Universität zu Köln

Scheele, Lisa (2017). Designing Incentive Systems for Truthful Forecast Information Sharing Within a Firm. Case Study, Theory and Experiments. PhD thesis, Universität zu Köln.

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Abstract

In environments with uncertain demand, companies must rely on forecasts to plan and execute their internal supply processes. A phenomenon frequently observed in practice is that demand forecasts are systematically too high. One reason could be incentive systems that motivate employees in Marketing/Sales to maximize their sales volume. In this respect, inflated demand forecasts are a means to ensure sufficient inventory and to minimize the risk of shortages. The objective of this thesis is to design incentive systems that lead to accurate and unbiased demand forecasts. We motivate and contextualize our research question by the practical case of a company in the pharmaceutical industry. To analyze the results of the case study more systematically, we transfer the forecast information exchange into a game-theoretic model. In an environment with stochastic demand, a (better informed) Sales department sends a forecast to an Operations department. To incentivize truthful forecast information sharing, the incentive system of Sales contains a penalty for forecast errors. The utility functions are grounded in behavioral theories of mental accounting, loss aversion and lying aversion. We formalize the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe behavior that deviates substantially from expected-payoff-maximizing behavior in the directions predicted by our behavioral model. Based on our theory and estimates for the behavioral parameters of our model, we design forecast-error-based incentive systems for truthful forecast information sharing. We validate their effectiveness in a new experiment with out-of-sample treatments and out-of-sample subjects. We further confirm the robustness of our model by additional experiments and analyses.

Item Type:	Thesis (PhD thesis)
Creators:	Creators Email ORCID ORCID Put Code Scheele, Lisa scheele.lisa@gmail.com UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-80522
Date:	27 October 2017
Language:	English
Faculty:	Faculty of Management, Economy and Social Sciences
Divisions:	Faculty of Management, Economics and Social Sciences
Subjects:	Management and auxiliary services
Uncontrolled Keywords:	Keywords Language forecast information sharing, behavioral operations, experimental research, incentive systems, forecast error, signaling, marketing-operations interface English
Date of oral exam:	1 February 2018
Referee:	Name Academic Title Thonemann, Ulrich W. Prof. Dr. Sting, Fabian J. Prof. Dr.
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/8052