Prediction markets as a decision support tool in disassembling companies

Abstract

Disassembling companies are key participants in recycling networks which manage flows of waste and spare parts. However, due to the large number of dismantled parts and limited storage area, corresponding to the law requirements, it is necessary to anticipate the demand for the most sold parts. The high importance level of spare parts flow is a consequence of high economic potential as well as ecologic. Used spare parts are main source of revenues for disassembling companies, they are wanted by customers, and what is the most relevant – the utilization of used spare parts is the best scenario for products, which achieved end – of – life stage (vehicle). Disassembling companies mostly represents small and medium sized companies, what is related with low level of computerization, at each area of business activity, including recording parts selling and demand forecasting. In order to support decisions made at this area, it was prepared a concept of a tool based on the research method of predictive markets to anticipate the demand for used parts in dismantling facility. Predictive markets are based on the idea of crowdsourcing, using collective crowd intelligence to predict for example introduction of new medicines on the market, the directions of development of new technologies or competition activities. In the paper it was presented original approach to the demand forecasting in specific business which core flow is a reverse flow of waste.