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Retail analytics[electronic resource] :integrated forecasting and inventory management for perishable products in retailing /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	658.5
書名/作者:	Retail analytics : integrated forecasting and inventory management for perishable products in retailing // by Anna-Lena Sachs.
作者:	Sachs, Anna-Lena.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xvii, 111 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Business logistics - Management.
標題:	Retail trade - Management.
標題:	Retail trade - Forecasting.
標題:	Economics/Management Science.
標題:	Production/Logistics/Supply Chain Management.
標題:	Operation Research/Decision Theory.
標題:	Operations Research, Management Science.
標題:	Sales/Distribution/Call Center/Customer Service.
ISBN:	9783319133058 (electronic bk.)
ISBN:	9783319133041 (paper)
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-13305-8

Retail analytics[electronic resource] :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:

340937
Business logistics
--Management.

LC Class. No.: HD38.5

Dewey Class. No.: 658.5

Retail analytics[electronic resource] :integrated forecasting and inventory management for perishable products in retailing /
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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.
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