Customer behavior and adoption · Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus s
How Users Drive Value in Two-Sided Markets: Platform Designs That Matter
Zhou Zhou, Lingling Zhang, Marshall Van Alstyne (2024). How Users Drive Value in Two-Sided Markets: Platform Designs That Matter. MIS Quarterly. https://doi.org/10.25300/MISQ/2023/17012.
Plain-English take
Cross-period same-side network effects contribute to user stickiness, while within-period cross-side effects persist conditional on stickiness. Using Groupon data, the authors verify the model and identify platform-design choices that can enhance stickiness when cross-period same-side effects are weak. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
How much weight to give this
3.5/5 Moderate evidence for a specific setting
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.
Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus search goods.
Groupon's largest 108 markets from January through December 2012, with LivingSocial used to control for competition; the publisher page also reports a category-classification survey of 818 respondents covering 78 categories.
Based on the publisher-described design and comparison; see the article for complete analysis.
Publisher record was fetched directly; full text was not assumed open.
Double-blind? Blinding was not established from the retrieved publisher record.
Research question
What the authors investigated
When is a user-growth strategy effective, and how do users drive value in a two-sided market?
Design
Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus search goods.
Sample and setting
Groupon's largest 108 markets from January through December 2012, with LivingSocial used to control for competition; the publisher page also reports a category-classification survey of 818 respondents covering 78 categories.
Reported result
What the study found
Cross-period same-side network effects contribute to user stickiness, while within-period cross-side effects persist conditional on stickiness. Using Groupon data, the authors verify the model and identify platform-design choices that can enhance stickiness when cross-period same-side effects are weak.
This is a paraphrase of the source. Check the original paper for definitions, estimates, statistical uncertainty and analysis details.
Scope and transfer
Limitations to keep in view
Not stated on the fetched publisher article page; the page reports robustness analyses but does not present a limitations statement in the visible article text.
Possible founder application
Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Evidence access
Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
The publisher article states that fast user growth does not necessarily imply user stickiness, develops a dynamic network-effects/CLV2 model, and says: 'Using Groupon data, we verify our insights.' Its empirical-setting section specifies 108 Groupon markets observed from January to December 2012 and the page reports an 818-respondent survey for category classification. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.
If only an abstract or metadata was available, the profile is limited to claims supported there. A paper's paywall does not change its evidentiary status, but it limits what we can substantiate from accessible text.