Prior theory claims that buyback and revenue-sharing contracts achieve equivalent channel-coordinating solutions when applied in a dyadic supplier–retailer setting. This suggests that a supplier should be indifferent between the two contracts. However, the sequence and magnitude of costs and revenues (i.e., losses and gains) vary significantly between the contracts, suggesting the supplier’s preference of contract type, and associated contract parameter values, may vary with the level of loss aversion. We investigate this phenomenon through two studies. The first is a preliminary study investigating whether human suppliers are indeed indifferent between these two contracts. Using a controlled laboratory experiment, with human subjects taking on the role of the supplier having to choose between contracts, we find that contract preferences change with the ratio of overage and underage costs for the channel (i.e., the newsvendor critical ratio). In particular, a buyback contract is preferred for products with low critical ratio, whereas revenue sharing is preferred for products with high critical ratio. We show these results are consistent with the behavioral tendency of loss aversion and are more significant for subjects who exhibit higher loss aversion tendencies in an out of context task. In the second (main) study, we examine differences in the performance of buyback and revenue-sharing contracts when suppliers have the authority to set contract parameters. We find that the contract frame influences the way parameters are set and the critical ratio again plays an important role. More specifically, revenue-sharing contracts are more profitable for the supplier than buyback contracts in a high critical ratio environment when accounting for the supplier’s parameter-specification behavior. Also, there is little difference in performance between the two contracts in a low critical ratio environment. These results can help inform supply managers on what types of contracts to use in different critical ratio settings. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2182 . This paper was accepted by Martin Lariviere, operations management.

This study experimentally investigates ordering behavior in the competitive newsvendor problem. We consider a duopoly market setting with two identical newsvendors selling the same perishable goods in a common market. Our experimental results show that average observed orders systematically deviate from the Nash equilibrium, and exhibit a similar pull‐to‐center pattern as in the classic non‐competitive newsvendor experiments: average orders fall below the Nash equilibrium in the high‐margin condition, and above the Nash equilibrium in the low‐margin condition. More importantly, the observed orders in the duopoly market are significantly higher than that in the non‐competitive newsvendor market, even in situations where standard inventory models predict no difference. We explain the ordering behavior using a strategic experience‐weighted attraction (EWA) model, which captures players' propensities for strategic thinking in game settings. Our empirical analysis suggests that the strategic EWA model generates more accurate predictions of future ordering behavior than an existing linear adaptive model without concerning strategic thinking. Further analysis shows that individuals are heterogeneous in their propensities to be a strategic player. Our research indicates the importance of modeling strategic behavior when analyzing behavioral decisions in competitive (game) environments.

We examine a supply chain with a single supplier and multiple retailers to predict retailers’ actual ordering behaviors. If retailer orders exceed supplier capacity, a proportional rationing rule applies to capacity allocation among retailers. We propose a behavior model based on cognitive hierarchy theory, in which retailers with different levels of strategic-reasoning capabilities form heterogeneous beliefs about other players’ capabilities when choosing their orders. This behavioral model yields three interesting predictions. First, retailers’ orders increase as the number of retailers decreases or the supplier’s production capacity shrinks. Second, the orders tend to increase as the retailer population becomes more “sophisticated.” Third, retailers’ profits first increase in relation to their strategic-reasoning capabilities and then decrease, indicating an inverted U-shaped relationship between profits and strategic-reasoning capabilities. We experimentally examine the capacity allocation game with participants motivated by financial incentives. The experimental results and structural model estimation confirm the predictions of the behavioral model. Data are available at https://doi.org/10.1287/mnsc.2016.2655 . This paper was accepted by Gad Allon, operations management.

T he field of behavioral operations has produced a rich tradition of experiments in newsvendor decision-making. Our study provides a meta-analysis of 24 papers in this research area; we confirm that the pull-to-center (PtC) effect, where average order quantities in a sample lie in between average demand and optimal order quantities, is a very stable observable phenomenon across studies. However, we also show that the asymmetry in the PtC effect between high-margin and low-margin conditions varies significantly from study to study; factors that allow predicting the extent and direction of the PtC asymmetry include the likelihood of obtaining losses, the way underage costs are presented to subjects, and the existence of a decision support system. We validate these factors using a controlled experiment. In conclusion, the PtC asymmetry appears less as a fundamental attribute of human behavior, but rather as a function of the design aspects of the experiment.

Problem definition: We have witnessed a rapid rise of on-demand platforms, such as Uber, in the past few years. Although these platforms allow workers to choose their own working hours, they have limited leverage in maintaining availability of workers within a region. As such, platforms often implement various policies, including offering financial incentives and/or communicating customer demand to workers in order to direct more workers to regions with shortage in supply. This research examines how behavioral biases such as regret aversion may influence workers’ relocation decisions and ultimately the system performance. Academic/practical relevance: Studies on on-demand platforms often assume that workers are rational agents who make optimal decisions. Our research investigates workers’ relocation decisions from a behavioral perspective. A deeper understanding of workers’ behavioral biases and their causes will help on-demand platforms design appropriate policies to increase their own profit, worker surplus, and the overall efficiency of matching supply with demand. Methodology: We use a combination of behavioral modeling and controlled laboratory experiments. We develop analytical models that incorporate regret aversion to produce theoretical predictions, which are then tested and verified via a series of controlled laboratory experiments. Results: We find that regret aversion plays an important role in workers’ relocation decisions. Regret-averse workers are more willing to relocate to the supply-shortage zone than rational workers. This increased relocation behavior, however, is not sufficient to translate to a better system performance. Platform interventions, such as demand information sharing and dynamic wage bonus, can help further improve the system. We find that workers’ regret-aversion behavior may lead to an increased profit for the platform, a higher surplus for the workers, and an improved demand-supply matching efficiency, thus benefiting the entire on-demand system. Managerial implications: Our research emphasizes the importance and necessity of incorporating workers’ behavioral biases such as regret aversion into the policy design of on-demand platforms. Policies without considering the behavioral aspect of workers’ decision may lead to lost profit for the platform and reduced welfare for workers and customers, which may ultimately hurt the on-demand business.