The tendency of orders to increase in variability as one moves up a supply chain is commonly known as the bullwhip effect. We study this phenomenon from a behavioral perspective in the context of a simple, serial, supply chain subject to information lags and stochastic demand. We conduct two experiments on two different sets of participants. In the first, we find the bullwhip effect still exists when normal operational causes (e.g., batching, price fluctuations, demand estimation, etc.) are removed. The persistence of the bullwhip effect is explained to some extent by evidence that decision makers consistently underweight the supply line when making order decisions. In the second experiment, we find that the bullwhip, and the underlying tendency of underweighting, remains when information on inventory levels is shared. However, we observe that inventory information helps somewhat to alleviate the bullwhip effect by helping upstream chain members better anticipate and prepare for fluctuations in inventory needs downstream. These experimental results support the theoretically suggested notion that upstream chain members stand to gain the most from information-sharing initiatives.supply chain management, bullwhip effect, behavioral experiments, information sharing, dynamic decision making

In this paper, we provide a perspective on why behavioral research is critical to the operations management (OM) field, what prior research exists, and what opportunities lie ahead. The use of human experiments in operations management is still fairly novel despite a small stream of publications going back more than 20 years. We develop a framework for identifying the types of behavioral assumptions typically made in analytical OM models. We then use this framework to organize the results of prior behavioral research and identify future research opportunities. Our study of prior research is based on a search of papers published between 1985 and 2005 in six targeted journals including the

We examine the problem of developing supply contracts that encourage proper coordination of forecast information and production decisions between a manufacturer and distributor of high fashion, seasonal products operating in a two-mode production environment. The first production mode is relatively cheap but requires a long lead time while the second is expensive but offers quick turnaround. We focus on contracts of the form (w 1, w 2, b) where w i is the wholesale price offered for production mode i and b is a return price offered for items left over at the end of the season. We find that such a contract can coordinate the manufacturer and distributor to act in the best interest of the channel. The pricing conditions needed to ensure an efficient solution vary depending on the degree of demand forecast improvement between periods and the manufacturer's access to forecast information. We also examine whether these conditions ensure a Pareto optimal solution with respect to two traditional production settings.supply contracts, coordination, production planning, return option, value of information

Motivated by a study of the logistics systems used to manage consumable service parts for the U.S. military, we consider a static threshold-based rationing policy that is useful when pooling inventory across two demand classes characterized by different arrival rates and shortage (stockout and delay) costs. The scheme operates as a (Q, r) policy with the following feature. Demands from both classes are filled on a first-comefirst-serve basis as long as on-hand inventory lies above a threshold level K. Once on-hand inventory falls below this level, low priority (i.e., low shortage cost) demand is backordered while high priority demand continues to be filled. We analyze this static policy first under the assumption that backorders are filled according to a special threshold clearing mechanism. Structural results for the key performance measures are established to enable an efficient solution algorithm for computing stock control and rationing parameters (i.e., Q, r, and K). Numerical results confirm that the solution under this special threshold clearing mechanism closely approximates that of the priority clearing policy. We next highlight conditions where our policy offers significant savings over traditional 'round-up' and 'separate stock' policies encountered in the military and elsewhere. Finally, we develop a lower bound on the cost of the optimal rationing policy. Numerical results show that the performance gap between our static threshold policy and the optimal policy is small in environments typical of the military and high technology industries.

We examine the impact of point of sale (POS) data sharing on ordering decisions in a multi-echelon supply chain. In particular, we focus on how exposure to POS data may help reduce the "bullwhip effect," the tendency of orders to increase in variability as one moves up a supply chain. Theoretical studies have shown that exposure to POS data can lead to a reduction in the bullwhip effect when suppliers have no prior knowledge of the demand distribution. The benefit of sharing POS data in stable industries, where the demand distribution is commonly known, is less clear. We study this phenomenon from a behavioral perspective in the context of a simple, serial, supply chain subject to information lags and stochastic demand. We find, using a controlled simulation experiment, that sharing POS information does help reduce some components of the bullwhip effect in a stable demand setting, namely the order oscillation of upstream members. We offer one possible explanation for this improvement by examining the relationship between order decisions and demand line information. (BULLWHIP EFFECT; SUPPLY CHAIN MANAGEMENT; POS DATA; EXPERIMENTAL ANALYSIS) *

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.

A psychological contract defines the perceived reciprocal obligations that characterize a relationship between an individual and organizational entity. Breach of a psychological contract can negatively affect work behaviors and attitudinal perceptions, and may also elicit an emotional response (violation) which can help to explain these negative consequences. This research focuses on the role of psychological contracts in a supply chain setting. We explore when and how three conditions of psychological contract breach – attribute, severity, and timing – negatively impact outcomes, and assess the mediating role of psychological contract violation in this relationship. To evaluate our hypotheses, we employ a laboratory experiment in which participants assume the role of a purchasing manager. We impose various breach factors and observe their relative impact on the decision‐making behavior and fairness perceptions of the participant. We show that while the breach factors significantly impact task behavior, these relationships are not explained by psychological contract violation. However, violation is useful in explaining, in part, the results pertaining to fairness perceptions.

The bullwhip effect describes the tendency for the variance of orders in supply chains to increase as one moves upstream from consumer demand. Previous research attributes this phenomenon to both operational and behavioral causes. Operational causes are features of the institutional setting that lead rational agents to amplify changes in demand, while behavioral causes arise from suboptimal decisionmaking. This paper examines causes of the bullwhip through experiments with a serial supply chain, using the Beer Distribution Game. Unlike prior studies, we control all four commonly cited operational causes of the bullwhip, including uncertainty about customer demand. We eliminate demand uncertainty completely by making customer demand constant and known to all participants. Despite these controls, order amplification, instability, and supply line underweighting remain pervasive. We propose a new behavioral cause of the bullwhip, coordination risk, that arises when players place excessive orders to address the perceived risk that others will not behave optimally. We test two strategies to mitigate coordination risk: (1) holding additional on-hand inventory, and (2) creating common knowledge by informing participants of the optimal policy. Both strategies reduce, but not eliminate, the bullwhip effect. Holding excess inventory reduces order amplification by providing a buffer against the endogenous risk of coordination failure. Such coordination stock differs from traditional safety stock, which buffers against exogenous demand uncertainty. Surprisingly, neither strategy reduces supply-line underweighting. We conclude that the bullwhip can be mitigated but its behavioral causes appear robust.