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Risk taking with multi-threshold based payoffs

Author: Tziri, Ioanna INSEAD Area: Decision SciencesPublisher: Fontainebleau : INSEAD, 2008.Language: EnglishDescription: 117 p. ; 30 cm.Type of document: INSEAD ThesisThesis Note: For the degree of Ph.D. in management, INSEAD, January 2008Bibliography/Index: Includes bibliographical referencesAbstract: In my dissertation, I consider decisions under uncertainty when payoffs are contingent on performance surpassing thresholds. In the first two chapters, I consider such a situation where the payoffs depend on two thresholds, a lower and an upper threshold. For example, a decision maker (e.g., a salesperson) may face getting fired if her performance is below the lower threshold, a fixed salary if the performance is between the two thresholds, and a bonus on top of the fixed salary if the performance exceeds the upper threshold. Siemens recently introduced a similar scheme, in which the managers are regularly evaluated as being in the red, amber, or green zones. This is also analogous to a situation where a decision maker's utility has discontinuous jumps at a "survival level" and an "aspiration level," being flat otherwise. I study how a person subject to such a compensation scheme makes decisions, in particular choosing the level of risk in her performance. For example, suppose a person had the opportunity to modify the spread (the standard deviation) of the probability distribution for her performance - i.e. the riskiness of their strategy. I look at how such a compensation scheme might impact the choice of the spread in the performance distribution. As mentioned above, this situation involves two thresholds with respect to a single attribute of her performance. In the third chapter, I extend the analysis to multi-attribute and multi-threshold situations. In addition, I show how to allocate limited human resources across attributes when compensation is contingent on performance exceeding some thresholds in each of the multiple attributes. To summarize, I explore mathematically and experimentally how people should and do behave, given multi-threshold decision problems. The main purpose of this dissertation is to establish the theoretical framework, determine the optimal decisions in order to achieve the maximum expected payoff under multi-threshold based compensation schemes, and study how people deviate from such optimal decisions. My findings can assist decision makers to achieve higher payoffs in multi-threshold situations as well as assist managers to design the incentive schemes with appropriate thresholds. List(s) this item appears in: Ph.D. Thesis
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For the degree of Ph.D. in management, INSEAD, January 2008

Includes bibliographical references

In my dissertation, I consider decisions under uncertainty when payoffs are contingent on performance surpassing thresholds. In the first two chapters, I consider such a situation where the payoffs depend on two thresholds, a lower and an upper threshold. For example, a decision maker (e.g., a salesperson) may face getting fired if her performance is below the lower threshold, a fixed salary if the performance is between the two thresholds, and a bonus on top of the fixed salary if the performance exceeds the upper threshold. Siemens recently introduced a similar scheme, in which the managers are regularly evaluated as being in the red, amber, or green zones. This is also analogous to a situation where a decision maker's utility has discontinuous jumps at a "survival level" and an "aspiration level," being flat otherwise. I study how a person subject to such a compensation scheme makes decisions, in particular choosing the level of risk in her performance. For example, suppose a person had the opportunity to modify the spread (the standard deviation) of the probability distribution for her performance - i.e. the riskiness of their strategy. I look at how such a compensation scheme might impact the choice of the spread in the performance distribution. As mentioned above, this situation involves two thresholds with respect to a single attribute of her performance. In the third chapter, I extend the analysis to multi-attribute and multi-threshold situations. In addition, I show how to allocate limited human resources across attributes when compensation is contingent on performance exceeding some thresholds in each of the multiple attributes. To summarize, I explore mathematically and experimentally how people should and do behave, given multi-threshold decision problems. The main purpose of this dissertation is to establish the theoretical framework, determine the optimal decisions in order to achieve the maximum expected payoff under multi-threshold based compensation schemes, and study how people deviate from such optimal decisions. My findings can assist decision makers to achieve higher payoffs in multi-threshold situations as well as assist managers to design the incentive schemes with appropriate thresholds.

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