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Titlebook: Retail Analytics; Integrated Forecasti Anna-Lena Sachs Book 2015 Springer International Publishing Switzerland 2015 Behavioral operations m

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發(fā)表于 2025-3-21 20:03:14 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Retail Analytics
副標(biāo)題Integrated Forecasti
編輯Anna-Lena Sachs
視頻videohttp://file.papertrans.cn/829/828918/828918.mp4
概述Presents a data driven approach that integrates demand forecasting and inventory management.Presents an optimal inventory policy for a multi-product newsvendor setting with an aggregated service level
叢書(shū)名稱(chēng)Lecture Notes in Economics and Mathematical Systems
圖書(shū)封面Titlebook: Retail Analytics; Integrated Forecasti Anna-Lena Sachs Book 2015 Springer International Publishing Switzerland 2015 Behavioral operations m
描述.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 forbakery products..
出版日期Book 2015
關(guān)鍵詞Behavioral operations management; Inventory management; Retail; Substitution; Unobservable lost sales
版次1
doihttps://doi.org/10.1007/978-3-319-13305-8
isbn_softcover978-3-319-13304-1
isbn_ebook978-3-319-13305-8Series ISSN 0075-8442 Series E-ISSN 2196-9957
issn_series 0075-8442
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

書(shū)目名稱(chēng)Retail Analytics影響因子(影響力)




書(shū)目名稱(chēng)Retail Analytics影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Retail Analytics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Retail Analytics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Retail Analytics被引頻次




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書(shū)目名稱(chēng)Retail Analytics讀者反饋




書(shū)目名稱(chēng)Retail Analytics讀者反饋學(xué)科排名




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沙發(fā)
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Literature Review,In the following we will review literature on unobservable lost sales estimation, assortment planning and behavioral operations management.
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https://doi.org/10.1007/978-3-319-13305-8Behavioral operations management; Inventory management; Retail; Substitution; Unobservable lost sales
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發(fā)表于 2025-3-23 00:18:27 | 只看該作者
Introduction,ck of supply chain coordination which leads to expired excess inventories (Gustavsson et al. 2011). A study by the United States Department of Agriculture found that 11.4?% fresh fruit, 9.7?% fresh vegetables, and 4.5?% fresh meat and seafood are wasted annually (Buzby et al. .). In Germany, 11 mill
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發(fā)表于 2025-3-23 02:52:36 | 只看該作者
Safety Stock Planning Under Causal Demand Forecasting,al data. A time series based framework uses a forecast (and a measure of forecast error) to parameterize the demand model. However, demand might depend on many other factors rather than just time and demand history. Inspired by a retail inventory management application where customer demand, among o
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發(fā)表于 2025-3-23 06:19:41 | 只看該作者
The Data-Driven Newsvendor with Censored Demand Observations,ch based on a data-driven approach. For this purpose, we extend the model introduced in Chap. 3 To improve the forecast accuracy, we simultaneously estimate unobservable lost sales, determine the coefficients of the exogenous variables which drive demand, and calculate the optimal order quantity. Si
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