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Retail analytics = integrated foreca...

Sachs, Anna-Lena.

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Retail analytics = integrated forecasting and inventory management for perishable products in retailing /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Retail analytics/ by Anna-Lena Sachs.
Reminder of title:	integrated forecasting and inventory management for perishable products in retailing /
Author:	Sachs, Anna-Lena.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xvii, 111 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Literature Review -- Safety Stock Planning under Causal Demand Forecasting -- The Data-Driven Newsvendor with Censored Demand Observations -- Data-Driven Order Policies with Censored Demand and Substitution -- Empirical Newsvendor Decisions under a Service Contract -- Conclusions.
Contained By:	Springer eBooks
Subject:	Business logistics - Management. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-13305-8
ISBN:	9783319133058 (electronic bk.)

Retail analytics = integrated forecasting and inventory management for perishable products in retailing /
Sachs, Anna-Lena.

Retail analyticsintegrated forecasting and inventory management for perishable products in retailing /[electronic resource] :by Anna-Lena Sachs. - Cham :Springer International Publishing :2015. - xvii, 111 p. :ill., digital ;24 cm. - Lecture notes in economics and mathematical systems,6800075-8442 ;. - Lecture notes in economics and mathematical systems ;655..

Introduction -- Literature Review -- Safety Stock Planning under Causal Demand Forecasting -- The Data-Driven Newsvendor with Censored Demand Observations -- Data-Driven Order Policies with Censored Demand and Substitution -- Empirical Newsvendor Decisions under a Service Contract -- Conclusions.

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.

ISBN: 9783319133058 (electronic bk.)

Standard No.: 10.1007/978-3-319-13305-8doiSubjects--Topical Terms:

756850
Business logistics
--Management.

LC Class. No.: HD38.5

Dewey Class. No.: 658.5

Retail analytics = integrated forecasting and inventory management for perishable products in retailing /
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245 1 0 $a Retail analytics $h [electronic resource] : $b integrated forecasting and inventory management for perishable products in retailing / $c by Anna-Lena Sachs.
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300 $a xvii, 111 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in economics and mathematical systems, $x 0075-8442 ; $v 680
505 0 $a Introduction -- Literature Review -- Safety Stock Planning under Causal Demand Forecasting -- The Data-Driven Newsvendor with Censored Demand Observations -- Data-Driven Order Policies with Censored Demand and Substitution -- Empirical Newsvendor Decisions under a Service Contract -- Conclusions.
520 $a 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.
650 0 $a Business logistics $x Management. $3 756850
650 0 $a Retail trade $x Management. $3 668906
650 0 $a Retail trade $x Forecasting. $3 2133294
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650 2 4 $a Operation Research/Decision Theory. $3 1620900
650 2 4 $a Operations Research, Management Science. $3 1532996
650 2 4 $a Sales/Distribution/Call Center/Customer Service. $3 1620159
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