Retail Operations

We analyze empirical data and develop models to enhance the performance of retailers. Our models assist in making informed decisions on various aspects such as inventory management, food waste reduction, efficient store replenishment, assortment planning, returns planning, demand forecasting, managing promotions, store layout, product pricing, and staff planning.

We work closely with companies such as Jumbo Supermarkten, Ahold Delhaize, Plus Retail, Spar, Lidl, Coolblue, Bol, Mediamarkt, DAF,  and international retailers who are member of the ECR Retail Loss group.  

The research can be divided in three themes:

  1. Food waste reduction
  2. Revenue management and pricing
  3. Inventory management and ordering behavior

Some of our research projects

Food waste reduction

Food waste is a significant  global issue leading to the wastage of large amounts of food, water, energy and CO2 before it even reaches the final consumer. Recognizing this problem, many governments, institutions and industries are now designing new legislation and implementing innovative ways to tackle it.. Scientists around the globe are also intensifying their efforts to help alleviate this issue.

Ourresearch contributes to addressing food waste by developing innovative replenishment logic for perishable items, which considers the full age-information of the inventory. Additionally, we derive formulas that express the key performance indicators such as  On Shelf Availability, percentage of waste and the number of order lines in terms of  relevant input parameters like average daily demand, shelf life and case pack-size. Recent research aims to quantify the percentage of customers who do not pick the oldest product on the shelf (grabbing behavior) .

Revenue management and pricing

Our research on revenue management focusses on two main areas. The first area involves  using price discounts to boost sales for perishable food items which nearing  their expiration date. In this context, we aim to find the optimal  discounting policy in a stochastic environment. The second area examines revenue management decisions in a broader context. For instance, we collaborate  with fashion retailers to analyze the impact of their strategic decisions,such as omni-channel offerings, on consumer purchasing and return behaviors, and how these  decisions affects profitability. Additionally, we  utilize clickstream data from firms鈥� e-commerce platforms, enabling optimized pricing and promotion decisions.

Inventory management and ordering behavior

To support the trade-off between On Shelf Availability and inventory holding costs for non-perishable items, we have developed models and software tools. These tools assist decision makers in determining the optimal timing and quantity of replenishment orders. Our models and tools are available for free and include basic models for single-product, single-location problems, as well as  more advanced models for multi-product scenarios with space, budget or capacity constraints. Additionally, we  study  ordering behavior to  better understand why humans may deviate from the advice given by automated store ordering systems.

More information:

For more information, please feel free to reach out to Karel van Donselaar