Defensive financial decisions support for retailers in Greek pharmaceutical industry

Georgios Marinakos (), Sophia Daskalaki () and Theodoros Ntrinias ()

Central European Journal of Operations Research, 2014, vol. 22, issue 3, 525-551

Abstract: In this paper, we present a decisions support solution designed for Greek pharmacies comprising a cash flow management system for early warning of financial distress and a financial advisor based on a neural network. The cash flow monitoring system integrates accounting elements with real time transactions and a predictive linear regression model while the decision support module is developed with the help of a neural network. For any given business unit the system associates accounting entries with information about credit times to reflect the precise instants of cash flows and using inflows/outflows equations monthly, eventually build its liquidity curve and cash flow balance over time. Alongside, a linear regression module is introduced to estimate future cash reserves based on past profitability ratios. Lastly, combining the power of artificial neural networks with expertise in this sector of pharmaceutical business, the financial decision support tool focuses on the retailers that face financial difficulties and suggests alternative solutions for escaping from distress and insolvency. The model has an ambitious and useful purpose, to inform and consult the owners of the business units and other members of the pharmaceutical chain, thus reduce financial risk for the chain. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Financial performance monitoring; Profitability and liquidity; Cash flow management; Decision support systems; Neural networks (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10100-013-0325-4

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