Retail Analytics: Integrated Forecasting and Inventory Management for Perishable Products in Retailing

Download Retail Analytics: Integrated Forecasting and Inventory Management for Perishable Products in Retailing written by Anna Lena-Sachs in PDF format. This book is under the category Business and bearing the isbn/isbn13 number 3319133047/9783319133041. You may reffer the table below for additional details of the book.


SKU: 818de4d2ec21 Category: Tag:



Anna Lena-Sachs






132 pages









Book Description

The difficult tasks of demand forecasting and inventory management for perishable products in retailing are tackled in this downloadable ebook titled Retail Analytics: Integrated Forecasting and Inventory Management for Perishable Products in Retailing (PDF). It examines the ways in which data obtained from point-of-sale (PoS) scanner systems can be used to enhance inventory management decisions and develops a data-driven strategy that integrates demand forecasting and inventory management for perishable products. This strategy also takes into account unobservable lost sales and substitution when there is a shortage of a particular item. Following that, the e-book presents numerical studies that make use of actual data gathered at a major European retail chain in order to demonstrate the benefits of the new method. A new inventory function that represents the causal relationship between demand and external factors such as price and weather is developed using linear programming. These factors include the price of goods and the weather. In addition, the ebook determines an optimal inventory policy for a multi-product setting in which the decision-maker is confronted with an aggregated service level target. Additionally, the ebook investigates whether or not the decision-maker is susceptible to behavioral biases based on actual data for bakery products.

Table of contents

Table of contents :
Front Matter….Pages i-xvii
Introduction….Pages 1-4
Literature Review….Pages 5-12
Safety Stock Planning Under Causal Demand Forecasting….Pages 13-33
The Data-Driven Newsvendor with Censored Demand Observations….Pages 35-56
Data-Driven Order Policies with Censored Demand and Substitution in Retailing….Pages 57-78
Empirical Newsvendor Decisions Under a Service Level Contract….Pages 79-101
Conclusions….Pages 103-105
Back Matter….Pages 107-111

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