Fixing Phantom Stockouts: Optimal Data-Driven Shelf Inspection Policies

@inproceedings{Chen2014FixingPS,
  title={Fixing Phantom Stockouts: Optimal Data-Driven Shelf Inspection Policies},
  author={Li Chen},
  year={2014}
}
  • Li Chen
  • Published 3 August 2014
  • Business
A "phantom stockout" is a retail stockout phenomenon caused either by inventory shrinkage or by shelf execution failure. Unlike the conventional stockout which can be corrected by inventory replenishment, a phantom stockout persists and requires human interventions. In this paper, we propose two partially-observable Markov decision models: one for the shrinkage problem and the other for the shelf execution failure problem. In the shrinkage model, the actual inventory level is not known unless… 

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References

SHOWING 1-10 OF 41 REFERENCES

Inspection and Replenishment Policies for Systems with Inventory Record Inaccuracy

It is proved that an inspection adjusted base-stock (IABS) policy is optimal for the single-period problem and in the finite-horizon problem, and it is shown that CCABS is almost as effective as the IABS policy.

Information-Sensitive Replenishment when Inventory Records Are Inaccurate

A periodic review inventory system with imperfect inventory records and unobserved lost sales is considered, and it is found that the myopic heuristic is likely sufficiently good in practical settings targeting high service levels.

Partially Observed Inventory Systems: The Case of Rain Checks

The methodology of the unnormalized probability is used to establish the existence of an optimal feedback policy when the periodic cost has linear growth and uniqueness and continuity of the solution to dynamic programming equations are proved when the discount factor is sufficiently small.

Inventory Systems with Imperfect Asset Information

An inventory stock record is in error when the stock record is not in agreement with the physical stock. Such discrepancies may be introduced due to time lags between flow of information and

Partially Observed Inventory Systems: The Case of Zero-Balance Walk

This work studies a partially observed inventory system where the demand is not observed, inventory level is noticed when it reaches zero, the unmet demand is lost, and replenishment orders must be decided so as to minimize the total discounted costs over an infinite horizon.

Information inaccuracy in inventory systems: stock loss and stockout

Analytical and simulation modelling demonstrate that even a small rate of stock loss undetected by the information system can lead to inventory inaccuracy that disrupts the replenishment process and creates severe out-of-stock situations.

If the Inventory Manager Knew: Value of Visibility and RFID under Imperfect Inventory Information

Today many companies rely on computerized tracking of inventory. Although computerized inventory tracking is generally assumed to be accurate, in reality, actual on-hand inventory deviates from the

The Role of Execution in Managing Product Availability

The drivers of inventory record inaccuracy and misplaced products are described, the need for additional empirical research is identified, and analytical approaches that could benefit from the incorporation of execution problems are noted.

Execution: The Missing Link in Retail Operations

In spite of making substantial investments in information technology planning systems, retailers are struggling with two execution problems—" inventory record inaccuracy" and "misplaced stock keeping