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Improving sourcing decisions in NPD projects: Monetary quantification of points of difference
Author(s) -
Wouters Marc,
Anderson James C.,
Narus James A.,
Wynstra Finn
Publication year - 2009
Publication title -
journal of operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.649
H-Index - 191
eISSN - 1873-1317
pISSN - 0272-6963
DOI - 10.1016/j.jom.2008.07.001
Subject(s) - profitability index , new product development , product (mathematics) , process (computing) , business , structural equation modeling , industrial organization , marketing , operations management , computer science , economics , finance , geometry , mathematics , machine learning , operating system
During new product development (NPD), firms make critical design and sourcing decisions that determine the new product's cost, performance, competitive position, and profitability. The purchase price of materials and components for the new product provides only part of the picture for design and sourcing decisions. All‐encompassing analyses of cost and performance, such as total cost of ownership, are extraordinarily difficult to implement because they are demanding in terms of time, data and cooperation. We study monetary quantification of points of difference, which enables an NPD team to base its decisions instead on more focused, strategically‐pertinent analyses of costs and performance. We propose a substantive model of its antecedents and consequences. We then test this model with data from matched samples of 144 project leaders and 144 cost analysts who participated in the same NPD projects. Using structural equation modeling, we also test hypothesized differences in perspectives between project leaders and cost analysts. Results demonstrate the pivotal role of monetary quantification of points of difference among the sourcing alternatives being considered, especially for cost analysts. Results also demonstrate that Decision Justification to senior management drives the NPD team's decision‐making process. Finally, monetary quantification of points of difference leads to Uncertainty Reduction, which is found to be the primary antecedent of the judged success of applying analysis of cost and performance.