Data Mining and Soft Computing in Business Model for Decision Support System

Abstract

Several studies were taken to effectively determine the importance of data mining in business model development for decision support system. It was later discovered that most businesses have invested heavily in the data mining process which enables them to easily study and analyse the market environment and improve their domination in the market. Data mining is a process used by most firms to effectively collect information about certain topic. One factor that business model development usually focuses more on is the value of measurable performance and increased innovation in the market. The aim of the current research is to investigate the values and key roles played by data mining prospects in the business model development. It also revolves around current techniques used within business model development that are crucial in enhancing the position and competitiveness of a firm in the market. Although the data mining prowess varies in regards to the firm and effort used, the main concept remains on how to fully have the firm understand the effects and role played by data mining techniques in their overall business flow. In methodology, secondary sources are categorically used to enhance the overall flow of the study question by comparing them and analyzing them using the techniques provided. The results and analysis reveal that the effects of using data mining techniques are huge towards achieving success for various businesses. Moreover, the practical implications have categorically increased the notion of how influential the prospects of data mining can be when applied in businesses.

Inventory Optimization Using an AI-Powered Holistic Model for Decision-Support System

“…The results and analysis demonstrate that the impact of utilizing data mining techniques is significant in obtaining success for different firms. Furthermore, the practical consequences have significantly enhanced the understanding of the impact data mining can have on enterprises [35]. Peng 2022 et.…”