Economic Supply and Demand with Data Analytics Functionalities

The primary goal of this article is to start a discussion about the possibility to connect supply and demand with data analytics functionalities in the frame of a dynamic system environment. So, a number of classical supply and demand topics, concepts, and definitions, as well as state-of-the-art data analytics concepts are reviewed firstly. Then, the critical modeling problem of both concepts “supply” and “demand” using system dynamics is introduced, analyzed, and examined. Finally, supply, demand, big data and data analytics are considered in a system dynamics modeling environment.

Actually, the proposed paper provides an initial approach (introduction) to the main (basic) procedures, analytical approaches and methods of data and big data analysis. In particular, a framework to help program staff in their job and approaches on supply and demand issues using big data procedures and methods is presented. Accordingly, this article aims to support the work of data analytics and statistics staff across various content areas with big data functionalities.

This article was created because the state-of-the-art concept “using data and information in meaningful and smart ways” includes many opportunities and possibilities and obviously a great deal of information is involved. Doubtless, some of this information has a great complexity and it is highly dependent upon specialized data, information and knowledge like the “data analytics” concept. However, there are many ways of “using data in smart ways” that are more primitive and that involve relatively simple enough procedures.

Hence, the purpose of the current paper is to provide data analytics functionalities in supply and demand applications with a contemporary framework for thinking about, working with, and benefiting from an increased ability to use big data smartly and efficiently.

Finally, the current paper should be characterized as a knowledge generation opinion article which recommends the inclusion of data analytics and distributed technology in supply and demand industry in order to enhance functionalities and compatibility to state-of-the-art ICT.