Designing Incentive Systems for Truthful Forecast Information Sharing Within a Firm
We consider a firm where the sales division ( Sales ) is responsible for demand forecasting and the operations division ( Operations ) is responsible for ordering. Sales has better information about the demand than Operations and sends a nonbinding demand forecast to Operations . To incentivize trut...
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Published in | Management science Vol. 64; no. 8; pp. 3690 - 3713 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Linthicum
INFORMS
01.08.2018
Institute for Operations Research and the Management Sciences |
Subjects | |
Online Access | Get full text |
ISSN | 0025-1909 1526-5501 |
DOI | 10.1287/mnsc.2017.2805 |
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Abstract | We consider a firm where the sales division (
Sales
) is responsible for demand forecasting and the operations division (
Operations
) is responsible for ordering.
Sales
has better information about the demand than
Operations
and sends a nonbinding demand forecast to
Operations
. To incentivize truthful information sharing, we include a forecast error penalty in the incentive system of
Sales
. Besides monetary payoffs, we also add behavioral factors to the utility function of
Sales
. We model the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe human behavior that is in line with the predictions of the behavioral model but deviates substantially from expected-payoff-maximizing behavior. We use the behavioral model to design incentive systems for truthful information sharing and validate the approach in an experiment with out-of-sample treatments and out-of-sample subjects. We conduct additional experiments to provide further robustness to the results.
The experimental data and e-companion are available at
https://doi.org/10.1287/mnsc.2017.2805
.
This paper was accepted by Martin Lariviere, operations management. |
---|---|
AbstractList | We consider a firm where the sales division (SALES) is responsible for demand forecasting and the operations division (OPERATIONS) is responsible for ordering. Sales has better information about the demand than Operations and sends a nonbinding demand forecast to OPERATIONS. To incentivize truthful information sharing, we include a forecast error penalty in the incentive system of SALES. Besides monetary payoffs, we also add behavioral factors to the utility function of SALES. We model the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe human behavior that is in line with the predictions of the behavioral model but deviates substantially from expected-payoff-maximizing behavior. We use the behavioral model to design incentive systems for truthful information sharing and validate the approach in an experiment with out-of-sample treatments and out-of-sample subjects. We conduct additional experiments to provide further robustness to the results. We consider a firm where the sales division (Sales) is responsible for demand forecasting and the operations division (Operations) is responsible for ordering. Sales has better information about the demand than Operations and sends a nonbinding demand forecast to Operations. To incentivize truthful information sharing, we include a forecast error penalty in the incentive system of Sales. Besides monetary payoffs, we also add behavioral factors to the utility function of Sales. We model the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe human behavior that is in line with the predictions of the behavioral model but deviates substantially from expected-payoff-maximizing behavior. We use the behavioral model to design incentive systems for truthful information sharing and validate the approach in an experiment with out-of-sample treatments and out-of-sample subjects. We conduct additional experiments to provide further robustness to the results. The experimental data and e-companion are available at https://doi.org/10.1287/mnsc.2017.2805 . This paper was accepted by Martin Lariviere, operations management. We consider a firm where the sales division ( Sales ) is responsible for demand forecasting and the operations division ( Operations ) is responsible for ordering. Sales has better information about the demand than Operations and sends a nonbinding demand forecast to Operations . To incentivize truthful information sharing, we include a forecast error penalty in the incentive system of Sales . Besides monetary payoffs, we also add behavioral factors to the utility function of Sales . We model the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe human behavior that is in line with the predictions of the behavioral model but deviates substantially from expected-payoff-maximizing behavior. We use the behavioral model to design incentive systems for truthful information sharing and validate the approach in an experiment with out-of-sample treatments and out-of-sample subjects. We conduct additional experiments to provide further robustness to the results. The experimental data and e-companion are available at https://doi.org/10.1287/mnsc.2017.2805 . This paper was accepted by Martin Lariviere, operations management. We consider a firm where the sales division (SALES) is responsible for demand forecasting and the operations division (OPERATIONS) is responsible for ordering. Sales has better information about the demand than Operations and sends a nonbinding demand forecast to OPERATIONS. To incentivize truthful information sharing, we include a forecast error penalty in the incentive system of SALES. Besides monetary payoffs, we also add behavioral factors to the utility function of SALES. We model the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe human behavior that is in line with the predictions of the behavioral model but deviates substantially from expected-payoff-maximizing behavior. We use the behavioral model to design incentive systems for truthful information sharing and validate the approach in an experiment with out-of-sample treatments and out-of-sample subjects. We conduct additional experiments to provide further robustness to the results. History: Accepted by Martin Lariviere, operations management. Funding: The authors gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft through the DFG Research Group "Design and Behavior" [FOR 1371]. Supplemental Material: The experimental data and e-companion are available at Keywords: behavioral operations * experimental economics * asymmetric forecast information * information sharing * sales incentives * forecast error * signaling |
Audience | Trade Academic |
Author | Thonemann, Ulrich W. Scheele, Lisa M. Slikker, Marco |
Author_xml | – sequence: 1 givenname: Lisa M. surname: Scheele fullname: Scheele, Lisa M. – sequence: 2 givenname: Ulrich W. surname: Thonemann fullname: Thonemann, Ulrich W. – sequence: 3 givenname: Marco surname: Slikker fullname: Slikker, Marco |
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Snippet | We consider a firm where the sales division (
Sales
) is responsible for demand forecasting and the operations division (
Operations
) is responsible for... We consider a firm where the sales division (Sales) is responsible for demand forecasting and the operations division (Operations) is responsible for ordering.... We consider a firm where the sales division (SALES) is responsible for demand forecasting and the operations division (OPERATIONS) is responsible for ordering.... |
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SubjectTerms | Analysis asymmetric forecast information behavioral operations Demand Employee incentives experimental economics forecast error Forecasts and trends Human acts Human behavior Incentives Information behavior Information sharing Management science Observations Planning sales incentives signaling |
Title | Designing Incentive Systems for Truthful Forecast Information Sharing Within a Firm |
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