Background: The key players in the vehicles’ recycling system are disassembling facilities, which manage flows of waste and reusable parts. The focus of the company’s business activity lies in stream of reusable parts, which is the most valuable, considering possibilities of selling (economic value) and resources saving (ecologic value). As a result of conducted research problem with demand forecasting was identified, which was affected by the specific domain of business. The major objective of the paper was to present how to support demand forecasting on parts in disassembling facility with the use of predictive markets.

Methods: The problem area related to the demand forecasting in the disassembling companies was identified based on the previously conducted research and observations. The desk-research method was used to verify current knowledge on the forecasting methodology. Taking it into account, the predictive markets method was chosen in a specific research problem.

Results: In the paper, the idea of predictive markets was presented. What is more, general procedure of its implementation and practical application in supporting decision in disassembling companies were described.

Conclusions: Predictive markets which are based on the idea of crowdsourcing, use collective crowd intelligence, supporting many business areas, including automotive industry. The predictive market method was successfully adopted in disassembling facility in order to support decisions on demand forecasting of reusable parts. The main challenge in introducing predictive markets for enterprises application is IT support and that outlines direction for future research