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Retail Analytics

Integrated Forecasting and Inventory Management for Perishable Products in Retailing

  • Anna-Lena¬†Sachs

Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 680)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Anna-Lena Sachs
    Pages 1-4
  3. Anna-Lena Sachs
    Pages 5-12
  4. Anna-Lena Sachs
    Pages 103-105
  5. Back Matter
    Pages 107-111

About this book

Introduction

This book addresses the challenging task of demand forecasting and inventory management in retailing. It analyzes how information from point-of-sale scanner systems can be used to improve inventory decisions, and develops a data-driven approach that integrates demand forecasting and inventory management for perishable products, while taking unobservable lost sales and substitution into account in out-of-stock situations. Using linear programming, a new inventory function that reflects the causal relationship between demand and external factors such as price and weather is proposed. The book subsequently demonstrates the benefits of this new approach in numerical studies that utilize real data collected at a large European retail chain. Furthermore, the book derives an optimal inventory policy for a multi-product setting in which the decision-maker faces an aggregated service level target, and analyzes whether the decision-maker is subject to behavioral biases based on real data for bakery products.

Keywords

Behavioral operations management Inventory management Retail Substitution Unobservable lost sales

Authors and affiliations

  • Anna-Lena¬†Sachs
    • 1
  1. 1.Department of Supply Chain Management & Management ScienceUniversity of CologneCologneGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-13305-8
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Business and Economics
  • Print ISBN 978-3-319-13304-1
  • Online ISBN 978-3-319-13305-8
  • Series Print ISSN 0075-8442
  • Series Online ISSN 2196-9957
  • Buy this book on publisher's site
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