鑽石舞台

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現實世界中的許多分析問題都會涉及兩個重大挑戰:預測和優化。由於每個挑戰都具有典型的複雜性，因而解決相關問題的標準範式是先預測後優化。而對於機器學習，總的來說，其目的是最小化預測誤差，而不考慮如何在下游優化問題中使用預測。相反，我們提出了一個新的、非常通用的框架，稱為智能「預測，然後優化」(SPO)。該框架直接利用優化問題結構——即其目標和約束——來設計更好的預測模型。我們框架的一個關鍵組成部分是SPO損失函數，該函數衡量了由預測引起的決策錯誤。由於訓練一個關於SPO損失的預測模型在計算上的挑戰性，我們使用對偶理論推導出一個凸代理損失函數，並稱之為SPO+損失。最重要的是，我們證明了在適當條件下，SPO+損失與SPO損失在統計意義上是一致的。我們的SPO+損失函數可以跟蹤處理任何帶有線性目標的多面體優化、凸優化、甚至混合整數優化問題。對最短路徑和投資組合優化問題的數值實驗發現SPO框架可以在先預測後優化範式下帶來顯著的改進，特別是當被訓練的預測模型被錯誤指定時。我們發現，即使真實數據是高度非線性的，使用SPO+損失訓練的線性模型也傾向於占優隨機森林算法。

Many real-world analytics problems involve two significant challenges: prediction and optimization. Because of the typically complex nature of each challenge, the standard paradigm is predict-then-optimize. By and large, machine learning tools are intended to minimize prediction error and do not account for how the predictions will be used in the downstream optimization problem. In contrast, we propose a new and very general framework, called Smart 「Predict, then Optimize」 (SPO), which directly leverages the optimization problem structure—that is, its objective and constraints—for designing better prediction models. A key component of our framework is the SPO loss function, which measures the decision error induced by a prediction. Training a prediction model with respect to the SPO loss is computationally challenging, and, thus, we derive, using duality theory, a convex surrogate loss function, which we call the SPO+ loss. Most importantly, we prove that the SPO+ loss is statistically consistent with respect to the SPO loss under mild conditions. Our SPO+ loss function can tractably handle any polyhedral, convex, or even mixed-integer optimization problem with a linear objective. Numerical experiments on shortest-path and portfolio-optimization problems show that the SPO framework can lead to significant improvement under the predict-then-optimize paradigm, in particular, when the prediction model being trained is misspecified. We find that linear models trained using SPO+ loss tend to dominate random-forest algorithms, even when the ground truth is highly nonlinear.

參考文獻：Adam N. Elmachtoub, Paul Grigas. Smart 「Predict, then Optimize」. Management Science, 2022, 68(1), 9–26.

2、零售店中的議價：基於維也納的研究

在西方，標價是正常現象，很少看到消費者收到低於標價的折扣。然而，我們發現，當詢問商店時，大約40%的時間會給予10%的折扣。對於高價產品和非銷售產品，小型企業更有可能提供折扣。更普遍的是，不同企業類型的價格授權行為的差異可表明監控成本和員工技能是議價行為的重要驅動因素。

In the West, where posted prices are the norm, it is uncommon to observe consumers receive discounts below the posted price. Nevertheless, we find that when stores are asked, a discount is granted approximately 40% of the time, with a median discount percentage of 10%. Discounts are more likely to be offered by small-scale firms, for higher-priced products, and for nonsale items. More generally, differences in price delegation behavior across firm types serve as an indicator that monitoring costs and employee skills are important drivers of bargaining behavior.

參考文獻：Sandro Shelegia, Joshua Sherman. Bargaining at Retail Stores: Evidence from Vienna. Management Science, 2022, 68(1), 27–36.

3、創新的新穎性:競爭、顛覆和反壟斷政策

我們設計了一個模型來分析創新的新穎性，並探索它對市場競爭性質和創新質量的意義。一個創新者不僅要決定是否創新，還要決定如何大膽創新，其中，創新的地方越新奇——與之前的越不同——結果就越不確定。我們指出，在這種環境下存在阿羅替代效應的一種變體，即新進入者比現有者追求更多的創新技術。儘管如此，我們的研究表明，新進入者擾亂現有者的可能性比現有者擾亂自身的可能性要小，而且在市場中失敗的可能性也更小。通過模型擴展，我們允許現有者獲得進入者的創新，並指出這逆轉了阿羅效應。由於進入者尋求對現有者的價值最大化，使得收購的前景對創新更有利可圖，但同時也抑制了創新的新穎性。這種逆轉表明，嚴格的反壟斷政策對激勵創業企業大膽創新具有積極作用。

We develop a model to capture the novelty of innovation and explore what it means for the nature of market competition and quality of innovations. An innovator decides not only whether to innovate but how boldly to innovate, where the more novel is the innovation—the more different it is from what has come before—the more uncertain is the outcome. We show in this environment that a variant of the Arrow replacement effect holds in that new entrants pursue more innovative technologies than do incumbents. Despite this, we show that the new entrant is less likely to disrupt an incumbent than the incumbent is to disrupt itself, and less likely to fail in the market. We extend the model to allow the incumbent to acquire the entrant postinnovation and show that this reverses the Arrow effect. The prospect of acquisition makes innovation more profitable but simultaneously suppresses the novelty of innovation as the entrant seeks to maximize her value to the incumbent. This reversal suggests a positive role for a strict antitrust policy that spurs entrepreneurial firms to innovate boldly.

參考文獻：Steven Callander, Niko Matouschek. The Novelty of Innovation: Competition, Disruption, and Antitrust Policy. Management Science, 2022, 68(1), 37–51.

4、資產價格的昂貴解釋

我們提出了一個模型，在這個模型中，投資者不能毫無成本地處理資產價格的信息。在交易階段，投資者是有限理性的，他們對價格的解釋會給價格注入噪聲，因而會引發內生的噪聲交易。我們的設置預測了價格慣性和得到了過度的回報波動和過度的交易量。在整體均衡中，投資者通過權衡優於市場的利益與獲得複雜性的成本來選擇複雜性水平。由於複雜收購可能存在戰略互補，進而導致多重均衡的結果。

We propose a model in which investors cannot costlessly process information from asset prices. At the trading stage, investors are boundedly rational, and their interpretation of prices injects noise into the price, generating a source of endogenous noise trading. Our setup predicts price momentum and yields excessive return volatility and excessive trading volume. In an overall equilibrium, investors optimally choose sophistication levels by balancing the benefit of beating the market against the cost of acquiring sophistication. There can exist strategic complementarity in sophistication acquisition, leading to multiple equilibria.

參考文獻：Jordi Mondria, Xavier Vives, Liyan Yang. Costly Interpretation of Asset Prices. Management Science, 2022, 68(1), 52–74.

5、社交網絡中網紅營銷的分析架構：對網紅的選擇與調度

各種社交媒體平台上用戶數量的爆炸性增長已經改變了企業制定營銷活動戰略的方式。為了利用龐大的社交網絡，企業已將注意力轉向網紅營銷，他們聘請獨立的網紅在社交媒體平台上推廣他們的產品。儘管最近網紅營銷有所增長，但網絡播種問題(即確定網紅以最佳方式發布企業信息或廣告)既沒有在學術文獻中得到嚴格研究，也沒有在實踐中得以解決。我們設計了一個數據驅動的優化框架，以實現企業的利益最大化，分別設計了兩個模型，以幫助企業成功地進行(i)短期和(ii)長期網紅營銷活動。模型基於與營銷人員的互動以及對企業在社交媒體信息的觀察，並通過對Twitter數據進行實證分析對模型參數進行估計。我們的實證分析發現了多網紅的集體影響效應，並發現模型中包含了兩個重要參數，即多重暴露效應和遺忘效應。對於短期活動，我們設計了一個優化模型來選擇網紅並給出模型的結構特性。利用這些性質，我們提出了一個基於多項式時間的數學規劃模型，以提供接近最優的解決方案。對於長期問題，我們設計了一個有效的解決方法，以實現同時選擇網紅並在規劃期內安排他們的消息發布。通過與實踐中使用的多個基準測試方法對比，我們展示了我們的解決策略在短期和長期問題上的優越性。最後，我們為處在網紅營銷的背景下的企業提供了一些管理啟示。

Explosive growth in the number of users on various social media platforms has transformed the way firms strategize their marketing activities. To take advantage of the vast size of social networks, firms have now turned their attention to influencer marketing wherein they employ independent influencers to promote their products on social media platforms. Despite the recent growth in influencer marketing, the problem of network seeding (i.e., identification of influencers to optimally post a firm’s message or advertisement) neither has been rigorously studied in the academic literature nor has been carefully addressed in practice. We develop a data-driven optimization framework to help a firm successfully conduct (i) short-horizon and (ii) long-horizon influencer marketing campaigns, for which two models are developed, respectively, to maximize the firm’s benefit. The models are based on the interactions with marketers, observation of firms』 message placements on social media, and model parameters estimated via empirical analysis performed on data from Twitter. Our empirical analysis discovers the effects of collective influence of multiple influencers and finds two important parameters to be included in the models, namely, multiple exposure effect and forgetting effect. For the short-horizon campaign, we develop an optimization model to select influencers and present structural properties for the model. Using these properties, we develop a mathematical programming based polynomial time procedure to provide near-optimal solutions. For the long-horizon problem, we develop an efficient solution procedure to simultaneously select influencers and schedule their message postings over a planning horizon. We demonstrate the superiority of our solution strategies for both short- and long-horizon problems against multiple benchmark methods used in practice. Finally, we present several managerially relevant insights for firms in the influencer marketing context.

參考文獻：Rakesh R. Mallipeddi, Subodha Kumar, Chelliah Sriskandarajah, Yunxia Zhu. A Framework for Analyzing Influencer Marketing in Social Networks: Selection and Scheduling of Influencers. Management Science, 2022, 68(1), :75–104.

6、雲定價:現貨市場反擊

雲計算提供商必須經常持有許多可用的空閒計算容量(例如，用於維護或為具有長期合同的用戶提供服務)。一個自然的想法是在二級市場上（例如通過可搶占的現貨市場）出售這些閒置計算容量。直觀地看，這應該會增加提供商的利潤。然而，這忽略了可能發生在均衡狀態下的「市場蠶食」效應，以及供應商因搶占而承受的額外成本。為了研究提供現貨市場的可行性，我們將排隊理論和博弈論相結合，對供應商利潤優化問題進行模型，以分析由此產生的排隊系統的均衡。我們的主要研究結果是，在一個易於檢查的條件下，供應商可以通過提供現貨市場(使用閒置資源)和固定價格市場，同時實現利潤增長和為用戶創造帕累托改進。最後，通過數值實驗，我們分析了提供者的成本及其策略對其利潤的影響。

Cloud computing providers must constantly hold many idle compute instances available (e.g., for maintenance or for users with long-term contracts). A natural idea, which should intuitively increase the provider’s profit, is to sell these idle instances on a secondary market, for example, via a preemptible spot market. However, this ignores possible 「market cannibalization」 effects that may occur in equilibrium as well as the additional costs the provider experiences due to preemptions. To study the viability of offering a spot market, we model the provider’s profit optimization problem by combining queuing theory and game theory to analyze the equilibria of the resulting queuing system. Our main result is an easy-to-check condition under which a provider can simultaneously achieve a profit increase and create a Pareto improvement for the users by offering a spot market (using idle resources) alongside a fixed-price market. Finally, we illustrate our results numerically to demonstrate the effects that the provider’s costs and her strategy have on her profit.

參考文獻：Ludwig Dierks, Sven Seuken. Cloud Pricing: The Spot Market Strikes Back. Management Science, 2022, 68(1), 205-122..

7、司機、乘客和服務提供商:共享經濟對出行的影響 （需要重新修改翻譯）

人們普遍認為，拼車（即在一次旅程中多人乘坐同一輛車的出行方式），通過更高效地利用汽車座位，有可能顯著減少交通量。我們介紹了一種模式，在此模式下，乘客向拼車平台支付一定的費用，隨後平台將費用支付給司機。我們將集體決策建模為匿名非原子博弈，其中不僅考慮了有限的策略集，還考慮了收入異質個體的收益函數。我們研究了如何組織拼車，以及拼車平台的引入如何影響交通和所有權，其中平台通過選擇座位出租價格以最大化收入或福利。我們發現，擁有與使用成本的比率決定了拼車的組織方式。如果這一比例較低，拼車就會以點對點(P2P)服務的形式提供;如果這一比例較高，拼車就會以企業對客戶(B2C)服務的形式提供。在P2P的情況下，只有當司機需要滿足自己的交通需求時，才會由司機發起搭車。在B2C的情況下，即使並非出於專職司機的個人需求，汽車也需要一直由專職司機駕駛。我們表明，儘管拼車的引入可能會降低汽車擁有率，但它可以導致交通流量的增加。我們的研究結果還表明，隨着擁有成本的增加，交通流量和擁有率可能會增加，而一個收益最大化的平台可能更傾向於使汽車只占用幾個座位，從而導致高交通流量。我們將這些結果與社會福利最大化平台的結果進行了對比。

It is widely believed that ride sharing, the practice of sharing a car such that more than one person travels in the car during a journey, has the potential to significantly reduce traffic by filling up cars more efficiently. We introduce a model in which individuals may share rides for a certain fee, paid by the rider(s) to the driver through a ride-sharing platform. Collective decision making is modeled as an anonymous nonatomic game with a finite set of strategies and payoff functions among individuals who are heterogeneous in their income. We examine how ride sharing is organized and how traffic and ownership are affected if a platform, which chooses the seat rental price to maximize either revenue or welfare, is introduced to a population. We find that the ratio of ownership to usage costs determines how ride sharing is organized. If this ratio is low, ride sharing is offered as a peer-to-peer (P2P) service, and if this ratio is high, ride sharing is offered as a business-to-customer (B2C) service. In the P2P case, rides are initiated by drivers only when the drivers need to fulfill their own transportation requirements. In the B2C case, cars are driven all the time by full-time drivers taking rides even if these are not motivated by their private needs. We show that, although the introduction of ride sharing may reduce car ownership, it can lead to an increase in traffic. We also show that traffic and ownership may increase as the ownership cost increases and that a revenue-maximizing platform might prefer a situation in which cars are driven with only a few seats occupied, causing high traffic. We contrast these results with those obtained for a social welfare-maximizing platform.

參考文獻：Saif Benjaafar, Harald Bernhard, Costas Courcoubetis, Michail Kanakakis, Spyridon Papafragkos. Drivers, Riders, and Service Providers: The Impact of the Sharing Economy on Mobility. Management Science, 2022, 68(1), 123–142.

8、低工資工人和非競爭性協議可執行性

我們利用2008年俄勒岡州針對計時工資工人的非競爭性協議(NCAs)，為揭示NCAs對低薪工人的影響提供了第一手證據。我們發現，對小時工禁用NCA平均提高了2%-3%的小時工資。由於只有一部分工人簽署了NCA，所以我們通過按小時計酬人群中使用NCA的普遍程度衡量該估計值，結果表明，儘管存在於不受NCA約束的勞動力市場的溢出效應會降低真正的估計效果，但是實際上受NCA約束的員工仍可能高達14% -21%。雖然在年齡、教育和工資分配中均發現了工資的積極影響，但在女性工作者和NCAs更常見的職業中，這種影響更強。俄勒岡州的低工資NCA禁令還改善了俄勒岡州的平均職業狀況，提高了工作之間的流動性，並在不影響工作時間的情況下提高了有薪工人的比例。

We exploit the 2008 Oregon ban on noncompete agreements (NCAs) for hourly-paid workers to provide the first evidence on the impact of NCAs on low-wage workers. We find that banning NCAs for hourly workers increased hourly wages by 2%–3% on average. Since only a subset of workers sign NCAs, scaling this estimate by the prevalence of NCA use in the hourly-paid population suggests that the effect on employees actually bound by NCAs may be as great as 14%–21%, though the true effect is likely lower due to labor market spillovers onto those not bound by NCAs. Whereas the positive wage effects are found across the age, education, and wage distributions, they are stronger for female workers and in occupations where NCAs are more common. The Oregon low-wage NCA ban also improved average occupational status in Oregon, raised job-to-job mobility, and increased the proportion of salaried workers without affecting hours worked.

參考文獻：Sareh Nabi, Houssam Nassif, Joseph Hong, Hamed Mamani, Guido Imbens. Low-Wage Workers and the Enforceability of Noncompete Agreements. Management Science, 2022, 68(1), 143–170.

9、基於優先級的最優分配機制

本文提出一種易於設計最優優先系統的方法。該系統在考慮代理選擇行為的同時，可以將代理分配到異質的項目中。我們從延期驗收和最優交易周期等特殊情況優化相應的機制。與之前的文獻不同，我將機制中的這些輸入，即代理的優先分配和項目的配額，作為待優化的參數。該方法基於採用收益管理方法分析單邊匹配的大型市場模型，用以解決以社會福利為目標的一類分類規劃問題。我將這一方法應用於學校選擇問題，並表明限制選擇可能有利於學生。此外，我計算了波士頓地區小學選擇的優化選擇集和優先級。

This paper develops a tractable methodology for designing an optimal priority system for assigning agents to heterogeneous items while accounting for agents』 choice behavior. The space of mechanisms being optimized includes deferred acceptance and top trading cycles as special cases. In contrast to previous literature, I treat the inputs to these mechanisms, namely the priority distribution of agents and quotas of items, as parameters to be optimized. The methodology is based on analyzing large market models of one-sided matching using techniques from revenue management and solving a certain assortment planning problem whose objective is social welfare. I apply the methodology to school choice and show that restricting choices may be beneficial to student welfare. Moreover, I compute optimized choice sets and priorities for elementary school choice in Boston.

參考文獻：Peng Shi. Optimal Priority-Based Allocation Mechanisms. Management Science, 2022, 68(1), 171–188.

10、遠大前景：融合計量經濟學與分析學以提高對電影成功的預測

關於機器學習和整合社交媒體數據能夠在多大程度上提高商業應用的預測準確性，存在着大量的炒作。為了評估這種炒作是否有必要，我們在仿真實驗中採用了來自電影行業的數據，並與計量經濟學方法和預測分析文獻中的工具進行了對比。此外，我們提出了新的策略，這些策略結合了每個文獻中的元素，試圖在控制收入的潛在關係中捕捉更豐富的異質性模式。我們的結果證實了社交媒體數據的重要性，以及在使用新的大數據源進行預測時，結合計量經濟學和機器學習的混合策略的價值。具體來說，儘管最小二乘支持向量回歸和遞歸劃分策略在預測精度方面都大大優於降維策略和傳統計量經濟學方法，但使用混合方法還可以獲得更大的收益。此外，我們通過蒙特卡洛實驗證明，社交媒體對票房結果的度量和其他電影特徵對票房結果的影響具有顯著的異質性，並因而導致了上述收益。

There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches with tools from the predictive analytics literature. Further, we propose new strategies that combine elements from each literature in a bid to capture richer patterns of heterogeneity in the underlying relationship governing revenue. Our results demonstrate the importance of social media data and value from hybrid strategies that combine econometrics and machine learning when conducting forecasts with new big data sources. Specifically, although both least squares support vector regression and recursive partitioning strategies greatly outperform dimension reduction strategies and traditional econometrics approaches in forecast accuracy, there are further significant gains from using hybrid approaches. Further, Monte Carlo experiments demonstrate that these benefits arise from the significant heterogeneity in how social media measures and other film characteristics influence box office outcomes.

參考文獻：Steven F. Lehrer, Tian Xie. The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success. Management Science, 2022, 68(1), 189–210.

11、中層管理人員、人員流動和績效:零售連鎖店的長期實地實驗

在一項隨機對照試驗中，一家大型零售連鎖店的首席執行官(CEO)為被試商店的經理們設定了新的目標，要求他們「盡其所能」降低員工離職率。這種實驗將離職率降低了五分之一到四分之一，並持續了9個月才逐漸消失，但在提醒後又重新出現。並且這一實驗設置對銷售額沒有影響。進一步的分析表明，被試門店經理在人力資源上花費的時間更多，在客戶服務上花費的時間更少。我們的研究結果表明，中層管理者有助於減少人員流動，但他們在資源有限且多任務的條件下，面臨着將資源投入到不同活動之間的權衡。雖然，本文中的實驗確實提高了效率，但是這些只發生在企業這一層面。

In a randomized controlled trial, a large retail chain’s Chief Executive Officer (CEO) sets new goals for the managers of the treated stores by asking them to 「do what they can」 to reduce the employee quit rate. The treatment decreases the quit rate by a fifth to a quarter, lasting nine months before petering out, but reappearing after a reminder. There is no treatment effect on sales. Further analysis reveals that treated store managers spend more time on human resources (HR) and less on customer service. Our findings show that middle managers are instrumental in reducing personnel turnover, but they face a trade-off between investing in different activities in a multitasking environment with limited resources. The treatment does produce efficiency gains. However, these occur only at the firm level.

參考文獻：Guido Friebel, Matthias Heinz, Nikolay Zubanov. Middle Managers, Personnel Turnover, and Performance: A Long‐Term Field Experiment in a Retail Chain. Management Science, 2022, 68(1), 211–229.

12、團隊激勵、社會凝聚力與績效:一個自然的實地實驗

我們在荷蘭的122家零售連鎖店開展了實地實驗，以研究團隊激勵、團隊社會凝聚力和團隊績效之間的相互作用。理論上，我們預測由於社會凝聚力減少了搭便車行為，因而團隊激勵對團隊績效的影響會隨着團隊的社會凝聚力而增加。此外，團隊激勵可能會導致更多的同事支持或更高的同伴壓力，從而影響團隊的社會凝聚力。在干預前後，我們在隨機選擇的商店子集中引入了短期團隊激勵，並對所有商店進行了度量，包括包括團隊的銷售業績、團隊的社會凝聚力、同事支持和同伴壓力。團隊激勵對銷售的平均實驗效果為1.5個百分點，與0沒有顯著差異。與理論相一致，干預前測量的實驗效果估計值隨着社會凝聚力的增加而增加。此外，社會凝聚力本身不受團隊激勵的影響。

We conducted a field experiment in a Dutch retail chain of 122 stores to study the interaction between team incentives, team social cohesion, and team performance. Theory predicts that the effect of team incentives on team performance increases with the team’s social cohesion because social cohesion reduces free-riding behavior. In addition, team incentives may lead to more coworker support or to higher peer pressure and thereby, can affect the team’s social cohesion. We introduced short-term team incentives in a randomly selected subset of stores and measured for all stores, both before and after the intervention, the team’s sales performance and the team’s social cohesion as well as coworker support and peer pressure. The average treatment effect of the team incentive on sales is 1.5 percentage points, which does not differ significantly from zero. In line with theory, the estimated treatment effect increases with social cohesion as measured before the intervention. Social cohesion itself is not affected by the team incentives.

參考文獻：Josse Delfgaauw, Robert Dur, Oke Onemu, Joeri Sol. Team Incentives, Social Cohesion, and Performance: A Natural Field Experiment. Management Science, 2022, 68(1), 230–256.

13、新商標的價值評估

企業通常在推出新產品或服務時註冊商標。我們發現，新商標註冊數量對預測企業盈利能力、股票回報據和分析師在盈利預測中的反應不足有正向作用。利用《聯邦商標反淡化法》(FTDA)作為商標保護的外生衝擊，我們發現，更強的商標保護增強了新商標註冊的可預測性。總之，本文研究結果表明，投資者低估了新商標註冊的價值。

Firms often register trademarks as they launch new products or services. We find that the number of new trademark registrations positively predicts firm profitability, stock returns, and underreaction by analysts in their earnings forecasts. Using the Federal Trademark Dilution Act (FTDA) as an exogenous shock to trademark protection, we find that greater trademark protection strengthens the predictability of new trademark registrations. Together, our evidence suggests that investors undervalue new trademark registrations.

參考文獻：Po-Hsuan Hsu, Dongmei Li, Qin Li, Siew Hong Teoh, Kevin Tseng. Valuation of New Trademarks. Management Science, 2022, 68(1), 257–279.

14、自動駕駛汽車在解決城市最後一英里配送中的價值

本文證實了與目前的送貨員在配送包裹前必須停放車輛的系統相比，自動輔助配送可以帶來顯著改善。我們以自動駕駛汽車為研究對象，該自動駕駛汽車可以將送貨員送至城市中預定的地點，隨後，送貨員將貨物步行送至最後的收貨地址。然後，車輛搭載送貨人員前往下一個裝貨點。通過這種方式，送貨員將永遠不需要尋找停車位或走回停車位。基於客戶數量、車輛行駛速度、送貨人行走速度和裝貨時間，我們在由客戶構成的實心矩形網格上刻畫了自動駕駛情況的最優解，表明可以在多項式時間內找到該最優解。為了衡量自動駕駛案例的完成時間，我們引入了包裹配送服務的傳統模型，其中包括搜索停車位的時間。結果表明，如果忽略尋找停車位的時間，引入自動駕駛汽車將完成所有客戶的配送時間減少了0%-33%。在考慮停車次數非零的情況下，在更長的停車時間、更小的容量和更低的裝載包裹的固定時間下，送貨員節省了30%-77%的時間。

We demonstrate that autonomous-assisted delivery can yield significant improvements relative to today’s system in which a delivery person must park the vehicle before delivering packages. We model an autonomous vehicle that can drop off the delivery person at selected points in the city where the delivery person makes deliveries to the final addresses on foot. Then, the vehicle picks up the delivery person and travels to the next reloading point. In this way, the delivery person would never need to look for parking or walk back to a parking place. Based on the number of customers, driving speed of the vehicle, walking speed of the delivery person, and the time for loading packages, we characterize the optimal solution to the autonomous case on a solid rectangular grid of customers, showing the optimal solution can be found in polynomial time. To benchmark the completion time of the autonomous case, we introduce a traditional model for package delivery services that includes the time to search for parking. If the time to find parking is ignored, we show the introduction of an autonomous vehicle reduces the completion time of delivery to all customers by 0%–33%. When nonzero times to find parking are considered, the delivery person saves 30%–77% with higher values achieved for longer parking times, smaller capacities, and lower fixed time for loading packages.

參考文獻：Sara Reed, Ann Melissa Campbell, Barrett W. Thomas. The Value of Autonomous Vehicles for Last-Mile Deliveries in Urban Environments. Management Science, 2022, 68(1), 280–299.

15、先行動好麼？早期企業的專家評價中的位置效應

關於先提出/先被評估的好處，經常有相當多的憂慮和相互矛盾的建議。因此，我們分析了專業評估者如何根據評估順序對創業計劃進行評價。以中國北京舉行的一場創新基金大賽為研究背景，其中該大賽的獎金十分豐厚，評估師是准隨機分配的，並在沒有同行影響的情況下評估書面申請。這使我們能夠可靠地恢復因果位置效應。我們還通過理論分析並測試評估者先前(情境特定)判斷經驗的異質性如何調節位置效應。總的來說，首先評估的提案要求排名前10%的總資產僅等同於未被先評估的位於後10%的提案的評估。企業和評估者的固定效應模型得出了一致的結論。我們將在討論部分考慮可能緩解這些位置影響的評估設計元素。

There is often considerable anxiety and conflicting advice concerning the benefits of presenting/being evaluated first. We thus investigate how expert evaluators vary in their evaluations of entrepreneurial proposals based upon the order in which they are evaluated. Our research setting is a premiere innovation fund competition in Beijing, China, where the prize money at stake is economically meaningful, and evaluators are quasi-randomly assigned to evaluate written grant proposals without the possibility of peer influence. This enables us to credibly recover a causal position effect. We also theorize and test how heterogeneity in evaluators』 prior (context-specific) judging experience moderates position effects. Overall, we find that a proposal evaluated first requires total assets in the top 10th percentile to merely equal the evaluation of a proposal in the bottom 10th percentile that is not evaluated first. Firm and evaluator fixed-effects models yield consistent findings. We consider evaluation design elements that may mollify these position effects in the discussion section.

參考文獻：Jiang Bian, Jason Greenberg, Jizhen Li, Yanbo Wang. Good to Go First? Position Effects in Expert Evaluation of Early-Stage Ventures. Management Science, 2022, 68(1), 300–315.

16、客戶轉換成本如何決定企業範圍? 來自移動通訊市場的證據

本文研究了客戶轉換成本變化對單一產品企業和多產品企業相對優勢的影響。提供單一產品的企業可以根據客戶的需求量身定製產品，而多產品企業可以以靈活的形式為客戶創造價值，允許客戶隨着偏好的變化而改變產品種類，且不需要更換供應商。我們認為，當客戶面臨高轉換成本時，這種價值創造機制更有效。我們利用突然降低客戶轉換成本的移動電信部門外生政策的變化(號碼可攜號轉網)，，驗證了這一預測。我們的結果顯示，當客戶轉換成本下降時，多產品企業的增長低於單產品企業，並且與先前相比，提供多產品的企業進入頻率有所降低。該研究強調了客戶轉換成本是如何促進或抑制企業範圍的選擇。

This paper examines the relative advantages of single-product and multiproduct firms following changes in customer switching costs. Whereas a single-product firm can closely tailor offerings to customers』 needs, a multiproduct firm can create value for customers in the form of flexibility, allowing them to change between product varieties as preferences evolve without needing to switch providers. We argue that this value-creation mechanism is more effective when customers face high switching costs and explore this prediction in the mobile telecommunications sector, using an exogenous policy change (mobile number portability) that suddenly decreases customer switching costs. Our results reveal that when customer switching costs fall, multiproduct firms see lower growth than single-product firms, and entry with a multiproduct offering becomes less frequent than before. The study highlights how customer switching costs can enable or inhibit choices of firm scope.

參考文獻：Niloofar Abolfathi, Simone Santamaria, Charles Williams. How Does Firm Scope Depend on Customer Switching Costs? Evidence from Mobile Telecommunications Markets. Management Science, 2022, 68(1), 316–332.

17、運用多個企業的企業家的行為與績效:基於資源再配置視角的分析

先前的研究表明，同時經營不止一家企業的投資組合企業家比運營單一企業的企業家更能成功地創業。但是，他們的企業不太可能生存下來。為了調和這一矛盾，本文提出了一個框架，在這個框架中，運營多個企業的企業家的主要優勢不是事先選擇最佳商業機會的優越能力，而是事後跨業務重新部署人力和資本資源的能力。這就減少了他們在新項目上的投資。這種重新部署的選擇有助於他們退出未能通過最初市場測試的新業務。因此，運營多個企業的企業家的異質性終止決策比事前商機選擇更能解釋新企業績效差異。我們通過超過5700名企業家的縱向數據集測試了這些想法，並找到了一致的證據，即：運營多個企業的企業在進入時沒有表現出系統性的更高績效; 因為存在選擇效應和資源重新部署，績效差異只會隨着時間的推移而出現。

Prior research suggests portfolio entrepreneurs—businesspeople who run more than one firm simultaneously—launch more successful ventures than their single-business counterparts. However, their ventures are less likely to survive. In an attempt to reconcile this paradox, this paper presents a framework in which portfolio entrepreneurs』 main advantage is not a superior ability to select the best business opportunities ex ante, but rather the ability to redeploy human and capital resources across businesses ex post, which reduces the sunkenness of their investments in new projects. This redeployment option facilitates their exit from new businesses that fail initial market tests. Thus, portfolio entrepreneurs』 heterogeneous termination decisions explain a greater portion of new firm performance differential than ex ante opportunity selection. We test these ideas using a longitudinal data set of more than 5,700 entrepreneurs and find consistent evidence. Portfolio companies do not show systematically higher performance at the time of entry; a performance difference emerges only over time, as the selection effect and resource redeployment occur.

參考文獻：Simone Santamaria. Portfolio Entrepreneurs』 Behavior and Performance: A Resource Redeployment Perspective. Management Science, 2022, 68(1), 333–354.

18、慈善眾籌平台中項目與回歸捐贈者的匹配

我們提出了一種方法，將回歸的捐贈者與慈善眾籌平台上的籌款活動匹配起來。該方法基於一個捐贈者效用最大化的結構性計量經濟學模型，其中，捐贈者可以從捐贈中獲得利他(來自他人的福利)和利己(來自個人動機)效用——即慈善捐贈的一個獨特特徵。我們使用donorschoose.org(最大的K-12教育眾籌平台)的綜合數據集來評估我們的模型。我們發現，與文獻中流行的個性化推薦方法相比，所提出的模型更能準確地識別捐贈者在未來一段時間內回歸時願意捐贈的項目以及他們願意捐贈多少。從估計模型中，我們發現，主要的利己因素誘發了超過三分之二的捐款，但在籌款活動的過程中，這兩種動機發揮了共生的作用: 在項目的早期階段，當項目的可行性還不明確時，利己主義的動機會推動資金的投入，而利他主義的動機則會在項目的後期助力實現資金目標。最後，我們考慮所有項目的需求和不同的預算和捐助者的偏好，以最大化每周的總資金為目標，利用所提出的模型設計了一個建議政策。我們估計,基於過去14周的數據,與以前相比，這樣的政策使得捐款提高了2.5%,更可行的項目分得資金提升了9%，獲得資助的項目增加了17%，捐贈者效用提升了15%。與直覺相反，我們發現，隨着時間的推移，每周資金最大化的政策比每周總效用最大化的政策得到的捐助者的效用更高。其原因是，資金最大化政策將捐款集中在更可行的項目上，從而導致更多的資助項目，最終提升了捐助者效用。

We propose an approach to match returning donors to fundraising campaigns on philanthropic crowdfunding platforms. It is based on a structural econometric model of utility-maximizing donors who can derive both altruistic (from the welfare of others) and egoistic (from personal motivations) utilities from donating—a unique feature of philanthropic giving. We estimate our model using a comprehensive data set from DonorsChoose.org—the largest crowdfunding platform for K–12 education. We find that the proposed model more accurately identifies the projects that donors would like to donate to on their return in a future period, and how much they would donate, than popular personalized recommendation approaches in the literature. From the estimated model, we find that primarily egoistic factors motivate over two-thirds of the donations, but, over the course of the fundraising campaign, both motivations play a symbiotic role: egoistic motivations drive the funding in the early stages of a campaign when the viability of the project is still unclear, whereas altruistic motivations help reach the funding goal in the later stages. Finally, we design a recommendation policy using the proposed model to maximize the total funding each week considering the needs of all projects and the heterogeneous budgets and preferences of donors. We estimate that over the last 14 weeks of the data period, such a policy would have raised 2.5% more donation, provided 9% more funding to the projects by allocating them to more viable projects, funded 17% more projects, and provided 15% more utility to the donors from the donations than the current system. Counterintuitively, we find that the policy that maximizes total funding each week leads to higher utility for the donors over time than a policy that maximizes donors』 total utility each week. The reason is that the funding-maximizing policy focuses donations on more viable projects, leading to more funded projects, and, ultimately, higher realized donors』 utility.

參考文獻：Yicheng Song, Zhuoxin Li, Nachiketa Sahoo. Matching Returning Donors to Projects on Philanthropic Crowdfunding Platforms. Management Science, 2022, 68(1), 355–375.

19、在廉價談話溝通中我們是戰略上天真還是以信任和可信賴為指導?

在許多商業和經濟環境中，利益衝突方之間經常進行廉價談話的溝通。當前，存在兩種截然不同的行為經濟學理論，即信任嵌入模型和level-k模型，用來解釋人類決策者之間的廉價談話是如何起作用的。信任嵌入模型認為，決策者的信任和值得信賴是由非金錢動機所驅動的。相比之下，level-k模型認為決策者純粹是自利的，但他們的戰略思考能力有限。儘管兩種理論在不同的背景下，都成功地解釋了廉價談話行為，但它們指出了人類行為的不同驅動因素。在本文中，我們第一次在同一背景下對這兩種理論進行直接比較。結果表明，在一個充分代表了許多實際情況的閒聊環境中，這兩個模型作出了特徵上截然不同且經驗上可區分的預測。通過來自此情景的過去的實驗數據，我們確定了每個模型能夠很好地捕捉到廉價談話行為的哪些方面，以及哪個模型(或模型組合)具有更好的解釋能力和預測性能。我們發現，信任嵌入模型的解釋是主要的。因此，我們的研究結果強調了在系統和流程上進行投資的重要性，以促進信任和值得信賴的關係，從而促進更有效的廉價交談互動。

Cheap-talk communication between parties with conflicting interests is common in many business and economic settings. Two distinct behavioral economics theories, the trust-embedded model and the level-k model, have emerged to explain how cheap talk works between human decision makers. The trust-embedded model considers that decision makers are motivated by nonpecuniary motives to be trusting and trustworthy. In contrast, the level-k model considers that decision makers are purely self-interested but limited in their ability to think strategically. Although both theories have been successful in explaining cheap-talk behaviors in separate contexts, they point to contrasting drivers for human behaviors. In this paper, we provide the first direct comparison of both theories within the same context. We show that, in a cheap-talk setting that well represents many practical situations, the two models make characteristically distinct and empirically distinguishable predictions. We leverage past experiment data from this setting to determine what aspects of cheap-talk behavior each model captures well and which model (or combination of models) has better explanatory power and predictive performance. We find that the trust-embedded model emerges as the dominant explanation. Our results, thus, highlight the importance of investing in systems and processes to foster trusting and trustworthy relationships in order to facilitate more effective cheap-talk interactions.

參考文獻：Xiaolin Li, Özalp Özer, Upender Subramanian. Are We Strategically Naïve or Guided by Trust and Trustworthiness in Cheap-Talk Communication?. Management Science, 2022, 68(1), 376–398.

20、管理自我複製的創新產品

受自我複製3D打印機和創新農牧產品的啟發，我們研究了自我複製創新產品製造商的最佳生產和銷售策略，重點是獨特的「保留或出售」權衡—即新生產的單位是應該出售以滿足需求和刺激未來的需求，還是加入庫存以增加生產能力。我們採用連續時間最優控制框架，將生產方面的自我複製模型與需求方面的典型創新-擴散模型相結合。通過分析該模型，我們確定了區分強可複製性和弱可複製性制度的條件，其中生產和銷售分別優先於對方，並全面描述了它們不同的最優策略。這些見解在包括積壓的需求、流動性約束、隨機創新擴散、啟動庫存決策和外生需求等擴展中被證明是穩健和有用的。。我們還發現，社交營銷策略特別適合在強複製下的自我複製的創新商品。

Inspired by self-replicating three-dimensional printers and innovative agricultural and husbandry goods, we study optimal production and sales policies for a manufacturer of self-replicating innovative goods with a focus on the unique 「keep-or-sell」 trade-off—namely, whether a newly produced unit should be sold to satisfy demand and stimulate future demand or added to inventory to increase production capacity. We adopt the continuous-time optimal control framework and marry a self-replication model on the production side to the canonical innovation-diffusion model on the demand side. By analyzing the model, we identify a condition that differentiates Strong and Weak Replicability regimes, wherein production and sales, respectively, take priority over the other and fully characterize their distinct optimal policies. These insights prove robust and helpful in several extensions, including backlogged demand, liquidity constraints, stochastic innovation diffusion, launch inventory decision, and exogenous demand. We also find that social marketing strategies are particularly well suited for self-replicating innovative goods under Strong Replication.

參考文獻：Bin Hu, Zhankun Sun (2021) Managing Self-Replicating Innovative Goods. Management Science 68(1):399-419.

21、時間是最明智的顧問：家庭保健中醫護人員與患者接觸時間的價值

家庭醫療保健是美國醫療保健領域快速發展的領域。我們研究了它在向基於價值的護理轉變中的作用，因為它被視為降低成本和使用昂貴的下游醫療保健服務的途徑。使用關於家庭健康訪問的新數據集，我們研究醫護人員在對最近出院的患者進行家庭健康訪問期間花費的時間是否以及如何影響患者重新入院的可能性。由於未觀察到的患者健康狀況可能會影響家庭健康訪問的時間長度和再次入院的可能性，我們使用每個醫護人員在重點訪問前後30天內進行的所有其他事件的平均訪問長度作為訪問長度的工具。使用這種工具變量方法並控制操作、人口統計學和病人病情相關的特徵，我們發現：平均而言，在重點家庭健康訪問期間多出的一分鐘與該訪問後再次入院的可能性減少1.39%有關。我們的發現表明，就診時間增加 10% 會使家庭健康就診後再次入院的可能性降低 6%。我們記錄了這種效應在不同患者類型和就診類型中的異質性。我們進行的成本效益分析表明，投資於額外的家庭保健能力的成本被減少住院所帶來的成本節約所抵消。

Home healthcare is a rapidly growing area of the health sector in the United States. We study its role in the shift toward value-based care, as it is viewed as an avenue for achieving reductions in the cost and utilization of expensive downstream healthcare services. Using a novel data set on home healthcare visits, we examine whether and how the amount of time that a provider spends during a home health visit with a recently discharged patient impacts the patient’s likelihood of being readmitted to the hospital. Because unobserved patient health status may influence both the length of a home health visit and the likelihood of hospital readmission, we use the within-provider average visit length of all other episodes』 visits conducted by each provider in the 30-day period before and after the focal visit as an instrument for visit length. Using this instrumental variable approach and controlling for operational, demographic, and patient condition-related characteristics, we find the following: on average, an extra minute during a focal home health visit is associated with a 1.39% decrease in the likelihood of readmission to the hospital following that visit. Our finding suggests that a 10% increase in visit length would decrease the likelihood of readmission following a home health visit by 6%. We document heterogeneity in this effect across different patient types and visit types. We conduct a cost–benefit analysis that suggests that the cost of investing in additional home health capacity is outweighed by the cost savings arising from fewer hospitalizations.

參考文獻：Hummy Song, Elena Andreyeva, Guy David (2021) Time Is the Wisest Counselor of All: The Value of Provider–Patient Engagement Length in Home Healthcare. Management Science 68(1):420-441.

22、具有左位偏差的實證討價還價模型：汽車貸款月供研究

本文研究了在處理數字時雙方都存在左位偏差時的價格討價還價問題。實證分析側重於美國汽車金融市場，使用了 3500 萬輛汽車貸款的大型數據集。在討價還價中加入左位偏差是由幾個有趣的觀察結果推動的。汽車貸款的預定每月還款額以 9 美元和 0 美元結尾，尤其是超過 100 美元時。此外，9 美元期末貸款的利率較高，0 美元期末貸款利率較低。我們開發了一個納什討價還價模型，允許汽車經銷商的消費者和財務經理都存在左位偏差。結果表明，雙方都受制於這種基本的人為偏見：以9 美元和下一個以 0 美元結尾的付款額之間的感知差異大於 1 美元，尤其是以 99 美元和 00 美元結尾的付款額之間的感知差異。所提出的模型可以解釋不同結尾數字的貸款的支付聚合和利率差異現象。我們使用反事實來顯示左位偏差的細微影響，這可以增加和減少付款。總體而言，與沒有偏見的基準案例相比，雙方的偏見導致每筆貸款的平均還款額增加了 33 美元。

This paper studies price bargaining when both parties have left-digit bias when processing numbers. The empirical analysis focuses on the auto finance market in the United States, using a large data set of 35 million auto loans. Incorporating left-digit bias in bargaining is motivated by several intriguing observations. The scheduled monthly payments of auto loans bunch at both $9- and $0-ending digits, especially over $100 marks. In addition, $9-ending loans carry a higher interest rate, and $0-ending loans have a lower interest rate. We develop a Nash bargaining model that allows for left-digit bias from both consumers and finance managers of auto dealers. Results suggest that both parties are subject to this basic human bias: the perceived difference between $9- and the next $0-ending payments is larger than $1, especially between $99- and $00-ending payments. The proposed model can explain the phenomena of payments bunching and differential interest rates for loans with different ending digits. We use counterfactuals to show a nuanced impact of left-digit bias, which can both increase and decrease the payments. Overall, bias from both sides leads to a $33 increase in average payment per loan compared with a benchmark case with no bias.

參考文獻：Zhenling Jiang (2021) An Empirical Bargaining Model with Left-Digit Bias: A Study on Auto Loan Monthly Payments. Management Science 68(1):442-465.

23、零售結構性投資中尋求回報

不斷增長的零售結構性投資產品市場以及此類產品定價過高的經驗證據，提出了私人投資者在結構性投資情境下風險偏好增強的假設。本文設計了一個基於累積前景理論的兩階段框架田野試驗來驗證這一假設。首先引出受試者對基礎指數未來表現的預期。然後應用二分法推導20個簡單的量身定製存款的確定性等價量。研究結果支持了風險偏好增加假設，揭示了研究對象在評估存款時會獲得大量收益，而忽略了尾部損失事件。類似的結果也出現在後續的實驗中，即用風險型存款替換不確定存款。儘管以往研究認為複雜條款的誤解和樂觀情緒會導致結構性工具的錯誤定價，但目前的實驗表明，在控制預期的情況下，非標準的風險偏好表現在對簡單的定義明確的產品的估值上。

The growing market for retail structured investment products and empirical evidence for excessive pricing of such products raise the hypothesis that private investors show increased risk appetite in structured investment contexts. A two-stage framed field experiment building on cumulative prospect theory is designed to test this hypothesis. Subjects』 expectations regarding the future performance of an underlying index are elicited first. A bisection algorithm is then applied to derive the certainty equivalents of 20 simple individually tailored deposits. The results support the increased risk appetite hypothesis, revealing that subjects reach for substantial gains and underweight tail loss events when evaluating the deposits. Similar results emerge in a follow-up experiment where the uncertain deposits are replaced by risky versions. While previous studies propose that misperception of complex terms and optimism contribute to the mispricing of structured instruments, the current experiments show that nonstandard risk appetite manifests in the valuation of simple well-defined products, controlling for expectations.

參考文獻：Doron Sonsino, Yaron Lahav, Yefim Roth (2021) Reaching for Returns in Retail Structured Investment. Management Science 68(1):466-486.

24、人群中的隱藏專家：使用元預測來利用單問題預測問題的專業知識

現代預測算法利用群體的智慧可做出比最好的可辨識專家更好的預測。然而，當人群存在系統性偏差或在各預測者之間專業知識差異較大時，這些算法可能是不準確的。最近的研究表明，即使沒有任何外部信息（如預測者過去的表現），元預測—對他人平均預測的預測—也可以用來修正偏差。我們探討元預測是否也可以通過識別和利用預測者的專業知識來改善預測。我們開發了由Prelec、Seung和McCoy提出意外流行算法（Surprisingly Popular algorithm）的基於置信度的版本。與原算法一樣，我們的新算法對偏差具有魯棒性。然而，與原始算法不同的是，根據預測，我們的版本總是對具有更多信息量的私人信號的預測者比具有較少信息量的預測者賦予更高的權重。在一系列的實驗中，我們發現改進後的算法在加權知情預測者方面比原算法做得更好，並且表明在類似的決策問題上更經常正確的個體比其他預測者對最終決策的貢獻更大。實證表明，對於一組500個的決策問題，改進算法優於原算法。

Modern forecasting algorithms use the wisdom of crowds to produce forecasts better than those of the best identifiable expert. However, these algorithms may be inaccurate when crowds are systematically biased or when expertise varies substantially across forecasters. Recent work has shown that meta-predictions—a forecast of the average forecasts of others—can be used to correct for biases even when no external information, such as forecasters』 past performance, is available. We explore whether meta-predictions can also be used to improve forecasts by identifying and leveraging the expertise of forecasters. We develop a confidence-based version of the Surprisingly Popular algorithm proposed by Prelec, Seung, and McCoy. As with the original algorithm, our new algorithm is robust to bias. However, unlike the original algorithm, our version is predicted to always weight forecasters with more informative private signals more than forecasters with less informative ones. In a series of experiments, we find that the modified algorithm does a better job in weighting informed forecasters than the original algorithm and show that individuals who are correct more often on similar decision problems contribute more to the final decision than other forecasters. Empirically, the modified algorithm outperforms the original algorithm for a set of 500 decision problems.

參考文獻：Tom Wilkening, Marcellin Martinie, Piers D. L. Howe (2021) Hidden Experts in the Crowd: Using Meta-Predictions to Leverage Expertise in Single-Question Prediction Problems. Management Science 68(1):487-508.

25、貸款合同菜單對借款人行為的影響

我們研究呈現給決策者的合同菜單（包括她可能無法選擇的合同）如何影響她選擇有回報但有風險的行動，而不是選擇回報低、風險小的行動。我們通過一系列以向美國學生借款人提供的貸款還款選項為模型的實驗室實驗來做到這一點，在不同可用和不可用貸款還款計劃菜單以及是否知道不可用選項的設置下，分析借款人的任務（職業）選擇。在這些實驗中，我們觀察到與標準經濟模型的預測不一致的行為，在標準經濟模型中，代理人可以輕鬆做出複雜的決策，並且選擇集中的每個備選方案都獨立於其他潛在選項進行評估。相反，我們提供的證據表明，擴大選擇菜單或讓代理人意識到她被拒絕的選擇會影響合同的價值。我們的實證研究結果與行為模型最為一致，這些模型允許對事後被證明為次優的選擇產生預期的遺憾，或者對簡單性的偏好，以及對無需做出選擇的感激。

We study how the menu of contracts presented to a decision maker—including contracts she may be precluded from choosing—affects her choice of remunerative but risky actions relative to lower paying, less risky alternatives. We do this through a series of laboratory experiments modeled after the loan repayment options offered to U.S. student borrowers, analyzing borrowers』 task (career) choices in settings that vary the menu of available and unavailable loan repayment plans and knowledge of unavailable options. In these experiments, we observe behavior that is inconsistent with predictions from standard economic models in which agents can easily make complex decisions and each alternative in a choice set is evaluated independently of other potential options. Instead, we provide evidence that expanding the menu of choices or making an agent aware of choices that she has been denied can affect how a contract is valued. Our empirical findings are most consistent with behavioral models that allow for anticipated regret over a choice that turns out to be suboptimal ex post or preferences for simplicity and gratitude for being unburdened from having to make a choice.

參考文獻：Katharine G. Abraham, Emel Filiz-Ozbay, Erkut Y. Ozbay, Lesley J. Turner (2021) Effects of the Menu of Loan Contracts on Borrower Behavior. Management Science 68(1):509-528.

26、多重信念、支配地位和動態一致性

本文研究多重信念下的多期決策。我們探討完全序和不完全序的動態一致性。我們關注一個支配性概念，其通過排除在一組信念中被占優的策略，支持在多種不確定性特徵下的決策制定。我們揭示了兩類動態不一致性的區別，我們把這種區別標記為謬誤的（fallacious）和易錯的（fallible）不一致性。當先驗最優策略在第二階段次優時，會出現謬誤的不一致性，從而要求決策者偏離原策略。從第二期偏好的角度看，當一個先驗的次優的第二期行動不再是次優的時候，就會發生易錯的不一致。我們給出了動態一致性的相應定義，並證明了兩類一致性對於完全序是等價的，而對於不完全序則是不同的。主觀期望效用是動態一致的，而非期望效用決策規則，如minmax則不是。我們表明，對信念的支配關係介於兩者之間：它不受更嚴重的謬誤的不一致的影響，但受到問題較少的易錯的不一致的影響。我們用一個數值例子說明了方法和概念，此算例解決了一個焦點的、現實的氣候變化風險和模糊性問題。

This paper investigates multiperiod decisions under multiple beliefs. We explore the dynamic consistency of both complete and incomplete orderings. We focus on a dominance concept that supports decision-making under multiple characterizations of uncertainty by ruling out strategies that are dominated across a set of beliefs. We uncover a distinction between two types of dynamic inconsistency, which we label fallacious and fallible inconsistency. Fallacious inconsistency occurs when an a priori optimal strategy is suboptimal in the second period, thus requiring the decision-maker to depart from the original strategy. Fallible inconsistency occurs when an a priori suboptimal second-period action ceases being suboptimal from the perspective of the second-period preferences. We introduce corresponding definitions of dynamic consistency and show that the two types of consistency are equivalent for complete orderings, but differ for incomplete orderings. Subjective expected utility is dynamically consistent and non-expected-utility decision rules, such as minmax, are not. We show that the dominance relation over beliefs falls between these two: it is immune to the more severe fallacious inconsistency, but not to the less problematic fallible inconsistency. We illustrate the method and concepts using a numerical example addressing a focal, real-world problem of risk and ambiguity regarding climate change.

參考文獻：Tommi Ekholm, Erin Baker (2021) Multiple Beliefs, Dominance and Dynamic Consistency. Management Science 68(1):529-540.

27、組合概率預測：60%和60%是60%，但可能（Likely）和可能（Likely）是非常可能（Very Likely）

我們如何結合他人的概率預測？先前的研究表明，當顧問提供數字概率預測時，人們通常會對其進行平均（即他們更接近於顧問的平均預測）。然而，如果顧問們說某個事件"可能（likely）"或"可能（probable）"發生呢？在八項研究中(n = 7，334)，我們發現，與 "計算 "數字概率相比，人們更傾向於"計算 "語言概率（即比任何單獨顧問的預測更接近確定性）。例如，當顧問們都說一個事件是"可能的（likely）"時，參與者會說它是"非常可能的（very likely）"。對於高於和低於 50% 的概率、假設情景和真實事件，以及同時或依次呈現其他預測的情形下，都會出現這種影響。我們還表明，這種組合策略會延續到隨後的消費者決策，這些決策依賴於顧問的可能性判斷。我們討論並排除了幾種可能的作用機制。

How do we combine others』 probability forecasts? Prior research has shown that when advisors provide numeric probability forecasts, people typically average them (i.e., they move closer to the average advisor’s forecast). However, what if the advisors say that an event is 「likely」 or 「probable?」 In eight studies (n = 7,334), we find that people are more likely to act as if they 「count」 verbal probabilities (i.e., they move closer to certainty than any individual advisor’s forecast) than they are to 「count」 numeric probabilities. For example, when the advisors both say an event is 「likely,」 participants will say that it is 「very likely.」 This effect occurs for both probabilities above and below 50%, for hypothetical scenarios and real events, and when presenting the others』 forecasts simultaneously or sequentially. We also show that this combination strategy carries over to subsequent consumer decisions that rely on advisors』 likelihood judgments. We discuss and rule out several candidate mechanisms for our effect.

參考文獻：Robert Mislavsky, Celia Gaertig (2021) Combining Probability Forecasts: 60% and 60% Is 60%, but Likely and Likely Is Very Likely. Management Science 68(1):541-563.

28、公共數據的私人影響：Landsat 衛星地圖增加了黃金髮現並鼓勵進入者進入

公共數據如何影響私營部門在位者和進入者的相對績效？運用一個簡單的理論框架，我認為公開數據減少了投資不確定性，便於發現新的市場機會，增加了新進入者相對於在位者的相對市場份額。我通過估算美國國家航空航天局衛星測圖計劃Landsat的公共數據對黃金勘探行業在位者（資深者）和進入者（資淺者）新礦床發現率的影響，來說明這些預測。我利用各地區Landsat覆蓋範圍內不同的時間變化和雲覆蓋來確定公共數據對黃金髮現模式的因果影響。我發現，在一個地區被測繪後，Landsat數據使重大黃金髮現率幾乎翻倍，並使新進入者的市場份額從大約10%增加到25%。公共數據似乎在驅動企業間績效差異方面發揮着重要的作用，但研究相對較少。

How does public data shape the relative performance of incumbents and entrants in the private sector? Using a simple theoretical framework, I argue that public data reduces investment uncertainty, facilitates the discovery of new market opportunities, and increases the relative market share of new entrants relative to incumbents. I shed light on these predictions by estimating the impact of public data from Landsat, a U.S. National Aeronautics and Space Administration satellite mapping program, on the discovery rates of new deposits by incumbents (seniors) and entrants (juniors) in the gold exploration industry. I exploit idiosyncratic timing variation and cloud cover in Landsat coverage across regions to identify the causal effect of public data on the patterns of gold discovery. I find that Landsat data nearly doubled the rate of significant gold discoveries after a region was mapped and increased the market share of new entrants from about 10% to 25%. Public data seem to play an important, yet relatively underexplored, role in driving performance differences across firms.

參考文獻：Abhishek Nagaraj (2021) The Private Impact of Public Data: Landsat Satellite Maps Increased Gold Discoveries and Encouraged Entry. Management Science 68(1):564-582.

29、從分析師反饋到自願資本支出指導、投資效率和公司績效的管理學習

我們檢驗預測：發布自願資本支出指導的管理者從分析師反饋中學習，這種學習提高了投資效率和企業績效。我們的發現與這些預測是一致的。首先，我們發現，經理人的資本支出調整和資本支出指導修正與分析師反饋正相關，分析師反饋通過事後指導分析師資本支出預測與經理人資本支出指導的差異來衡量。第二，投資效率變化與分析師反饋呈正相關。第三，後續公司財務績效與經理人的資本支出調整和資本支出指導修正的預測值均呈正相關。這些發現擴展了有關管理學習和投資效率來源的先前證據，有助於解釋在資本支出指導方面，管理者從相關股價效應中學習的潛力有限的情況下，管理者積極發布自願指導。

We test predictions that managers issuing voluntary capex guidance learn from analyst feedback and that this learning enhances investment efficiency and firm performance. Our findings are consistent with these predictions. First, we find that managers』 capex adjustments and capex guidance revisions relate positively with analyst feedback measured by differences between postguidance analyst capex forecasts and managerial capex guidance. Second, changes in investment efficiency relate positively with analyst feedback. Third, subsequent firm financial performance relates positively with the predicted values of both managers』 capex adjustments and capex guidance revisions. These findings extend prior evidence regarding sources of managerial learning and investment efficiency and help to explain the active issuance of voluntary guidance by managers in settings where, as for capex guidance, the potential for managerial learning from related share price effects is limited, as we also explain.

參考文獻：Jihun Bae, Gary C. Biddle, Chul W. Park (2021) Managerial Learning from Analyst Feedback to Voluntary Capex Guidance, Investment Efficiency, and Firm Performance. Management Science 68(1):583-607.

30、估值不確定性與賣空限制：來自IPO後市場的證據

我們使用首次公開募股（IPO）的設定來提供證據，證明估值不確定性和賣空限制的綜合作用會導致股市的重大錯誤定價。我們預計在即期後市場最容易出現高價的IPO首日回報率為47%，鎖定期滿回報率為-9%。我們對證券借貸市場數據的詳細分析證實了這些IPO經歷了嚴重的賣空限制，在鎖定期滿前後最為嚴重。本文既解釋了IPO的異常定價，又突出了估值不確定性和賣空限制在解釋股權錯誤定價中的重要性。

We use the initial public offering (IPO) setting to provide evidence that the combination of valuation uncertainty and short-sales constraints generates significant equity market mispricing. The IPOs that we predict to be most susceptible to overpricing in the immediate aftermarket have first-day returns of +47% and lockup expiration returns of −9%. Our detailed analysis of securities lending market data confirms that these IPOs experience severe short-sales constraints that peak around the lockup expiration. Our paper both explains the anomalous pricing of IPOs and highlights the importance of valuation uncertainty and short-sales constraints in explaining equity mispricing.

參考文獻：Panos N. Patatoukas, Richard G. Sloan, Annika Yu Wang (2021) Valuation Uncertainty and Short-Sales Constraints: Evidence from the IPO Aftermarket. Management Science 68(1):608-634.

31、證券市場的管道：交易後收費對交易和福利的影響

我們分析與證券市場的「管道」（即清算、結算、託管）相關的交易對手信息和成本的市場設計選擇如何影響市場質量和福利。我們的模型比較了用來分配費用的兩種交易後的費用結構。一種是對所有交易收取統一的費用，另一種是基於邊際成本的內部化交易收取較少的費用（這兩種交易者來自同一經紀人，處理成本較低）。市場設計和收費結構都會影響報價攻擊性和交易量及其構成。在邊際成本收費和交易對手信息可用的情況下，交易員通過報價的激進性來決定目標對手是哪個，權衡執行概率與收費。社會規劃者可以通過要求基於邊際成本收費，並為交易者提供披露交易對手信息的選擇，實現福利最大化。

We analyze how market design choices about counterparty information and costs related to the 「plumbing」 (i.e., clearing, settlement, and custody) of securities markets affect market quality and welfare. Our model compares two post-trade fee structures for allocating these costs. One charges a uniform fee for all trades and the other, marginal cost–based structure a reduced fee for internalized trades (which, both traders being from the same broker, is less costly to process). Both market design and fee structure affect quote aggressiveness and trading volume and its composition. With marginal cost–based fees and counterparty information being available, traders decide which counterparties to target through quote aggressiveness, trading off execution probability against fee. A social planner can maximize welfare by requiring marginal cost–based fees and providing traders the choice to disclose counterparty information.

參考文獻：Hans Degryse, Mark Van Achter, Gunther Wuyts (2021) Plumbing of Securities Markets: The Impact of Post-trade Fees on Trading and Welfare. Management Science 68(1):635-653.

32、保證理論：平衡代價高昂的正式控制與高層的語氣

高層非正式語氣（TATT）被廣泛認為是組織控制的基本要素，但由於其柔和性，TATT的研究並沒有強調數學建模。我觀察到TATT引用了最高管理層設定的例子。我將TATT建模為其他等同條件下，反映了首席執行官（CEO）不會為了個人利益而轉移組織資源的預期。該設置假定，CEO是從一個勞動力池中隨機抽取的，勞動力池中包括那些看重職業前景（高類型）或不看重職業前景（低類型）的候選人。對解僱和職業受損的恐懼意味着高類型相比於低類型傾向於更少的機會主義，而低類型會為了個人利益而轉移組織資源。與信任和脆弱性相輔相成的觀點相反，我確定了TATT和最優成本正式控制是互補的條件。但我也在同樣的設定中表明，TATT和最優正式控制可以相互替代。這一結果也解釋了為什麼高水平的TATT可能不會受到外部審計師或某些利益相關者的歡迎，並解釋了模稜兩可的薩班斯-奧克斯利法案報告。

Informal tone at the top (TATT) is widely regarded as a fundamental ingredient of organizational control, yet because of its soft nature, the scholarship on TATT has not emphasized mathematical modeling. Observing that TATT refers to the example set by top management, I model TATT as, ceteris paribus, reflecting the expectation that the chief executive officer (CEO) will not divert organizational resources for personal benefit. The setting assumes that CEOs are randomly drawn from a labor pool containing candidates who either value career prospects (high type) or who do not value career prospects (low type). The fear of dismissal and a damaged career mean that high types tend to be less opportunistic than low types, who divert for personal gain. Contrary to the belief that trust and vulnerability go hand in hand, I identify conditions where TATT and optimal costly formal controls are complements. But I also show in the same setting that TATT and optimal formal controls can be substitutes. The results also explain why high levels of TATT may not be welcomed by the external auditor or certain stakeholders and explain ambiguous Sarbanes-Oxley reports.

參考文獻：Mark Penno (2021) A Theory of Assurance: Balancing Costly Formal Control with Tone at the Top. Management Science 68(1):654-668.

33、邊緣對沖：參數化貨幣疊加

我們提出了一種利用貨幣價值、套利和動量來代理預期貨幣收益的全球股票投資者最優貨幣對沖策略。一個基準風險約束保證了疊加（overlay）緊密地模仿一個完全對沖的投資組合。我們將此與naïve對沖和替代性對衝進行了嚴格的樣本外檢驗，並考慮了交易和再平衡成本以及保證金要求。其他套期保值方法通常會降低風險，但會付出代價。有的傾向於高回報的短期貨幣，而所有的貨幣都會在摩擦中產生大量的成本，主要是保證金要求和股權再平衡成本。本文提出的策略使用可預測的回報來降低這種成本。與完全對沖基準相比，Sharpe率增長17%，年化Jensen-α增長0.93%。值得注意的是，無論如何，該策略的大部分實施成本都將由基準承擔。這降低了其邊際成本，並凸顯了套期保值與投機整合的特定協同作用。

We propose an optimal currency hedging strategy for global equity investors using currency value, carry, and momentum to proxy for expected currency returns. A benchmark risk constraint ensures the overlay closely mimics a fully hedged portfolio. We compare this with naïve and alternative hedges in a demanding out-of-sample test, with transaction and rebalancing costs and margin requirements. Other hedging methods generally reduce risk but at a cost. Some tend to short currencies with high returns and all incur substantial costs with frictions, mostly margin requirements and equity rebalancing costs. The proposed strategy uses predictable returns to reduce this cost. It produces a statistically significant 17% gain in Sharpe ratio and an annualized Jensen-α of 0.93% versus a fully hedged benchmark. Notably, most of the implementation costs of the strategy would be incurred by the benchmark anyway. This reduces its marginal cost and highlights a specific synergy of integrating hedging with speculation.

參考文獻：Pedro Barroso, Jurij-Andrei Reichenecker, Marco J. Menichetti (2021) Hedging with an Edge: Parametric Currency Overlay. Management Science 68(1):669-689.

34、具有許多大模型的投資組合選擇

本文提出了一種具有許多大模型的貝葉斯平均異質向量自回歸投資組合選擇策略，在眾多日、周、月數據集上的樣本外表現優於現有方法。該戰略假設超額收益大致由一個帶有大量解釋變量的隨時間變化的回歸決定，這些解釋變量是過去收益的樣本平均。投資者通過跟蹤許多模型來考慮每個時期都有機制變化的可能性，但懷疑是否有任何規範能夠完美地預測未來收益的分布，並計算出對模型錯誤規範具有魯棒性的投資組合選擇。

This paper proposes a Bayesian-averaging heterogeneous vector autoregressive portfolio choice strategy with many big models that outperforms existing methods out-of-sample on numerous daily, weekly, and monthly datasets. The strategy assumes that excess returns are approximately determined by a time-varying regression with a large number of explanatory variables that are the sample means of past returns. Investors consider the possibility that every period there is a regime change by keeping track of many models, but doubt that any specification is able to perfectly predict the distribution of future returns, and compute portfolio choices that are robust to model misspecification.

參考文獻：Evan Anderson, Ai-ru (Meg) Cheng (2021) Portfolio Choices with Many Big Models. Management Science 68(1):690-715.

35、過去不成功的回購對未來回購決策的影響

我們發現，當管理者在過去的股票回購中虧損時，他們回購股票的可能性較小，但沒有發現有力的證據表明過去的回購收益會影響未來的回購活動。這種不對稱的敏感性對於年輕的CEO和任期最短的CEO來說最為強烈。另外，對於之前在股市經歷不利的 CEO，未來的回購對過去的回購損失更為敏感。未來回購對過去損失的敏感性平均每年使公司損失約 3.7%。當這一成本被分解為系統性和特異性的部分時，我們發現近一半（1.8%）來自於對特異性衝擊的錯誤判斷。過去的回購損失對CEO未來的獎金有顯著的負面影響，並增加了未來CEO非自願離職的可能性。我們還發現，過去回購的負面結果鼓勵了隨後的股息使用。我們的研究結果表明，過去回購的結果通過非行為（職業關注）和行為（蛇咬效應）因素產生了重大的經濟後果。

We find that managers are less likely to repurchase stocks when they lose money on past stock repurchases but find no robust evidence that past gains on repurchases influence future repurchasing activity. This asymmetric sensitivity is strongest for young CEOs and those with the shortest tenure. Also, future repurchases are more sensitive to past repurchase losses for CEOs whose previous lifetime experience with the stock market is unfavorable. The sensitivity of future repurchases to past losses costs firms, on average, about 3.7% per year. When this cost is decomposed into systematic and idiosyncratic components, we find that nearly half (1.8%) comes from mistiming idiosyncratic shocks. Past losses on repurchases have a significant and negative impact on the CEO’s future bonus and increase the likelihood that future CEO termination is involuntary. We also find that negative outcomes from past repurchases encourage the subsequent use of dividends. Our findings suggest that outcomes of past repurchases have economically significant consequences through both nonbehavioral (career concerns) and behavioral (snakebite effect) factors.

參考文獻：Geoffrey C. Friesen, Noel Pavel Jeutang, Emre Unlu (2021) The Effect of Unsuccessful Past Repurchases on Future Repurchasing Decisions. Management Science 68(1):716-739.

36、消亡的傳染擴散

我們研究了在不完全信息下的多企業均衡中的違約問題。違約與公司的資產負債表和匯總一致。研究結果表明，隨着經濟中企業數量的增加，其他企業衝擊所產生的債務和股權的內生波動性和跳躍幅度消失。因此，信用利差僅漸近依賴於企業自身的現金流風險。本文研究得到的傳染擴散消失的結果，對最近基於生產經濟的研究結果提出了質疑，在這些研究中，風險數量（證券的波動率和跳躍幅度）是外生給定的，這使得信用利差主要歸因於傳染。

We study default in a multifirm equilibrium setting with incomplete information. Defaults are consistent with the firm’s balance sheet and aggregation. We show that the endogenous volatility and jump size of debt and equity generated by other firms』 shocks vanish as the number of firms in the economy increases. As a result, credit spreads depend asymptotically only on the firms』 own cash flow risk. Our vanishing contagion spread result calls into question recent findings based on production economies, in which quantities of risk (volatilities and jump sizes of securities) are specified exogenously, that attribute credit spreads mostly to contagion.

參考文獻：Diogo Duarte, Rodolfo Prieto, Marcel Rindisbacher, Yuri F. Saporito (2021) Vanishing Contagion Spreads. Management Science 68(1):740-772.

37、投資者情緒和股票期權行權條款

利用行權條款的細節信息，我們證實了在投資者情緒高漲時期授予的股票期權往往具有較短的行權期和持續時間，並且相對於情緒低落時期，其更有可能完全行權或在授予日期後一年內行權的部分明顯增多。我們進一步發現，當公司主要由投資期限較短的投資者（例如，臨時機構）持有時，情緒對行權條款的影響更為明顯。此外，在情緒高漲時期，短期行權條款與未來的併購活動和資本支出呈正相關。總體而言，我們的研究結果與理論預測一致，即在投機市場中，股東用短期導向的薪酬合同來激勵經理人，以促使經理人採取維持過高估值的行動。

Using the details of vesting terms, we document that stock options granted in high-investor-sentiment periods tend to have shorter vesting periods and durations and are more likely to vest completely or have a significantly larger fraction vested within one year of the grant date, relative to low-sentiment periods. We further find that the sentiment effect on vesting terms is more pronounced when firms are largely held by investors with short investment horizons (e.g., transient institutions). Moreover, short vesting terms in high-sentiment periods are positively associated with future mergers-and-acquisitions activity and capital expenditures. Overall, our findings are consistent with theoretical predictions that, in a speculative market, shareholders incentivize managers with short-term-oriented compensation contracts to induce managers to pursue actions maintaining overvaluation.

參考文獻：Shawn X. Huang, Sami Keskek, Juan Manuel Sanchez (2021) Investor Sentiment and Stock Option Vesting Terms. Management Science 68(1):773-795.

38、關於 "激勵持續努力的最優合同 "的評論

在這篇評論中，我們首先用一個反例來證明論文（[Sun P， Tian F (2018) Optimal contract to induce continued effort. Management Sci. 64(9):4193–4217]）第 4節中提出的最優合同結構在兩個參與者的貼現率不同時可能是錯誤的。之後我們給出正確的最優合同結構，這包括泛化合同空間以允許隨機終止。在廣泛的模型參數下的數值實驗表明，這種隨機終止在最優合同中很少發生。此外，通過最優合同相對於無隨機終止的最好合同的相對改進程度來衡量的次優差距是非常小的。

In this comment, we first use a counterexample to demonstrate that the optimal contract structure proposed in section 4 of the paper [Sun P, Tian F (2018) Optimal contract to induce continued effort. Management Sci. 64(9):4193–4217] can be wrong when the two players』 discount rates are different. We then specify correct optimal contract structures, which involve generalizing the contract space to allow random termination. Numerical study with a wide range of model parameters illustrates that such a random termination only occurs sparingly in optimal contracts. Moreover, the suboptimality gap, measured by the relative improvement of the optimal contract over the best contract without random termination, is extremely small.

參考文獻：Ping Cao, Feng Tian, Peng Sun (2021) Comment on 「Optimal Contract to Induce Continued Effort」. Management Science 68(1):796-808.