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Cited by 227

The DOI matches its OpenAlex record; 2 of the 2 references it cites were found in a registry or an index.

Successful Innovation Using Strategies to Reduce Consumer Resistance An Empirical Test

Sundaresan Ram·1989·Journal of Product Innovation Management

Abstract

This article focuses on a relatively neglected concept in new product management: innovation resistance. Specifically, it examines why consumers develop resistance to innovations at the attitude formation and intention-to-buy stages of their decision process, and what strategies marketing firms have within their direct control to reduce this resistance. S. Ram identifies two major sources of innovation resistance: perceived risk and cognitive resistance. These are studied in the context of four product groups and two distinct strategies to reduce innovation resistance. The results show that a strategy of innovation modification works to reduce resistance caused by perceived economic and functional risk. On the other hand, communication strategies can reduce resistance caused by perceived social or psychological risk. Sources of innovation resistance and appropriate strategies vary across different product groups.

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OpenAlex · 10.1016/0737-6782(89)90011-8

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Metadata

Authors
Ram, S.
Venue
Journal of Product Innovation Management
Publisher
Wiley
Published
1989-03-01
Volume
6
Issue
1
Pages
20-34
ISSN
0737-6782 (ISSN-L)
OpenAlex
W2065920751
Cited by
227
References
2
FWCI
2.38
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Successful Innovation Using Strategies to Reduce Consumer Resistance An Empirical Test. https://app.cochat.ai/papers/10.1016/0737-6782(89)90011-8
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Ram, S. (1989). Successful Innovation Using Strategies to Reduce Consumer Resistance An Empirical Test. Journal of Product Innovation Management. https://doi.org/10.1016/0737-6782(89)90011-8

Data sources

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.