The DOI matches its Crossref record.
Modeling Multinational Diffusion Patterns: An Efficient Methodology
Abstract
The objective of this study is to develop an econometric model for the diffusion of innovations at the individual country level, but which also allows the parameters of the process to differ systematically across countries. The conceptualization rests on behavioral and spatial theories of diffusion and extends the domain to international markets. The cross-national model of innovation diffusion which is developed highlights substantive differences and similarities among international markets. It also provides estimates for the diffusion parameters, even for countries where sales data are not available, thereby yielding some insights into the nature of the expected diffusion pattern in these countries prior to market entry.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Steenkamp, J.-B. E. M., ter Hofstede, F., & Wedel, M. (1999) · Journal of Marketing · doi:10.2307/1251945 · Cited by 1,282
Social contagion and income heterogeneity in new product diffusion: A meta-analytic test
Van den Bulte, C., & Stremersch, S. (2004) · Marketing Science · doi:10.1287/mksc.1040.0054 · Cited by 434
Disruptiveness of innovations: measurement and an assessment of reliability and validity
Govindarajan, V., & Kopalle, P. K. (2006) · Strategic Management Journal · doi:10.1002/smj.511 · Cited by 410
Cross-National Analysis of Diffusion of Consumer Durable Goods in Pacific Rim Countries
Takada, H., & Jain, D. (1991) · Journal of Marketing · doi:10.1177/002224299105500206 · Cited by 391
Does culture explain acceptance of new products in a country?: An empirical investigation
Yeniyurt, S., & Townsend, J. D. (2003) · International Marketing Review · doi:10.1108/02651330310485153 · Cited by 302
Hechavarría, D. M., Terjesen, S. A., Ingram, A. E., Renko, M., Justo, R., & Elam, A. (2017) · Small Business Economics · doi:10.1007/s11187-016-9747-4 · Cited by 268
How cultural differences in uncertainty avoidance affect product perceptions
Anne Lee, J., Garbarino, E., & Lerman, D. (2007) · International Marketing Review · doi:10.1108/02651330710755320 · Cited by 100
Using Survey Data to Predict Adoption and Switching for Services
Weerahandi, S., & Moitra, S. (1995) · Journal of Marketing Research · doi:10.1177/002224379503200110 · Cited by 29
Metadata
- Authors
- Gatignon, H., Eliashberg, J., & Robertson, T. S.
- Venue
- Marketing Science
- Published
- 1989-08
- Volume
- 8
- Issue
- 3
- Pages
- 231-247
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W1982329432
- Cited by
- 325
- References
- 0
- FWCI
- 5.34
- Type
- journal article
- Language
- en
- Open access
- closed
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.
