Mobile travel services: A three-country study into the impact of local circumstances

In this paper we explore the difference in acceptance patterns of mobile services that are related to travelling in three countries: Finland, The Netherlands and New Zealand. The objective of this paper is to understand differences in the use of Mobile Travel Services in three countries that differ with regard to national travel patterns. This paper also contributes to the discussion of the relevance of the Technology Acceptance Model for mobile applications by focusing on the importance of context characteristics, such as the degree of mobility of the user, the social situation people are in, and their need for social interaction. Based on surveys in the three countries as executed in 2009, we use structural equation modelling to find differences in patterns. The paper concludes that context factors have an impact on the relation between the core concepts as used in TAM and DOI approach, and that t here is a clear need for closer research in the moderating effect of physical (e.g. mobile and fixed context) and social context, as well as the need for social interaction. Moreover it is clear that country specific characteristics play a role in the acceptance of mobile travel services. As we pointed out in many of our research projects before the acceptance and use of mobile services requires deep understanding from individual, context and technology related characteristics and their mutual interactions

Kiosks 21: a new role for information kiosks?

Discusses and analyses the latest generation of information kiosks, Kiosks 21, which features information provision/promotion, interaction, transaction and relationships. In contrast to their task based predecessors, these kiosks focus on customer service delivery to ‘customers in context’. Five case studies of such kiosks located respectively in an airport, railway station, car rental base, hotel lobby, and shopping mall are analysed to demonstrate the way in which the kiosks are implemented to meet the differing requirements of customers in different contexts. Case studies are analysed in terms of kiosk design and location, user profile, information architecture, interface design, communication, and commerce. A range of areas for research and development are proposed.</p

Integrating big data into a sustainable mobility policy 2.0 planning support system

It is estimated that each of us, on a daily basis, produces a bit more than 1 GB of digital content through our mobile phone and social networks activities, bank card payments, location-based positioning information, online activities, etc. However, the implementation of these large data amounts in city assets planning systems still remains a rather abstract idea for several reasons, including the fact that practical examples are still very strongly services-oriented, and are a largely unexplored and interdisciplinary field; hence, missing the cross-cutting dimension. In this paper, we describe the Policy 2.0 concept and integrate user generated content into Policy 2.0 platform for sustainable mobility planning. By means of a real-life example, we demonstrate the applicability of such a big data integration approach to smart cities planning process. Observed benefits range from improved timeliness of the data and reduced duration of the planning cycle to more informed and agile decision making, on both the citizens and the city planners end. The integration of big data into the planning process, at this stage, does not have uniform impact across all levels of decision making and planning process, therefore it should be performed gradually and with full awareness of existing limitations

The work-related affordances of business travel: a disaggregated analysis of journey stage and mode of transport

Sociological understanding of how business travellers make use of travel time is somewhat lacking. This article addresses this gap in knowledge via presenting an analysis of survey-based data collected from business people travelling by plane, train and car. Through disaggregating the data by travel mode, journey stage, technology use and task type the article provides a level of granular detail in the general patterns of business travellers’ travel time behaviour not previously provided by other surveys. Utilizing the concept of ‘affordances’, the article shows how the type of work activities undertaken are shaped by the dynamic interaction between the characteristics in the travel environment, the type of work tasks undertaken and work technologies utilized in carrying out these tasks and the active choices of business travellers

Automatic Recognition of Public Transport Trips from Mobile Device Sensor Data and Transport Infrastructure Information

Automatic detection of public transport (PT) usage has important applications for intelligent transport systems. It is crucial for understanding the commuting habits of passengers at large and over longer periods of time. It also enables compilation of door-to-door trip chains, which in turn can assist public transport providers in improved optimisation of their transport networks. In addition, predictions of future trips based on past activities can be used to assist passengers with targeted information. This article documents a dataset compiled from a day of active commuting by a small group of people using different means of PT in the Helsinki region. Mobility data was collected by two means: (a) manually written details of each PT trip during the day, and (b) measurements using sensors of travellers' mobile devices. The manual log is used to cross-check and verify the results derived from automatic measurements. The mobile client application used for our data collection provides a fully automated measurement service and implements a set of algorithms for decreasing battery consumption. The live locations of some of the public transport vehicles in the region were made available by the local transport provider and sampled with a 30-second interval. The stopping times of local trains at stations during the day were retrieved from the railway operator. The static timetable information of all the PT vehicles operating in the area is made available by the transport provider, and linked to our dataset. The challenge is to correctly detect as many manually logged trips as possible by using the automatically collected data. This paper includes an analysis of challenges due to missing or partially sampled information in the data, and initial results from automatic recognition using a set of algorithms. Improvement of correct recognitions is left as an ongoing challenge.Comment: 22 pages, 7 figures, 10 table

Travel Disruption: Three Case Studies

Six stages of travel disruption from travellers are identified from the survey data of peole affected by the volcanic ash flight ban (2010), the loss of road bridges in Workington, west Cumbria (2009-2010) and severe winter weather over most of the UK in December 2010. This report describes expectations of normal travel and how social practices reflect those expectations. It details the expectations travellers had about what should happen when travel is disrupted, how they 'touch the new travel context', revise their plans and the consequences for them and others. It reports on how travellers say it will change their expectations and practices for future trave

Travel Disruption: Three Case Studies

This report draws together the findings of three studies of travel disruption and its impacts on travellers: the volcanic ash cloud which disrupted aviation in Europe in 2010, the loss of road bridges between November 2009 and April 2010 at Workington, Cumbria and the severe winter weather across the UK in the winter of 2010-2011. It proposes a six phase cycle: normality, when transport provision matches expectations drawn from experience, tickets, timetables, etc;, disruption, when the transport provision fails to meet expectations; touching the new context when travellers seek to assess how the changed conditions affect their travel plans; the revised plan, when travellers make new plans on the basis of what they know about the context, the consequences, which includes counting the cost of changed travel plans in terms of extra expenditure of time, money, effort, prolonged absences as well as any benefits emanating from the experience; reflection and incorporation whereby the experience of disruption is assimilated int the new normality; this can include trust of agents, information, travelling more prepared for disruption or being aware of new channels of information or help