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Appraisal for different area types


Originally it was hoped that schemes could be classifi ed by different area types, at least for three: London, rural and urban. Although the data from the Carplus Annual Survey was sorted by ONS area type there was insuffi cient data for more rural schemes to provide robust estimates of the impacts and thus provide benchmarking data. An inspection of the records showed that there was a similar wide variety in patterns of use (i.e. increases and decreases in mileage) as with the urban and urban fringe results. The approach is therefore to use a simple split between London and England and Wales.


However, the cost benefi t calculator set out in this report and as a spreadsheet creates some differences between urban and rural settings by allowing for a range in the number of members per car: this increases the costs savings for urban schemes and reduces them for rural schemes. Due to the low number of car clubs currently operating in a rural context we have used average fi gures for the whole of England and Wales and similar marginal cost changes for all schemes. However, the research underpinning any bid may provide more specifi c fi gures for users as well as for number of vehicles. These can be entered directly into the spreadsheet as a substitute for the default average fi gures. The spreadsheet contains a note where this has been done.


While marginal external costs per kilometre of car use are much lower in rural than in urban areas, and alternatives to car use are harder to fi nd, car club members may have travelled further before. Distances


tend to be longer and this is refl ected in rural car use, in addition rural cars tend to be older than average. Thus any mileage related reduction would be greater than average, as would the lower carbon emissions from using LEVs or ULEVs. The latter is, however, quite small in terms of total benefi ts.


One further adjustment was made in the context of the Isle of Wight, which has obvious constraints in terms of local car mileages. Census data for the journey to work was used to estimate a shorter average trip length, and this factor (0.797) was applied to reduce both the carbon and the MEC benefi ts.


A further key issue for rural areas is wider social benefi ts in terms of overcoming lack of access to a car. How far this extends to labour market benefi ts is not clear: it is unlikely that the car club would be used for commuting (this is the case for most existing clubs). However, the diffi culties in rural areas of accessing local facilities including shops, health and leisure centres, without a car can be addressed, in association with other measures, by car club use. This links back to the earlier section which discussed option values and accessibility benefi ts.


More evidence is also needed for these specifi c areas on how the use of other modes by car club members is greater than car owners. This will grow as the number of car clubs grows outside London and other urban areas. It forms part of the data recommendations at the end of this report.


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