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在本文章中，我们对顶刊《Management Science》于2026年2月份在线发布的文章中进行了精选（共10篇），并总结其基本信息，旨在帮助读者快速洞察行业最新动态。本月 MS 发文聚焦市场营销与消费者决策、供应链运营管理、公司金融与财务决策、机制设计与公共品分配、平台经济与行为运营管理等核心方向，深入研究了供应链金融场景中的多维信号传递机制、即时零售全渠道品类规划优化、竞技游戏玩家参与度最大化的匹配策略设计、企业债务重组中的性别差异效应等前沿问题。研究方法涵盖了动态博弈建模与重复搜寻模型、信号传递博弈与信息经济学分析、整数规划与凸包优化算法、机器学习模型设定检验、多期计量实证分析、机制设计与多项式时间算法等先进理论与技术。

文章1

● 题目：Searching for Rewards

为奖励而搜索

● 原文链接：https://doi.org/10.1287/mnsc.2024.05203

● 作者：T. Tony Ke , Jiwoong Shin , Xu Zhu

● 发布时间：2026-2-2

● 摘要：

Loyalty programs are widespread across various markets, offering members rewards based on their past purchases for future benefits. This study offers new insights into the strategic use of loyalty programs and their impact on market competition by exploring the dynamics of loyalty programs within a repeated ordered search framework, in which consumers sequentially search for the optimal product across multiple firms over two periods. Our findings highlight distinct roles for price discounts and rewards in influencing consumer decisions. Price discounts discourage further search in the current shopping period, whereas rewards encourage consumer loyalty by inducing prominence in subsequent visits. As search costs increase, firms tend to offer lower price discounts but higher rewards, and this results in a higher industry profit but lower consumer surplus. Compared with their absence, loyalty programs decrease both industry profit and consumer welfare, leading to a lose–lose outcome. Moreover, we demonstrate that, when the firms are heterogeneous in terms of their network sizes, those with larger networks tend to offer lower rewards yet achieve greater consumer loyalty in contrast to the firms with smaller networks, which compensate with higher rewards.

忠诚度计划在各类市场中广泛普及，该计划基于会员的过往消费行为向其提供奖励，为会员带来未来消费收益。本研究通过在重复有序搜寻框架下探究忠诚度计划的动态规律，为忠诚度计划的策略性运用及其对市场竞争的影响提供了全新见解；在该框架中，消费者会在两期内跨多家企业序贯搜寻最优产品。研究结果揭示了价格折扣与奖励在影响消费者决策方面的差异化作用。价格折扣会抑制消费者在当前购物期内的进一步搜寻行为，而奖励则通过提升企业在消费者后续访问中的凸显性来增强消费者忠诚度。随着搜寻成本的上升，企业倾向于提供更低的价格折扣与更高的奖励，这将推高行业整体利润，同时降低消费者剩余。与不实施忠诚度计划的情形相比，忠诚度计划的推行会同时降低行业利润与消费者福利，最终形成双输结果。此外，本文研究表明，当企业在网络规模上存在异质性时，与网络规模较小的企业相比，网络规模较大的企业往往提供更低的奖励，却能实现更高的消费者忠诚度，而网络规模较小的企业则会通过提供更高的奖励来弥补自身劣势。

文章2

● 题目：Multidimensional Signaling with Supplier Credit Guarantees

供应商信用担保下的多维信号传递

● 原文链接：https://doi.org/10.1287/mnsc.2024.07052

● 作者：Huihui Liu , Haotian Song , Wenqiang Xiao

● 发布时间：2026-2-6

● 摘要：

This paper investigates credit guarantees in a supply chain setting involving a supplier, a capital-constrained buyer, and a bank. We find that under complete information, credit guarantees increase order quantities but paradoxically raise wholesale prices, overall rendering the credit guarantee not useful for improving the operational efficiency. However, under information asymmetry, either a partial or full guarantee emerges in equilibrium, with the wholesale price maintained at its optimal full-information level. This underscores the pivotal role of credit guarantees in effective signaling and delineates the distinct functions of the wholesale price and the guarantee—the former on operational efficiency and the latter on signaling efficacy. Further comparative analysis of the supplier and buyer performances under the two contract types reveals that credit guarantees do not always benefit both parties.

本文研究了由一家供应商、一家资金约束买方与一家银行构成的供应链场景中的信用担保问题。研究发现，在完全信息条件下，信用担保虽能提升订货量，却反常推高批发价格，整体而言无法对改善运营效率产生积极作用。然而，在信息不对称条件下，均衡状态下会出现部分担保或全额担保的情形，同时批发价格能够维持在完全信息对应的最优水平。这一结果凸显了信用担保在有效信号传递中的核心作用，厘清了批发价格与担保机制的差异化功能 —— 前者作用于运营效率，后者决定信号传递的效能。本文进一步对两类合约模式下供应商与买方的绩效展开比较分析，发现信用担保并非总能使供需双方同时获益。

文章3

● 题目：An Integer Programming Approach for Quick-Commerce Assortment Planning

即时零售品类规划的整数规划方法

● 原文链接：https://doi.org/10.1287/mnsc.2023.02996

● 作者：Yajing Chen, Taotao He , Ying Rong , Yunlong Wang

● 发布时间：2026-2-6

● 摘要：

In this paper, we explore the challenge of assortment planning in the context of quick commerce, a rapidly growing business model that aims to deliver time-sensitive products. In order to achieve quick delivery to satisfy the immediate demands of online customers in close proximity, personalized online assortments need to be included in brick-and-mortar store offerings. With the presence of this physical linkage requirement and distinct multinomial logit choice models for online consumer segments, the firm seeks to maximize overall revenue by selecting an optimal assortment of products for local stores and by tailoring a personalized assortment for each online consumer segment. We employ an integer programming approach to solve this NP-hard problem to global optimality. In particular, we derive convex hull results to represent the consumer choice of each online segment under a general class of operational constraints, and to characterize the relation between assortment decisions and choice probabilities of products. Our convex hull results, coupled with a modified choice probability–ordered separation algorithm, yield formulations that provide a significant computational advantage over existing methods. Finally, we illustrate how our convex hull results can be used to address other assortment optimization problems.

本文探究了即时零售场景下的品类规划难题，即时零售是一种旨在配送时效敏感型产品、正高速发展的商业模式。为实现快速配送，满足周边线上消费者的即时需求，需将线上个性化品类纳入实体门店的商品供给范围。在存在该实体联动要求，且不同线上消费者细分群体对应差异化多项 Logit 选择模型的前提下，企业通过为本地门店选择最优商品品类、为每个线上消费者细分群体定制个性化品类，实现整体收益最大化。本文采用整数规划方法求解该 NP 难问题，得到全局最优解。具体而言，本文推导了凸包相关结论，用以刻画通用运营约束体系下各线上细分群体的消费者选择行为，同时厘清品类决策与商品选择概率之间的关联。本文提出的凸包结论结合改进的选择概率排序分离算法，所构建的模型形式相较现有方法具备显著的计算优势。最后，本文阐释了所提凸包结论在解决其他品类优化问题中的应用价值。

文章4

● 题目：Matchmaking Strategies for Maximizing Player Engagement in Video Games

电子游戏中最大化玩家参与度的匹配策略

● 原文链接：https://doi.org/10.1287/mnsc.2023.02957

● 作者：Mingliu Chen , Adam N. Elmachtoub , Xiao Lei 

● 发布时间：2026-2-6

● 摘要：

Managing player engagement is vital to the online gaming industry, given that many games generate revenue through subscription models and microtransactions. We scrutinize engagement management in the prevalent category of competitive video games, where players are frequently matched against one another, and matchmaking systems substantially impact engagement. We propose a dynamic model to analyze player dynamics and optimize matchmaking policies for maximum engagement. Our model takes into account two essential factors in competitive games: heterogeneous skill levels and players’ aversion to losing. Additionally, the model enables us to consider pay-to-win strategies and AI-powered bots, which are contentious methods of influencing player engagement and endogenously affect the optimal matchmaking policy. To provide sharp insights, we analyze a specific case where there are two skill levels, and players churn only after experiencing a losing streak. The optimal matchmaking policy considers both short-term rewards by matching players myopically and long-term rewards by adjusting skill distribution. The pay-to-win system can positively impact player engagement when the majority of players are low-skilled, because adopting pay-to-win also affects skill distribution. This result challenges the conventional wisdom that typically regards pay-to-win as trading player experience for revenue. When incorporating AI-powered bots, we demonstrate that optimizing the matchmaking policy can significantly reduce the number of required bots. We then extend our model and conduct a case study with real data from an online chess platform. The optimal policy can improve engagement by 4%–6% or reduce the percentage of bots by 3% in comparison with skill-based matchmaking.

玩家参与度管理对在线游戏行业至关重要，多数游戏均通过订阅模式与微交易实现盈利。本文针对竞技类电子游戏这一主流品类展开玩家参与度管理研究，该品类中玩家需频繁与其他玩家匹配对战，匹配系统对玩家参与度有着显著影响。本文提出一个动态模型，用以分析玩家行为动态，并优化匹配策略以实现玩家参与度最大化。该模型纳入了竞技游戏的两个核心要素：异质性技能水平与玩家的失利厌恶。此外，该模型可纳入付费取胜策略与 AI 人机，这两类方式是影响玩家参与度的争议性手段，且会内生性地影响最优匹配策略。为得到精准的研究洞见，本文分析了一个特定场景：玩家仅分为两个技能等级，且仅在遭遇连败后才会流失。最优匹配策略需同时兼顾两方面：一是通过短视化玩家匹配获取短期收益，二是通过调整技能分布实现长期收益。当玩家群体以低技能水平玩家为主时，付费取胜机制能够对玩家参与度产生正向影响，原因在于付费取胜机制的应用同样会改变技能分布。该研究结果对传统认知形成了挑战 —— 传统观点通常认为付费取胜是以牺牲玩家体验为代价换取收益。在纳入 AI 人机的场景下，本文研究表明，优化匹配策略能够显著降低所需的人机数量。本文随后对模型进行了拓展，并基于某在线国际象棋平台的真实数据开展了案例研究。结果显示，与基于技能的匹配机制相比，本文提出的最优策略可将玩家参与度提升 4%~6%，或将人机占比降低 3%。

文章5

● 题目：Expectations Matter: When (Not) to Use Machine Learning Earnings Forecasts

预期至关重要：何时应（不应）使用机器学习盈利预测

● 原文链接：https://doi.org/10.1287/mnsc.2024.05808

● 作者：John L. Campbell , Harrison Ham , Zhongjin (Gene) Lu , Katherine Wood

● 发布时间：2026-2-12

● 摘要：

We comprehensively examine the usefulness of machine learning technology to predict a firm’s earnings and offer three main findings. First, although prior literature suggests machine learning can offer better earnings forecasts than analysts, we show that this result is highly sensitive to machine learning model specification choices (i.e., 80% of evaluated machine forecasts fail to beat analysts). Second, we examine why the most accurate machine learning forecast consistently beats analysts, finding that they correct for predictable analyst biases that are both linear and nonlinear and largely relate to analysts’ prior forecast errors, forecasted earnings levels, and the firm’s stock price. Finally, we find that investors’ earnings expectations, as revealed through stock prices, largely—but do not fully—correct for these predictable analyst biases, with delayed price realization up to nine months. In additional analysis, we find that optimal machine learning specification choices remain stable over time and that, although the machine’s outperformance narrows in recent periods, it remains substantial among small-cap stocks. Overall, our study moves beyond the question of whether machine forecasts are superior to human forecasts and instead focuses on which machine forecast specifications matter, as well as when and why machine forecasts are most superior. In so doing, we provide code and estimates for the most accurate machine forecast specification and demonstrate that investors’ expectations appear to largely (but not fully) align with them.

本文全面考察了机器学习技术在企业盈利预测中的应用价值，并得出三项核心研究结论。第一，尽管既有文献表明机器学习能够给出优于分析师的盈利预测结果，但本文研究发现，该结论对机器学习的模型设定选择高度敏感 —— 即受测的机器学习预测模型中，有 80% 无法跑赢分析师预测。第二，本文探究了预测精度最高的机器学习模型能够持续跑赢分析师的内在原因，发现这类模型修正了分析师可预测的线性与非线性偏差，而这些偏差主要与分析师往期预测误差、预测盈利水平以及企业股价密切相关。最后，本文研究发现，股价所反映的投资者盈利预期，虽能在很大程度上修正这些可预测的分析师偏差，但无法实现完全修正，对应的价格兑现滞后最长可达 9 个月。

在拓展性分析中，本文发现机器学习的最优模型设定在时间维度上保持稳定；尽管近年来机器学习的超额预测表现有所收窄，但其在小盘股样本中仍具备显著的预测优势。总体而言，本文的研究跳出了 “机器学习预测是否优于人工预测” 的既有争论，转而聚焦于核心问题：何种机器学习预测设定具备实际价值，以及机器学习预测在何时、因何能实现最优的预测表现。基于此，本文提供了预测精度最高的机器学习模型设定对应的代码与估计结果，并验证了投资者预期与该模型的预测结果大体（但并非完全）趋同。

文章6

● 题目：Information Provision and the Curse of Knowledge

信息供给与知识的诅咒

● 原文链接：https://doi.org/10.1287/mnsc.2023.01839

● 作者：Snehal Banerjee , Jesse Davis, Naveen Gondhi

● 发布时间：2026-2-13

● 摘要：

Common wisdom suggests that the “curse of knowledge” (COK), whereby better-informed individuals are unable to ignore their private information when forecasting others’ beliefs, reduces the quality of communication. We study how this bias affects costly information provision by a founder who wants to raise financing from an outside investor. When the founder exhibits COK about the content of her communication, there is less information provision and payoffs tend to be lower for both players. However, we show that when the founder exhibits COK about the context of her message, the bias can lead to more information production and better investment decisions. Moreover, this can exacerbate the conflict of interest between the founder and the outsider.

传统观点认为，“知识的诅咒”（COK）—— 即信息占优的个体在预测他人的信念时，无法忽略自身掌握的私有信息 —— 会降低沟通质量。本文研究了该偏差如何影响计划向外部投资者融资的创始人的有成本信息供给行为。当创始人就其沟通内容表现出知识的诅咒时，信息供给水平会下降，且博弈双方的收益往往都会降低。然而本文研究发现，当创始人就其信息传递的语境表现出知识的诅咒时，该偏差反而会提升信息生成水平，带来更优的投资决策。此外，这一效应还可能加剧创始人与外部投资者之间的利益冲突。

文章7

● 题目：Optimal Tax Timing with Transaction Costs

考虑交易成本的最优纳税时机选择

● 原文链接：https://doi.org/10.1287/mnsc.2023.03118

● 作者：Min Dai , Yaoting Lei , Hong Liu , Chen Yang 

● 发布时间：2026-2-16

● 摘要：

We develop a dynamic portfolio model incorporating capital gains tax (CGT), transaction costs, and year-end taxation. We find that even tiny transaction costs can lead to significant deferral of large losses and that transaction costs affect loss deferrals much more than gain deferrals. Our model can thus help explain the puzzle that even when investors face equal long-term/short-term CGT rates, they may still defer realizing large capital losses for an extended period of time, displaying the disposition effect. In addition, we find that misestimating transaction costs is costly. We also provide several unique, empirically testable predictions and shed light on recently proposed tax policy changes.

本文构建了一个纳入资本利得税（CGT）、交易成本与年末计税规则的动态投资组合模型。研究发现，即便极小的交易成本，也会导致大额亏损的显著递延，且交易成本对亏损递延的影响程度远高于对利得递延的影响。因此，本文模型能够解释如下谜题：即便投资者面临的长期与短期资本利得税税率相同，其仍可能在较长时期内递延大额资本亏损的实现，表现出处置效应。此外，本文发现，对交易成本的误估将产生高昂的成本。本文还提出了若干独特的、可实证检验的预测结论，并为近期拟推行的税收政策调整提供了理论启示。

文章8

● 题目：Gender Gap in Debt Renegotiation

债务重组中的性别差距

● 原文链接：https://doi.org/10.1287/mnsc.2024.05802

● 作者：Paulo Manoel , Vinicius Brunassi Silva

● 发布时间：2026-2-18

● 摘要：

We study the role of gender in corporate debt renegotiation. Using in-court reorganizations from Brazil, we find that male-led creditors are more likely to reject plans put forward by female-led debtors. Although we cannot definitively identify the underlying mechanism driving this pattern, our findings align more consistently with gender-based discrimination compared with alternative explanations. This behavior may be costly: Female-led debtors deliver higher recoveries under reorganization than under liquidation, implying that rejections potentially create deadweight losses. Supporting a miscalibrated-beliefs explanation, we observe that the gender-based rejection gap narrows when male creditors have prior exposure to successful female-led businesses, pointing to a potential path for mitigation.

本文研究了性别因素在企业债务重组中的作用。基于巴西法庭内破产重整的样本数据，本文发现，男性主导的债权人更有可能否决女性主导的债务人提交的重整计划。尽管本文无法确切识别驱动这一现象的内在机制，但相较于其他替代性解释，本文研究结论与性别歧视假说的契合度更高。该行为可能带来高昂的成本：女性主导的债务人在重整程序下实现的清偿率显著高于清算程序，这意味着否决重整计划可能会产生无谓损失。本文的研究结果为信念校准偏差假说提供了支撑：当男性债权人过往接触过经营成功的女性主导企业时，这种基于性别的重整计划否决率差距会显著收窄，这为缓解该性别差距提供了可行路径。

文章9

● 题目：Simple and (Approximately) Optimal Mechanism in Efficiency and Equality Tradeoff

效率与公平权衡下的简单（近似）最优机制

● 原文链接：https://doi.org/10.1287/mnsc.2022.02785

● 作者：Zhou Chen , Qi Qi , Changjun Wang , Zhen Wang

● 发布时间：2026-2-18

● 摘要：

Many large cities have adopted a policy of restricting the number of new vehicle licenses in order to address the challenges of traffic and air pollution problems. An important question that then arises is how to allocate these limited new license quotas among a large set of demanders while taking both social efficiency and equality into consideration. Inspired by this practical problem, we study the problem of designing simple and optimal mechanisms to tradeoff between efficiency and equality in a similar public goods allocation problem. We first propose a truthful two-group mechanism framework that is both general and simple and then use it to compute the optimal solution that maximizes social efficiency while guaranteeing a certain level of equality. Interestingly and surprisingly, under some natural conditions regarding the players’ private values, we show that the optimal mechanisms within the proposed framework are always the mechanisms that first run an auction and then run a lottery (ATL for short). In addition, beyond the framework and those conditions, we prove that the ATL mechanism can always guarantee at least 1−𝑐+𝑐2 (𝑐∈[0,1] is the minimum equality level) of the optimal solution efficiency. This approximation ratio can in practice be further improved to near-optimal when resources are scarce and the natural conditions hold. We further establish a theoretical connection between these natural conditions and common value distributions, demonstrating that these conditions are widely satisfied in practice. Finally, we implement several experiments to verify the ATL mechanism’s optimality and robustness.

众多大型城市为应对交通拥堵与空气污染问题，已普遍实施新增机动车牌照数量管控政策。由此产生的一个核心问题是，如何在大量需求者之间分配这些有限的新增牌照额度，同时兼顾社会效率与公平。受这一现实问题启发，本文针对同类公共品分配问题，研究了如何设计能够实现效率与公平权衡的简单最优机制。本文首先提出了一个通用且简洁的真实显示双群体机制框架，基于该框架求解了在保障既定公平水平的前提下实现社会效率最大化的最优解。有趣且出人意料的是，在关于参与者私人估值的若干自然条件下，本文证明，所提框架内的最优机制始终是先拍卖后摇号机制（简称 ATL）。此外，在跳出该框架与上述条件的一般情形中，本文证明 ATL 机制始终能保证实现不低于最优解效率的 1−𝑐+𝑐²（其中𝑐∈[0,1] 为最低公平水平）。在资源稀缺且满足上述自然条件的现实场景中，该近似比可进一步提升至接近最优水平。本文进一步建立了上述自然条件与常见估值分布之间的理论关联，证明这些条件在现实场景中普遍成立。最后，本文通过多组实验验证了 ATL 机制的最优性与稳健性。

文章10

● 题目：Transportation and Inventory Planning in Serial Supply Chain with Heterogeneous Capacitated Vehicles

带异质运力受限车辆的串行供应链运输与库存规划

● 原文链接：https://doi.org/10.1287/mnsc.2022.04106

● 作者：Kartik Kulkarni, Manish Bansal

● 发布时间：2026-2-25

● 摘要：

We study serial supply chain problems where a product is transported from a supplier to a warehouse (inbound transportation), and then from the warehouse (outbound transportation) to a retailer such that demand for a given planning horizon is satisfied. We consider heterogeneous vehicles of varying capacities for transportation in each time period, and the objective is to plan inbound and outbound transportation along with inventory in each time period so that overall inventory and transportation costs are minimized. These problems belong to the class of two-echelon lot-sizing (2-ELS) problems with the warehouse and retailer as the first and second echelons, respectively. We address an open question raised in van Hoesel et al. [van Hoesel S, Romeijn HE, Morales DR, Wagelmans APM (2005) Integrated lot sizing in serial supply chains with production capacities. Management Sci. 51(11):1706–1719]: Does there exist a polynomial-time algorithm for 2-ELS with a single capacitated vehicle for each of the inbound and outbound transportation? Specifically, we introduce polynomial-time algorithms for this problem and its three generalizations with multiple capacitated vehicles for inbound and/or outbound transportation, thereby generalizing the results of Kaminsky and Simchi-Levi [Kaminsky P, Simchi-Levi D (2003) Production and distribution lot sizing in a two stage supply chain. IIE Trans. 35(11):1065–1075] and Sargut and Romeijn [Sargut FZ, Romeijn HE (2007) Capacitated production and subcontracting in a serial supply chain. IIE Trans. 39(11):1031–1043] for 2-ELS with a single capacitated vehicle for inbound transportation and uncapacitated outbound transportation. We showcase the practical applications of these approaches in efficiently solving discrete two- and multiechelon lot-sizing problems that arise in freight transportation, the international shipping industry, and the tire manufacturing industry. Based on our computational experiments, we observe that the algorithm for discrete 2-ELS with a capacitated vehicle for inbound and outbound transportation is computationally efficient in comparison with solving the mixed binary formulations of two- and multiechelon lot-sizing problems using an off-the-shelf optimization solver.

本文研究了一类串行供应链问题：产品先由供应商运输至仓库（入向运输），再由仓库运输至零售商（出向运输），需满足既定计划期内的市场需求。本文考虑各时段运输可使用不同运力规格的异质车辆，研究目标为规划各时段的入向、出向运输方案与库存水平，使总库存成本与运输成本最小化。该类问题属于双层批量规划（2-ELS）问题范畴，其中仓库与零售商分别对应第一层级与第二层级。

本文解答了 van Hoesel 等人提出的开放问题 [van Hoesel S, Romeijn HE, Morales DR, Wagelmans APM (2005) Integrated lot sizing in serial supply chains with production capacities. Management Sci. 51 (11):1706–1719]：针对入向与出向运输各配置单辆运力受限车辆的双层批量规划问题，是否存在对应的多项式时间算法？具体而言，本文针对该问题及其三类拓展情形（入向和 / 或出向运输配置多辆运力受限车辆），提出了对应的多项式时间算法，从而拓展了 Kaminsky 与 Simchi-Levi [Kaminsky P, Simchi-Levi D (2003) Production and distribution lot sizing in a two stage supply chain. IIE Trans. 35 (11):1065–1075]、Sargut 与 Romeijn [Sargut FZ, Romeijn HE (2007) Capacitated production and subcontracting in a serial supply chain. IIE Trans. 39 (11):1031–1043] 的研究结论 —— 上述已有研究仅针对入向运输配置单辆运力受限车辆、出向运输无运力约束的双层批量规划问题展开。

本文验证了所提方法的实际应用价值，其可高效求解货运、国际航运与轮胎制造行业中出现的离散型双层及多层级批量规划问题。基于数值实验结果，本文发现：与采用现成优化求解器直接求解双层及多层级批量规划问题的混合 0-1 规划模型相比，针对入向与出向运输均配置运力受限车辆的离散型双层批量规划问题所设计的算法，具备更优异的计算效率。