Abstract
A decision model is developed to help managers select the most appropriate sequences of plans for product Research and Development (R and D) projects that have strict constraints on budget, time, and resources. In recent years, many organizations have changed from a discipline orientation to a focus on integrated programs and related outcomes. For decision-maker of these high-profile R and D programs, it is critical to understand which activities are most important, considering both investment feasibility and cost-effectiveness. This study proposes a two-dimensional decision model that integrates analytic hierarchy process (subjective judgment method) and data envelopment analysis (objective judgment method) to perform this essential task. Based on information about these two decision science tools, the model develops a two-axis evaluation space for research alternatives. By locating particular activities in this decision space, a program manager can compare and prioritize alternative research investments.
Highlights
A large corporation often faces a decision on the scope of product research and development (R and D) projects
This study proposes integrating two complementary decision tools that have particular promise in R and D management environment: analytic methods better than benefit-contribution methods
Most Majorities of them can be classified as subjective and objective approaches depending on the information provided
Summary
A large corporation often faces a decision on the scope of product research and development (R and D) projects. The subjective approaches include the Analytic Hierarchy Process[14], Delphi method[13], and weighted least square method[15] etc. Objective approaches determine weights by making use of mathematical models, but they neglect subjective judgment Major concerns in the two-dimensional Subjective Weight Restriction Method: Several types decision model are compared, prioritize alternative of subjective weight restrict methods Various researchers have provided a give different weights and subjectivity is the good review of these approaches to R and D project major drawback. Combining the consistency indices in all the comparison matrices provides each consistency index and ratio to evaluate on the common recognition of the entire hierarchy
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