Indicators to meet the needs of New Zealand

Accessibility assessment requires appropriate core accessibility indicators. This makes the task both feasible and manageable at all levels of governance ranging from national policy to neighbourhood consultation.

Accessibility indicators are used to measure and make comparisons between the accessibility of particular locations to other locations. Although it is not the purpose of this research to develop accessibility indicators for New Zealand, the type of indicator to be measured guides the assessment tool required.

There are five key properties that accessibility indicators should possess. These include (adapted from Davidson 2009):

·         Consistency – if there is no real change in the system, then the indicator should not change. If there is real change in the system then it should change.

·         Ordinality – an improvement to the system should result in a change to the indicator in a particular direction. Further improvement should result in a greater change to the indicator in the same direction.

·         Linearity – in order to be properly useful in looking at tradeoffs in projects, or knowing how much better one project is than another, the indicator must also be a linear measure. Linearity is required whenever indicators are to be combined.

·         Meaningfulness – units should be a meaningful measure of the system being described. For example, $, min.

·         Transferability – the indicator must be able to be moved from city to town and preferably rural areas as well and still remain relevant and comparable between locations.

The New Zealand Household Travel Survey (NZHTS) is a good starting point when looking to develop core accessibility indicators for New Zealand as it is an already established source of data that contains current information on individual travel patterns of New Zealanders. However, the survey cannot be used to identify where there are spatial opportunities for improvement, and it also cannot generally be used to forecast future travel patterns (Milne et al 2011).