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005 20151013141916.0
007 cr nn 008mamaa
008 141210s2015 gw | s |||| 0|eng d
020 _a9783319133058
_9978-3-319-13305-8
024 7 _a10.1007/978-3-319-13305-8
_2doi
050 4 _aHD28-70
072 7 _aKJMV5
_2bicssc
072 7 _aKJMV8
_2bicssc
072 7 _aBUS087000
_2bisacsh
082 0 4 _a658.5
_223
100 1 _aSachs, Anna-Lena.
_eauthor.
245 1 0 _aRetail Analytics
_h[electronic resource] :
_bIntegrated Forecasting and Inventory Management for Perishable Products in Retailing /
_cby Anna-Lena Sachs.
260 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXVII, 111 p. 14 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Economics and Mathematical Systems,
_x0075-8442 ;
_v680
505 0 _aIntroduction -- 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 _aThis 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 _aEconomics.
650 0 _aOperations research.
650 1 4 _aEconomics/Management Science.
650 2 4 _aProduction/Logistics/Supply Chain Management.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aSales/Distribution/Call Center/Customer Service.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319133041
830 0 _aLecture Notes in Economics and Mathematical Systems,
_x0075-8442 ;
_v680
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-13305-8
912 _aZDB-2-SBE
942 _2ddc
_cEBOOK
999 _c3182
_d3182