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authorRalph Amissah <ralph@amissah.com>2015-05-15 00:37:16 -0400
committerRalph Amissah <ralph@amissah.com>2015-05-15 00:37:16 -0400
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tree6a58666bf4220350aea8a147400e09d3e0ee3dab /data/samples/current/en/democratizing_innovation.eric_von_hippel.sst
parentdebian/changelog (5.0.2-1) (diff)
parentmarkup: provide bibliography & glossary examples (for sisu-7.1.0) (diff)
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@@ -3909,444 +3909,1351 @@ In this book I have explored how and why users, individually and in firms and in
2. In the general literature, Armstrong's (2001) review on forecast bias for new product introduction indicates that sales forecasts are generally optimistic, but that that upward bias decreases as the magnitude of the sales forecast increases. Coller and Yohn (1998) review the literature on bias in accuracy of management earnings forecasts and find that little systematic bias occurs. Tull's (1967) model calculates $15 million in revenue as a level above which forecasts actually become pessimistic on average. We think it reasonable to apply the same deflator to LU vs. non-LU project sales projections. Even if LU project personnel were for some reason more likely to be optimistic with respect to such projections than non-LU project personnel, that would not significantly affect our findings. Over 60 percent of the total dollar value of sales forecasts made for LU projects were actually made by personnel not associated with those projects (outside consulting firms or business analysts from other divisions).
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%% index di.eric_von_hippel_index.txt democratizing_innovation.eric_von_hippel_index.txt