What the study found
The study finds that a retailer’s best data analytics strategy changes with the supplier’s encroachment cost, which is the cost a supplier faces when moving into the retailer’s market. Under a shared data platform, the retailer may use perfectly accurate analytics at very high or very low encroachment costs, while moderate costs can lead to informative but biased forecasts.
Why the authors say this matters
The authors conclude that their findings offer practical guidance for retailers using learning algorithms and for choosing how to organize data governance in vertical distribution channels. The study suggests there is a nonmonotonic relationship between analytics accuracy and suppliers’ encroachment efficiency, and it highlights the potential benefits of transparent, integrated data analytics.
What the researchers tested
The researchers studied the problem using a Bayesian persuasion framework, in which the retailer’s analytics strategy is treated as a signaling rule that maps market states into predictions with partial informational granularity. They compared two data governance structures: a shared data platform that gives the same demand predictions to both retailer and supplier, and a separate data platform that gives the retailer more accurate predictions than the supplier.
What worked and what didn't
On a shared data platform, perfectly accurate analytics are adopted when the supplier’s encroachment cost is very high or very low. At moderate encroachment costs, the shared platform produces informative but biased forecasts, and the abstract says these can benefit both firms because of the ease of double marginalization; under a separate platform, no informative predictions are generated for the supplier at moderate costs.
What to keep in mind
The summary provides theoretical results from a Bayesian persuasion model, so the findings are framed within that specific setup. The abstract does not describe empirical testing, and it does not give additional limitations beyond the model comparison.
Key points
- The retailer’s data analytics strategy changes with the supplier’s encroachment cost.
- A shared data platform can produce informative yet biased forecasts at moderate encroachment costs.
- The study says these biased forecasts may benefit both firms because of double marginalization.
- Under a separate platform, the supplier receives no informative predictions at moderate encroachment costs.
- The retailer prefers a shared platform when the supplier’s encroachment cost is relatively high.
Disclosure
- Research title:
- Retailer data analytics choices depend on supplier encroachment cost
- Authors:
- Yonghui Chen, Guangrui Ma, Qiao‐Chu He, Ying-Ju Chen, Zuo-Jun Max Shen
- Institutions:
- Applied Optimization (United States), Hong Kong University of Science and Technology, Hong Kong University of Science and Technology, Southern University of Science and Technology, University of Hong Kong, University of Hong Kong, University of Hong Kong, University of Liverpool, University of Liverpool
- Publication date:
- 2026-02-26
- OpenAlex record:
- View
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