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Cross-Functional Integration and New Product Success: An Empirical Investigation of the Findings
Abstract
Although cross-functional integration is often considered an important element in a successful new product development program, a great deal of variance exists in extant literature regarding how integration is defined and implemented and how relevant studies are conducted. The authors attempt to bring clarity to a diverse set of 25 studies that investigate cross-functional integration by empirically analyzing 146 correlations between integration and aspects of new product success. The authors examine the impact of 12 potential moderators that affect the integration–success link using meta-analysis techniques. The findings indicate that though cross-functional integration may indeed have a direct impact on success, the combination of integration with other variables may be of greater importance. Furthermore, because most of the nine variables that significantly affect the integration–success relationship are either managerially controlled or industry specific, the findings imply that firms should design cross-functional structures to maximize their effectiveness. Other variables that affect the integration–success relationship reflect researchers’ methodological decisions, suggesting that care should be taken when designing and interpreting the results of such studies. The authors discuss the implications of these findings and directions for further research.
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Metadata
- Authors
- Troy, L. C., Hirunyawipada, T., & Paswan, A. K.
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2008-11
- Volume
- 72
- Issue
- 6
- Pages
- 132-146
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W2008805920
- Cited by
- 377
- References
- 73
- FWCI
- 30.11
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.