Newsvendor pull-to-center reconsidered (original) (raw)

Revenue Management vs. Newsvendor Decisions: Does Behavioral Response Mirror Normative Equivalence

W e study and compare decision-making behavior under the newsvendor and the two-class revenue management models, in an experimental setting. We observe that, under both problems, decision makers deviate significantly from normative benchmarks. Furthermore, revenue management decisions are consistently higher compared to the news-vendor order quantities. In the face of increasing demand variability, revenue managers increase allocations; this behavior is consistent with normative patterns when the ratio of the selling prices of the two customer segments is less than 1/2, but is its exact opposite when this ratio is greater than 1/2. Newsvendors' behavior with respect to changing demand variability , on the other hand, is consistent with normative trends. We also observe that losses due to leftovers weigh more in newsvendor decisions compared to the revenue management model; we argue that overage cost is more salient in the newsvendor problem because it is perceived as a direct loss, and propose this as the driver of the differences in behavior observed under the two problems.

The Newsvendor Problem: The Role of Prospect Theory and Feedback

European Journal of Operational Research, 2020

Experimental studies on newsvendor ordering behavior offer conflicting explanations as to the cause of the deviation from the optimal risk-neutral behavior. With one exception, studies have neither explored prospect theory as possible explanations, nor investigated exactly how this prospecting behavior comes to be. We conduct two experiments and demonstrate that a newsvendor, indeed, exhibits prospecting behavior and that this behavior is triggered by the relative value of the overage and the underage costs. These relative values help create a frame of reference that puts the newsvendor in either a gain-frame or a loss-frame. When the overage cost is less than the underage cost, a newsvendor is in a loss-frame and acts in a risk-seeking manner by ordering more than the optimal, and when the overage cost is more than the underage cost, the newsvendor is in a gain-frame and acts in a risk-averse manner by ordering less than the optimal, as prospect theory suggests. We also show the newsvendor does not use mean demand anchoring with insufficient adjustment heuristic to determine either the initial or the subsequent order quantity. The newsvendor is willing to change the decision in response to changes in parameters, consistent with prospect theory. Two forms of feedback are also supplied; however, feedback does not result in improved decision-making with a commensurate reduction in either systematic bias or prospecting behavior. Surprisingly, the newsvendor becomes more risk-seeking over time rather than risk-neutral. We conclude with a discussion of our findings, managerial insights, and possible future directions.

Task Decomposition and Newsvendor Decision Making

In three behavioral laboratory experiments, we compare newsvendor ordering decisions made directly to newsvendor ordering decisions made in a decomposed way by soliciting point forecasts, uncertainty judgments, and service level decisions. Decomposing orders in such a way can lead to performance improvements compared to ordering directly. However, we also demonstrate that if the underlying demand uncertainty is too high, or if the cost structure emphasizes underage costs, decomposition may fail as a decision approach. Under such conditions, decision makers are prone to incorporate too much random judgment error or set service levels too high, which reduces the efficacy of this decision approach. We further demonstrate that if accompanied by decision support in the form of suggested quantities, task decomposition becomes the better performing approach to decision making more generally. Decision support and task decomposition therefore appear as complementary methods to improve decision performance.

Behavioral Decision Making in the (Q,R) Purchasing Model: An Experimental Study

This paper presents and analyzes the results of a decision-making experiment in inventory management under uncertainty. The experiment included 81 participants who played the role of a small car importer facing random demand as in the (Q,R) model. The results show strong evidence of learning and convergence, and the average reorder point (R) closely approaches the optimal level for maximizing profits. However, the participants' decisions are still biased by realizations of extreme values of demand and loss of potential sales. We argue that participants are affected by recency, loss aversion, and, possibly, their own risk aversion.