This paper builds on and reinterprets “Operations and Supply Chain Management in China”, which offers a comprehensive account of the rapid institutional, educational, and research development of Operations and Supply Chain Management (OSCM) in China. While the Institutional–Dynamic–Organizational (IDO) framework effectively captures domestic structural transformation, it under-theorizes a critical external driver of this evolution: international knowledge exposure and collaboration. To address this gap, we complement the domestic institutional perspective with a bibliometric study of published articles in Production and Operations Management from 1992 to 2026. The evidence shows that China's growing presence in OSCM research is overwhelmingly collaboration-mediated, with China–U.S. co-authorship constituting the dominant channel of integration. The rise of China in top-tier OSCM journals is therefore not primarily an autonomous national trajectory, but a structurally embedded phenomenon within global co-authorship networks. Our findings suggest that China's OSCM evolution cannot be fully explained by domestic institutional expansion, policy support, or educational scaling alone. Instead, it reflects a broader process of exposure-driven co-evolution within a globally integrated knowledge system. In this system, international collaboration is not merely a byproduct of scientific development but a central mechanism shaping the structure and trajectory of global OSCM knowledge production.
Dockless bike sharing has been widely recognized for its potential environmental benefits by bridging the last-mile gap and encouraging a shift toward greener modes of travel. However, these benefits depend on large-scale bike adoption rather than mere service presence. Unfortunately, this adoption is often undermined by limited bike supply or unfavorable operating contexts. Leveraging the staggered rollout of Ofo and Mobike across Chinese cities, we employ a quasi-experimental stacked difference-in-differences design to identify how air quality changes following the entry of dockless bike sharing. The twin-platform setting enables two complementary analyses. First, treating the two platforms as a unified provider, we find that bike introduction significantly improves urban air quality by 3.82%, corresponding to a 3.13-point reduction in the Air Quality Index (AQI). These results remain robust across extensive alternative specifications and validation checks. Second, distinguishing between the two platforms reveals a supply-side mechanism. Dual-platform entry reduces AQI by 6.47 points, which is more than twice the baseline estimate. In contrast, single-platform entry has no significant impact. We also examine the contextual determinants that may influence bike-riding demand. Heterogeneity analyses indicate larger air quality improvements in cities with more domestic migrants, larger well-educated populations, more severe traffic congestion, denser public transit networks, and stronger bike-lane infrastructure, but smaller improvements where terrain is steep or rainfall is frequent. Overall, our study moves beyond average effects by showing how platform market structure and local demand conditions shape the realized environmental benefits of dockless bike sharing.
Flight delays have a significant impact on airlines, passengers, and the U.S. economy. Airlines also use flight on-time performance (OTP) – a metric based on the proportion of delayed flights – to attract travelers by demonstrating service reliability. It is well established that adding buffers to flight time and ground time improves on-time arrivals. However, such buffers can impose significant costs. The flight and ground times comprise multiple activities, and prior research has primarily focused on studying the impact of aggregate buffers. In this paper, we study the impact of increasing the buffer of a critical ground time activity, namely boarding time, potentially without increasing the aggregate ground time buffer, on flight delays. To do so, we use the context of Delta Air Lines' recent policy changes wherein the airline increased the boarding time for domestic narrow-body flights by 5 minutes and started compensating flight attendants for pre-flight boarding. Using a Difference-in-Difference-in-Differences framework, we analyze and quantify the impact of these policies on Delta’s flight delays. Our findings indicate a significant reduction in departure delays following the policy changes, with increased boarding time playing a critical role in improving on-time departures. Our analysis finds no evidence that boarding compensation contributed to the improvement in on-time departures. We show that the increase in boarding time can improve the likelihood of on-time departures, potentially without requiring additional total ground time or incurring additional scheduling costs. We observe that the benefit is more pronounced for longer flights, busier routes, and later departures in the day. Airlines are often criticized for relying on costly, ad hoc schedule buffering to improve OTP. However, our results demonstrate that carefully planning buffer time for critical activities can significantly improve operational performance.
Firms use bundles to influence customer demand, but supplying those bundles often requires operational capacity that is shared across the portfolio. Changing the price, composition, or availability of one bundle can therefore trigger two reallocations: customers reallocate expenditure across bundles, and the firm reallocates operational capacity across the demand those bundles generate. We develop a data-driven framework that links these two decisions. Heterogeneous consumers choose discrete bundle quantities subject to a common budget, while the firm jointly chooses bundle prices and quantities subject to bundle-specific and shared-resource requirements. We estimate the demand and supply models from observed discrete decisions using Bayesian Markov Chain Monte Carlo, retaining the integer structure in estimation and counterfactual analysis. We apply the framework to three empirical settings: public bike sharing, online retail, and theme-park services. The empirical analyses reveal several consequences of evaluating bundles as part of a portfolio. Customer value and profit contribution need not be aligned: a bundle that creates substantial customer value can make little or no incremental contribution to optimized profit, and removing some bundles can increase profit after the remaining portfolio is re-optimized. Price responses differ across bundles because discrete purchases adjust at different thresholds. A bundle's response to tighter shared-resource requirements depends on how its resource use changes the allocation of operational capacity elsewhere in the portfolio, rather than on its characteristics alone. Finally, deeper discounts need not generate larger incremental profit contributions; in the theme-park application, an intermediate discount can outperform both deeper and shallower discounts after the portfolio is re-optimized. Bundle design is a portfolio problem: a bundle's contribution depends not only on the demand it generates, but also on the customer and operational adjustments it induces elsewhere in the portfolio.
Operations of online user-generated content (UGC) platforms often involve tackling under-provision , wherein users lack motivation to contribute sufficient content. We study a novel design deployed to address this issue: the integration of a proprietary social feature that allows users to post casual free-form content (e.g., casual social content) alongside standard formal content on the platform. Leveraging a quasi-experiment on a large Chinese online knowledge-sharing platform, we assess the effects of integrating such a social feature on users’ formal knowledge contribution (i.e., writing answers to others’ questions ). Using difference-in-differences (DiD) analyses paired with various matching strategies, such as propensity score matching and look-ahead propensity score matching, we find that users who adopt and frequently use the feature (i.e., high adopters) show a stronger incentive to contribute answers without compromising quality. These results are further validated by a set of robustness checks. Further mediation analysis suggests that such a complementary effect might be because of two mechanisms related to the integrated social feature’s multi-self presentation function: first, the new feature increases high adopters’ engagement on the platform and leads them to consume more knowledge content, which in turn facilitates knowledge contribution; second, high adopters receive more social recognition benefits by building a more complete self through the integrated social feature, and such increased social recognition benefits further motivate more subsequent content contribution. Moreover, employing a text-mining approach to assess the semantic similarity between users’ casual social content and their formal knowledge contributions, we find that the complementary effect is amplified for high adopters whose casual posts remain more closely connected to their formal knowledge domain (i.e., are more semantically aligned with their formal knowledge). Our results have novel implications for platform design and operations to motivate users to contribute valuable content.
