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vehicle performance attributes . The user utility has some overlapping components such as fuel price and availability , and the actual perceived performance of the vehicle based on the fuel choice . The values of the factors will dynamically change over time and shape the quality and quantity of the WOM and the influence it has on the potential consumer . For example , in a static condition the utility at a given point in time may be very positive for SO vehicles due to the current fuel price and possible marketing and incentives , but the perception and resulting WOM from existing consumers may be negative due to the actual experience on fuel availability and price over time .
Unlike battery electric vehicles , compressed natural gas vehicles , and fuel cell vehicles that are dependent on a single dedicated fuel , the SO vehicles have multiple fuel options . Fuel purchase post vehicle purchase is determined by user by comparing consumer utility � � for two fuel options ( regular gasoline and SO fuel ) and is important for determining SO vehicle and ethanol market growth . The Keith model doesn ’ t take into account the post vehicle purchase consumer choice presented to SO vehicle owners of what fuel to use to maximize their current utility based on fuel price , availability , and vehicle performance . Presumably , consumers choose the SO platform to take advantage of extra features ( better range , acceleration , etc .) offered by means of using SO . While SO vehicles are downward compatible and can run on non-SO gasoline , their performance is subpar . A consumer considering � � might decide to choose regular gasoline fuel due to high SO fuel price or its low availability . The resulting performance gap or efforts expended to search for SO fuel impacts perception and consumer experience as described in the unfavorable view formation section of this paper , which in turn influences market adoption .
The model makes no pre-determinations as to how future consumers may respond to fuel price , fuel availability , and vehicle performance . In reality , consumers are heterogeneous . If the average utility of using a non-SO fuel is greater for a SO vehicle , this will result in some fraction of those consumers using the non-SO fuel based on the relative utility . Depending on the frequency of this condition , SO adopters will develop a negative view of the technology and will result in lower total ethanol consumption .
The existing model developed by Keith ( 2014 ) is used as the foundation with an additional module developed for the consumer view . The exogenous inputs and variable set points are drawn from the literature and model developed by Keith ( 2014 ). The incorporation of the asymmetrical feedbacks of favorable and unfavorable WOM in the new model ( see Appendix A ; see also Figure 10 ) can inform the system parameters in which the needs of the stakeholders can all simultaneously be met .
The model evolved from the traditional aging chain and co-flow structure ( typically required to track attributes ) to one with a single stock and four-dimensional subscripts . This approach offers benefits and flexibility needed to capture the additional system complexity and allows the model to be used in other applications .
The following subscripts are used :
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Drivers change their views based on direct experience
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