Referrals · Three longitudinal quasi-experimental field studies

Online Social Interactions: A Natural Experiment on Word of Mouth versus Observational Learning

Journal of Marketing Research · 2011

Yubo Chen, Qi Wang, Jinhong Xie

Summary

Negative word of mouth was more influential than positive word of mouth.

For your marketing

Possible founder application

Separates testimonial sentiment from visible adoption signals such as customer counts or use cases. Test which form of social proof helps which buyer rather than treating them as interchangeable.

Reported result

What the study found

Negative word of mouth was more influential than positive word of mouth. Positive purchase-statistic information raised sales, while negative purchase-statistic information had no effect; observational-learning effects increased with review volume.

Research question

What the authors investigated

How do consumer opinions (word of mouth) and visible purchase behavior (observational learning) separately affect product sales?

Design

Three longitudinal quasi-experimental studies using policy shifts at Amazon.com as a natural experimental setting.

Sample and setting

Products and sales on Amazon.com; specific sample sizes are not listed in the abstract.

Scope and transfer

Limitations to keep in view

The abstract omits sample and identification details; the evidence relies on one retailer and product marketplace. Purchase statistics may operate differently in considered B2B software buying.

Research sources

SAGE publisher abstract retrieved with Firecrawl; full text not inspected.

Study strength

3.5/5 Useful evidence with meaningful caveats

How this was assessed

The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.

Design · 1.6/2

A quasi-experimental design can support causal claims if its assumptions hold.

Sample · 0.4/1

A usable sample size is not stated in the profile's accessible source.

Comparison · 0.8/1

Nonrandom comparison; causal interpretation depends on the design assumptions.

Can we check it? · 0.5/1

This profile could be checked against an abstract or metadata, not the full paper.

Double-blind? Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used.