1. 在线广告、数据共享和消费者控制

原标题：Online Advertising, Data Sharing, and Consumer Control

期刊：Management Science

作者：Justin P. Johnson, Thomas Jungbauer, Marcel Preuss

出版时间：2024-01-30

DOI：10.1287/mnsc.2022.03385

摘要：我们从产权角度出发，研究了广告交易所之间的竞争如何影响这些交易所向广告商提供的定向选择。当广告商对有关消费者主动购买兴趣的数据拥有强大的产权时，广告交易所之间的竞争就会导致数据共享过少。这可能会损害消费者的利益，因为他们收到的相关广告太少，而广告商本身也会因为类似囚徒困境的情况而受到损害。我们发现，将财产权重新分配给消费者，即赋予他们选择退出追踪的权利，也可以通过改变广告交易商提供更好的定向选择的动机，使允许追踪的消费者受益。此外，我们还发现，苹果和谷歌限制第三方追踪并引入诸如谷歌的主题等替代追踪系统的举措，可能通过削弱广告商的数据产权来使消费者受益。由于这些系统默认共享更多数据，因此即使这些系统的准确性低于第三方追踪系统，这种情况也会发生。

Abstract: Invoking a property rights approach, we examine how competition between advertising exchanges influences the targeting options that these exchanges make available to advertisers. When advertisers have strong property rights over data regarding consumers’ active purchase interests, competition between ad exchanges leads to too little sharing of data. This may harm consumers, who receive too few pertinent ads, and advertisers themselves can also be harmed due to a situation resembling a prisoner’s dilemma. We find that reallocating property rights to consumers, that is, giving them the right to opt out of tracking may also benefit consumers who allow tracking by altering the incentives of ad exchanges to offer improved targeting options. In addition, we show that initiatives by Apple and Google to limit third-party tracking and to introduce alternative tracking systems such as Google’s Topics might benefit consumers by weakening the data property rights of advertisers. Because more data are shared by default under such systems, this can be true even if these systems are less accurate than third-party tracking systems.

2. 基于在线评论的产品重新设计和创新：多阶段组合搜索方法

原标题：Product Redesign and Innovation Based on Online Reviews: A Multistage Combined Search Method

期刊：Journal on Computing

作者：Jindong Qin, Pan Zheng, Xiaojun Wang

出版时间：2024-01-17

DOI：10.1287/ijoc.2022.0333

摘要：在电子商务平台上发布的在线评论为设计师开发新产品提供了新的信息来源。过去利用用户生成的文本数据进行新产品开发（NPD）的研究通常仅专注于提取和识别待改进的产品特征。然而，对产品特征的竞争性分析以及更具体的改进策略并没有得到深入探讨。本研究充分利用在线评论文本丰富的语义属性，提出了一种新颖的在线评论驱动建模框架。这种新方法可以提取细粒度的产品特征；计算它们的重要性、性能和竞争力；并为每个特征构建一个竞争网络。因此，决策过程得到了帮助，并且针对NPD的具体产品改进策略超越了该领域现有的建模方法。具体而言，首先利用多重嵌入模型将在线评论分类为重新设计和创新相关的主题，然后采用互信息多层特征提取方法相应地提取重新设计和创新的产品特征。此外，通过个性化的单向二部图算法计算特征的重要性和性能，并获取特征的竞争力和竞争力网络。最后，构建重要性-性能-竞争力分析图，并通过多阶段组合搜索算法开发产品改进策略。案例研究和比较实验显示了该方法的有效性，并为产品供应商、经理和设计师等利益相关者提供了新颖的商业见解。

Abstract: Online reviews published on the e-commerce platform provide a new source of information for designers to develop new products. Past research on new product development (NPD) using user-generated textual data commonly focused solely on extracting and identifying product features to be improved. However, the competitive analysis of product features and more specific improvement strategies have not been explored deeply. This study fully uses the rich semantic attributes of online review texts and proposes a novel online review–driven modeling framework. This new approach can extract fine-grained product features; calculate their importance, performance, and competitiveness; and build a competitiveness network for each feature. As a result, decision making is assisted, and specific product improvement strategies are developed for NPD beyond existing modeling approaches in this domain. Specifically, online reviews are first classified into redesign- and innovation-related themes using a multiple embedding model, and the redesign and innovation product features can be extracted accordingly using a mutual information multilevel feature extraction method. Moreover, the importance and performance of features are calculated, and the competitiveness and competitiveness network of features are obtained through a personalized unidirectional bipartite graph algorithm. Finally, the importance performance competitiveness analysis plot is constructed, and the product improvement strategy is developed via a multistage combined search algorithm. Case studies and comparative experiments show the effectiveness of the proposed method and provide novel business insights for stakeholders, such as product providers, managers, and designers.

3. 通过在线农业平台提高农民收入：来自实地的证据

原标题：Improving Farmers’ Income on Online Agri-Platforms: Evidence from the Field

期刊：Manufacturing & Service Operations Management

作者：Retsef Levi, Manoj Rajan, Somya Singhvi, Yanchong Zheng

出版时间：2024-03-06

DOI：10.1287/msom.2022.0437

摘要：问题定义：为了改善小农户的福利，多个国家（例如埃塞俄比亚和印度）推出了在线农业平台，以改变传统市场。然而，关于这些平台的影响以及更一般地说，它们如何可以被利用以实现更高效的农业供应链和市场仍存在着不一致的证据。本文描述了与印度卡纳塔克邦政府密切合作进行的工作，旨在设计、实施和评估该州在线农业平台——联合市场平台（UMP）上的新的两阶段拍卖的影响。方法学/结果：为了确保可实施性并保护农民的收入，拍卖设计受到实际运营考虑以及与该领域大多数交易商的半结构化访谈的指导。通过对实地见解的新行为拍卖模型的制定，确定了何时提出的两阶段拍卖可以为农民带来比传统的单阶段、首价封闭竞标拍卖更高的收入。该新拍卖机制于2019年2月在UMP上的一个主要豆类市场上实施。截至2019年5月底，价值超过600万美元（USD）的大宗商品已在新一轮拍卖中成交。差异分析法（DID）表明，该实施为在处理市场交易的10000多个农民带来了3.6%的显著价格增长（相当于55%-94%的利润增长）。管理含义：本文的结果提供了关于如何通过在线农业平台在资源受限环境中启用创新的价格发现机制的实际经验。重要的是，这些设计的成功在很大程度上取决于对影响实体市场交易的系统运营和行为因素的慎重考虑。

Abstract: Problem definition: To improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched online agri-platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and, more generally, how they can be leveraged to enable more efficient agricultural supply chains and markets. This paper describes work conducted in close collaboration with the state government of Karnataka, India, to design, implement, and assess the impact of a new two-stage auction on the state’s online agri-platform, the United Market Platform (UMP). Methodology/results: To ensure implementability and protect farmers’ revenue, the auction design is guided by practical operational considerations, as well as semistructured interviews with a majority of the traders in the field. A new behavioral auction model informed by the field insights is developed to determine when the proposed two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By the end of May 2019, commodities worth more than $6 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 3.6% price increase (corresponding to a 55%–94% profit gain) for over 10,000 farmers who traded in the treatment market. Managerial implications: The results from this paper offer tangible lessons on how innovative price discovery mechanisms could be enabled by online agri-platforms in resource-constrained environments. Importantly, the success of these designs critically depends on careful considerations of systemic operational and behavioral factors that affect trades in the physical markets.

4. 用户如何在双边市场中推动价值：重要的平台设计

原标题：How Users Drive Value in Two-Sided Markets: Platform Designs That Matter

期刊：MIS Quarterly

作者：Zhou Zhou; Lingling Zhang; Van Alstyne, Marshall

出版时间：2024-03-21

DOI：10.25300/MISQ/2023/17012

摘要：现有研究普及了一种观点，即强大的网络效应产生“赢家通吃”的结果，这导致平台投资于用户增长，并鼓励投资者补贴这些平台。然而，用户增长并不一定意味着强大的用户粘性。如果没有用户粘性，当前时期的强大网络效应可能会在未来时期消退，从而使用户增长战略无效。通过给网络效应增加一个时间维度，我们开发了一个跨期和期内网络效应模型，以解释不同类型的网络效应如何驱动价值。我们强调跨期同侧网络效应有助于用户粘性，而期内跨侧网络效应的持续取决于用户粘性。我们认为平台具有异质跨期同侧网络效应的一个原因是“产品学习”机制：预计不确定性较高的产品具有更强的跨期同侧网络效应。基于不同的驱动因素，我们将客户终身价值模型（CLV2）扩展到双边平台市场，使我们能够衡量不同的干预措施如何推动平台价值。使用Groupon数据，我们验证了我们的见解，并讨论了在跨期同侧网络效应较弱时增强用户粘性的平台设计选择。

Abstract: Extant research has popularized the perspective that strong network effects produce “winner-take-all” outcomes, which leads platforms to invest in user growth and encourages investors to subsidize these platforms. However, user growth does not necessarily imply strong user stickiness. Without user stickiness, strong network effects in the current period may fade in future periods, thus rendering a user growth strategy ineffective. By adding a time dimension to network effects, we developed a model of cross-period and within-period network effects to explain how different types of network effects drive value. We emphasize that the cross-period same-side network effect contributes to user stickiness, while the within-period cross-side network effect persists conditional on user stickiness. We propose that one reason for platforms having heterogeneous cross-period same-side network effects is because of the “product learning” mechanism: it is expected that products with higher uncertainty have a stronger cross-period same-side network effect. Based on different drivers, we extend the customer lifetime value model (CLV2) to two-sided platform markets, allowing us to measure how different interventions drive platform value. Using Groupon data, we verify our insights and discuss platform design choices that enhance user stickiness when the cross-period same-side network effect is weak.

5. 双边市场中的质量选择：一种受约束的价格歧视方法

原标题：Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach

期刊：Operations Research

作者：Bar Light, Ramesh Johari, Gabriel Weintraub

出版时间：2024-01-05

DOI：10.1287/opre.2020.0754

摘要：在线平台收集有关参与者的丰富信息，然后与他们分享部分信息，以改善市场结果。在本文中，我们研究了双边市场中的以下信息披露问题：如果平台希望实现收益最大化，平台应该允许哪些卖家参与，平台应该与买家分享多少关于参与卖家质量的可用信息？我们在两个不同的双边市场模型中研究了这个信息披露问题：一个是平台选择价格，卖家选择数量（类似于共享单车），另一个是卖家选择价格（类似于电子商务）。我们的主要结果提供了一些条件，在这些条件下，实践中常见的简单信息结构（如禁止某些卖家进入平台和不区分参与卖家）能使平台收益最大化。平台的信息披露问题自然会转化为一个受约束的价格歧视问题，其中的约束条件由所研究的特定双边市场模型的均衡结果决定。我们通过分析这个有约束的价格歧视问题得出结构性结果。

Abstract: Online platforms collect rich information about participants and then share some of this information back with them to improve market outcomes. In this paper, we study the following information disclosure problem in two-sided markets: if a platform wants to maximize revenue, which sellers should the platform allow to participate, and how much of its available information about participating sellers’ quality should the platform share with buyers? We study this information disclosure problem in the context of two distinct two-sided market models: one in which the platform chooses prices and the sellers choose quantities (similar to ride sharing), and one in which the sellers choose prices (similar to e-commerce). Our main results provide conditions under which simple information structures commonly observed in practice, such as banning certain sellers from the platform and not distinguishing between participating sellers, maximize the platform’s revenue. The platform’s information disclosure problem naturally transforms into a constrained price discrimination problem in which the constraints are determined by the equilibrium outcomes of the specific two-sided market model being studied. We analyze this constrained price discrimination problem to obtain our structural results.

6. 不使用价格行使市场力量：线上杂货店的服务时间

原标题：Exercising Market Power Without Using Prices: Service Time in Online Grocery

期刊：Management Science

作者：Itai Ater, Adi Shany

出版时间：2024-04-04

DOI：10.1287/mnsc.2022.01820

摘要：本文研究了在线杂货商如何在全国统一定价的情况下，通过服务时间来应对当地的竞争和需求条件。利用三年内每周两次从172个以色列当地市场收集的综合数据，我们发现在线杂货商在所有市场都会设定相同的价格。相比之下，在竞争更激烈的市场和低需求日，服务时间更短。接下来，我们利用进入决策的地区和时间差异，研究当新的在线杂货商进入市场时，原有企业如何调整其服务时间。在低需求日和垄断市场中，现有企业的服务时间明显缩短。这种下降始于进入市场前不久，当新进入者构成较大竞争威胁时，下降幅度更大。在高需求日和竞争性市场中，我们没有发现服务时间在进入市场前几个月有明显变化。我们的研究结果表明，当价格反应迟钝时，企业会利用服务时间来行使其本地市场支配力，而运营方面的考虑因素会影响企业的反应程度。

Abstract: This paper studies how online grocers use service time to respond to local competition and demand conditions when prices are uniformly set at the national level. Using comprehensive data collected twice a week over three years from 172 Israeli local markets, we show that an online grocer sets identical prices in all markets. By contrast, service time is shorter in more competitive markets and on low-demand days. Next, we exploit regional and temporal variation in entry decisions to examine how the incumbent adjusts its service time when new online grocers enter the market. The incumbent’s service time falls significantly on low-demand days and in monopolistic markets. This decrease begins shortly before entry and is greater when the entrant poses a larger competitive threat. On high-demand days and in competitive markets we do not find a significant change in service time in the months surrounding entry. Our findings suggest that firms use service time to exercise their local market power when prices are unresponsive and that operational considerations affect the extent to which they respond.

7. 数据沙漠和黑匣子：社会经济地位对消费者画像的影响

原标题：Data Deserts and Black Boxes: The Impact of Socio-Economic Status on Consumer Profiling

期刊：Management Science

作者：Nico Neumann, Catherine E. Tucker, Levi Kaplan, Alan Mislove, Piotr Sapiezynski

出版时间：2024-01-31

DOI：10.1287/mnsc.2023.4979

摘要：数据经纪人使用黑匣子方法对个人进行广告定位的画像和分段，但往往效果参差不齐。我们通过5个互补的现场测试和15家数据经纪人提供的证据表明，对这些属性的画像准确性和覆盖率的差异主要取决于被画像的对象是谁。相对更富裕的消费者，例如收入较高或居住在富裕地区的人，既更有可能被画像，也更有可能被准确地画像。职业地位（白领与蓝领工作）、种族和族裔、性别以及家庭安排通常会影响画像信息的准确性和可用性的可能性，尽管这在国家和我们是否考虑画像属性的在线或离线覆盖范围中有所不同。我们的分析表明，成功的消费者背景画像可以与个人的数字足迹范围相关联，包括他们在线时间的长短和拥有的数字设备数量。来自低收入背景的人具有较窄的数字足迹，导致这些人的“数据沙漠”。供应商特征，包括画像方法的差异，几乎不能解释我们的数据中画像准确性的变化，但解释了被画像的可能性的变化。由于对不同背景的个体的不同访问权限，供应商之间的差异也会间接影响画像结果。我们讨论了我们的发现对政策和营销实践的影响。

Abstract: Data brokers use black-box methods to profile and segment individuals for ad targeting, often with mixed success. We present evidence from 5 complementary field tests and 15 data brokers that differences in profiling accuracy and coverage for these attributes mainly depend on who is being profiled. Consumers who are better off—for example, those with higher incomes or living in affluent areas—are both more likely to be profiled and more likely to be profiled accurately. Occupational status (white-collar versus blue-collar jobs), race and ethnicity, gender, and household arrangements often affect the accuracy and likelihood of having profile information available, although this varies by country and whether we consider online or offline coverage of profile attributes. Our analyses suggest that successful consumer-background profiling can be linked to the scope of an individual’s digital footprint from how much time they spend online and the number of digital devices they own. Those who come from lower-income backgrounds have a narrower digital footprint, leading to a “data desert” for such individuals. Vendor characteristics, including differences in profiling methods, explain virtually none of the variation in profiling accuracy for our data, but explain variation in the likelihood of who is profiled. Vendor differences due to unique networks and partnerships also affect profiling outcomes indirectly due to differential access to individuals with different backgrounds. We discuss the implications of our findings for policy and marketing practice.