Previous studies have shown that individuals make suboptimal decisions in a variety of supply chain and inventory settings. We hypothesize that one cause is that individuals are overconfident (in particular, overprecise) in their estimation of order variation. Previous work has shown theoretically that underestimating the variance of demand causes orders to deviate from optimal in predictable ways. We provide two experiments supporting this theoretical link. In the first, we elicit the precision of each individual's beliefs and demonstrate that overprecision significantly correlates with order bias. We find that overprecision explains almost one-third of the observed ordering mistakes and that the effect of overprecision is robust to learning and other dynamic considerations. In the second, we introduce a new technique to exogenously reduce overprecision. We find that participants randomly assigned to this treatment demonstrate less overprecision and less biased orders than do those in a control group. This paper was accepted by Peter Wakker, decision analysis.

Whether and how trust and trustworthiness differ between a collectivist society, e.g., China, and an individualistic one, e.g., the United States, generates much ongoing scientific debate and bears significant practical values for managing cross-country transactions. We experimentally investigate how supply chain members' countries of origin—China versus the United States—affect trust, trustworthiness, and strategic information sharing behavior in a cross-country supply chain. We consider a two-tier supply chain in which the upstream supplier solicits demand forecast information from the retailer to plan production; but the retailer has an incentive to manipulate her forecast to ensure abundant supply. The levels of trust and trustworthiness in the supply chain and supplier's capability to determine the optimal production quantity affect the efficacy of forecast sharing and the resulting profits. We develop an experimental design to disentangle these three aspects and to allow for real-time interactions between geographically distant and culturally heterogeneous participants. We observe that, when there is no prospect for long-term interactions, our Chinese participants consistently exhibit lower spontaneous trust and trustworthiness than their U.S. counterparts do. We quantify the differences in trust and trustworthiness between the two countries, and the resulting impact on supply chain efficiency. We also show that Chinese individuals exhibit higher spontaneous trust toward U.S. partners than Chinese ones, primarily because they perceive that individuals from the United States are more trusting and trustworthy in general. This positive perception toward U.S. people is indeed consistent with the U.S. participants' behavior in forecast sharing. In addition, we quantify that a Chinese supply chain enjoys a larger efficiency gain from repeated interactions than a U.S. one does, as the prospect of building a long-term relationship successfully sustains trust and trustworthiness by Chinese partners. We advocate that companies can reinforce the positive perception of westerners held by the Chinese population and commit to long-term relationships to encourage trust by Chinese partners. Finally, we also observe that both populations exhibit similar pull-to-center bias when solving a decision problem under uncertainty (i.e., the newsvendor problem).Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1905 .This paper was accepted by Yossi Aviv, operations management.

Relying on the rapid development of information and internet technologies, e-commerce has boomed over the past decade. As a link between manufacturers and consumers, the e-commerce platform has a crucial position in the online retailing market. The e-commerce platform not only provides an online marketplace through which the manufacturers directly sell products to consumers but also purchases and resells manufacturers’ products to consumers. Therefore, when the e-commerce platform provides services to manufacturers, it is faced with the selection of two sales methods: reselling or marketplace. Using a game theoretic model, we focus on the strategic interactions between an e-commerce platform and two brand manufacturers in four different business modes. The results show that the e-commerce platform profits more when both brand manufacturers directly sell products through the online marketplace. From the two brand manufacturers’ points of view, using the e-commerce platform as a reseller is always more profitable than directly selling, no matter which business mode they are in. The above findings have important implications for the selling decisions of the e-commerce platform and brand manufacturers. Furthermore, an interesting and counterintuitive result is that the new brand manufacturer benefits more than the existing brand manufacturer when consumers’ acceptance of the new brand products is becoming lower. When production costs are low, only the two brand manufacturers can achieve a mutually beneficial situation by selling products to the e-commerce platform. Moreover, the competition among brand manufacturers is beneficial to the e-commerce platform. Our research provides a theoretical basis for brand manufacturers and the e-commerce platform to make more rational decisions, and it updates the existing knowledge about brand competition and e-commerce platform’s business mode choices.

Artificial intelligence-powered recommendation systems have gained popularity as a tool to enhance user experience and boost sales. Platforms often need to make decisions about which seller to recommend and the strength of the recommendation when conducting recommendations. Therefore, it is necessary to explore the recommendation strategy of the platform in the case of duopoly competition. We develop a game model where two competing manufacturers sell products through an agency contract on a common platform, and they can decide whether or not to provide recommendations to the manufacturers. Our highlight lies in the endogenous recommendation strength of the platform. The findings suggest that it is optimal for the platform to offer recommendation services when the commission rate is high. The platform also prefers to only recommend one manufacturer in the market with low or high competition, but it prefers to recommend both manufacturers in moderately competitive markets. From the view of manufacturers, they can benefit from the recommendation service as long as the commission rate is not too low. Moreover, recommending only one manufacturer consistently yields stronger recommendations compared to recommending multiple manufacturers. However, the impact of recommendation on prices is influenced by the commission rate and product substitutability. These results have significant implications for platform decision making and provide valuable insights into the trade-offs involved in the development of recommendation systems.