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Cited by 1,467

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Why Some New Products are More Successful than Others

Henard, David H., Szymanski, David M.·2001·Journal of Marketing Research

Abstract

Product innovation is increasingly valued as a key component of the sustainable success of a business's operations. As a result, there has been a noticeable increase in the number of studies directed at explicating the drivers of new product success. To help managers and researchers synthesize this growing body of evidence, the authors conduct a meta-analysis of the new product performance literature. Of the 24 predictors of new product performance investigated, product advantage, market potential, meeting customer needs, predevelopment task proficiencies, and dedicated resources, on average, have the most significant impact on new product performance. The authors also find that the predictor–performance relationships can vary by measurement factor (e.g., the use of multi-item scales, subjective versus objective measures of performance, senior versus project management reporting, time elapsed since product introduction) or contextual factor (e.g., services versus goods, Asian versus North American markets, competition in high-technology versus low-technology markets). They discuss the implications of these findings and offer directions for further research.

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Crossref · 10.1509/jmkr.38.3.362.18861

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Metadata

Authors
Henard, D. H., & Szymanski, D. M.
Venue
Journal of Marketing Research
Published
2001-08
Volume
38
Issue
3
Pages
362-375
ISSN
  • 0022-2437 (ISSN-L)
  • 1547-7193
OpenAlex
W2176801670
Cited by
1,467
References
5
FWCI
68.75
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.