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Commonly studied hunter-gatherer traits, such as grouping and sharing, may require special attention when self-selection introduces bias into typical analyses. We therefore re-examine forager sociality by asking a series of nested questions: (1) To what extent are foraging groups random samples from the larger population? (2) What social and economic factors might explain the composition of foraging groups? (3) If certain groups of individuals preferentially forage together, do these same groups also preferentially share with each other when resident at their permanent settlement? (4) To what extent can we understand behavior in the foraging context without consideration of other contexts in which individuals live and work, and vice versa? Among the Ache of Paraguay, we show that foraging treks are not representative of the larger population, individuals vary in the kinds of treks in which they participate, and those who tend to share together at the reservation are more likely to forage together on trek.

Purpose — In order to analyse applicability, comparability and limitations of GPS technology in travel surveys, different mobility survey techniques were tested in an Austrian pilot study.

Methodology/approach — Four groups of voluntary respondents recorded their travel behaviour over a time period of three consecutive days. The groups were assigned to three different and combined methods of data collection: Paper–pencil trip diaries, passive GPS tracking, active GPS tracking and prompted recall interviews.

Findings — The resulting mobility parameters show that self-reported paper– pencil surveys yield accurate sociodemographic information on the respondents as well as trip purposes and modes of transportation, although too few trips are reported. Passive GPS-based methods minimize the strain for respondents. Methods that combine GPS-based data collection and questionnaire provide the most reliable mobility data at the moment.

Research limitations/implications — Due to funding restrictions the sample sizes had to be relatively small (235 participants). Further development in research methodology will increase the effectiveness of automated data analysis, for example more accurate detection of activities and transport modes. The usefulness of GPS-based data collection in a large-scale surveys is planned to be tested in the next Austrian national travel survey.

Originality/value of paper — The pilot study allows a detailed comparison of traditional and GPS-based travel survey methods for the first time, due to data collection combined with prompted recalls.

In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

Purpose — Describe the system set-up and processing requirements for a long-duration longitudinal Global Positioning System (GPS)/prompted-recall (PR) survey conducted in Sydney, Australia and assess reaction and cognition of participants.

Design/methodology/approach — The survey uses data collected using an in-car GPS device within a PR interface accessed over the Internet by participants. Technical requirements, interface design and survey administration of the survey are discussed. This is followed by an assessment of participant burden and cognition by analysing user activity on the PR and comparing participant responses to information inferred from the GPS data.

Findings — New technologies have allowed for increasingly sophisticated data collection efforts but they require substantial resources to translate this into a usable form. This study shows these technologies can be used to conduct long-duration travel studies in a way that is appealing and engaging to participants. However, it was found that responses to the PR are sometimes inconsistent and caution should be drawn in taking PR responses as the ‘ground truth’.

Research limitations/implications — The relatively low participant burden of this study shows long-duration studies are feasible if care is taken to limit the work required by participants. The inconsistency of the responses to the PR suggest future surveys may need to employ mechanisms that are better able to aid participants in accurately completing the survey.

Originality/value — Details the requirements of running a long-duration GPS/PR survey and assesses participant burden and cognition of the survey which are often not reported.

Purpose — The paper reports on a research project exploring new approaches for analysing travel demand induced by changes in generalised costs of travel and activity participation. The description of the survey approach, which to our knowledge is novel in its application, reports descriptive analyses of the respondents' reactions to the changes implied in the household interviews.

Methodology — A sample of respondents were administered a 5 day travel diary, from which 1 day was selected for further analysis. Travel times for trips conducted that day were changed using predefined heuristics based on the household characteristics to attain significant changes in the generalised costs of the reported trips. Respondents were then presented with these hypothetical scenarios in face-to-face interviews. All household members were asked to state how the implied changes would have affected their activity scheduling on the specified day, i.e. to adapt their reported schedule to the new conditions.

Findings — The postulated induced travel effect could be observed, in that the modifications to the generalised costs of travel affect the respondents' travel patterns in general, and the number and durations of conducted out-of-home activities in particular. However, the predominant reaction to changing travel times is the adaptation of departure time, which does not directly interfere with trip generation. Indicators of the effects have been shown, and are quite weak as far as activity generation effects are concerned. The activities most likely to be re-planned are leisure activities and sojourns at the home location, as is consistent with expectations.

Purpose — Fare validation data from transit smart card automatic fare collection (AFC) systems have properties that align with the direction of large-scale mobility surveys and the evermore demanding data needs of the transit industry. In addition to applications in transit planning and service monitoring, travel patterns and behaviour can effectively be studied by exploiting the continuous stream of observations from the same card. The paper proposes a methodology to enrich fare validation data in order to generate information that is hard to obtain with traditional travel surveys.

Methodology/approach — The methodology aims to synthesize individual-level attributes by summarizing multi-day validation records from each card. These new dimensions are then transposed to various levels of aggregation and studied simultaneously in multivariate analysis. The methodology can also be applied to synthesize other multi-day attributes and is transferable to other modes and other travel behaviour studies.

Findings — Results show that validation data can effectively be used to measure the distribution of travel patterns in time and space as well as the variation of those phenomena over time. The paper provides several examples based on millions of validation records from the metro sub-network of Montréal, along with interpretations and some practical implications.

Research limitations/implications — Limitations and bias regarding the data and the methodology as well as the strategies to handle them are discussed within the context of passive travel survey and travel behaviour studies.

Practical implications — Practitioners in transit planning, operations, marketing and modelling can benefit from studying the increasingly accessible and massive smart card datasets through a deeper understanding of multi-day travel patterns and behaviour of transit users.

Originality/value — This paper outlines a data modelling approach and simple-to-implement methodology which exploit the multi-day property of fare validation data from a smart card AFC. The concept of multi-day attributes is introduced. The analyses show that the approach is effective for extracting information on travel behaviour and its variation which would otherwise be hard to obtain through traditional travel surveys, opening up another dimension of this data source for practitioners and transport modellers alike.