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Logistics, Supply Chain and Financial Predictive Analytics: Theory and Practice

Deep, Kusum and Jain, Madhu and Salhi, Said, eds. (2019) Logistics, Supply Chain and Financial Predictive Analytics: Theory and Practice. Asset Analytics . Springer, Singapore, Singapore, 254 pp. ISBN 978-981-1308-71-0. E-ISBN 978-981-1308-72-7. (doi:10.1007/978-981-13-0872-7) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:68430)

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Abstract

This book addresses a broad range of problems commonly encountered in the fields of

financial analysis, logistics and supply chain management, such as the use of big data analytics

in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed

in the book are co-operative/non-cooperative supply chain models for imperfect quality items

with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality

constrained portfolio problem; and determining initial, basic and feasible solutions for

transportation problems by means of the “supply demand reparation method” and “continuous

allocation method.” In addition, the book delves into a comparison study on exponential

smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed

deteriorating items varying with ramp type demand rate and shortages; an inventory model

with shortages and deterioration for three different demand rates; outlier labeling methods for

medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and

the design of a “least cost ration formulation application for cattle”; a preservation technology

model for deteriorating items with advertisement dependent demand and trade credit; a time

series model for stock price forecasting in India; and asset pricing using capital market curves.

The book offers a valuable asset for all researchers and industry practitioners working in these

areas, giving them a feel for the latest developments and encouraging them to pursue further

research in this direction.

Lifelong 40%

Item Type: Edited book
DOI/Identification number: 10.1007/978-981-13-0872-7
Uncontrolled keywords: analytics, logistics, supply chain, finance
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Central Services > Research and Innovation Services
Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Said Salhi
Date Deposited: 25 Jul 2018 15:58 UTC
Last Modified: 06 Oct 2021 11:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/68430 (The current URI for this page, for reference purposes)
Salhi, Said: https://orcid.org/0000-0002-3384-5240
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