EURO 2024 Copenhagen
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3780. The Analytical Edge in Circular Economy: Predictive Analytics for Reusable Packaging Success

Invited abstract in session TA-50: Retail Analytics, stream Retail Operations.

Tuesday, 8:30-10:00
Room: M2 (building: 101)

Authors (first author is the speaker)

1. Alexander Niclas Popovic
Chair of Production Management, WHU - Otto Beisheim School of Management
2. Arnd Huchzermeier
Production Management, WHU - Otto Beisheim School of Management

Abstract

Driven by environmental pollution concerns and legislative pressure, an increasing number of Industry 5.0 initiatives and impact startups have recently emerged, focusing on establishing circular economy business models. One emerging industry is combating plastic waste through innovative reusable packaging systems.

In this study, we examine the case of the German startup Vytal, which offers a deposit-free reusable packaging system for take-out food, utilizing serialized containers. We develop a forecasting framework to estimate the distribution of net demand, consisting of container issues and returns. Accurate net demand forecasts are critical for optimizing asset utilization and inventory management of reusables. We propose a forecasting framework based on a pool of distributed lag models for estimating container issues and returns. Each model exploits the relationship between container issues and returns to make accurate predictions, and we combine them into an "optimal" model using an adaptive Markov Chain Monte Carlo algorithm. Furthermore, we examine several extensions of our basic model and analyze the benefits of including additional covariates, as well as leveraging cross-location forecasts into our model.

We use a unique dataset from Vytal to demonstrate that our proposed forecasting framework outperforms existing models and algorithms from both the literature and our case company in terms of forecast accuracy and computational inference efficiency.

Keywords

Status: accepted

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