Improving the crystal ball: harnessing consumer input to create retail prediction markets

Abstract

Purpose -Retail buyers' decisions result in billions of dollars of merchandise being purchased and offered for sale by retailers around the world. At present, retail buyers do not appear to be adequately harnessing consumer input to improve their forecasts. The purpose of this paper is to address this issue by introducing a new approach involving both retail buyers' consensus forecasts and those from a sample of "ordinary" consumers. Design/methodology/approach -The authors introduce a new approach to online forecasting that involves both retail buyers' consensus forecasts and those from a sample of "ordinary" consumers. Findings -The results suggest an opportunity to create what are termed retail prediction markets that offer significant potential to improve the accuracy of buyers' forecasts. Originality/value -The authors go beyond crowd sourcing technology and show how retail prediction markets may offer significant potential to improve the accuracy of retail buyers' forecasts.

Internet retailing: the past, the present and the future

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