Trust 4% Privacy + Anonymity 8% Privacy + Anonymity Privacy + Trust 4% Privacy + Trust Privacy + Anonymity + 46% Privacy + Anonymity + 49% Trust Trust
    • Designing Instant Mobility ServicesThe influent criteria Privacy Correspondence analysis biplot 1 Trust Must been present in .5 Dimension 2 (31.6%) Privacythe same time Trust Anonimality Aonimality 2 0 Privacy Anonimality and and Trust Privacy Anonimality Trust -.5The role of the criteria Privacy and Trust« Anonimality’ have a Privacy and Trust -1little role -2 -1.5 -1 -.5 0 Dimension 1 (62.4%) .5 1 Conditions location transmission acceptability Conditions travel recordness acceptability coordinates in symmetric normalization
    • Register Personnal preferences’ acceptability
    • Evaluating Instant mobility services’ acceptability
    • Evaluating Instant Mobility services’ acceptability
    • 1st conclusions of acceptability survey A confirmed need for information for daily or regular comuting today Importance of mobile use today Good acceptability of the future services, tailored to their preferences and with better quality, especially punctuality and frequency (more than comfort and security) Good acceptability for location (real time and storage) and personal preferences with conditions of anonymity , easyness and possibility to manage their own data.
    • To continue A professional drivers target in progress :  http://www.tfaforms.com/252331 Topics related the services designed :  optimized itineraries planning,  updated guidance thanks to real time and precise knowledge of the traffic and events on the roads,  itineraries rescheduling according to delivery demands, and  load/parcel exchanges between drivers, all of this in a personalized approach integrating eco-driving assistance for drivers. Same tests about acceptability on the services, the location, preferences, etc. Please answer and make this survey a success !!
    • Focus on ride sharing factors of success To developp a sustainable market of drivers and passengers (critical mass to be achieved quickly) Incentives:  a community to build the trust  alternative vehicles or car pooling for emergency or availability issues  according to the survey : efficiency, relevance and punctuality Subsidies Capacities: car pool lanes, parking facilities (cities, employers) at meeting points Levers:  adaptation to their personal needs : sense of freedom  gamification and nudges (Thaler R.H, Sunstein C.R, 2009)  social networks to better manage : information, communication, exchanges and pedagogy
    • Focus on ride sharing factors of success Existing services: Zimride (2007, California),Lyft (2012,California) and Netlyft (Can)  Smartphone apps (Zimride since 2012)  Drivers and traveller : two different apps  26000 carpools for Zimride Factors of success :  Fun : carstache for Lyft  Easiness and quickness of responses  Communities driven : Lyft started with the Defense employees, Zimride also use Communities (http://www.zimride.com/howitworks)  Trust built on driving test, in-person interview and inspection of the vehicle, ranking system of the drivers
    • Focus on ride sharing factors of success The strengh of cooperative models : example of Waze The use of Social Networks and Community management:  first to match supply and demand, a keystone for ride sharing, by using channels that are already engrained in internet users habits (social networks represent 22% of the time spent on the internet worldwide) -> to achieve sufficient scale for the network to be functional.  to develop notoriety/popularity, arouse interest and generate a desire to belong (marketing/communications function of social networks) or the social web as a source of information and decision support for consumactors; change behaviours; “word of mouth” effect.
    • Focus on ride sharing factors of success The use of Social Networks (SN) also to:  Generate participation: create interacting communities of citizens, policy makers, service providers sharing the same interests (service, ride sharing, same workplace, same neighborhood, hobbies, etc.) to develop a new, ecological, collaborative way of travelling  Trust : use crowdsourcing data to better chose (see Mobility Bank in Helsinki), use SN to anonymise user location  80% of consumers may trust pairs recommandations in social networks - only 14% trust the advertising of the web. Source : Forrester’s customer Experience (2011)  Automatic sensors for traffic management (via smartphones, cars, Twitter) combined with human sensors (e.g. Waze) to develop reality mining, combining “big data” sources to influence local authorities to encourage new uses.
    • that also could enhance multimodal communities A P2P exchanges already in place in public transports like Waze on the road:  Twitter that allows to share data between travelers. Ex : #qml @infotrains, STAR with@starbusmetro (2200 followers) , RATP in Paris, TFL in London, @SNCF_infopresse  Prevent or localize controllers: CheckMyMetro, MetroEclaireur  Share point of interest (a musician in the subway): Roadify in Brooklyn  Operator leaded : KLM Meet and Seat (travel with your FB or Linked In friends)  To meet new people : Croisé dans le métro (romantic encouters in public transports in Paris, Bruxelles, Lille, Lyon, Marseille, Montréal, Rennes et Toulouse), Submate (Barcelona, Bilboa, Hong Kong, London, Madrid, Paris, NY)
    • Thank youAmel AttourMaître de conférence/ Associate ProfessorEcole des Mines de Nancy Nathalie DubusUniversité de lorraine, BETA-CNRS-UMR7522 Chef de projet en innovationCampus ARTEM - CS 14 234 - 54042 Nancy Cedex Orange Labs Networks & Carrierstél: (33) 03.55.66.27.32 tél. +33 4 92 94 53 44amal.attour@mines.inpl-nancy.framel.attour@univ-lorraine.fr mob +33 6 86 71 26 86 nathalie.dubus@orange.com