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Consumers need to perceive improved utility in the fuel and vehicles relative to competing options . Otherwise market adoption will ��� occur . Risk aversion may often lead to suboptimal choices ( Denrell , 2008 ). This behavior is currently observed with FFVs , where despite vehicles and stations , the average FFV refuels with E85 is less than once per year ( Alliance of Automobile Manufacturers , 2013 ). Analysis shows that the choice is often driven by availability and convenience of access as well as price and range ( Pouloit & Babcock , 2014 ). Consumers respond to their individual and immediate needs ( Walther et al ., 2010 ). Concurrently , early failures or poor experiences can preclude future experiences that may correct the perceived utility ( Denrell , 2008 ). The SO vehicles offer a platform that when fueled with SO gasoline blends can offer efficiency , performance , and range , but can also run on non-SO fuel ( see Table 1 ) with reduced performance . The utility of the SO platform must be positive relative to the competing options in order for widespread adoption to occur .
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The causal loop diagram based on the
stakeholder characteristics ( see Figure
5 ) illustrates the complex relationships and feedbacks between stakeholders . The variables in red capture the word-ofmouth ( WOM ) and add to the traditional alternative fuel structure developed by Keith ( 2012b ). Specifically , it illustrates the tension and interplay between the energy companies , fuel producers , and retailers ( black font dark blue arrows ), OEMs ( brown font , teal arrows ), and consumers ( red font and light blue arrows ). Even this relatively high-level causal loop diagram contains significant complexity , including reinforcing loops that can work in both vicious and virtuous cycles depending on the strength of favorable versus unfavorable WOM . The qualitative static analysis of the causal loop demonstrates the importance of dynamic modeling of the complex interactions and choices in the multi-stakeholder system . Understanding the exact behavior and causes under a given set of exogenous inputs calls for formal modeling and is covered in the results and discussion sections .
Static analysis of the causal loop diagram generates questions and hypothesis for dynamic model testing . First , for SO vehicles availability of infrastructure is not sufficient to ensure stable adoption . Second , the experience from using the vehicle and infrastructure depends on the availability of fuel , vehicle performance on given fuel options , and price of the fuel . Unfavorable consumer experience can overwhelm or undermine efforts to introduce the platform through marketing and classical familiarity accumulation . Third , aggressive vehicle deployment and long delays in fuel production capacity may cause the virtuous reinforcement to flip to vicious and system collapse reinforcement when consumers become dissatisfied with fuel price or availability .
Model
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The current alternative fuel adoption
model developed by Keith utilizes the social contagion / diffusion model common in SD ( Keith , 2012b ; Sterman , 2000 ). This model does not contain any mechanisms for market growth turning to collapse based on unfavorable experience and consumer perception . This limits the opportunity to observe a growth then collapse scenario other than through exogenously imposed limits on infrastructure . Even then ,
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