000 03569cam a22005415i 4500
001 21664309
003 OSt
005 20250925114116.0
006 m |o d |
007 cr |||||||||||
008 141210s2015 gw |||| o |||| 0|eng
010 _a 2019740855
020 _a9783319133058
024 7 _a10.1007/978-3-319-13305-8
_2doi
035 _a(DE-He213)978-3-319-13305-8
040 _aDLC
_beng
_epn
_erda
_cAIMIT LIBRARY
072 7 _aKJMV
_2bicssc
072 7 _aBUS087000
_2bisacsh
072 7 _aKJMV
_2thema
082 0 4 _a005.768
_21
_bSACA
100 1 _aSachs, Anna-Lena.
_937611
245 1 0 _aRetail analytics :
_bintegrated forecasting and inventory management for perishable products in retailing /
_cBy Anna-Lena Sachs.
250 _a1st ed.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _axvii,111p. ;
_bPB.
_c23.5 cm
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.
588 _aDescription based on publisher-supplied MARC data.
650 0 _aProduction management.
_937612
650 0 _aOperations research.
_937613
650 0 _aDecision making.
_937614
650 0 _aManagement science.
_937615
650 0 _aSales management.
_937616
650 1 4 _aOperations Management.
_0https://scigraph.springernature.com/ontologies/product-market-codes/519000
_937617
650 2 4 _aOperations Research/Decision Theory.
_0https://scigraph.springernature.com/ontologies/product-market-codes/521000
_937618
650 2 4 _aOperations Research, Management Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M26024
_937619
650 2 4 _aSales/Distribution.
_0https://scigraph.springernature.com/ontologies/product-market-codes/524000
_937620
776 0 8 _iPrinted edition:
_z9783319133065
776 0 8 _iPrinted edition:
_z9783319133041
776 0 8 _iPrinted edition:
_z9783030212650
830 0 _aLecture Notes in Economics and Mathematical Systems,
_x0075-8442 ;
_v680
_937621
942 _2ddc
_cBK
_e1st
_k005.768 SACA
999 _c222969
_d222969