Observation bias: The impact of demand censoring on newsvendor level and adjustment behavior

In an experimental newsvendor setting we investigate three phenomena: Level behavior ? the decision-maker's average ordering tendency; adjustment behavior ? the tendency to adjust period-to-period order quantities; and observation bias ? the tendency to let the degree of demand feedback influence order quantities. We find that the portion of mismatch cost due to adjustment behavior exceeds the portion of mismatch cost due to level behavior in three out of four conditions. Observation bias is studied through censored demand feedback, a situation which arguably represents the majority of newsvendor settings. When demands are uncensored, subjects tend to order below the normative quantity when facing high margin and above the normative quantity when facing low margin, but in neither case beyond mean demand (a.k.a. the pull-to-center effect). Censoring in general leads to lower quantities, magnifying the below-normative level behavior when facing high margin but partially counterbalancing the above-normative level behavior when facing low margin, violating the pull-to-center effect in both cases.

An Experimental Comparison of News Vending and Price Gouging

The newsvendor problem is a workhorse model in operation management research. We introduce a related game that operates in the price dimension rather than the inventory dimension: the price gouging game. Using controlled laboratory experiments, we compare news vending and price gouging behavior. We replicate the standard pull-to-center effect for news vending and find that the equivalent pattern occurs with price gouging. Further, we find that the pull-to-center is asymmetric both for newsvendors and price gougers. More broadly, the experimental results reveal that choices are similar across the theoretically isomorphic games, suggesting that observed behavior in newsvendor experiments is representative of a broader class of games and not driven by the operations context that is often used in newsvendor experiments. Finally, we do not find evidence that behavior in these games is systemically affected by sex, risk attitude, or cognitive reflection

Opportunity Loss Minimization and Newsvendor Behavior

To study the decision bias in newsvendor behavior, this paper introduces an opportunity loss minimization criterion into the newsvendor model with backordering. We apply the Conditional Value-at-Risk (CVaR) measure to hedge against the potential risks from newsvendor’s order decision. We obtain the optimal order quantities for a newsvendor to minimize the expected opportunity loss and CVaR of opportunity loss. It is proven that the newsvendor’s optimal order quantity is related to the density function of market demand when the newsvendor exhibits risk-averse preference, which is inconsistent with the results in Schweitzer and Cachon (2000). The numerical example shows that the optimal order quantity that minimizes CVaR of opportunity loss is bigger than expected profit maximization (EPM) order quantity for high-profit products and smaller than EPM order quantity for low-profit products, which is different from the experimental results in Schweitzer and Cachon (2000). A sensitivity analysis of changing the operation parameters of the two optimal order quantities is discussed. Our results confirm that high return implies high risk, while low risk comes with low return. Based on the results, some managerial insights are suggested for the risk management of the newsvendor model with backordering

Algorithm-Human-Algorithm: A New Classification Approach to Integrating Judgemental Adjustments

Modern-day firms face the predicament of blending the comparative advantages of their two core resources: machines and humans. When forecasting demand (e.g., for a product), extant literature documents that always permitting (or prohibiting) human revision of a machine forecast is beneficial if the humans\u27 private information role is larger (or smaller) than that of machine-accessible public information. We propose and design a complementary framework that shifts the focus to the regulation of each human revision; and, in doing so, adjusts for human vulnerability to systematic biases. To test our framework, we collaborate with a European retailer to compile a large dataset (~1.1 mn transactions) on machine-led demand forecasts and human revisions. In an out-of-sample analysis, our revision-level regulation approach picks the best of available forecasts in 14% more instances, compared to an always-permit or prohibit strategy at the product-store level. Our approach is theory-driven and easy to implement for practitioners

Strategic risk in contract design

Supply chains facing asymmetric information can either operate in a cooperative mode with information and benefit sharing or can choose a non-cooperative form of interaction and align their incentives via screening contracts. In the cooperative mode, supply chain efficiency can be achieved, but high levels of trust and trustworthiness are required. In the non-cooperative mode, the contract mechanism guarantees a second best supply chain performance, but only if all parties choose their equilibrium strategies without trembles. Experimental evidence, however, shows that both operating modes often fail due to strategic risk. Cooperation is disrupted by deceptive signals and the lack of trust, whereas non-cooperative strategies suffer from persistent out-of-equilibrium behavior. We present an experiment on supply chain interaction with reduced strategic risk in both operating modes. We find that supply chain performance can reach a second-best level in either operating mode, if strategic risk is sufficiently reduced. We present two means to reduce strategic risk. First, a punishment mechanism leads to a better matching of trust and trustworthiness and supports the cooperative operating mode. Second, an enforcement of self-selection supports the non-cooperative equilibrium by increasing the attractiveness of screening contracts. We conclude that supply chain managers should seek to reduce the variability of the supply chain partners\u27 behavior no matter what operating mode is considered

Behavioral Implications of Demand Perception in Inventory Management

The newsvendor problem is one of the rudimentary problems of inventory management with significant practical consequences, thus receiving considerable attention in the behavioral operational research literature. In this chapter, we focus on how decision makers perceive demand uncertainty in the newsvendor setting and discuss how such perception patterns influence commonly observed phenomena in order decisions, such as the pull-to-center effect. Drawing from behavioral biases such as over precision, we propose that decision makers tend to perceive demand to be smaller than it actually is in high margin contexts, and this effect becomes more pronounced with increases in demand size. The opposite pattern is observed in low margin settings; decision makers perceive demand to be larger than the true demand, and this tendency is stronger at lower mean demand levels. Concurrently, decision makers tend to perceive demand to be less variable than it actually is, and this tendency propagates as the variability of demand increases in low margin contexts and decreases in high margin contexts. These perceptions, in turn, lead to more skewed decisions at both ends of the demand spectrum. We discuss how decision makers can be made aware of these biases and how decision processes can be re-designed to convert these unconscious competencies into capabilities to improve decision making

Decision behavior in supply chains with random production yields

Dealing with supply risks is one of the challenges of decision makers in supply chains as producing and sourcing become more and more complex. Theoretical research on different types of supply uncertainty as well as their management is well covered. Behavioral aspects in this context, however, have not received much attention so far. In this paper, we present an experimental study which aims at investigating how subjects make decisions of ordering and producing in the presence of random production yields at a supplier, i.e. production output is a random fraction of production input. Subjects were confronted with the situation of either the buyer or the supplier in a simple two-tier supply chain with deterministic demand and had to make the respective quantity decisions. Results show that buyers have a good understanding of the situation and are likely to follow a probabilistic choice rule. In addition to that, hedging against supply risks drives their behavior of over-ordering. Suppliers on the other hand start off with moderate production decisions but improve over time which indicates learning effects. Furthermore, the study shows that additional sharing of information on yield rates is no cure for inefficient behavior of the buyer

An Experimental Investigation of Outsourcing through Competition

Our research uses laboratory experiments to examine the theoretical results of competition between suppliers in an outsourcing setup. We consider a supply chain in which a single buyer needs to outsource the manufacturing of a product among N potential suppliers. The buyer allocates demand to suppliers not on the basis of price, but rather on service. We analyze the levels of service suppliers will decide to provide when competing on three different criteria specified by the buyer. For the first, suppliers compete by providing the buyer a specific service level (fill-rate), and for the second by maintaining a specific quantity of on-hand inventory. For the third criteria, suppliers compete based on a parameter designed to optimize the supply chain in favor of the buyer. Prior research and existing theory predict that the decisions will reach stability at the Nash equilibrium for all three types of competition. Theory also predicts these equilibrium points will be ordered, from competitions based on service level as the lowest and those based on the optimal criteria as the highest. Our experimental results show that the equilibrium points reached by subjects are in fact ordered as theory predicts. However, there are large and statistically significant differences between those equilibrium points and the theoretical predictions. Using the Quantal Response Equilibrium (QRE) we show that random errors can explain some of these discrepancies. Our analyses also suggest that, under optimal criteria for competition, other behavioral factors such as rival chasing and loss aversion can play an influential role

Investigating the Fair Treatment of Suppliers and its Trust Fostering Role and Performance Benefits

An increasing number of companies have begun to make efforts to treat their suppliers fairly as a part of wider corporate social responsibility (CSR) initiatives. Few studies, however, have investigated the performance implications of such efforts for buying firms. This paper uses both organisational climate theory and social exchange theory to investigate (1) if buying firms' efforts in the form of a code of conduct for its procurement practitioners pay off, and (2) its mechanisms from the perspectives of procurement practitioners. We use a multi-method approach, combining analysis of survey data complemented by results from a behavioural experiment. First, survey data were gathered from 327 Korean manufacturing companies and analysed using structural equation modelling. Second, the findings were complemented by a behavioural experiment involving 120 subjects. The results support the positive performance implications of fair supplier treatment in the form of codes of conduct for procurement practitioners. The paper also offers insights into how such efforts benefit buying firms, which is due to the trust in the buyer-supplier relationship fostered by the resulting ethical behaviours of procurement practitioners