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【文献速递】Marketing Science,Volume 44, Issue 5, September-October 2025
采编: 陈姝霖 校对: 李健博 终审:邵兵家
2025年9-10月的Marketing Science（UTD 24）有12篇文章，主题有隐私监管对消费者营销的预期与非预期后果、大规模枪击事件及其对零售业的影响、用于内容实验的大语言模型辅助在线学习算法、专家的产品选择建议、可持续消费对企业策略的影响、B2B 市场中职业关联对价格与盈利能力的作用、带约束条件的可扩展定向营销策略优化、禁止主动派发门店传单对零售业的影响、短视频平台广告投入价值、企业隐私声誉在长期博弈中的承诺机制作用、基于细分数据的电动汽车动态离散需求模型、搜索疲劳对消费者选择延迟及企业策略的影响等。
1.Frontiers: The Intended and Unintended Consequences of Privacy Regulation for Consumer Marketing
前沿：隐私监管对消费者营销的预期与非预期后果
2.Mass Shootings and Their Impact on Retail
大规模枪击事件及其对零售业的影响
3.LOLA: LLM-Assisted Online Learning Algorithm for Content Experiments
LOLA：用于内容实验的大语言模型辅助在线学习算法
4.Expert’s Recommendations in Product Choices: Information Provision, Conflicts of Interest, and Consumer Protection among U.S. Kidney Disease Patients
专家的产品选择建议：美国肾病患者的信息供给、利益冲突及消费者保护5.Sustainable Consumption: A Strategic Analysis
可持续消费：一项战略分析
6.The Value of Professional Ties in B2B Markets
B2B市场中职业关联的价值探析
7.Optimizing Scalable Targeted Marketing Policies with Constraints
带约束条件的可扩展定向营销策略优化
8.Banning Unsolicited Store Flyers: Does Helping the Environment Hurt Retailing?
禁止主动派发门店传单：助力环保是否会损害零售业？
9.Is the Money Spent on Short-Form Video Social Platforms Worth It? The Role of Advertising Spillover in a Large-Scale Randomized Field Experiment on ByteDance
短视频社交平台投入是否值得？字节跳动大规模随机实地实验中的广告溢出效应研究
10.Reputation for Privacy
隐私声誉研究
11.CCP Estimation of Dynamic Discrete Choice Demand Models with Segment Level Data and Continuous Unobserved Heterogeneity: Rethinking EV Subsidies vs. Infrastructure
基于细分市场数据与连续未观测异质性的动态离散选择需求模型 CCP 估计：电动汽车补贴与基础设施的再思考
12.Search Fatigue, Choice Deferral, and Closure
搜索疲劳、选择延迟与决策终结
摘要
1.Frontiers:The Intended and Unintended Consequences of Privacy Regulation for Consumer Marketing
前沿：隐私监管对消费者营销的预期与非预期后果
作者：Jean-Pierre Dubé, John G. Lynch, Dirk Bergemann, Mert Demirer, Avi Goldfarb, Garrett Johnson, Anja Lambrecht, Tesary Lin, Anna Tuchman和Catherine Tucker
Abstract:As businesses increasingly rely on granular consumer data, the public has increasingly pushed for enhanced regulation to protect consumers’ privacy. We provide a perspective based on the academic marketing literature that evaluates the various benefits and costs of existing and pending government regulations and corporate privacy policies. We make four key points. First, data-based personalized marketing is not automatically harmful. Second, consumers have heterogeneous privacy preferences, and privacy policies may unintentionally favor the preferences of the rich. Third, privacy regulations may stifle innovation by entrepreneurs who are more likely to cater to underserved, niche consumer segments. Fourth, privacy measures may favor large companies who have less need for third-party data and can afford compliance costs. We also discuss technology platforms’ recent proposals for privacy solutions that mitigate some of these harms but, again, in a way that might disadvantage small firms and entrepreneurs.
摘要：随着企业对精细化消费者数据的依赖程度日益加深，公众也不断呼吁加强监管以保护消费者隐私。本文基于营销学术文献提出一种观点，对现行及待实施的政府监管措施与企业隐私政策所具备的各类益处及成本进行评估，并得出四个核心结论：第一，基于数据的个性化营销并非必然具有危害性；第二，消费者的隐私偏好存在异质性，而隐私政策可能会在无意中更偏向高收入群体的偏好；第三，隐私监管可能会抑制企业家的创新活力，而这类群体往往更倾向于服务那些未被充分满足的细分消费群体的需求；第四，隐私保护措施可能对大型企业更为有利，因为它们对第三方数据的需求较低，且有能力承担合规成本。此外，本文还探讨了科技平台近期提出的隐私解决方案，这些方案虽能在一定程度上缓解上述部分问题，但同样可能会加剧小型企业和创业者劣势的风险。
2. Mass Shootings and Their Impact on Retail
前沿：大规模枪击事件及其对零售业的影响
作者：Khai Chiong, Seung Mok (Simon) Kim和TI Tongil Kim
Abstract: Mass shootings in the United States have become more frequent, often targeting retail locations such as shopping malls that attract high foot traffic. We combine detailed data on mass shootings with debit and credit card transaction data at individual stores to assess the economic impact of mass shootings. Using a difference-in-differences framework, we find that affected stores experience lower demand, smaller order sizes, decreased foot traffic, and reduced customer dwell times, resulting in a significant decline in retail revenues. We also find the impact of mass shootings diminishes with distance, adversely affecting stores within a radius of up to 1.25 miles. Additionally, we examine the likelihood of store closures after incidents and factors contributing to store survival. Overall, we estimate the annual economic cost of mass shootings at $27 billion in lost revenues to retail businesses. Consistent with consumers’ fear and safety concerns, we observe heterogeneous effects by business type (e.g., nonessential stores are more impacted than essential stores), channel substitution from in-person to online shopping, and moderation by local exposure to gun-related violence.
摘要：美国大规模枪击事件的发生频率日益上升，这类事件常瞄准商场等客流量大的零售场所。本研究将大规模枪击事件的详细数据与各门店的借记卡及信用卡交易数据相结合，系统评估此类事件对零售业造成的经济影响。通过双重差分模型分析发现，受事件影响的门店面临需求下降、订单规模缩小、客流量减少及顾客停留时间缩短等问题，最终导致零售收入显著下滑。研究还表明，大规模枪击事件的影响程度随距离增加而减弱，仅会对事件发生地1.25英里半径范围内的门店产生不利影响。此外，本文还考察了事件发生后门店倒闭的可能性，以及影响门店存续的相关因素。综合测算显示，大规模枪击事件每年给零售业造成的收入损失高达270亿美元。与消费者因恐惧和安全担忧而改变行为的逻辑一致，研究观察到了不同业态间的异质性影响（如非必需品类门店受冲击更大），从线下到线上购物的渠道替代现象，以及当地涉枪暴力事件的暴露程度也会对上述影响产生调节作用。
3.LOLA: LLM-Assisted Online Learning Algorithm for Content Experiments
LOLA：用于内容实验的大语言模型辅助在线学习算法
作者：Zikun Ye, Hema Yoganarasimhan和Yufeng Zheng
Abstract: Modern media firms require automated and efficient methods to identify content that is most engaging and appealing to users. Leveraging a large-scale data set from Upworthy (a news publisher), which includes 17,681 headline A/B tests, we first investigate the ability of three pure–large language model (LLM) approaches to identify the catchiest headline: prompt-based methods, embedding-based methods, and fine-tuned open-source LLMs. Prompt-based approaches perform poorly, while both OpenAI embedding–based models and the fine-tuned Llama-3-8B achieve marginally higher accuracy than random predictions. In sum, none of the pure LLM–based methods can predict the best-performing headline with high accuracy. We then introduce the LLM-assisted online learning algorithm (LOLA), a novel framework that integrates LLMs with adaptive experimentation to optimize content delivery. LOLA combines the best pure-LLM approach with the upper confidence bound algorithm to allocate traffic and maximize clicks adaptively. Our numerical experiments on Upworthy data show that LOLA outperforms the standard A/B test method (the current status quo at Upworthy), pure bandit algorithms, and pure-LLM approaches, particularly in scenarios with limited experimental traffic. Our approach is scalable and applicable to content experiments across various settings where firms seek to optimize user engagement, including digital advertising and social media recommendations.
摘要：现代媒体企业需要自动化且高效的方法，以识别对用户最具吸引力和感染力的内容。本研究利用新闻发布平台Upworthy的大规模数据集（包含17681 组标题A/B测试数据），首先考察了三种纯大型语言模型（LLM）方法识别最吸睛标题的能力，具体包括提示词驱动法、嵌入驱动法以及微调开源 LLM 法。结果显示，提示词驱动法表现不佳，而基于OpenAI嵌入的模型与微调后的 Llama-3-8B模型，其准确率仅略高于随机预测。综上，所有纯 LLM 方法均无法高精度预测表现最佳的标题。为此，我们提出了LLM辅助在线学习算法（LOLA），这是一个将LLM与自适应实验相结合的新型框架，旨在优化内容推送效果。LOLA将最优纯LLM方法与上限置信区间算法相融合，能够自适应地分配流量并最大化点击量。在Upworthy数据集上开展的数值实验表明，LOLA的性能优于标准 A/B 测试法（Upworthy当前采用的常规方法）、纯Bandit算法及纯LLM方法，尤其在实验流量有限的场景中优势更为显著。该方法具备可扩展性，适用于各类场景下的内容实验，只要企业以优化用户参与度为目标，无论是数字广告还是社交媒体推荐领域，均可应用此方法。
4.Expert’s Recommendations in Product Choices: Information Provision, Conflicts of Interest, and Consumer Protection among U.S. Kidney Disease Patients
专家的产品选择建议：美国肾病患者的信息供给、利益冲突及消费者保护
作者：Reza Roshangarzadeh, TI Tongil Kim和Shervin Shahrokhi Tehrani
Abstract: Consumers in high-stakes product markets, such as healthcare or finance, often rely on experts’ recommendations before making a purchase decision. However, how an expert constructs a specific set of recommendations and how it subsequently affects consumer choices and outcomes have been understudied. We propose an empirical framework that econometrically recovers experts’ recommendations and combines them with heterogeneous consumers’ choice of products or services. We then apply the framework to examine kidney disease patients’ choice of dialysis facilities. Using detailed data on more than 16,900 U.S. patients with kidney disease who had consultations with over 750 physicians between 2015 and 2017, we study physicians’ dialysis facility recommendations and patients’ subsequent choice of facilities. We find that physicians are more likely to recommend facilities with which they are affiliated and those close to patients. Policy simulations suggest that quality information provision through five-star ratings has likely lowered mortality, thereby helping patients. In contrast, reducing conflicts of interest by banning the usage of affiliation as a basis for physicians’ facility recommendations can inadvertently hurt patients as evidenced by an increase in mortality. The study provides relevant consumer-centric insights into recent efforts to change market regulations and policies in this healthcare market.
摘要：在医疗、金融等高风险产品市场中，消费者在做出购买决策前，往往依赖专家的建议。然而，目前关于专家如何构建具体建议推荐方案以及其如何影响消费者选择与最终结果的研究仍较为薄弱。本文提出了一个实证分析框架，通过计量方法还原专家的建议内容，并将其与异质性消费者对产品或服务的选择行为相结合。我们将该框架应用于肾病患者对透析机构的选择研究中，利用2015-2017年间美国16900余名肾病患者（曾咨询过750余名医生）的详细数据，分析了医生给出的透析机构建议及患者后续的机构选择行为。研究发现，医生更倾向于推荐与自身存在合作关系，以及地理位置靠近患者的机构。政策模拟结果显示，通过五星评级形式向患者提供透析机构的质量信息，可能降低患者死亡率，从而对患者产生积极帮助。相反，若通过禁令限制医生基于合作关系推荐机构，虽然可以减少利益冲突，却可能会因患者死亡率上升而对患者造成不利影响。本研究为近期医疗市场监管政策调整提供了以消费者为核心的相关洞见。
5.Sustainable Consumption: A Strategic Analysis
可持续消费：一项战略分析
作者：Wilfred Amaldoss和Siddharth Prusty
Abstract: Consumers’ growing concern for the environment has motivated firms to offer sustainable products in several categories. An exploratory survey shows that many consumers desire sustainable products and are willing to pay more for them, but some consumers dislike sustainable products and want to pay less for them. Using a theoretical model where firms are horizontally differentiated and two groups of consumers have divergent preferences for sustainable products, we investigate the strategic implications of sustainable consumption. First, our analysis shows that when consumers’ dislike for sustainable products is moderate, the price could increase as the dislike increases. Moreover, price could decrease if consumers’ desire for sustainable products increases. Second, we find that competing firms’ profits can decrease with consumers’ desire for sustainability but increase with consumers’ dislike for sustainability. Third, we clarify when and why enforcing minimal sustainability standards for products can backfire and reduce consumer surplus. Finally, we extend the model to capture additional facets of sustainable consumption, such as multiproduct firms, sustainable luxury goods, and political orientation of consumers, and tease out its counterintuitive implications for the firms supplying sustainable products.
摘要：消费者对环境问题的关注度日益提升，这促使企业在多个品类中推出可持续产品。一项探索性调查显示，许多消费者渴望获得可持续产品，且愿意为其支付更高价格，但也有部分消费者对可持续产品持排斥态度，仅愿以更低价格购买。通过构建横向差异化企业模型，结合两组消费者对可持续产品的分歧偏好，本研究揭示了可持续消费的战略性影响。第一，本文分析表明，当消费者对可持续产品的排斥程度处于中等水平时，产品价格可能会随排斥程度的上升而提高。此外，若消费者对可持续产品的渴望程度上升，产品价格反而可能下降。第二，竞争企业的利润可能会随消费者对可持续性的渴望程度提高而下降，却会随消费者对可持续性的排斥程度提高而上升。第三，本文明确了实施产品最低可持续标准何时及为何可能产生反效果，导致消费者剩余下降。最后，本文对模型进行了拓展，以涵盖可持续消费的更多维度，如多产品企业、可持续奢侈品、消费者的政治倾向等，进一步揭示了可持续产品供应中存在的反直觉规律。
6.The Value of Professional Ties in B2B Markets
B2B市场中职业关联的价值探析
作者：Navid Mojir和Sriya Anbil
Abstract:We study how a particular form of social ties (i.e., professional ties proxied by past employment) affects price and profitability in business-to-business (B2B) markets. Although most of the work on social ties focuses on information diffusion in business-to-consumer markets, we ask the following. Do B2B buyers receive higher or lower prices from sellers with whom they have professional ties? Can professional ties benefit both buyers and sellers and create win-win exchanges? Answering these questions is challenging because it is difficult to observe B2B prices, the individual decision makers (IDMs), and elements of differentiation that drive price variation. Moreover, potentially endogenous formation of social ties exacerbates the identification challenge. We resolve these challenges by leveraging proprietary data from the Federal Reserve on the repo market, the largest market for short-term loans with daily transactions of more than $2 trillion. In addition, we use financial disclosure laws to unmask IDMs at sellers and use LinkedIn to reveal their ties. We leverage exogenous movement of IDMs in and out of decision-making positions to identify the effect of professional ties on price. We show that a seller IDM, who is the buyer’s former employee, charges the buyer 1/4 basis points more than other buyers with no ties (i.e., 25 basis points relative to median price, or 13% of average cross-sectional price variance). The mechanism driving this price increase is “supply reliability.” Sellers with a professional tie to the buyer act more reliably toward that buyer during supply-demand imbalances. We perform several robustness checks, including leveraging the Federal Reserve’s monetary policy actions in response to the COVID-19 pandemic, to show that an exogenous increase in the aggregate cash supply diminishes the effect of professional ties, consistent with a supply reliability mechanism. Our work suggests professional ties can affect B2B prices beyond observable supply-demand dynamics and provide value for sellers and buyers.
摘要：本文研究了特定形式的社会关联（即通过过往雇佣关系衡量的职业关联）如何影响B2B市场中的价格与盈利能力。尽管多数关于社会关联的研究聚焦于B2C市场中的信息传播，但本文围绕以下问题展开探讨。B2B买家从与其存在职业关联的卖家处获得的价格会更高还是更低？职业关联能否同时使买卖双方形成双赢的交易关系？回答这些问题的核心挑战在于B2B市场中的价格、个体决策者以及导致价格差异的差异化要素均难以观测。此外，社会关联可能存在的内生性形成机制，进一步加剧了因果识别的难度。为解决这些挑战，本文利用了美国联邦储备委员会关于回购市场的专有数据，该市场是全球最大的短期贷款市场，日均交易量超过 2 万亿美元。此外，研究借助财务披露法规识别出卖方的个体决策者，并通过领英数据揭示这些决策者与买家之间的职业关联。本文利用个体决策者在决策岗位上的外生性变动（入职或离职），识别职业关联对价格的影响效应。研究发现，若卖家的个体决策者曾是买家的员工，该卖家向该买家收取的价格会比无关联买家高1/4个基点，这一涨幅相当于中位数价格的 25 个基点，或横截面平均价格方差的 13%。驱动这一价格上涨的机制是“供给可靠性”。在供需失衡时期，与买家存在职业关联的卖家会向该买家提供更稳定的供给。通过包括利用美联储疫情期间货币政策操作在内的多项稳健性检验，结果显示总现金供给的外生性增加会削弱职业关联的影响效应，这与供给可靠性机制的逻辑一致。本文的研究表明，在 B2B 市场中，职业关联对价格的影响超出了可观测的供需动态范畴，且能为买卖双方均创造价值。
7.Optimizing Scalable Targeted Marketing Policies with Constraints
带约束条件的可扩展定向营销策略优化
作者：Haihao Lu, Duncan Simester和Yuting Zhu
Abstract: Targeted marketing policies target different customers with different marketing actions. Although most research has focused on training targeting policies without managerial constraints, in practice, many firms face managerial constraints when implementing these policies. For example, firms may face volume constraints on the maximum or minimum number of actions they can take or on the minimum acceptable outcomes for different customer segments. They may also face similarity (fairness) constraints that require similar actions with different groups of customers. Traditional optimization methods face challenges when solving problems with either many customers or many constraints. We show how recent advances in linear programming can be adapted to the targeting of marketing actions. We provide a theoretical guarantee comparing how the proposed algorithm scales compared with state-of-the-art benchmarks (primal simplex, dual simplex, and barrier methods). We also extend existing guarantees on optimality and computation speed, by adapting them to accommodate the characteristics of targeting problems. We implement the proposed algorithm using data from a field experiment with over 2 million customers and six different marketing actions (including a no-action “Control”). We use this application to evaluate the computation speed and range of problems that the algorithm can solve, comparing it to benchmark methods. The findings confirm that the algorithm makes it feasible to train large-scale targeting problems that include volume and similarity constraints.
摘要：定向营销策略的核心在于针对不同用户实施差异化营销行为。尽管多数研究聚焦于在无管理约束条件下构建定向策略，但在实际场景中，许多企业在执行这类策略时会面临各类管理约束。例如，企业可能面临行为数量约束，即针对不同客群的最大/最小干预数量限制，或各细分市场的最低业绩门槛要求。也可能面临相似性（公平性）约束，即要求对不同客户群体采取具有一定相似性的营销行为。传统优化方法在处理客户数量庞大或约束条件繁多的问题时面临显著挑战。本文阐述了如何将线性规划领域的最新进展应用于营销行为定向问题。本文从理论层面证明了所提算法相较于当前主流基准算法（原始单纯形法、对偶单纯形法及内点法）的规模扩展优势，并通过调整现有算法最优性与计算速度的理论保证条件，使其适配定向营销问题的特征。基于一项涵盖 200 多万客户、包含 6 种不同营销行为（含不采取任何行动的对照组）的实地实验数据，本文对所提算法进行了实证检验。通过与基准方法的对比，评估了该算法的计算速度及可解决问题的范围。研究结果表明，该算法能够有效应对包含数量约束与相似性约束的大规模定向营销问题，为这类问题的求解提供了可行路径。
8.Banning Unsolicited Store Flyers: Does Helping the Environment Hurt Retailing?
禁止主动派发门店传单：助力环保是否会损害零售业？
作者：Jonne Y. Guyt, Arjen van Lin和Kristopher O. Keller
Abstract:Retailers often use store flyers to communicate the availability, price, and promotions of their products. Many households inspect store flyers for promotions, and the majority still prefer to receive store flyers in print. Yet, many are said to throw out store flyers unread, creating excessive waste that is environmentally damaging because of the excess use of paper, ink, and logistics. Legislation to reduce the distribution and waste associated with unsolicited store flyers has been proposed, but if and how much such a cut in distribution would affect households’ grocery shopping behavior remain unclear. This paper investigates a recent policy change by seven Dutch municipalities that implemented a ban on unsolicited store flyers by moving from an opt-out policy to an opt-in policy at some point between 2018 and 2020. Using household scanner data, the authors assess changes in shopping behavior along nine comprehensive dimensions relevant to retailers, brand manufacturers, and policymakers using a stacked, synthetic difference-in-differences approach. Although store flyer distribution decreased by 50% under the new policy, the drastic change did not substantially affect grocery shopping behavior. These findings are robust to different time windows and modeling approaches.
摘要：零售商通常会通过商店传单向消费者传递产品的供应情况、价格及促销信息。许多家庭会查看商店传单以了解促销活动，且大多数家庭仍倾向于接收纸质传单。然而，据调查有大量传单会未拆阅就丢弃，这种因纸张、油墨的过量使用以及物流环节所造成的浪费对环境造成不利影响。目前已有相关立法提案，旨在减少主动派发的商店传单的分发量及由此产生的浪费，但这种分发量削减会否影响家庭的食品杂货购物行为、影响程度如何，目前尚不明确。本文研究了荷兰 7 个自治市近期的一项政策调整：这些地区在 2018 至 2020 年间的某一时期，将商店传单的派发政策从“默认接收、可选择退出”（opt-out）改为“默认不接收、可选择加入”（opt-in），实质形成了对主动派发传单的禁令。本文利用家庭扫描数据（记录消费者购买行为的详细数据），采用堆叠式合成双重差分法，从 9 个涵盖零售商、品牌生产商及政策制定者关切点的综合维度，评估了家庭购物行为的变化。结果显示，新政策下商店传单的分发量减少了 50%，但这一剧烈变化并未对家庭的食品杂货购物行为产生显著影响。且该研究结论在不同时间窗口设定及不同建模方法下均具有稳健性。
9.Is the Money Spent on Short-Form Video Social Platforms Worth It? The Role of Advertising Spillover in a Large-Scale Randomized Field Experiment on ByteDance
短视频社交平台投入是否值得？字节跳动大规模随机实地实验中的广告溢出效应研究
作者：Yitian (Sky) Liang, Xinlei (Jack) Chen, Shengnan Han, Jinglong Zhang和Yubo Chen
Abstract:Short-form videos have taken over social media and attracted attention from advertisers. But doubts remain about the advertising efficacy on these platforms. In a large-scale randomized experiment on ByteDance, we show that advertising spillover plays a pivotal role in the advertising campaign. Most of the advertising effect comes from advertising spillover beyond ByteDance with exposed users being eight times more likely to convert from outside than from within ByteDance. When considering advertising spillover outside ByteDance, the average cost per conversion, which brands commonly use to evaluate the cost of campaigns, shrinks by 5 or 25 times, depending on the methods used to calculate it. Advertising spillover can also affect a brand’s targeting strategy. Whereas commonly used demographic variables by the automobile brand are effective for target marketing with only platform data, they are not when considering advertising spillover outside ByteDance. Instead, a behavioral variable proposed herein (prior brand home page visits) effectively moderates the advertising effect but has no impact when ignoring advertising spillover in the analysis. Our findings underscore the importance of information sharing between platforms and brands, which in practice is typically not the case.
摘要：短视频已主导社交媒体领域，并吸引了广告商的广泛关注，但外界对这类平台的广告效果仍存疑虑。在字节跳动平台开展的一项大规模随机实验中，我们发现广告溢出效应在广告活动中发挥着关键作用：广告效果的绝大部分来源于字节跳动平台之外的溢出效应，接触过广告的用户在平台外完成转化的概率，是在平台内完成转化概率的 8 倍。当纳入字节跳动平台外的广告溢出效应时，品牌方常用于评估广告活动成本的核心指标，即平均转化成本，会显著降低，降幅因计算方法不同可达 5 倍至 25 倍。广告溢出效应还会影响品牌的定向营销策略。以某汽车品牌为例，其常用的人口统计变量仅依靠平台内数据时，对定向营销具有一定效果，但在纳入平台外广告溢出效应后，这类变量便不再有效。相反，本文提出的一项行为变量（用户此前对品牌主页的访问记录）能有效调节广告效果，而若在分析中忽略广告溢出效应，该变量则无法产生任何影响。我们的研究结果凸显了平台与品牌方之间信息共享的重要性，而在实际操作中，这种信息共享往往未能实现。
10.Reputation for Privacy
隐私声誉研究
作者：Yunfei (Jesse) Yao
Abstract:As consumers become increasingly concerned about their privacy, firms can benefit from committing not to sell consumer data. However, the holdup problem prevents firms from doing so in a static setting. This paper studies whether reputation consideration of the firm can serve as a commitment device in a long-run game when consumers have imperfect monitoring technology. We find that a patient enough monopoly can commit because its reputation will suffer from a persistent punishment if consumers detect the data sale. In contrast, reputation may fail to serve as a commitment device when there are multiple firms. The penalty for selling data is temporary when consumers do not know exactly which firm sold the data. In addition, selling data imposes a negative externality on other firms, but each firm does not take it into account in equilibrium. We characterize conditions under which duopolistic firms lose the ability to commit even if they are arbitrarily patient. Reputation cannot serve as a commitment device under any conditions as the number of firms increases because each firm is penalized less for selling the data but not rewarded more for not doing so. Lastly, we explore several ways of restoring firms’ commitment power through regulation.
摘要：随着消费者对自身隐私的关注度日益提升，企业若承诺不售卖消费者数据，往往能从中获益。然而，在静态场景下，敲竹杠问题会阻碍企业践行这一承诺。本文研究了当消费者采用非完美监控技术时，在长期博弈框架下，企业的声誉考量能否成为一种承诺机制。研究发现，对于足够有耐心的垄断企业而言，其完全可以做出不售数据的承诺，因为一旦消费者察觉数据被售卖，企业的声誉将面临持续性惩罚。相反，当市场中存在多家企业时，声誉可能无法发挥承诺机制的作用。若消费者无法确切知晓究竟是哪家企业售卖了数据，售卖行为所面临的惩罚将是暂时性的。此外，售卖数据会对其他企业产生负外部性，但在均衡状态下，每家企业都不会将这种外部性纳入决策考量。本文明确了双寡头企业即便具备极高耐心，仍无法维持承诺的具体条件。随着企业数量增加，在任何情况下声誉都无法充当承诺机制，因为企业售卖数据所面临的惩罚会不断减轻，而不售卖数据也不会获得额外奖励。最后，本文还探讨了通过监管手段恢复企业承诺能力的多种路径。
11.CCP Estimation of Dynamic Discrete Choice Demand Models with Segment Level Data and Continuous Unobserved Heterogeneity: Rethinking EV Subsidies vs. Infrastructure
基于细分市场数据与连续未观测异质性的动态离散选择需求模型 CCP 估计：电动汽车补贴与基础设施的再思考
作者：Cheng Chou和Tim Derdenger
Abstract:When multiple groups of consumers reside in the same market, we determine that we can write each group’s conditional choice probabilities (CCPs) as a function of unobserved consumer heterogeneity. Moreover, we can specify choice probabilities of one group as a function of another by shifting the unobserved component. Armed with our novel CCP estimator, we develop an approach to identify and estimate a dynamic discrete demand model for durable goods with nonrandom attrition of consumers and continuous unobserved consumer heterogeneity but without the usual need for value function approximation or reducing the dimension of state space by ad hoc behavioral assumptions. We illustrate the empirical value of our method by estimating consumer demand for electric vehicles (EVs) in the state of Washington during the period of 2016–2019. We also determine the impact of a different federal tax credit based on the electric range of a car rather than the size of the battery, which was the existing policy during the data period, and we evaluate how best to seed a nascent market that presents indirect network effects to drive faster adoption. Should the government incentivize adoption through consumer tax credits or through EV infrastructure?
摘要：当多个消费者群体共存于同一市场时，我们确定可将每组消费者的条件选择概率表示为未观测到的消费者异质性的函数。此外，通过转移未观测成分，我们还能将某一组消费者的选择概率设定为另一组消费者选择概率的函数。借助我们提出的新型条件选择概率估计量，我们开发了一种方法，用于识别和估计耐用品的动态离散需求模型。该模型适用于存在消费者非随机流失与连续未观测消费者异质性的场景，且无需像常规方法那样进行价值函数近似，也无需通过特设行为假设来降低状态空间维度。为验证所提方法的实证价值，我们对 2016-2019 年期间美国华盛顿州消费者的电动汽车需求进行了估计。我们还分析了一项替代性联邦税收抵免政策（基于汽车的纯电续航里程，而非数据期内现行政策所依据的电池容量）的影响，并评估了在存在间接网络效应的新兴市场中，应采取何种最优策略推动市场快速渗透。政府究竟应通过消费者税收抵免，还是通过电动汽车基础设施建设来激励市场采纳？
12.Search Fatigue, Choice Deferral, and Closure
搜索疲劳、选择延迟与决策终结
作者：Z. Eddie Ning, J. Miguel Villas-Boas和Yunfei (Jesse) Yao
Abstract: When gathering information to make decisions, individuals often have to delay making a decision because the process of gathering information is interrupted, and the individual is not yet ready to make a decision. The paper considers a model of choice deferral based on time-varying search costs, potentially based on search fatigue, in which individuals have to strategically decide whether to defer choice when information gathering is interrupted, taking into account the current available information, and when they will be able to resume gathering information. We find that individuals are more likely to defer choice when information gathering is interrupted less frequently, when individuals can resume gathering information sooner, and when they discount the future less. We also consider the case in which individuals incur costs of restarting a process of information gathering and cases in which the individual has greater or less information about the extent of search fatigue. The paper also considers optimal pricing, user interface design, and retargeting decisions, and it shows how they should respond to the length of consumer browsing sessions and gaps between browsing sessions. The paper illustrates the importance of modeling fatigue and interruptions in the search process.
摘要：在个人收集信息以制定决策的过程中，常因信息收集过程中断而不得不推迟决策，而此时个体尚未做好决策准备。本文构建了一个基于时变搜索成本，潜在诱因是搜索疲劳的选择延迟模型。在该模型中，个体需结合当前已获取的信息以及恢复信息收集的时间节点，从策略层面决定当信息收集被中断时是否应推迟选择。研究发现，当信息收集中断频率较低，个体能更快恢复信息收集，以及个体对未来的贴现程度较低时，个体更可能推迟选择。本文还探讨了个体需承担信息收集过程重启成本，以及个体对搜索疲劳程度的了解程度存在差异的情景。本文还研究了最优定价、用户界面设计与再营销决策，并阐明了这些策略应如何根据消费者浏览会话时长及会话间隔进行调整。本文的研究结果充分凸显了在搜索过程模型中纳入疲劳因素与中断因素的重要性。
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