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Information elicitation for aggregate demand prediction with costly forecasting

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Abstract

This paper presents a multiple newsvendor-type purchasing problem where demand forecasts of a number of individual consumer agents can be generated at a price. Firstly, we derive the optimal solution for the model. Next, an information elicitation mechanism is presented that results in the optimal solution despite the autonomous, self-interested participants and the information asymmetry in between consumers and the supplier. Specifically, the incentive compatibility, efficiency, individual rationality and budget balance properties of the mechanism are proved and also illustrated by several numerical experiments.

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Notes

  1. Note that in contrast to the usual notation, for convenience, we minimize the score.

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Acknowledgments

This work has been supported by the Hungarian Scientific Research Fund (OTKA), Grant No. 113038, by the European Union 7th Framework Programme Project No. NMP 2013-609087, Shock-robust Design of Plants and their Supply Chain Networks (RobustPlaNet), and by the János Bolyai Scholarship No. BO/00659/11/6. The author would like to thank József Váncza for his help and support during the research and to the anonymous reviewers for their valuable remarks.

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Authors and Affiliations

  1. Fraunhofer Project Center for Production Management and Informatics, Institute for Computer Science and Control, Hungarian Academy of Sciences, Kende u. 13-17, Budapest, 1111, Hungary

    Péter Egri

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  1. Péter Egri
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Correspondence to Péter Egri.

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Egri, P. Information elicitation for aggregate demand prediction with costly forecasting. Auton Agent Multi-Agent Syst 30, 681–696 (2016). https://doi.org/10.1007/s10458-015-9301-9

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