a b s t r a c tPrevious research has shown that when solving a newsvendor problem, individuals systematically and persistently deviate from the profit maximizing quantity. This paper investigates the relationship between cognitive reflection and newsvendor decision making, testing experienced supply chain professionals and subjects affiliated with a university business school in a newsvendor experiment. We find that in high and medium critical ratio environments, individuals with higher cognitive reflection exhibit a lower tendency to chase demand. We also find that cognitive reflection is related to task outcome measures including average expected profit, average order quantity and order quantity variance, and that cognitive reflection is a better predictor of performance than college major, years of experience, and managerial position. These results suggest that cognitive reflection contributes to an understanding of newsvendor decision-making behavior.

Supply chain performance often depends on the individual decisions of channel members. Even when individuals have access to relevant information, order variation tends to increase when moving up the supply chain, a phenomenon known as the bullwhip effect. While prior research has investigated several structural/environmental factors which can mitigate the bullwhip effect, the underlying behavioral factors contributing to it are an open question. Using a production and distribution decision‐making simulation representing a four‐stage serial supply chain, we find that the cognitive profile of decision makers contributes to the bullwhip effect. We found that the specific decision tendency to underweight the supply line is linked to an individual's level of cognitive reflection. Furthermore, performance differs for entire supply chains and for specific echelons, and holds under standard mitigation efforts. The findings have implications for supply chain design, education, and industry.

W e analyze how individuals make forecasts based on time-series data. Using a controlled laboratory experiment, we find that forecasting behavior systematically deviates from normative predictions: Forecasters overreact to forecast errors in relatively stable environments, but underreact to errors in relatively unstable environments. The performance loss that is due to such systematic judgment biases is larger in stable than in unstable environments.

W e investigate newsvendor ordering behavior under competition. We present a laboratory experiment that documents the behavioral ordering regularities in competitive newsvendor environments, and an analytical model extending the standard theory of newsvendor competition by including an optimal best-response policy for competing with a behaviorally biased newsvendor. We test the effectiveness of this policy using an out-of-sample experiment and find that it results in improved market share, service level and profitability.

T his research analyzes how individual differences affect performance in judgmental time-series forecasting. Decision makers with the ability to balance intuitive judgment with cognitive deliberation, as measured by the cognitive reflection test, tend to have lower forecast errors. This relationship holds when controlling for intelligence. Furthermore, forecast errors increase for very fast or very slow decisions. We provide evidence that forecast performance can be improved by manipulating decision speed.

Based on a simulation, the authors of “Newsvendor Demand Chasing Revisited” recommended using correlation of orders with lagged demand to measure chasing behavior. They concluded that measuring chasing with regression based on partial adjustment is prone to false positives. We show the purported false positives are due to autocorrelation and recommend using partial adjustment regression-based approaches to evaluate chasing. This paper was accepted by Jayashankar Swaminathan, operations management.

We investigate the impact of using a clear scoring rule in a sealed bid multi‐dimensional (A+B) procurement auction, as frequently used in government procurement. The central procurement agency in Chile (ChileCompra) asked for help to understand how concealing the scoring rule affected buyers. Using an experiment, we analyze the effect of transparently communicating the scoring rule on bidding outcomes by comparing the buyer's surplus and supplier profits when buyers expressly communicate the weight they place on a nonmonetary (B) attribute, versus when this information is concealed from bidders. In addition, we compare outcomes where the scoring rule is made visible only after the offers are submitted. If the scoring rule is not disclosed, outcomes are poorer for buyers, and sellers see their profits increase.

W e investigate the impact of behavioral ordering on profits under competition. Specifically, we use controlled laboratory experiments to evaluate the differences in profits between a behavioral competitor (where a human places orders), and a management science-driven competitor (where orders are placed according to one of several plausible policies based on existing literature and managerial practice). Unlike the full-information game-theoretic models that assume rational decision-makers, these policies mimic practical situations by using less information and do not assume that their human competitors make fully rational decisions. Most prior literature focuses on non-competitive settings, where behaviorally biased deviations from optimal order quantities result in small expected profit losses. In contrast, under competition, we find that human decision-makers receive a substantially lower profit than the equilibrium expected profit, even as their competitors receive substantially higher profit.