# Literature verification notes

Verification date: 2026-08-14.

Primary / publisher-indexed sources checked.

1. Bass (1969), A New Product Growth for Model Consumer Durables, Management Science 15(5):215-227. DOI 10.1287/mnsc.15.5.215.
2. Dodson & Muller (1978), Models of New Product Diffusion Through Advertising and Word-of-Mouth, Management Science 24(15):1568-1578. DOI 10.1287/mnsc.24.15.1568.
3. Easingwood, Mahajan & Muller (1983), A Nonuniform Influence Innovation Diffusion Model of New Product Acceptance, Marketing Science 2(3):273-295. DOI 10.1287/mksc.2.3.273.
4. Godes & Mayzlin (2004), Using Online Conversations to Study Word-of-Mouth Communication, Marketing Science 23(4):545-560. DOI 10.1287/mksc.1040.0071.
5. Chevalier & Mayzlin (2006), The Effect of Word of Mouth on Sales: Online Book Reviews, Journal of Marketing Research 43(3):345-354. DOI 10.1509/jmkr.43.3.345.
6. Duan, Gu & Whinston (2008), The Dynamics of Online Word-of-Mouth and Product Sales—An Empirical Investigation of the Movie Industry, Journal of Retailing 84(2):233-242.
7. Chintagunta, Gopinath & Venkataraman (2010), The Effects of Online User Reviews on Movie Box Office Performance, Marketing Science 29(5):944-957. DOI 10.1287/mksc.1100.0572.
8. You, Vadakkepatt & Joshi (2015), A Meta-Analysis of Electronic Word-of-Mouth Elasticity, Journal of Marketing 79(2):19-39. DOI 10.1509/jm.14.0169.
9. Babić Rosario et al. (2016), The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors, Journal of Marketing Research 53(3). DOI 10.1509/jmr.14.0380.
10. Wang et al. (2019), Production of Online Word-of-Mouth: Peer Effects and the Moderation of User Characteristics, Production and Operations Management 28(7). DOI 10.1111/poms.13007.
11. Lei et al. (2022), Swayed by the Reviews: Disentangling the Effects of Average Ratings and Individual Reviews in Online Word-of-Mouth, Production and Operations Management 31(6). DOI 10.1111/poms.13695.
12. Yu et al. (2023), Online Reviews, Customer Q&As, and Product Sales: A PVAR Approach, PLOS ONE 18(11):e0290674. DOI 10.1371/journal.pone.0290674.
13. Karaman (2025), The Asymmetric Effects of Posting an Online Review on Future Spending and the Dark Side of Solicitations, Management Science. DOI 10.1287/mnsc.2023.01951.

Boundary notes:
- Review Propensity Field, Review Multiplier Surface, Review–Adoption Non-Identifiability Theorem, Proxy Transportability, Popularity–Sales Gap, AMNESS-WAD, and related diagnostic constructs are proposed in this paper.
- The No Universal Review Multiplier Theorem is a direct structural result under E[R]=rho*A.
- Review-to-sales empirical effects are not claimed to have one universal sign or magnitude; meta-analytic literature explicitly reports heterogeneity by platform, product, and metric.
- Reviews may be both causes and outcomes of sales/adoption; dynamic simultaneity is therefore a central modeling assumption, not a fixed one-way causal claim.