International Transportation (69) 1 | 2017 41 Air travel groups and their mobility profiles in-air traffic Towards seemless air travels - the DORA project and mobility (information) requirements of-air travellers Intermodality, seamless travel information, travel time reduction, intermodal routing, air transport, waiting time detection, in-door navigation, usability The research carried out in the DORA project, clearly demonstrated that traveller groups travelling by airplane were not yet sufficiently specified. DORA performed comprehensive activities to overcome this gap. The following article describes the definition process of defining potential user groups for the development of a seamless door-to-door journey planner. Michael Abraham, Wulf-Holger Arndt, Norman Döge T he name DORA means “Door-to-Door Information of Air Passengers”. It is a three years Research and Innovation Action project under the EU programme Horizon 2020 focused on Intelligent Transportation Systems (ITS Cluster). It has started on 01 June 2015. Main goal of the DORA project is to design and establish an integrated information system that helps passengers to optimise their travel from the origin of their travel to the airplane at the departing airport as well as from the arrival airport to their final destination including indoor navigation in the airports. Thus the DORA integrated information system created within the project together with necessary software platforms and end user applications supports the reduction of the overall time needed for a typical European air Photo: Rainer Sturm/ pixelio.de Travel Planning SCIENCE & RESEARCH International Transportation (69) 1 | 2017 42 SCIENCE & RESEARCH Travel Planning travel, including the time required for the transfer to and from the airports. The service is developed prototypically for the connection Berlin - Palma de Mallorca and demonstrated during a one-year test phase, beginning in June 2017. The main component of the service is an intermodal route planner based on real-time data on the road, rail and air traffic situation for the route from and to the airport. The information offer for the passengers is completed with newly developed solutions for terminal mobility, such as indoor navigation via smartphones and waiting queue detection at the security controls. In the event of a fault, alternative routes are automatically displayed to the passenger. In addition, the service is integrated into the information systems of transport companies and airport companies. Partner organisations of the project are the airport operators in Berlin and Palma de Mallorca, the cities of Berlin and Palma, the local traffic information providers and public transport companies as well as technology development companies and universities. Besides VMZ Berlin Betreibergesellschaft mbH, specific partners are the Berlin’s Senate Department for Urban Development and the Environment, Berlin-Brandenburg Transport Association, Berlin-Brandenburg Airport and the Technische Universität Berlin. Air Berlin is an associate partner of the project. Travel chains and user requirements In order to specify the technical requirements of the service to the needs of air travellers, specific user groups had to be determined. This required - as a first step - to have a look at every single element of the entire air travel chain as e. g. performed by Goswami et al. (2011). The resulting parts of the air travel chain, consisting of forerun, movement at the starting airport, movement at the destination airport, flight and follow-up movement to reach the final destination are shown in figure 1. In a second step different mobility alternatives of all potential travellers for all parts of the travel chain at forerun and follow-up ways to the pilot airports have been analysed in a complex process: The input data based on a review of the mobility options in the air passenger standard surveys, information provided by partners on site and expert interviews with mobility experts, staff at airports and public transport stations. Special emphasis was put on the mobility requirements of persons with special needs like people with walking impairment, families with pushchairs etc. In a last step the collected mobility options - describing the level of physical movements - were extended by a level of related mobility information. As a result, the complex travel chain, developed for DORA shows - on the example of the pilot connection - all potential mobility alternatives and related mobility information requirements on the side of the traveller. Figure 2 shows the different potential travel options for reaching the airport on the example of Berlin. If different transport options and the information regarding their usage and restrictions are available, the traveller is principally able to plan the whole travel chain. However, the decision what options will be chosen is mainly related to the personal preferences of the air traveller. As illustrated in Fi, for the small part of the forerun to the airport the amount of information is quite complex to oversee. Moreover, there exist strong relations between the different stages of the travel chain. In order to provide only the - for the trip planning - necessary information it was - prior to the technical development - important to assess by which information and preferences trip planning processes of air travellers are usually being shaped. Air traveller groups In order to understand personal mobility preferences and the criteria that are important for decisions related Figure 1: Air Travel Chain Components Figure 2: Travel Options and Related Mobility Information Requirements of Air Travelers on the Example of the Forerun to the Berlin Airports International Transportation (69) 1 | 2017 43 Travel Planning SCIENCE & RESEARCH to the trip planning process, it is important to understand the purpose of the trip. Freyer (2006) distinguishes two main traveller groups with different travel motifs. As figure 3 shows, these are leisure and business travellers. In 2012 the European tourism market was responsible for altogether 1,180 million trips. Leisure travel purposes were responsible for 88.4 % of all trips, while business purposes were the main travel reason for 11.6 % of all trips. In 2012, moreover, two thirds of all trips were towards a destination inside the country of origin, while one third had an outbound destination and were mostly undertaken for holiday purposes (Eurostat, 2015). Finally it can be stated that most of the air trips inside Europe are related to leisure travels. Nevertheless, business travellers on average are traveling by airplane more often. Taking this initial differentiation by Freyer into account it was in a next step necessary to observe criteria relevant for decision making throughout the trip planning phase. Under the assumption that the importance of criteria like time costs, time, environmental impact etc. varies across different groups of travellers, the group definition process was also considering socio-economic and socio-demographic criteria as important impact variables. The desk research investigating the availability of existing studies that observe the trip planning processes of air travellers revealed a significant research gap. Most existing studies considered air traveller flows to and from the airport only in meso or macroscopic transport models. On the individual, microscopic level trip planning processes of air travellers have not been observed in detail. Detailed classifications of air travellers have only been undertaken in marketing studies rather focusing the airportor travel agency-sided marketing processes and not the ways to and from the airport. These are for example following studies: 1. Airport Private Traveler Study (Gesellschaft für Konsumforschung GfK, 2011), 2. Future Traveller Tribes 2020 - Report for the Air Travel Industry (Henley Centre Headlight Vision and Amadeus, 2007), 3. Future Traveller Tribes 2030 - Understanding tomorrow’s Traveller (Future Foundation and Amadeus, 2015). The lack of existing studies and statistics required to apply an own research setting. Due to the fact that the organization of a comprehensive survey on the pilot connection - that would have allowed performing a detailed cluster analysis - was not possible, the strategy chosen applied an approach consisting of a qualitative and quantitative data analysis. This whole process is shown in figure 4. Following the approach of target group models, values of variables of existing studies on the characterization of air travellers and travel behaviour have been compared and combined. Characteristics Young Traveller Family Traveller Middle-aged Traveller Senior Traveller Age < 30 years of age 31-50 years of age 31-65 years of age > 65 years of age Income Majority lower and lower middle income class (<2000 EUR/ m) > 2500 EUR/ m All income groups (majority between 2000 EUR/ m and 4000 EUR/ m) 2000 EUR/ m- 6000 EUR/ m Most frequently used modes of transport for forerun Public transport, car (being brought), taxi, collective transport (charter/ tour bus) Car (being brought/ parked for the duration of the travel), public transport, charter/ tour bus, airport shuttle Public transport, car (being brought), taxi (between 31-40 years share of public transport 60 % on the modal split), charter/ tour bus Car (being brought), taxi, decreasing number of public transport users Most important criteria for transport mode choice forerun Reliability, safety and travel time Reliability, safety, travel time, barrier-freedom, price and environmental issues Reliability, safety, travel time Reliability, safety, travel time, barrier-freedom Most important criteria for transport mode choice follow-up movement Reliability, safety and travel time Reliability, safety, travel time barrier-freedom, price and environmental issues Reliability, safety, travel time Reliability, safety, travel time, barrier-freedom Information sources Homepages of airlines, airports and public transport providers Homepages of airlines, airports and public transport providers Majority no, minority webpages of public transport, airport, airline Travel agency (written, oral) Check-in behaviour Counter, online via PC Counter, online via PC Counter, check-in machine Counter Smartphone availability 85 % to 95 % 100 % 90 % Majority not Internet connection abroad 50 % to 60 % 75 % 50 % Majority not Table 1: Leisure traveller groups Figure 3: Main Traveller Groups and their Travel Motif (based on Freyer, 2006) International Transportation (69) 1 | 2017 44 SCIENCE & RESEARCH Travel Planning These initial groups were then further consolidated by a deeper analysis of selected variables of the dataset provided by the project partner FBB (Flughafen Berlin Brandenburg GmbH) which consisted of around 20,000 cases collected at the airports of Tegel and Schönefeld during their standard passenger survey. In addition an in-depth passenger survey with 419 usable cases was designed and carried out by the project partners ETRA (Grupoetra), Aena (Spanish Airport Operator), FBB (Airport operator Berlin) and TUB (Technische Universität Berlin). The main purpose of the quantitative analysis was to connect transport mode choice, check-In behaviour and socio-demographic characteristics of existing classifications. The initial group profiles were then reviewed by/ reshaped based on the results of five expert interviews with experts from the field of tourism research, airport operators, mobility research. This resulted in a final definition of traveller groups in the segment of leisure travellers (table 1): • Young travellers, • Family travellers, • Middle-aged travellers, • Senior travellers. This overview shows that the main distinguishing criteria are age and income. Regarding the transport mode choice it can be stated that the shares of public transport rise until the age of 40 and then start to decrease again. The main reasons for the use of cars of younger and older travellers is that they are mostly being brought by relatives or friends. For older people barrier-freedom especially when travelling with heavy luggage is the most important criterion for not choosing public transport. The transport mode choice of family travellers does not follow the general trend of all travellers regarding the public transport use. This seems to be mostly related to the luggage that has to be brought to the airport for all family members. Thus most of the family travellers are reaching the airport by-car. The defined traveller groups in the segment of business traveller shown in table 2 are: • Business travellers below 35 years of age, • Business travellers over 35 years of age. For the business traveller groups the main distinguishing criterion is the age. The typical business traveller is by majority male, as figure 5 illustrates, and very time critical and on average travelling more often than the leisure traveller. Since the business traveller is not traveling with heavy luggage he / she prefers the Online Check-In and is usually later at the airport than the leisure traveller, as figure-6 illustrates. Regarding the mode choice it can clearly be stated that younger business travellers mostly reach the airport by public transport while older business travellers prefer to drive by taxi. This can also be related to company specific policies. Moreover it has to be mentioned, that the presented user group profiles are also based on site (Palma and Berlin) specific interviews and surveys. The mode choice Characteristic Business travellers below 35 years of age Business travellers over 35 years of age Age < 35 years of age > 35 years of age Most frequently used modes of transport for forerun Public transport, taxi Taxi, public transport, car (also small shares of rented cars) Most important criteria for transport mode choice forerun Reliability, safety, comfort Reliability, safety, travel time Most important criteria for transport mode choice follow-up movement Reliability, safety, comfort Reliability, safety, travel time Information sources Internet search engines, websites of public transport providers, navigation system inside the vehicle Internet search engines, websites of public transport providers Check-in behaviour Online (PC and smartphone) Online (PC and smartphone) Smartphone availability 100 % 90 % Internet connection abroad 50 % 60 %% Table 2: Business traveller groups Figure 4: Main Approach to the Definition of DORA User Groups Figure 5: Sex of business and leisure travelers; DORA Berlin Airport Survey 2015 (n = 195) International Transportation (69) 1 | 2017 45 Travel Planning SCIENCE & RESEARCH already differs between both airports due to different available options and connectivity. For both, leisure and business travellers it can be stated that the younger the travellers the more smartphone affine they are. Nevertheless most of the people questioned indicated to use homepages and web portals of airlines, airports and public transport providers as the main sources to access information related to their travel. Thus a service like DORA would help to bring still segregated information together and make travel planning easier and more effective. Research gaps The investigation carried out revealed significant research gaps related to the processes of trip planning during the air travel phases of forerun and follow-up movement. A deeper cluster analysis of the FBB passenger survey of Berlin did not lead to a definition of an sufficient number of groups being shaped by group specific similarities in matter of socio-economic, socio-demographic, transport mode choice etc. characteristics. For Berlin the different ways of mode options to the airports of Tegel and Schönefeld alone lead to different mode choices of eventually comparable individuals. Other important factors could be flight times, target destinations, airlines, seasons, booked holiday package with organized transfer etc. Reaching a more consolidated definition of air traveller groups would require a in matters of survey design, timing more advanced and comparative study putting more emphasis on the isolation of other influential factors. DORA field test - test users wanted With the help of the defined User Groups different use cases have been defined that found direct entrance into the further specification of the technical set-up of the DORA service. In early June 2017 a first version of the DORA App - starting screen shown in figure 7 - and the related DORA trip planning website will be launched. The App version will provide the full initially described functionality for the test connection between Berlin and Palma and will be available for test purposes as an installation file for Smart Phones. During several iterations the App will be evaluated for one year. Since the number of 500 test users has to be reached, individuals who take part in the initial expert and later live test are welcomed throughout this period. ■ For more information, please check the DORA homepage: https: / / dora-project.eu/ page Mail: contact@dora-project.eu. REFERENCES EUROSTAT (2015): Statistic Portal of the European Union. Characteristics of Tourism Trips. Accessed: 20 July 2015. http: / / ec.europa.eu/ eurostat/ statistics-explained/ index.php/ Tourism_statistics_-_characteristics_of_tourism_trips Freyer, W. (2006): Tourismus. Einführung in die Fremdenverkehrsökonomie. München, Wien, R. Oldenbourg Verlag. 87 ff. ISBN 978-3-486-57874-4. Future Foundation and Amadeus (2015): Future Traveller Tribes 2030, Understanding Tomorrow’s Traveller. Accessed 6 July 2015. http: / / www.amadeus.com/ documents/ futuretraveller-tribes-2030/ travel-report-future-traveller-tribes-2030.pdf Gesellschaft für Konsumforschung GfK MobilitätsMonitor/ Initiative Airport Media (2011): Airport Private Traveler Study - Reiseverhalten, Einstellungen und Werte der Privatreisenden am Airport. Accessed 13 July 2015. http: / / www.flughafenwerbung.de Goswami, A.K. et al. (2011): Offsite passenger service facilities: A viable option for airport access? pp 263-270, in: Journal of Air Transport Management. Vol. 16. Issue 5. Elsevier Ltd. ISSN: 0969-6997. Henley Centre HeadlightVision and Amadeus (2007): Future Traveller Tribes 2020, Report for the Travel Industry. Accessed 13 July 2015. http: / / www.amadeus.com/ documents/ futuretraveller-tribes-2030/ travel-report-future-traveller-tribes-2020.pdf Michael Abraham, Dipl.-Ing. Researcher in the research unit „Mobility and Space“, Centre for Technology and Society, Technische Universität Berlin (DE) m.abraham@tu-berlin.de Norman Döge, Dipl. Geogr. Researcher in the research unit „Mobility and Space“, Centre for Technology and Society, Technische Universität Berlin (DE) doege@ztg.tu-berlin.de Wulf-Holger Arndt, Dr.-Ing. Head of the research unit „Mobility and Space“, Centre for Technology and Society, Technische Universität Berlin (DE) wulf-holger.arndt@tu-berlin.de Figure 7: DORA App Starting Screen Figure 6: Boxplots regarding arrival time before the official departure of professional and leisure travellers, DORA Berlin Airport Survey 2015 (n = 195)