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this only affects the immediate decision of potential consumers and does not capture long-term effects and delays of opinions in the technology platform . If the infrastructure lag is closed then sales would resume , but in reality the market doesn ’ t behave that way . Unfavorable opinions will be held and will impact the technology uptake . Since the unfavorable opinions tend to prevail , it is much harder to move people from an unfavorable view to a favorable view than it is to disappoint them because of a bad first-hand experience .
The inclusion of the unfavorable view and WOM has an asymmetrical impact . Favorable views result in a behavior similar to the conventional familiarity . If potential adopters with favorable views are willing to consider the new platform more ( which doesn ’ t guarantee adoption and depends on the choice model ), the potential adopters with unfavorable views are not going to even consider the technology unless their views change , and are removed from the market .
Unfavorable views form and evolve differently for users and potential adopters . Users change their views based on direct experience , while potential adopters of a technology rely on WOM . Figure 6 shows the main mechanisms of transmitting the views between users of SO vehicles and non-users . While users can change views of potential adopters this link is unidirectional , as potential adopters cannot change views of actual users . In addition , the structure shown in Figure 6 is working simultaneously in all directions , affecting and converting all potential views — favorable , unfavorable , and uninformed as people contact each other . Although not explicit , the strength of the conversion is different , and reflects inherent asymmetry of the unfavorable and favorable WOM mechanisms identified in the literature review .
In general SD models do not consider the effect of utility function on WOM . There is a single utility for a given technology platform that is evaluated by the consumer at the time of purchase and is assumed to remain constant for the duration of ownership of the durable good ( automobile ). Given the relatively higher utility of a platform a market failure will only occur when there is inadequate WOM to accumulate and sustain critical market share or volume ( Struben , 2006 ). However , utility not only affects the purchasing decision , but it influences the vehicle owner ’ s experience , and in turn shapes the quantity and quality of the WOM stories . In the model presented in this paper , the utility of the buyer and user are distinct variables . Utility of the buyer is defined as
UU ! = ff uu ! , uu ! , … , uu !
where uu ! , ii ∈ SS ! is the average perceived utility component ( attribute ) at the time of purchase , S b is the relevant set of utility components used to evaluate competing market offers at the time of purchase . Utility of a user is defined as
UU ! = ff uu ! , uu ! , … , uu !
where uu ! , ii ∈ SS ! is the actual utility component ( attribute ) during the use of the vehicle ,
S u� is the relevant set of utility components used to evaluate owned vehicle / product .
The utility of a user reflects the perception post purchase during the use of the durable good ( vehicle ) which may be affected by a different set of factors not considered by the consumer at the time of purchase , or which change over time . Generally , both sets don ’ t have to be equal , S b
≠ S u�
but there exists an overlapping subset of utility components used both for purchasing decision and for evaluating S b
∩ S u�
≠ Ø . The purchase utility function is determined by such parameters as fuel price , fuel availability , vehicle price , and
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