学术论文

Trust represents a key social mechanism facilitating collaboration in interorganizational relationships. Yet, the concept of interorganizational trust is still surrounded by substantial ambiguity, especially as it pertains to the levels of analysis at which it is located. Some scholars maintain that trust is an inherently individual-level phenomenon, whereas others insist that organizations constitute the central sources and referents of trust in interorganizational relationships. Our article addresses this controversy, aiming to reduce conceptual ambiguity and foster cumulative progress. Using a micro-sociological approach, we advance knowledge of the meaning and context-specific relevance of individual- vs. organizational-level trust. Specifically, we apply the notion of organizational actorhood to both the trustor and the trustee in an interorganizational relationship. We then build on micro-institutional and entitativity theory to offer a model of the antecedents of organizational actorhood that identifies a set of contextual conditions explaining the degree to which an organization rather than individuals within it constitutes the focal origin and target of trust. The contingent account we propose here helps bridge disparate traditions of scholarship on interorganizational trust by highlighting that trust can, but need not always, reside to a substantial extent at a supraindividual level of analysis.

This paper studies a large majority election with voters who have heterogeneous private preferences and exogenous private information about an unknown state of the world. We show that a Bayesian persuader can achieve any state-contingent outcome in some equilibrium by providing additional information. In this setting, without the persuader’s additional information, a version of the Condorcet jury theorem holds, in the sense that outcomes of large elections satisfy full-information equivalence. Persuasion does not require detailed knowledge of the voters’ private information, preferences, or the voting rule. It also requires almost no commitment power on the part of the persuader.

We examine changes in bank loan contracts after borrowers experience a nearby local newspaper closure. Compared to a sample of control firms, we find that the closure of a local newspaper leads to higher interest spreads for borrowers. This effect is more pronounced when there are fewer related lenders in the syndicate, when lenders have less prior lending experience in the local area, when the closed local newspapers are associated with increases in misconduct cases, and for institutional lenders who rely more heavily on others for monitoring. In addition, we observe that loan contract amendments become less frequent, while covenant strictness increases following newspaper closures. Our main findings are robust to various research design specifications and are not driven by deteriorating local economic conditions. Our findings suggest that local media still plays a significant role in the debt markets, even as society moves deeper into the internet era.

Problem definition: Inventory management problems with periodic and controllable resets occur in the context of managing water storage in the developing world and dynamically optimizing endcap promotion duration in retail outlets. In this paper, we consider a set of sequential decision problems in which the decision maker must not only balance holding and shortage costs but discard all inventory before a fixed number of decision epochs with the option for an early inventory reset. Methodology/results: Finding optimal policies for these problems through dynamic programming presents unique challenges because of the nonconvex nature of the resulting value functions. Moreover, this structure cannot be readily analyzed even with extended convexity definitions, such as K-convexity. Managerial implications: Our key contribution is to present sufficient conditions that ensure the optimal policy has an easily interpretable structure, which generalizes the well-known (𝑠,𝑆) policy from the operations management literature. Furthermore, we demonstrate that, under these rather mild conditions, the optimal policy exhibits a four-threshold structure. We then conclude with computational experiments, thereby illustrating the policy structures that can be extracted in various inventory management scenarios.

Problem definition: We consider the dynamic pricing problem of multiple products under (asymmetric) reference effects over an infinite horizon. Unlike existing literature, which is mostly focused on the single-product setting, our multiproduct setting takes into account the cross-product effects among substitutes and incorporates the memory-based reference prices into the multinomial logit (MNL) demand model. Even with the single-product logit demand, the structure of the optimal pricing policy is intractable. Therefore, we focus on the long-run patterns of the optimal pricing policy and also discuss the performance of the myopic pricing policy. Methodology/results: We first provide a comprehensive characterization of the myopic pricing policy, including its solution, long-run convergence behavior, and optimality gap. For the optimal pricing policy, we show an intricate connection between its long-run dynamics and types of reference effects. We demonstrate that the presence of any gain-seeking product renders a long-run constant pricing policy suboptimal. Conversely, the constant policy (or optimal steady state) can exist in both loss-neutral and loss-averse scenarios, where we provide a sufficient condition for such existence and give the analytical expression for the optimal steady state. We further show that when pricing perfect substitutes, the true optimal policy under the multiproduct framework is more likely to yield a long-run cyclic pattern than the policy derived from the single-product framework, a phenomenon that aligns well with the periodic discounts in real-world markets. Managerial implications: This discrepancy in the long-run behaviors between multi- and single-product-based policies highlights the importance of employing the multiproduct framework and addressing the cross-product effects, as sticking to the single-product framework while managing multiple substitutes can misrepresent long-run dynamics and result in suboptimality. In the multiproduct domain, our model suggests that retailers are more likely to benefit from appropriate price variations than maintaining a constant pricing policy.

Problem definition: Ride-hailing platforms face a supply-demand imbalance. During peak periods, the demand from passengers far exceeds the supply of drivers, whereas during off-peak periods, there is an abundance of supply but weak demand. The well-studied surge pricing can be challenging to implement in markets where prices are subject to regulation and are inflexible to adjust. We study an alternative operational approach that shifts the supply of drivers from off-peak to peak periods to address the supply-demand imbalance. Methodology/results: We propose two novel incentive schemes: the qualification scheme and the prioritization scheme. Specifically, the platform sets a work target for the peak period. Under the qualification scheme, the platform assigns off-peak service requests only to drivers who meet the peak period target. Under the prioritization scheme, the platform prioritizes off-peak requests for drivers who meet the peak period target. We analyze the effectiveness of these schemes, considering the openness of the platform’s supply system. For platforms with a closed system that only allows full-time drivers to provide service, the qualification scheme improves the total matching volume to a greater extent but hurts full-time drivers more than the prioritization scheme. For platforms with an open system that also allows the abundant part-time drivers to serve off-peak requests, the prioritization scheme outperforms the qualification scheme in improving total matching volume. Furthermore, the implementation of an incentive scheme in an open system may benefit both the platform and full-time drivers. Managerial implications: Our study suggests an alternative to surge pricing for on-demand platforms to address the supply-demand imbalance when prices are inflexible. It provides insights for platforms with varying levels of supply system openness in choosing appropriate incentive schemes. The welfare results offer guidance for platforms and policymakers regarding both matching volume and worker welfare.

Problem definition: We empirically study the market for ride-hailing services. In particular, we explore the following questions: (i) How do the two-sided market and prices jointly form in ride-hailing marketplaces? (ii) Does surge pricing create value, and for whom? How can its efficiency be improved? (iii) Can platforms’ strategy on revenue sharing with drivers be improved? (iv) What is the value generated by ride-hailing services, including hosting rival taxi services on ride-hailing apps? Methodology/results: We develop a discrete choice model for the formation of mutually dependent demand (customer side) and supply (driver side) that jointly determine pricing. Using this model and a comprehensive data set obtained from the largest mobile ride platform in China, we estimate customer and driver price elasticities and other factors that affect market participation for the company’s two main markets, namely, basic ride-hailing and taxi services. Based on these estimation results and counterfactual analysis, we demonstrate that surge pricing improves customer and driver welfare as well as platform revenues while counterintuitively reducing taxi revenues on the platform. However, surge pricing should be avoided during nonpeak hours because it can hurt both customer and platform surplus. We show that platform revenues can be improved by increasing drivers’ revenue share from the current levels. Finally, we estimate that the platform’s basic ride-hailing services generated customer value equivalent to $13.25 billion in China in 2024, and hosting rival taxi services on the platform boosted customer surplus by $3.6 billion. Managerial implications: Our empirical framework provides ride-hailing companies a way to estimate demand and supply functions, which can help with optimization of multiple aspects of their operations. Our findings suggest that ride-hailing platforms can improve profits by containing surge-pricing to peak hours only and boosting supply by increasing driver compensation. Finally, our results demonstrate that restricting ride-hailing services create significant welfare losses, whereas including taxi services on ride-hail platforms generates substantial economic value.

One advantage of advertising on social media is leveraging users’ expression of “likes” to influence the perceptions and responses of others in their network. Through a largescale field experiment on WeChat, three online lab studies and a theoretical model, we explore whether and how displaying more “likes” in an ad can effectively lead to more ad “likes” and clicks. We find that displaying the first “like” can significantly increase users’ tendencies to both “like” and click on an ad. However, on average, showing additional “likes” does not further increase the clicking propensity, although it consistently attracts more “likes.” We further find that displaying more “likes” increases the clickthrough rate for lesser-known brands but not for well-known brands, and has a stronger impact on the “like” rate for more socially engaged users than for less socially engaged ones. These findings are consistent with the interplay between informational and normative social influences in social advertising. The public visibility of “likes” makes liking more susceptible to normative social influence than clicking. The coexistence of these two forces can lead to an enhanced conformity effect on liking and a crowding-out effect on clicking. Our findings offer novel implications for managing social advertising and designing social media platforms.

Using a novel measure that captures negative ESG incidents at both listed and private suppliers, we provide large-scale evidence on the value implications of supply chain ESG. We find that firms with fewer supply chain ESG incidents exhibit higher future accounting performance and that this effect is stronger in the presence of more conscious customers and vulnerable supply chains. We also find that firms with robust supply chain ESG exhibit higher future stock returns and that this effect is more pronounced when information frictions are higher, which suggests that it takes time for the market to understand the value implications of supply chain ESG. Overall, we highlight the benefits of managing supply chain ESG and the decision usefulness of the related information.