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Purpose — This study proposes an optimal survey design method for multi-day and multi-period panels that maximizes the statistical power of the parameter of interest under the conditions that non-linear changes in response to a policy intervention over time can be expected.

Design/methodology/approach — The proposed method addresses balances among sample size, survey duration for each wave and frequency of observation. Higher-order polynomial changes in the parameter are also addressed, allowing us to calculate optimal sampling designs for non-linear changes in response to a given policy intervention.

Findings — One of the most important findings is that variation structure in the behaviour of interest strongly influences how surveys are designed to maximize statistical power, while the type of policy to be evaluated does not influence it so much. Empirical results done by using German Mobility Panel data indicate that not only are more data collection waves needed, but longer multi-day periods of behavioural observations per wave are needed as well, with the increase in the non-linearity of the changes in response to a policy intervention.

Originality/value — This study extends previous studies on sampling designs for travel diary survey by dealing with statistical relations between sample size, survey duration for each wave, and frequency of observation, and provides the numerical and empirical results to show how the proposed method works.

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.

The purpose of this paper is to present empirical evidence on how and why a poor rural community is engaged in certain calculative practices, and how these are embedded in a “total institution” defined in terms of “relations of production” and “relations in production”.

Focusing on the traditional fishing industry in the Sri Lankan village of Kalamatiya, this study employs a qualitative, ethnographic methodology to collect and analyse data.

The underlying calculative practices are shown to resemble an articulated mode of production fabricated with some heterogeneous complexities, especially patronage relations, village cultures, and local capital and political power, rather than mere economic rationalities.

The paper argues that the notions of the “total institution” and the “articulated MOP” can inform accounting researchers to conceptualise research sites beyond the organisation as a novel “field” for empirical studies.

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.