New product entry success : an examination of variable, dimensional and model evolution
Green, John Boyd, 1947- (1996) New product entry success : an examination of variable, dimensional and model evolution. PhD thesis, University of Warwick.
WRAP_THESIS_Green_1996.pdf - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Other (Permission e-mail)
Restricted to Repository staff only
Official URL: http://webcat.warwick.ac.uk/record=b1403936~S15
This thesis examines the evolution of antecedents, dimensions and initial screening
models which discriminate between new product success and failure. It advances on
previous empirical new product success/failure comparative studies by developing a
discrete simulation procedure in which participating new product managers supply
judgements retrospectively on new product strategies and orientations for two distinct
time periods in the new product program: (1) the initial screening stage and (2) a
period approximately 1 year after market entry. Unique linear regression functions
are derived for each event and offer different, but complimentary, temporally
appropriate sets of determining factors. Model predictive accuracy ascends over time
and conditional process moderators alter success factors at both time periods. Whilst
the work validates and synthesises much from the new product development
literature, is exposes probable measurement timing error when single retrospective
models assess success dimension rank at the initial screen.
Six of seven hypotheses are accepted and demonstrate that:
1. Many antecedents of success and measures of objective attainment are perceived
by NPD (new product development) managers to differ significantly over time.
2. Reactive strategy, NPD multigenerational history and a superior product are the
most important dimensions of success through one year post launch.
3. Current linear screening models constructed using retrospective methods produce
average prescriptive dimensions which exhibit measurement timing error when
used at the initial screen.
4. Success dimensions evolve from somewhat deterministic to more stochastic over
time with model forecasting accuracy rising as launch approaches based on better
5. Product market PiLC (the life expectancy of an introduction before modification
is necessary calculated in years and months) and its order of entry and level of
innovation alter aggregate success model accuracy and dimension rank.
6. Proper initial dimensional alignment and intra-process realignment based on
changing environments is critical to a successful project through one year post
The work cautions practitioners not to wait for better models to be developed but
immediately: (1) benchmark reasons for their current product market success, failure
and kill historical "batting average"; (2) enhance and/or replace
contributing/offending processes and systems based on these history lessons; (3)
choose or reject aggregate or conditional success/failure models based on team
forecasting ability; (4) concentrate on the selected model's time specific dimensions
of success and (5) provide/reserve adequate resources to adapt strategically over time
to both internal and external antecedent changes in the NPD environment.
Finally, it recommends new research into temporal, conditional and strategic tradeoffs
in internal and external antecedents/dimensions of success. Best results should
come from using both linear and curvilinear methods to validate more complex yet
statistically elegant NPD simulations.
|Item Type:||Thesis or Dissertation (PhD)|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor|
|Library of Congress Subject Headings (LCSH):||New products|
|Official Date:||April 1996|
|Institution:||University of Warwick|
|Theses Department:||Warwick Business School|
Actions (login required)