This book focuses on the architecture of decision support systems, as well as on the main techniques of analysis and modelling, having high practical applicability in forecasting and improving the economic decision-making processes. Aspects regarding the use of modern tools such as decision support systems are therefore developed, along with various economic decision making case studies.
The book is divided into six chapters, focusing on various business problems that can be assisted by decision support systems. Chapter 1 starts with a holistic approach, by analysing the structure of a decision support system and its main components. However, as a novelty in the field, this book treats and develops special modelling and analysis techniques of a decision support system in order to solve a wide range of business problems.
In this regard, Chapter 2 is dedicated to solving business problems by using special multi-attribute decision making methods for the case when uncertainty is expressed through fuzzy or interval data. Chapter 3 presents techniques for short term forecast that can be implemented in Microsoft Excel, while the next two chapters are devoted to the use of several statistical softwares, both for macroeconomic forecast and for specific business problems of a company.
The last chapter aims to offer a practical solution to predict financial distress in Romania by focusing on developing an integrated decision support system using SPSS software and several prediction models based on decision trees, logit and hazard models, as well as neural networks.
Thus this book is addressed not only to the students of the Faculty of Cybernetics, Statistics and Economic Informatics, but also to a broad group of specialists who wish to develop their managerial skills and to make the decision making process more efficient, through the use a support system dedicated to their specific needs.