4.4.5.4 Changes detectable in other social data?

The attention EVs receive from the general public is a further possible indicator of change (Boulton et al., 2023). A time series of view share (proportion of advert views that are for EV cars rather than non-EV cars) on AutoTrader, a prominent UK website, shows that there has been a general increase in view share from 2018 up to July 2023 (Figure  4.4.11). Also clear is that, at certain times, spikes in attention can occur, a few days after which view share returns to normal. These spikes in attention can be directly linked to specific external events: 

  1. 4th February, 2020: The UK Government announces a ban on sale of new petrol vehicles by 2035;
  2. 18th November, 2020: The UK Government brings forward the ban on sale of new petrol vehicles to 2030;
  3. 29th September, 2021: Potential HGV driver shortage, leading to uncertainty about petrol availability, panic buying and fuel shortages in the UK;
  4. 10th March, 2022: Spike in UK fuel prices associated with international fossil fuel volatility from Russian conflict in Ukraine;
  5. 8th June, 2022: Spike in UK fuel prices.
Figure: 4.4.12
Figure 4.4.12: Measuring the return time from specific events as an EOI in view share of EVs (compared to non-EVs) on AutoTrader UK. (a) The time series of view share (black), alongside the weekly mean UK unleaded fuel price (blue). Marked in grey vertical lines (i-v) are specific external events detailed in the main text. (b)-(f) The return time from each event is calculated as the number of days it takes for the time series to decrease by 75% of the distance from the spike back to the pre-spike value. Dotted grey lines show the pre-spike and spike dates as vertical lines. The 75% value is shown as a horizontal black line, and the date this is reached by the vertical black line. (g) The number of days after the spike it took for the system to reach the 75% value for each spike.

We measure how long it takes for attention to return to ‘normal’ after each spike (i)-(v) as an early opportunity indicator (see Section 1.6 and Section 2.5), by determining how long it takes for a spike in attention to decay by 75 per cent. For each successive spike (Figure 4.4.11b-f), there is a clear increase in the length of time it takes for decay to happen, i.e. for the system to return to 75 per cent of its pre-spike level (Figure 4.4.11b-f), increasing by a factor of approximately six from point (i) in June 2020, to (v) in June 2022. This shows that the system is slowing down and the incumbent state of ICEV dominance is losing stability over time. Colloquially, one can imagine this increase in return time suggests that events are affecting the system more intensely, such that it takes longer for interest in EVs to die down after the event has passed and that this indicates the system is losing stability. Just as for market share in the sales data, we can also observe increases in AR(1) and variance in view share across the whole period (Figure 4.4.12). 

Compared to sales data, this dataset provides the opportunity to measure actors’ instantaneous reactions to events, as they do not have to interact with the system in such a strongly committed way such as buying a vehicle. As such, we are able to better determine people’s interest using this novel dataset. These results imply that critical slowing down is occuring in the view share of EV adverts, and thus that a tipping point is being approached such that they may rapidly gain the majority of view share.

Figure: 4.4.13
Figure 4.4.13: Early opportunity indicators on EV view share time series. (a) The time series of view share (black) and the smoothed version (red) used to detrend (calculated using a Kernal smoothing function with bandwidth equal to 50). (b) AR(1) calculated from the time series in (a) once it has been detrended using a moving window equal to two years (as described in Chapter 1.6) and plotted at the end of the window used to create it. (c) As in (b) but for variance.
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