Journal on Policy & Complex Systems Volume 1, Number 2, Fall 2014 | Page 125

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The objective is to uncover the mechanisms influencing the adoption of the technologies . Given that empirical information is incomplete for the system , an exploratory approach to modeling is used . Although the resulting model cannot be taken as a precise image of the system , it does provide relevant insight into the resulting behavior from the structure ( Bankes , 1993 ).

In order to evaluate the influence of unfavorable and favorable WOM the customer satisfaction level CSL SO GAS as affected by the utility U 2
( Eq . ( 1 ) was defined exogenously with low starting points explored through the scenario evaluation . This means that U 2
< U 1 creates frustration from the actual experience being below expectations set at the time of purchase .
Ford ’ s loop knockout methodology was used to test the model mechanics and demonstrate the importance of the unfavorable WOM in determining market size ( Ford , 1999 ). Loop knockout identified the dominant loops and underlying factors and relationships that lead to the observed system behavior necessary to inform policy development . Simulations were run with the set of parameters corresponding to aggressive promotion of SO vehicles ($ 500 million of additional marketing / year ) ( Keith , 2012b ). Customer satisfaction level CSL SO GAS reflecting the combination of infrastructure availability , vehicle performance , and SO fuel price was defined on the dimensionless scale from -1 to 1 to start at negative 0.1 and end at 0 , leaving consumers unsatisfied with the value proposition of a new SO platform . Two identical scenarios were defined with only a difference in the sensitivity S to the negative WOM dynamics such that the square matrix M v , u of allowed directions and strengths of view changes from view v to view u becomes
M !,! = S
0
SSpp !
0
SSSS !
0
0
pp !
SSSS !
0
pp ! = pp !"#$%"&'( !" !"#$%&'$()* , pp ! = pp !"#$%&'$()* !" !"#$%"!"# pp ! = pp !"#"$%!&"'&( !" !"#$%"&'( , pp ! = pp !"#"$%!&"'&( !" !"#$%&'$()*
Where p 1 - p 4 are the strengths of the allowed transition between consumer views of a platform ( see Appendix A for full specification ). Having sensitivity S as a multiplier for all strengths except for p 3 ensured that setting S = 1 set up the scenario with the full effect of unfavorable and favorable WOM and by setting S = 0 the baseline scenario is set with no effect of unfavorable WOM , but where favorable WOM is functioning .
Figure 7 shows a simulation of the model based on conventional structure where there is no unfavorable WOM ( S = 0 ), which
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