View article

Past research in new product development (NPD) has conceptualized prototyping as a “design-build-test-analyze” cycle to emphasize the importance of the analysis of test results in guiding the decisions made during the experimentation process. New product designs often involve complex architectures and incorporate numerous components, and this makes the ex ante assessment of their performance difficult. Still, design teams often learn from test outcomes during iterative test cycles enabling them to infer valuable information about the performances of (as yet) untested designs. We conceptualize the extent of useful learning from analysis of a test outcome as depending on two key structural characteristics of the design space, namely whether the set of designs are “close” to each other (i.e., the designs are similar on an attribute level) and whether the design attributes exhibit nontrivial interactions (i.e., the …