Chapter 4. Conceptual and implementation frameworks
4.1 System overview
The system overview was developed to present how the elements related to the travel information and its effects relate to one another. The framework describes the interactions between key players: users, transport system, management authority and travel information and technology. The framework is especially useful to understand how the research objectives of this thesis are met and how the research brings many contributions to multiple stakeholders.
4.1.1 Interactions between stakeholders
Public agencies, sometimes with the help of private companies, aim to provide the best transport system to a population of users. They aim to improve the transport services by adapting their services to users’ needs while operating the transport system efficiently.
Chapter 4. Conceptual and implementation frameworks Policymakers need to make sure that the legal or financial parameters can be established and monitored to benefit the society as a whole. Information and Communication Technologies (ICT) serve as a support for data exchange between the infrastructure and operations providers and the users of transport network. On the one hand, these providers supply travel information to travellers. On the other hand, they get data feedback either through trip characteristics or through customer service interactions from which to evaluate their network performance.
The data exchange is often enhanced thanks to Intelligent Transport System (ITS) solutions. ITS includes all systems using information technology to inform, monitor, control or charge the traveller, or to provide travel-related services (Hensher 2000). For instance, ITS can provide various types of information, from alert messages and Variable Message Signs (VMS) to updated data feeding journey planning tools and mobile phone applications.
Depending on its characteristics, travel information can be considered in different ways at different stage of a journey. General information (such as maps, schedules, advertisements, and word-of-mouth) about the transport system helps in the building of perceptions about travel alternatives. Pre-trip information would typically be used for an unknown or irregular trip depending on the trip purpose.
The traveller’s choice would then be one of a travel mode or time-of-day. En route information is directly used if the traveller is within the transport system: maybe he/she encounters an unexpected disruption or change in plans or wants to confirm that the current plan is not going to be subject to delay or disruption. These different types of information are usually not mutually exclusive, however: they influence each other, both statically and dynamically.
Population demographics influence individual’s activities, their travel preferences and therefore their attitudes. The attitudes and perceptions of individuals in turn influence their decision-making mechanism in selecting travel alternatives.
The constraints of the transport network and infrastructure also influence (or limit) travel choices. ICT also plays other roles in parallel of the travel choices: it can help in managing the transport system or serves to highlight alternatives other than transport to achieve an activity.
Each individual’s choice is translated as an additional trip on the network. At the aggregate level, the cumulative impact of all travellers’ decisions on the transport network is captured
Chapter 4. Conceptual and implementation frameworks
as a feedback. This feedback, mostly aggregate data, informs the authorities managing the network and evaluating performance. This feedback loop occurs at different dynamic levels. It could be conveyed as a real-time update (information service, staff intervention, fleet of dynamic traffic management) or a long-term assessment (credibility of information, infrastructure improvement).
The relationships between key players have just been described above: both the travel information and the transport network systems are closely intertwined in a bilateral feedback loop enhanced by ICT. According to the research objectives presented in Chapter 1, factors other than travel information and transport system would need to be taken into account: the constraints on the transport network, the use of ICT for information and for travel, attitudinal and perception questions regarding information, and the stage of trip for consulting information.
Figure 4.1 illustrates the relationships between these actors as a system. The contributions of the research work are evident from the schematic drawing. Companies providing information can benefit in terms of potential revenue advertising by studying user profiles for specific sources at a specific moment and location. Public agencies and policymakers can understand better how travel information affects the ways in which users travel.
Several stakeholders, e.g. policymakers, transport providers, information providers and private developers, may benefit from the results of this research, since their goal, whether directly or indirectly, is to improve their clients’ satisfaction.
Chapter 4. Conceptual and implementation frameworks > Individual > Activity > Trip Socio-demographics Users • Mobility observations • Level-of-service performance Network characteristics Transport infrastructure General information
• Modification of travel patterns • Partial substitution of travel with ICT • Complementarity
Telecommunications facilitating engagement in many activities and mobility without need to travel Information Communication Technology (ICT) providers
Aim: provide & improve network performance -> Provide information to users
<- Using data feedback for evaluation
Management and Operations Public Agencies
• Consulting with public agencies • Offer services to users
Management and Operations (suporting role) Private companies
Travel information from ITS sources have different characteristics: • General, static information: traditional channels (map & schedule)
• Publicly broadcasted: radio alerts, TV, Variable Message Signs (VMS), public announcements • Personally customised and filtered information: mobile phone apps, journey planners, word-of-mouth
Intelligent Transport Systems (ITS) used to inform, monitor, control or charge the traveller or to provide travel-related services Travel information providers
Feedback (aggregate level) En-route information Scheduling of activity in time and space Travel is derived from the demand
for activity participation Activity
• Change in trip plan • Mode • Route • Departure time • Destination • Activity participation • Trip frequency • Travel distance • Speed • Residential location Decision-making Travel choice Pre-trip information
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• Processed feedback information at the aggregate level • Real-time update information with management intervention Dynamic process Data exchange Perceptions Attitudes• Developing regulatory rules for the best interest of its constituents
Regulatory role Policy makers
Chapter 4. Conceptual and implementation frameworks
4.1.2 Contributions
Understanding travellers’ behaviour in using travel information and making travel decisions is important to various parties. Different aspects of this research can be useful to several organisations and companies. The following list gives examples of how the results could benefit them:
• Policymakers may wish to develop information strategies to support policy objectives and the effective use of information tools by travellers. They should identify the needs in terms of travel information and travel, per segment of the population, based on existing profiles of information users and travellers. This can help to understand and predict the reactions of users (demand) to a change in information (supply) and create policies based on the prediction instruments developed specifically for this purpose.
• Transport providers, or public institutions (e.g. TfL (operations), Department for Transport (DfT)) may want to monitor the use of their transport infrastructure more effectively by providing specific information. In order to improve their effectiveness in deploying information services, they should understand the extent to which the media, providers and the type of travel information influence travellers’ decisions under disruption. Modelling the preferences of different information user profiles (e.g. based on demographics and travel patterns) and predicting traveller’s response to disruption may help authorities better manage usual and disrupted transport network conditions.
• Public information providers (e.g. TfL (communications), Traveline, and Transport Direct) would find resources to identify the profile of their clients and thus cater the most useful information. Information investment can be optimised for different sources by measuring the frequency of use and user satiation (decrease in use) using prediction models. It is also possible to determine the relative importance and significance of criteria for information acquisition and use (e.g. availability, affordability, quality, credibility). They may prioritise the most attractive sources for different information user profiles and trip contexts to enhance competitiveness in offering information services
• Private information providers (e.g. Google, Garmin and the Royal Automobile Club (RAC)) may wish to evaluate market size and user profile for different technologies and platforms in order to develop and price new information services, in the context
Chapter 4. Conceptual and implementation frameworks of a competitive market. In particular, the market shares of travel information sources can be predicted by quantifying the sensitivity of users to different "brands" publishing travel information and detecting which factors (e.g. demographics and travel patterns) influence this choice. Evaluating the price and willingness to pay for information based on its characteristics would assist providers to target their efforts in marketing strategies.
• Mobile phone application developers (e.g. Vodafone, O2, or any particular app developer) may wish to understand which features of travel information sources play a role in the selection of those sources in a competitive market, in order to develop apps that are preferred by specific consumer groups. It is useful for them to recognise profiles of information users and adapt information (e.g. type, format, content) based on user group needs and contexts. For advertising partners, business models for ad-supported phone apps can also be improved.
These example applications can be further investigated with regards to the specific needs of local public transport authorities. Although these are not within the scope of this research work, Chapter 8 introduces practical applications to interpret the model results.