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Complementary Drivers of New Product Development Performance: Cross‐Functional Coordination, Information System Capability, and Intelligence Quality
Author(s) -
Bendoly Elliot,
Bharadwaj Anandhi,
Bharadwaj Sundar
Publication year - 2011
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/j.1937-5956.2011.01299.x
Subject(s) - endogeneity , market intelligence , complementarity (molecular biology) , quality (philosophy) , new product development , industrial organization , information sharing , knowledge management , supply chain , sample (material) , business , computer science , marketing , microeconomics , economics , econometrics , philosophy , chemistry , epistemology , chromatography , biology , world wide web , genetics
Coordination efforts that access and align relevant cross‐functional expertise are regarded as an essential element of innovation success. In recent years, these efforts have been further augmented through complementary investments in information systems, which provide the technological platforms for information sharing and coordination across functional and organizational boundaries. Somewhat overlooked has been the critical mediating role of the intelligence gained through these efforts and capabilities. This study draws on the theory of complementarity to elaborate on the nature of this mediating concept. Theoretical predictions of the model are tested using instrument variable regression analysis of data collected from a sample of publicly traded US manufacturing firms. The findings suggest that the effects of both internal and external coordination on market intelligence and supply‐chain intelligence are moderated by the firm's information system capability. The effect of both types of intelligence quality on new product development performance was contingent with the effects being enhanced (attenuated) when the market conditions were dynamic (stable). The results are robust to common‐method bias, endogeneity concerns, and alternative estimation methods.