PALABRAS CLAVE

The specification of all MNL, ECMNL, and RPL models had the utility functions defined as linear in parameters. Both RPL and ECMNL forms of the MMNL model were estimated using cross-sectional and panel data and alternative specific and generic parameters specifications. Model estimation was undertaken using the NLOGIT 4 software.

The vehicle choice sub-model in the VFM incorporated the best performing of the MMNL models. This sub-model acted as a choice simulator to estimate the market shares of the vehicle alternatives based on the attribute values from the VFM scenarios.

Excel does not have the capability to perform Halton draws for estimating the simulated probabilities (see section 3.2.5) so random draws were used instead. To offset the poorer performance of this form of randomisation, the number of draws was increased from 200 to 5,000.

Even with a large number of random draws, the output from the VFM simulator for each VFM scenario varied slightly across repeated model runs. Therefore, for each VFM scenario, the choice simulator was run 10 times and the mean and variances of the output calculated. Section 5.4 contains a description of the VFM scenarios.

The performance of the choice simulator in the VFM was tested by comparing its output to that of the choice simulator in the NLOGIT software. The simulator was tested using a range of input values with the full choice set and a constrained

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choice set. Using the two-sample t-test it was found that the output from the two simulators was not statistically different at the 5% level³⁷.

The choice simulator, as applied in the VFM, is not used to directly model the choice behaviour of New Zealand car buyers, but that of New Zealand new and used vehicle importers. In New Zealand, with the exception of a small number of direct imports by individuals, vehicle importers determine what new and used LPVs will enter the country in response to demand from car buyers. The New Zealand branches, or local franchises, of the international vehicle manufacturers undertake the importation of new cars, and independent vehicle dealers, vehicle importers, and wholesalers are responsible for the importation of most of the used cars that enter New Zealand.

For this study, the assumption was that the decision making processes used by the vehicle importing industry reflected the preferences of New Zealand car buyers. It is, therefore, valid to use a discrete choice model estimated with data from a survey of New Zealand’s car buyers to model the choice behaviour of vehicle importers.

Experience with HEVs indicates that vehicle manufacturers are cautious when introducing new technologies into the market. Therefore, it is likely that the introduction of EVs will occur in a similar manner starting with a limited range of models that are available in limited quantities and in a limited number of markets.

Other studies that have assessed the uptake of EVs in New Zealand have attempted to take account of the effect of limited availability based on information provided by industry experts (Electricity Commission, 2010; Baxter et al., 2009; Duncan et al., 2010). In the present study, the focus has been on the effect of car buyers’

preferences on the uptake of EVs in New Zealand. It was assumed that from the date of first introduction, in this study 2012, New Zealand car buyers’ purchase behaviour would not be constrained by the availability of new EVs, but would be able to select from a full range of EV makes and models.

37 The results of the choice simulator verification test are presented in Appendix 4

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The output of the VFM choice simulator was modified to take account of two features of the New Zealand vehicle market. The first modification addressed the fact that most new cars entering the LPV fleet are bought by business and

government organisations and that these car buyers are only interested in new vehicles (Kerr, 2009). The second modification was to account for the importation of used EVs from Japan, which would initially only be available in limited quantities.

As discussed in section 5.2.3, the decision was made to combine the new and used ICEV alternatives into a single opt-out alternative so as to simplify the survey design and reduce the likelihood of hypothetical bias. This specification was appropriate for private car buyers who buy both new and used ICEVs, but for organisational buyers, who are only interested in new ICEVs, this model specification would not accurately estimate market shares.

Despite these limitations, applying the discrete choice model to the organisational car buyers’ market using a reduced choice set was considered an acceptable

provisional measure for the purposes of the present study, but with the caveat that a separate model should be developed.

Japan supplies approximately 95% of all the used cars that enter the New Zealand LPV fleet (New Zealand Transport Agency, 2011). The availability of used Japanese vehicles in New Zealand is largely a function of the effect of the Japanese vehicle automobile inspection registration system (the Shā-ken test) on Japanese car owners’ selling behaviour. In Japan when a vehicle turns 3 years old, it must get an inspection and thereafter be inspected every two years. As a vehicle ages, the expense of the Shā-ken test increases and most Japanese car owners sell their vehicles because of the increasing expense, not the result of a failed test. As a consequence most Japanese used vehicles that enter the New Zealand market are three years or older (Philpot and Shaw, 2006) with the seven to nine year age cohorts forming approximately half of the supply of used petrol imports and 70% of used diesel imports (Colegrave and Denne, 2006). The expectation is that in future the Shā-ken test will also apply to EVs and determine the age and availability of used EVs entering New Zealand.

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For this study, the assumption was that new EVs would become widely available in the Japanese market at the same time as in New Zealand and as the age of the Japanese EV fleet increased there would be a growing number of used EVs available for export to other countries. This increasing availability of used EVs was simulated in this study by gradually increasing the supply of used EVs based on the average cumulative age profile of used vehicles that entered New Zealand from 2001 to 2009 (Ministry of Transport, 2012b).

Figure 5.2: Cumulative availability profile of used imported EVs

Figure 5.2 shows the projected proportion of the demand for used imported EVs assumed to be available to New Zealand car buyers. For example, in 2015, there is a limited supply meeting only 7% of the demand for used imported EVs. By 2020, this proportion rises to 55% and, by 2025, as more Japanese owners of EVs sell their cars due to the Shā-ken test, over 98% of the New Zealand demand for used imported EVs is met.

The application of the choice simulator in each year in the modelling period occurred in three stages.

First stage: simulating the LPV purchases by organisations

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The choice simulator was restricted to ICEVs and new EVs and applied to the forecast demand for new cars by organisations in that year.

Second stage: first round of purchases by private buyers

With all the EV alternatives available, the choice simulator then allocated the forecast demand for new and used LPV demand by private car buyers. However, until a time when EVs imported from Japan were widely available for sale (Figure 5.2), the supply of used EVs was constrained and a proportion of private car buyers were estimated not to be able to buy a used imported EV. This unfulfilled demand was then transferred to the next stage.

Third Stage: second round of purchases by private buyers

The choice simulator allocated the frustrated demand from the second stage using a limited choice set that comprised new and used ICEVs and new EVs.

The aggregated demand from the three stages was entered into the vehicle stock database ready for the next annual period.