Decision support system modelling in perishable product industry
Research reports on the benefits of information systems in the perishable goods industry are few in number. The potential for effective information management in better control, supply, storage and distribution, and to reduce wastage, appears to be huge. The purpose of this research is to intervene in a perishable goods supply chain by implementing an OLAP cube for managerial data extraction and decision-making. In this research, we explore the DSS technology and its value for perishable product. The value of information is measured as CSFs improvement within the business operation. A principal objective is to understand the determinants for the value of information and the operating conditions that give rise to these determinants. Another related and important question is how other factors facilities in perishable product industry when DSS is used. I address the value of information in the context of single echelon and multiple echelon system. We going to measure the significance of DSS impact on CSFs I identified later in the studies. Research methodology includes quantitative research, the results are extensive and show the DSS impact on several CSFs. The most significant CSFs are sales, delivery, product lifetime, level of demand uncertainty, wastage level as product outdates. Whenever these factor levels are high, the value of DSS is high. My results show that facilities may not benefit equally from shared information of DSS.