A new generation of business traveller

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The DATASET2050 project does not only examine current European passenger profiles but also looks at possible passenger types in 2035 and 2050. To develop future demand profiles, current ones are either adjusted (see Current European PAX profiles), or new profiles are developed. As there is still a lot of uncertainty regarding how we are going to live and travel in the future, and since the project follows a data-driven approach, only passenger characteristics that can be supported by data are taken into consideration. Examples for developments supported by data are the ageing population in Europe, the increase in single households and the tendency to have fewer children per household.

For 2035, six future passenger profiles for the EU28 and EFTA countries are developed. Among these, the Digital Native Business Traveller was identified as one of the main passenger types in Europe. This group takes a journey mainly for occupational reasons and it can be seen as the new generation of business traveller. However, due to the high usage of technological devices one can assume that this passenger type is constantly connected and always online in continuous digital exchange with the private life, friends and family. He or she will be in the typically age of the working population of around 24 to 64 years, which today represents the digital savvy Generation Y and Generation Z. The income level and amount for transport expenditure will be medium to high. 0.5 to 1.5 trips per capita per year are taken, either alone or accompanied by another person. A large share of this passenger type will be female as the increase in female tertiary education enrolments might lead to an increase in working women within higher professions and hence an increase in women travelling for business purposes. Finally, he or she does not mind checking in luggage but takes only hand luggage when going on short trips. Public transport, taxi or car sharing are the preferred airport access mode choices.

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Figure: The new generation of business traveller is digital savvy and constantly connected, enabled by emerging technology and new innovations to come.

This is one example of how a typical passenger group in 2035 could possibly look like. The outcome of all passenger demand profiles will be put in contrast with coming work packages (i.e. future supply profile), enabling this way a complete assessment on the European door-to-door mobility in the future. More information about the remaining passenger types, the methodology and databases can be found in the report on future passenger profiles.

Current European PAX Profiles

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Have you ever wondered about all the different people at the airport? Almost all of us have already flown: for going on holidays, visiting friends and family or going on a business trip. Likewise, many have been sitting at the airport, waiting at the gate and watching different passengers walking past. An airport is a melting pot where people of all ages, backgrounds, income levels and interests come together. As part of the DATASET2050 project, passenger characteristics are examined and six general passenger profiles (PAX profiles) are generated to gain an understanding of what distinguishes current European air travellers.

These PAX profiles are derived using existing passenger studies as well as data on demographical, geographical, socio-economic and behavioural aspects. At first, profiles are distinguished by travel purpose, i.e. whether passenger travel for personal or for business reasons. Since the amount of passengers travelling for private reasons exceeds that of passengers travelling for business reasons (on average across all EU28 + EFTA countries ten per cent business trips), there are four groups describing leisure passengers and two groups describing business travellers, as can be seen in the figure below. Following, passenger groups are assigned to pre-defined age intervals taken from an analysis of European countries as well as respective average travel activity within the particular age group.

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Figure: PAX profiles according to travel purpose and age intervals with example profile information for “Executives”, “Family and Holiday Traveller” and “Best Agers” (own depiction based on PAX profile analysis)

All six passenger groups also differ by their income level. “Executives” have a high income; “Youngsters” have a low income and the remaining passenger groups have a medium income. Income alone has a great impact on travel budget and consequently on travel behaviour, i.e. how often someone is travelling or which transport mode is used to access the airport. Furthermore, the use of technical devices throughout the entire journey depends on age groups. Hence, all six passenger groups differ by the level of frequency in regard to mobile phone and internet usage. This translates to their booking and travelling behaviour as well. “Youngsters” and “Executives” are the two passenger groups using information and communication technologies (ICT) with a high frequency. “Youngsters”, for example, are digitally savvy and more likely to complete travel related tasks online compared to the group of “Best Agers”. Such processes along the journey could be online check-in or generating a boarding card on a mobile device.

The value of time also influences travel behaviour as passengers who value time a lot tend to save time along their journey and vice versa. Among all six PAX profiles, “Executives” and “Price-conscious Business Traveller” value time the most which is reflected, for instance, by their time-saving choice of hand luggage only. In contrast, “Youngsters” are young, often students or apprentices, and time rich but money poor. To compensate their low income, they tend to use public transport (often the longer access mode choice) to save money as they do not mind the additional time spent in public transport. “Family and Holiday Traveller” and “Best Agers” also have a rather low value of time.

The six passenger groups also differ by their length of stay. The trip length in terms of nights staying is another parameter influencing the amount of luggage a particular passenger is taking along the journey. The amount of nights spent at a particular destination differs both by travel purpose and by type of journey conducted. Business travellers tend to spend fewer nights per trip than leisure passengers. And “Youngsters” visiting friends in urban centres spend less nights than “Family and Holiday Traveller” on their summer vacation. In turn, this may influence the access mode selected, the time spent in luggage check-in processes, or during luggage collection at the destination airport. For instance, in order to minimize time and effort accrued to respective handling processes, business passengers reduce the amount of luggage taken along. Finally, it is important to mention that one person can be assigned to several PAX profiles. A manager of an international company can travel for business purposes (being assigned to the group of “Executives”) and in private life being a dad and flying with his wife and two children into the summer vacation (being a “Family and Holiday Traveller”).

More information on the PAX profiles and the analysis can be found in the DATASET2050 report “Data driven approach for a Seamless Efficient Travelling in 2050”.

Mobility datasets exploration tool

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Within the project, we have recently listed the sources of EU door-to-door mobility datasets, reports and papers. That information is crucial for us to build the subsequent data-driven tasks (including the model). On top of that, they could be extremely useful to anyone doing research or simply interested in the mobility topic.

Having this in mind, the consortium has developed a visual, interactive tool that provides all the information in a simple, attractive way.  By using a dynamic D3.js , it includes information about data sources together to their temporal data coverage, authors, description and availability

How it works? Click here: http://visual.innaxis.org/mobilityDataSETs/. The datasets have been categorized in 9 families, all of them relevant within mobility context.

  • Demographic
  • Passenger demand
  • Passenger type
  • Passenger behaviour
  • Door-to-kerb
  • Kerb-to-gate
  • Gate-to-kerb
  • Airside capacity
  • Competing services

By clicking in each of them (the text, right side), all the data sources available within that family are displayed. Doing a mouseover on each of them (right side), detailed information is given in a tool tip about the data coverage, sources etc. In the cases too many sources are available, scrolling is the way to see them all 🙂 Clicking on the [x] at the top brings you back to the main page.

enjoy!

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http://visual.innaxis.org/mobilityDataSETs/

 

Dynamics of European Demographics

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The objective of WP3 within DATASET2050 is to understand the current and future transport system from the passengers perspective, in a more detailed and thorough way than currently available. As a first step, it is necessary to better grasp passengers’ expectations, needs and requirements and their specific travel behaviour. In this context, population, and most importantly demography evolution, plays a crucial role in terms of current transport flows. Transport flows will obviously be derived from where do people live in Europe. As a general rule, fertility rate and emigration/immigration due to [un]employment levels are for the most cases the key drivers of European demographics.

Based on data from the German Federal Office for Building and Regional Planning, it has been published some days ago an interesting article on the European demographics. This article has been considered worth including in the monthly blogpost, given the synergies with the current research being performed within DATASET2050. Some general conclusions extracted from the analyses done in the article (and shown in the picture below) are the following:

  • European city suburbs have attracted new inhabitants coming both from the crowded city centres and from other surrounding (and further) rural areas
  • Both in Germany and in Poland, the trend is moving from the East to West, which clearly corresponds to the evolution of the employment levels at those areas.
  • Similar situation in Italy, where the south-north trend difference is remarkable
  • France population is growing, especially rapid in coastal areas. Population growth is quite homogeneous, given the good transport system available at country and local levels
  • In Spain, population growth is notable around Madrid, Barcelona and the coast. Population is decreasing in the north-west area of Spain and in Portugal
  • Easter Europe and the Baltic states have shrunk dramatically

Several maps and explanations zooming in different countries and cities are available at the original source.  Areas coloured green had an average annual increase in population over the 2001-2011 time span, and areas coloured brown experienced a decline in population. In areas coloured white, no significant change occurred.

enjoy it!

30jun

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