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Across Europe, on average more than 95% of all passenger cars and half of all light commercial vehicles are permanently available to a household. This includes both privately owned vehicles and company cars. The profiles of vehicle use can be specified as average annual distance driven per vehicle and for the fleet as a total, purpose of travel (trip destination), infrastructure use (urban, interurban or motorway road transport) and also fuel consumption together with data on CO₂ emissions. Indicators on vehicle use can be tracked in various ways:

• self-administered panels of households, which permit their vehicles to be followed for several years;

• national or local household travel surveys (with a seven-day trip diary);

• official vehicle inspection and vehicle registration files;

• ‘vehicle surveys’ based on vehicle registry data;

• traffic counts;

• data collected for road-charging purposes.

self-administered panels of households, which permit their vehicles to be followed for several years;

national or local household travel surveys (with a seven-day trip diary);

official vehicle inspection and vehicle registration files;

‘vehicle surveys’ based on vehicle registry data;

traffic counts;

data collected for road-charging purposes.

The paper will present a review of mainly vehicle-based survey methods used in France, Germany, Finland, the United Kingdom, the United States and Canada, describing existing sampling frames to their scope, advantages and limitations, as well as their costs. Issues addressed in this context will be further examined in terms of their methodological challenges as well as their purpose.

The leading questions underlying this paper as well as the corresponding workshop are: why is it necessary to have data on passenger travel or transportation; and, looking at international experience, how good are vehicle-based surveys in delivering the required information? In discussing problems experienced in the different countries with data collection and evaluation methods, emphasis will be put on potential strategies for methodological and technological improvement and problem solving. One example is the potential use, benefits and constraints of new survey technologies presented by vehicle tracking techniques.

The challenge of truckload routing is increased in complexity by the introduction of stochastic demand. Typically, this demand is generalized to follow a Poisson distribution. In this chapter, we cluster the demand data using data mining techniques to establish the more acceptable distribution to predict demand. We then examine this stochastic truckload demand using an econometric discrete choice model known as a count data model. Using actual truckload demand data and data from the bureau of transportation statistics, we perform count data regressions. Two outcomes are produced from every regression run, the predicted demand between every origin and destination, and the likelihood that that demand will occur. The two allow us to generate an expected value forecast of truckload demand as input to a truckload routing formulation. The negative binomial distribution produces an improved forecast over the Poisson distribution.

The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.

We know a great deal about the ways in which routines of news coverage may bias newspaper content, but little about how different article retrieval practices influence newspaper data assembled by scholars. Using the New York Times as a source of data on social movement activity, we compare depictions of protest by the African-American Civil Rights movement over time produced using the two most common article retrieval methods: index versus full-story coding. Full-story coding clearly offers more depth and greater breadth in terms of the events identified. Moreover, many of the same event characteristics associated with selection bias in newspaper reporting (e.g., size and confrontational nature of a protest event, presence of counter-demonstrators or police, and event sponsorship by a recognized social movement organization) are selected upon again when stories are indexed by New York Times staff.

Purpose – Information collected from police crash reports has long been the primary source of data for the analysis of factors that determine the likelihood of a crash (crash frequency) and its resulting severity (measured in terms of the extent of injuries to vehicle occupants). Proper cross-sectional analyses techniques, covered in this chapter, are important for guiding safety policy and countermeasures.

Methodology – This chapter provides an overview of some of the more commonly used cross-sectional statistical and econometric methods, and discusses the nuances and their limitations with regard to how they are applied to typical crash-report data.

Findings – The wide variety of analytic methods available to safety researchers makes the selection of appropriate methods critical. This chapter provides important guidance for safety researchers in their choice of methodological approach.

Implications – Understanding the importance of proper model specification, unobserved heterogeneity, endogeneity and other factors covered in this chapter is extremely important in analysing safety data and must be given full consideration before any results are finalised.

The mid-1990s marked a paradigm shift in the way physical activity is promoted, and walking is now considered the most suitable type of physical activity for widespread promotion. Accurate measurement underpins public health practice, hence the aims of this chapter are to: (1) provide a typology for the measurement of walking; (2) review methods to assess walking; (3) present challenges in defining walking measures; (4) identify issues in selecting instruments for the evaluation of walking and (5) discuss current efforts to overcome measurement challenges and methodological limitations. The taxonomy of walking indicates that secondary purpose walking is a more complex set of behaviours than primary purpose walks. It has many purposes and no specific domain or intensity, may lack regularity, and therefore poses greater measurement challenges. Objective measurement methods, such as accelerometers, pedometers, smartphones and other electronic devices, have shown good approximation for walking energy expenditure, but are indirect methods of walking assessment. Global Positioning System technology, the ‘Smartmat’ and radio-frequency identification tags are potential objective methods that can distinguish walkers, but also require complex analysis, are costly, and still need their measurement properties corroborated. Subjective direct methods, such as questionnaires, diaries and direct observation, provide the richest information on walking, especially short-term diaries, such as trip records and time use records, and are particularly useful for assessing secondary purpose walking. A unifying measure for health research, surveillance and health promotion would strongly advance the understanding of the impact of walking on health.