The DOI matches its Crossref record; 114 of the 114 references it cites were found in a registry or an index.
The effects of social- and self-motives on the intentions to share positive and negative word of mouth
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As viable tools for public self-enhancement (Alexandrov et al. 2013; Wojnicki and Godes 2008), referral behavior of innovative offerings helps consumers present themselves favorably, fulfilling their self-enhancement needs.”
From Unintended reward costs: the effectiveness of customer referral reward programs for innovative products and services (2019) · cites this paper as Alexandrov et al. 2013
In the citing paper
“They also expressed greater expected satisfaction of self-enhancement needs than participants in the less innovative condition ( M moreinnovative = 4.02; M lessinnovative = 2.96; t (55) = -2.59, p < .05) on a three-item scale from Alexandrov et al. (2013).”
From Unintended reward costs: the effectiveness of customer referral reward programs for innovative products and services (2019) · cites this paper as Alexandrov et al. (2013)
In the citing paper
“and expected greater satisfaction of self-enhancement needs ( M moreinnovative = 5.53; M lessinnovative = 4.43; t (49) = -5.74, p < .001) on a three-item scale from Alexandrov et al. (2013) than participants in the less innovative condition.”
From Unintended reward costs: the effectiveness of customer referral reward programs for innovative products and services (2019) · cites this paper as Alexandrov et al. 2013
Citations
Cites
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Exchange and Power in Social Life
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Research works printed but not linked: 3
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Cited by
Sorted by citations
Journal of the Academy of Marketing Science
Morgeson, F. V., III, Mithas, S., Keiningham, T. L., Aksoy, L., Morgeson, F. V., III, Mithas, S., & Keiningham, T. L. (2013) · Journal of the Academy of Marketing Science · doi:10.1007/11747.1552-7824 · Cited by 527
Swani, K., Milne, G. R., Brown, B. P., Assaf, A. G., & Donthu, N. (2016) · Industrial Marketing Management · doi:10.1016/j.indmarman.2016.07.006 · Cited by 345
Baker, A. M., Donthu, N., & Kumar, V. (2015) · Journal of Marketing Research · doi:10.1509/jmr.14.0099 · Cited by 327
Antecedents and outcomes of brand love: utilitarian and symbolic brand qualities
Bairrada, C. M., Coelho, F., & Coelho, A. (2018) · European Journal of Marketing · doi:10.1108/ejm-02-2016-0081 · Cited by 276
Kong, H. M., Witmaier, A., & Ko, E. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.021 · Cited by 330
Metadata
- Authors
- Alexandrov, A., Lilly, B., & Babakus, E.
- Affiliations
- University of Wisconsin–Oshkosh (US)
- University of Memphis (US)
- Corresponding author
- Alexandrov, Aliosha
- Venue
- Journal of the Academy of Marketing Science
- Published
- 2013-01-05
- Volume
- 41
- Issue
- 5
- Pages
- 531-546
- ISSN
- 0092-0703 (ISSN-L)
- 1552-7824
- OpenAlex
- W2073774300
- Cited by
- 448
- References
- 113
- Citations by year
- 2026: 27 · 2025: 44 · 2024: 39 · 2023: 42 · 2022: 40 · 2021: 49 · 2020: 39 · 2019: 41 · 2018: 32 · 2017: 33 · 2016: 19 · 2015: 31 · 2014: 10 · 2013: 1
- FWCI
- 62.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of the Academy of Marketing Science (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior in Brand Consumption and Identification
- Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
- Keywords
- word of mouth, social motives, self-enhancement, self-affirmation, social comparison, social bonding, positive word of mouth, negative word-of-mouth, social interaction, consumer motivation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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