The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing
Abstract
As technology advances, it becomes more feasible to load products with a large number of features, each of which individually might be perceived as useful. However, too many features can make a product overwhelming for consumers and difficult to use. Three studies examine how consumers balance their desires for capability and usability when they evaluate products and how these desires shift over time. Because consumers give more weight to capability and less weight to usability before use than after use, they tend to choose overly complex products that do not maximize their satisfaction when they use them, resulting in ”feature fatigue.” An analytical model based on these results provides additional insights into the feature fatigue effect. This model shows that choosing the number of features that maximizes initial choice results in the inclusion of too many features, potentially decreasing customer lifetime value. As the emphasis on future sales increases, the optimal number of features decreases. The results suggest that firms should consider having a larger number of more specialized products, each with a limited number of features, rather than loading all possible features into one product.
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Cites
The Usability Engineering Lifecycle
NIELSEN, J. (1993) · Usability Engineering · doi:10.1016/b978-0-08-052029-2.50007-3 · Cited by 2,657
The role of involvement in attention and comprehension processes
Celsi, R. L., & Olson, J. C. (1988) · Journal of Consumer Research · doi:10.1086/209158 · Cited by 2,070
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Why do humans reason? Arguments for an argumentative theory
Mercier, H., & Sperber, D. (2011) · Behavioral and Brain Sciences · doi:10.1017/s0140525x10000968 · Cited by 2,254
Lee, A. R., Son, S.-M., & Kim, K. K. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.08.011 · Cited by 814
Empirical investigation of Facebook discontinues usage intentions based on SOR paradigm
Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.01.020 · Cited by 425
Kareklas, I., Carlson, J. R., & Muehling, D. D. (2014) · Journal of Advertising · doi:10.1080/00913367.2013.799450 · Cited by 343
Adaptive personalization using social networks
Chung, T. S., Wedel, M., & Rust, R. T. (2016) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-015-0441-x · Cited by 184
Self-citation
Metadata
- Authors
- Thompson, D. V., Hamilton, R. W., & Rust, R. T.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 2005-11
- Volume
- 42
- Issue
- 4
- Pages
- 431-442
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W2105037366
- Cited by
- 704
- References
- 2
- FWCI
- 71.21
- Type
- journal article
- Language
- en
- Open access
- closed
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