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【文献速递】MIS Quarterly，Volume 49, Issue 3, September 2025
2025年9月的MIS Quarterly（UTD 24）有16篇文章，主题有论述性证据在判断新闻真假中的说服效应、TikTok话题舞蹈挑战对缩小音乐行业艺术家性别差距的影响、数字平台对非约束性合同履约效果的改善、初始激励对医生贡献的影响、高风险社会运动中集体感的构建、增强现实技术对注意力管理及工作绩效的影响、注意力分散环境中的移动广告、自动化系统评价的机器学习方案、基于美国专利实证探索人工智能创新模式、平台生态系统中的互补者困境、投资者对勒索软件攻击与未遂事件的差异化反应、医疗信息技术与理赔拒付的相互作用、管理者对人工智能的决策委托意愿、众包评价中战略模糊性的实证研究、1950-2015年信息技术企业收入停滞现象、在信息系统研究中中平衡新颖性、严谨性、相关性等。
目 录
1.Fake News and True News Assessment: The Persuasive Effect of Discursive Evidence in Judging Veracity
虚假与真实新闻的评估：论述性证据在真实性判断中的说服效应
2.Dancing to the #Challenge: The Effect of TikTok on Closing the Artist Gender Gap in the Music Industry
与#挑战共舞：TikTok对缩小音乐行业艺术家性别差距的影响
3.Do Digital Platforms Improve the Performance of Nonbinding Contracts? Evidence From the Amazon Freight Platform
数字平台能否改善非约束性合同的履约效果？来自亚马逊货运平台的证据
4.Engaging Physicians with Introductory Incentives: References to Online and Offline Income
引导医生参与的初始激励：线上与线下收益的参照效应
5.Producing the “We” in High-Risk Online Activism: Identity Configurations in My Stealthy Freedom
高风险网络行动中“我们”身份构建：“我的隐秘自由”运动中的身份配置
6.Augmented Reality at Work: Attention Management and Its Impact on Work Performance
工作场景中的增强现实技术：注意力管理及其对工作绩效的影响
7.Mobile Advertising in Distracted Environments: Exploring the Impact of Distractions on Dual-Task Interference
分心环境中的移动广告：探究注意力分散对双任务干扰的影响
8.Automating in High-Expertise, Low-Label Environments: Evidence-Based Medicine by Expert-Augmented Few-Shot Learning
高专业度、低标签环境下的自动化：基于专家增强小样本学习的循证医学实践
9.Organizing for AI Innovation: Insights From an Empirical Exploration of U.S. Patents
人工智能创新的组织模式：基于美国专利的实证探索
10.The Complementor’s Dilemma: Navigating Growth Ambitions and the Dependency on Focal Actors in Platform Ecosystems
互补者困境：平台生态系统中非核心参与者的野心增长与其对核心参与者的依赖
11.Does Ransomware Make Investors “WannaCry”? On Investors’ Divergent Reactions to Ransomware Hits and Near Misses
勒索软件会让投资者“想哭”吗？投资者对勒索软件攻击与未遂事件的差异化反应
12.The Interplay Between Healthcare Information Technologies and Denied Claims
医疗信息技术与理赔拒付之间的相互作用机制
13.Find the Good. Seek the Unity: A Hidden Markov Model of Human-AI Delegation Dynamics
寻善求同：人机委托动态中的隐马尔可夫模型
14.An Empirical Study of Strategic Opacity in Crowdsourced Evaluations
众包评价中战略模糊性的实证研究
15.Information Technology Firms and Revenue Stall, 1950-2015: Theory and Empirical Evidence
1950-2015 年信息技术企业收入停滞现象：理论与实证研究
16.Editor’s Comments: Rebalancing Novelty with Rigor and Relevance in Information Systems Research
主编寄语：在信息系统研究中平衡新颖性、严谨性、相关性
1.Fake News and True News Assessment: The Persuasive Effect of Discursive Evidence in Judging Veracity
虚假与真实新闻的评估：论述性证据在真实性判断中的说服效应
作者：Abayomi Baiyere, Jan M. Bauer, Ioanna Constantiou和Daniel Hardt
Abstract: Individuals are often unable to assess the veracity of news claims—especially on social media platforms. Recent research has suggested that interventions indicating normative signals, such as flagging false claims, are not always effective. We propose an approach in which users are provided with discursive evidence to consider in determining the veracity of claims rather than depending on normative true or false flags. We conducted a series of experiments to explore the effects of different forms of discursive evidence on individual judgments of the veracity of news claims. We found that providing such evidence can significantly improve individuals’ judgment of both true and false news claims—with certain caveats. Providing discursive evidence with high evidence strength leads to a general increase in veracity judgment. Discursive evidence containing items with lower evidence strength may shift believability—thus improving judgments for either true or false claims but degrading them for the other. We also identify important asymmetries between true and false claims, finding that the effect of some evidence may be improved if people are in a more critical mindset—for example, by priming them to think about the concept of truth and lies. Taken together, these results extend knowledge on the problem of fake news and may suggest effective approaches to address the problem without diminishing attention to true news.
摘要：在社交媒体平台上，用户往往难以辨别新闻的真伪。最新研究表明，采用规范性信号的干预措施（如标记虚假内容）效果有限。本文提出一种替代方案：向用户提供可自行判断的论述性证据（discursive evidence），而非简单的“真/假”规范性标签。我们通过一系列实验，检验不同形式的论述性证据对个体判断新闻真实性的影响。结果显示，在特定条件下，论述性证据能显著提升用户对真、假新闻的辨识力。高证明力的论述性证据能普遍提升真实性判断准确度；而低证明力证据则可能“拉偏”可信度——对真或假新闻中的一方判断更准，却牺牲另一方的准确性。此外，我们发现真、假新闻存在显著不对称效应：当用户处于更具批判性的思维状态（如事先被引导思考“真与假”的概念）时，部分证据的说服效果可被放大。综上，本研究拓展了“假新闻”问题的研究边界，并为在保持真实新闻关注度的前提下有效治理假新闻提供了可行路径。
2.Dancing to the #Challenge: The Effect of TikTok on Closing the Artist Gender Gap in the Music Industry
与#挑战共舞：TikTok对缩小音乐行业艺术家性别差距的影响
作者：Yifei Wang, Jui Ramaprasad和Anandasivam Gopal
Abstract: This study investigates how “Hashtag Dance Challenges” (HDCs), a phenomenon popularized on the short-video platform TikTok, are instrumental in helping music artists gain traction in the digital music marketplace. HDCs represent an appealing combination of music and dance, designed to engage users and achieve virality, thereby benefiting artists whose music is featured. This research focuses on how HDCs contribute to the success of women artists, as compared to men, in an industry known for its diversity but challenged by gender inclusivity. We apply role congruity theory to posit that women artists are in a better position to derive benefits from being featured on HDCs, relative to male artists, particularly in cases of gender concordance—when both the creator and the artist are women. We measure the benefits of HDCs using daily changes in the artist’s followership on Spotify, a leading music streaming service, and test our hypotheses using song and artist-level data collected from Spotify and TikTok. We found that artists featured in a new HDC achieve a significant increase in followership on Spotify, relative to similar artists not featured in an HDC. Further, we observed that women creators drive this effect, enhancing the daily growth of Spotify followers by approximately 3% more for women artists, underscoring the value of gender concordance. Our findings shed light on the role of short videos, especially through the vehicle of HDCs, in advancing women artists, while also promoting inclusivity within the digital music industry.
摘要：本研究考察短视频平台 TikTok 上风靡的“话题舞蹈挑战”（Hashtag Dance Challenges, HDC）如何助力音乐人在数字市场突围。HDCs将音乐与舞蹈深度结合，激发用户参与并实现病毒式传播，从而让音乐作品被选用的艺术家从中受益。在多样性著称但受性别平等问题困扰的音乐行业中，本研究重点分析了HDCs如何助力女性艺术家取得成功（与男性艺术家相比）。借助角色一致性理论，我们推断：当创作者与音乐人均为女性时，受众认同度更高，女性艺人能够从HDCs中获得的收益显著大于男性。研究以领先音乐流媒体服务平台Spotify上日增粉丝数来衡量HDCs效益，并利用从TikTok与Spotify收集的的歌曲及艺人层级数据，检验上述假设。结果显示：与未参与HDCs的同类艺术家相比，参与新HDCs的艺术家的Spotify粉丝量获得显著增长。更重要的是，该增益主要由女性创作者驱动，使女性艺人的日涨粉率再高出约3%，凸显了“性别一致”的价值。本研究揭示，以HDCs为载体的短视频生态，正成为推动女性艺家发展、促进数字音乐产业性别平等的新引擎。
3.Do Digital Platforms Improve the Performance of Nonbinding Contracts? Evidence From the Amazon Freight Platform
数字平台能否改善非约束性合同的履约效果？来自亚马逊货运平台的证据
作者：Ali S. Babakan, He Li和William J. Kettinger
Abstract: This research examines how digital platforms influence the performance of nonbinding contracts. Businesses in many industries with high uncertainty, such as trucking freight and construction, simultaneously use nonbinding contracts, which impose no legal sanctions for refusals, and spot markets, which facilitate real-time, flexible transactions with market-determined prices. Understanding the conditions under which nonbinding contracts perform is a major concern in these industries. Leveraging the entry of the Amazon Freight platform in the trucking freight industry, we demonstrate that adding a digital platform-enabled spot marketplace improves the performance of nonbinding contracts. We identified several mechanisms driving this effect: (1) expanding carriers’ transportation capacity, (2) lowering spot market prices, and (3) reducing shippers’ reliance on nonbinding contracts for shorter-haul truckloads. Moreover, the digital platform’s impact on enhancing nonbinding contract performance is particularly pronounced in markets with volatile demand and shorter hauls. This research contributes to understanding the impacts of digital platforms in highly uncertain industries that simultaneously use nonbinding contracts and spot markets. Our findings provide implications to policymakers and business managers on leveraging digital platforms to improve operational efficiency in highly uncertain industries.
摘要：本文考察数字平台如何影响非约束性合同的履约效果。在公路货运、建筑施工等不确定性极高的行业，企业往往同时采用两类机制：一类是不具法律强制力、拒绝履约亦无法律制裁的“非约束性合同”，另一类是价格实时浮动、灵活交易的“现货市场”。厘清非约束性合同何时能够奏效，已成为这些行业的核心关切。借助亚马逊货运平台（Amazon Freight）进入公路货运行业的准自然实验，我们发现：平台化现货市场的引入显著提升了非约束性合同的履约表现。其作用机制包括：（1）扩充承运商的运输能力；（2）压低现货市场价格；（3）减少托运人在短途运输上对非约束性合同的依赖。进一步分析显示，当市场需求波动剧烈且运输距离较短时，数字平台对非约束性合同履约效果的提升尤为显著。本研究为理解数字平台在同时采用非约束性合同与现货市场的高不确定性行业中的影响提供了理论贡献。研究发现为政策制定者与管理者如何利用数字平台提升运营效率提供了可行路径。
4.Engaging Physicians with Introductory Incentives: References to Online and Offline Income
引导医生参与的初始激励：线上与线下收益的参照效应
作者：Xiaofei Zhang, Karen Xie, Bin Gu和Xitong Guo
Abstract: Incentives make or break user contributions. While providing introductory incentives to attract new users has become increasingly popular among online communities, their impact on user contributions remains largely unknown. Utilizing a policy change that doubled the incentives paid to physicians in a leading online health community, we examined the impacts of both the initiation and the termination of such introductory incentives on physician contributions (in terms of patient consultations) and how the impacts varied according to the physician’s online and offline income. We found that despite an increase in physician contributions during the policy window, the introductory incentives unintentionally decreased physician contributions after the policy window ended. Additionally, physicians tended to anchor their contributions using their online rather than offline income as a reference point, suggesting that mental accounting was at play. Our findings provide a cautionary perspective on the unintended consequences of using introductory incentives and reveal the associated mechanisms of mental accounting when users make contributions (or not) to online communities. These findings provide important implications for incentive design and user engagement in online communities.
摘要：激励措施是影响用户贡献的关键因素。尽管在线社区中通过提供初始激励（introductory incentives）吸引新用户的做法日益普遍，但其对用户贡献的实际影响在很大程度上仍不明确。本研究利用某领先在线健康社区将医生所获激励翻倍的政策调整，考察了此类初始激励的实施与终止对医生贡献（以患者咨询量衡量）的影响，以及该影响如何随医生线上、线下收入的不同而变化。研究发现，尽管在政策实施期间医生贡献度有所提升，但初始激励在政策窗口结束后却意外导致医生贡献下降。此外，医生更倾向于以线上收入而非线下收入作为参考点来确定自身贡献水平，这表明心理账户机制在此过程中发挥了作用。本研究为使用初始激励可能产生的意外后果提供了警示视角，并揭示了用户为在线社区做出（或不做出）贡献时心理账户的作用机制。这些发现为在线社区的激励设计与用户参与策略提供了重要启示。
5.Producing the “We” in High-Risk Online Activism: Identity Configurations in My Stealthy Freedom
高风险网络行动中“我们”身份构建：“我的隐秘自由”运动中的身份配置
作者：Mahya Ostovar和Ulrike Schultze
Abstract: The research on online social movements generally concludes that collective identity, i.e., the sense of we-ness that individual protesters in a movement share, is not only unattainable but also dispensable, even though it is considered a defining feature of traditional movements. In this paper, we explore one of the boundary conditions of these findings, namely the riskiness of protest practices. Analysing the high-risk social movement, My Stealthy Freedom (MySF), which contests compulsory hijab in Iran in a way that hybridizes online and offline protest practices, we show that a sense of collectiveness can be instantiated in online social movements, why it is critical to the success of high-risk activism, and how it is (re)produced. Comparing and contrasting three instantiations of MySF, each of which was enacted on a different social media platform, we develop a theoretical model of how feelings of collectiveness are enacted in high-risk online activism. In addition to providing guidance for online movements where collective identity is desirable, our study challenges prior research on online activism by theorizing the role of embodiment, affect, and the dialectic between activists’ personal and the movement’s collective identity.
摘要：关于网络社会运动的研究普遍认为，集体认同（即运动中个体抗议者所共有的“我们感”）被视为传统社会运动的标志性特征，但它在在线运动中不仅难以实现，而且并非必需。本文探讨了这些研究结论的边界条件之一，即抗议行动的风险程度。通过分析高风险社会运动“我的隐秘自由”（My Stealthy Freedom，MySF）——该运动以线上与线下抗议行动相结合的方式，反对伊朗的强制性头巾政策。本研究揭示了集体感如何在高风险社会运动中得以构建、为何对高风险抗争的成功至关重要，以及通过何种机制实现（再）生产。通过对MySF运动在三个不同社交媒体平台上的具体实践形态进行对比分析，本文构建了一个理论模型，用以解释高风险网络行动主义中集体感的形成方式。本研究不仅为需要集体认同的网络运动提供实践指引，更通过理论化具身性、情感以及抗议者个人身份与运动集体身份之间的辩证关系，对以往网络行动主义研究提出了挑战。
6.Augmented Reality at Work: Attention Management and Its Impact on Work Performance
工作场景中的增强现实技术：注意力管理及其对工作绩效的影响
作者：Runge Zhu, Cheng Yi和Ting Li
Abstract: Augmented reality (AR) is rapidly emerging as a transformative display technology, blending computer-generated content with the real-world environment in real time. Using divided attention theory, this study investigates how different information delivery channels (i.e., AR vs. mobile phone) and the nature of information (i.e., dependence on specific physical context and complexity) affect work performance. A field experiment in the aircraft maintenance context demonstrates that the effect on work performance of providing information via AR vs. a mobile phone is mediated by work attentiveness. The findings reveal that the effectiveness of AR is particularly pronounced when information is highly dependent on the specific physical context but diminishes when information complexity is high. This research deepens our understanding of how presenting information directly in front of users’ eyes (i.e., via AR) affects their attention management and work performance. The findings have significant implications for firms in terms of how to leverage AR to enhance work performance in industrial settings.
摘要：增强现实（Augmented Reality，AR）正迅速成为一种变革性显示技术，能够将计算机生成内容与现实环境进行实时融合。本研究基于注意力分配理论，探讨不同信息传递渠道（AR与手机）及信息属性（即对特定物理场景的依赖性与信息复杂性）对工作绩效的影响。在飞机维修场景中开展的实地实验表明，通过AR与手机两种方式传递信息对工作绩效产生的影响，会以工作专注度为中介变量。研究结果显示，当信息高度依赖特定物理场景时，AR的应用效果尤为显著；而当信息复杂性较高时，AR的优势则会减弱。本研究深化了学界对“将信息直接呈现在用户视野中（即通过AR技术）”如何影响注意力管理与工作绩效的理解。这些发现对企业如何利用AR技术提升工业场景下的工作绩效具有重要启示。
7.Mobile Advertising in Distracted Environments: Exploring the Impact of Distractions on Dual-Task Interference
分心环境中的移动广告：探究注意力分散对双任务干扰的影响
作者：Siddharth Bhattacharya, Heather Kennedy, Vinod Venkatraman和Sunil Wattal
Abstract: It is increasingly common for consumers to engage with various tasks on their personal devices amid other distractions such as watching television at home, shopping at malls, or attending concerts. While this split in attention poses challenges, it also opens valuable opportunities for advertisers to strategically push targeted advertisements based on information about the user’s environment. Across a series of controlled lab experiments using a custom app developed for this study, we demonstrate how marketers can optimize pop-up advertising on consumers’ personal devices within distraction-filled environments. In doing so, we extend traditional insights from dual-task interference studies that have previously focused on corresponding tasks in isolation, without considering any stimuli from the environment. Our results indicate that, in the presence of additional stimuli from the environment, a facilitating relationship exists between the attention paid to a task and the effectiveness of pop-up advertisements interrupting the task. However, this relationship is moderated by the extent of attention diffusion from the environment. As the distance between the task and the environment increases, consumer attention to the task is more diffused, resulting in poorer encoding of the pop-up advertisements. Critically, optimizing the content and timing of pop-up advertisements to the environmental content can significantly improve their effectiveness. Our results have important implications for helping marketers develop actionable strategies for mobile advertising in distraction-filled environments.
摘要：消费者在个人设备上处理各类任务时，常同时面临其他干扰因素，如在家看电视、在商场购物或参加音乐会，这种情况日益普遍。尽管注意力分散会带来挑战，但也为广告商提供了宝贵机遇——他们可依据用户所处环境信息，战略性地推送定向广告。在一系列采用自主开发的定制应用程序进行的实验室控制实验中，我们揭示了营销人员如何在充满干扰的环境中优化消费者个人设备上的弹窗广告。在此过程中，研究拓展了传统双任务干扰研究的见解，以往此类研究主要关注孤立状态下的相关任务，未考虑环境中的任何刺激因素。研究结果表明，当存在额外环境刺激时，用户对任务的关注度与打断该任务的弹窗广告效果之间存在促进关系，但这种关系会受环境造成的注意力分散程度调节。随着任务与环境之间距离的增加，消费者对任务的注意力分散程度更高，导致弹窗广告的编码效果更差。关键在于，根据环境内容优化弹窗广告的内容与投放时机，可显著提升其效果。本研究结果对帮助营销人员制定分心环境下移动广告的可行策略具有重要启示。
8.Automating in High-Expertise, Low-Label Environments: Evidence-Based Medicine by Expert-Augmented Few-Shot Learning
高专业度、低标签环境下的自动化：基于专家增强小样本学习的循证医学实践
作者：Rong Liu, Jingjing Li, Marko Zivkovic和Ahmed Abbasi
Abstract: Many real-world process automation environments are rife with high-expertise and limited labeled data. We propose a computational design science artifact to automate systematic review (SR) in such an environment. SR is a manual process that collects and synthesizes data from medical literature to inform medical decisions and improve clinical practice. Existing machine learning solutions for SR automation suffer from a lack of labeled data and a misrepresentation of the high-expertise manual process. Motivated by humans’ impressive capability to learn from limited examples, we propose a principled and generalizable few-shot learning framework—FastSR—to automate the multistep, expertise-intensive SR process using minimal training data. Informed by SR experts’ annotation logic, FastSR extends the traditional few-shot learning framework by including (1) various representations to account for diverse SR knowledge, (2) attention mechanisms to reflect semantic correspondence of medical text fragments, and (3) shared representations to jointly learn interrelated tasks (i.e., sentence classification and sequence tagging). We instantiated and evaluated FastSR on three test beds: full-text articles from Wilson disease (WD) and COVID-19, as well as a public dataset (EBM-NLP) containing clinical trial abstracts on a wide range of diseases. Our experiments demonstrate that FastSR significantly outperforms several benchmarking solutions and expedites the SR project by up to 65%. We critically examine the SR outcomes and practical advantages of FastSR compared to other ML and manual SR solutions and propose a new FastSR-augmented protocol. Overall, our multifaceted evaluation quantitatively and qualitatively underscores the efficacy and applicability of FastSR in expediting SR. Our results have important implications for designing computational artifacts for automating/augmenting processes in high-expertise, low-label environments.
摘要：现实中许多流程自动化环境普遍存在高专业度且标注数据有限的问题。本研究提出一种计算设计科学构件，用于在此类环境中实现系统评价（Systematic review，SR）的自动化。SR是一项人工操作流程，需通过收集并综合医学文献中的数据来支持医疗决策并改进临床实践。现有用于SR自动化的机器学习方案存在标注数据匮乏、无法准确反映高专业要求的人工操作流程的问题。受人类从有限样本中学习卓越能力的启发，本研究提出一种具有严谨性与普适性的小样本学习框架——FastSR，旨在通过极少的训练数据，实现多步骤、专业知识密集型的SR流程的自动化。基于SR专家的标注逻辑，FastSR对传统小样本学习框架进行拓展，具体包括：（1）采用多样化表征以涵盖各类系统评价知识；（2）引入注意力机制以体现医学文本片段的语义对应关系；（3）构建共享表征以联合学习相关任务（即句子分类与序列标注）。研究在三个测试平台上对FastSR进行实例化与评估：威尔森病（Wilson disease）和新型冠状病毒肺炎（COVID-19）的全文文献，以及包含多种疾病临床试验摘要的公开数据集（EBM-NLP）。实验结果表明，FastSR的性能显著优于多种基准方案，且最多可将系统评价项目的效率提升65%。通过批判性对比FastSR与其他机器学习及人工系统评价方案的结果与实际优势，我们进一步提出新型FastSR增强协议。总体而言，多维度评估从定量与定性层面均印证了FastSR在提升系统评价效率方面的有效性与适用性。研究结果对在高专业知识、低标注数据环境中设计流程自动化/增强的计算构件提供了重要启示。
9.Organizing for AI Innovation: Insights From an Empirical Exploration of U.S. Patents
人工智能创新的组织模式：基于美国专利的实证探索
作者：Yu-Kai Lin和Likoebe M. Maruping
Abstract: Although the prevalence of artificial intelligence (AI) innovations is on the rise, firms frequently report failures and setbacks in their development and implementation of AI innovation efforts. One common issue behind many failing AI initiatives is that they are organized just like other information technology (IT) innovation efforts. To elucidate why and how the production of AI and IT innovations may need to be managed differently, this study juxtaposes these two types of innovations based on two key dimensions of the Schumpeterian framework: the form (product vs. process) and magnitude (radical vs. incremental) of innovations. By analyzing a matched sample of AI and IT patents, we found robust evidence that AI innovations are less radical and more process oriented than comparable IT innovations. Drawing upon our empirical discovery, we developed a conceptual framework to suggest a new way to think about organizing AI innovation. Our research contributes to the literature and practice on AI innovation by illuminating the comparative differences between AI innovations and other IT innovations and advancing a set of empirically derived propositions on how firms may be able to better manage their AI innovation activities.
摘要：尽管人工智能（AI）创新应用日益普及，但企业在开展和实施AI创新项目时，仍频繁报告失败与挫折。众多AI项目失败的一个共性问题在于，企业仍沿用传统信息技术（IT）创新的组织模式来管理AI创新。为阐明AI创新与IT创新的产出为何需要、以及如何通过差异化管理实现，本研究基于熊彼特（Schumpeterian）理论框架的两个关键维度——创新形式（产品创新 vs. 流程创新）与创新幅度（突破性创新 vs. 渐进性创新），对这两类创新进行对比分析。通过对一组匹配的AI专利与IT专利样本展开研究，我们发现有力证据表明：相较于同类IT创新，AI创新的突破性更弱，且更偏向流程导向。基于这一实证发现，本研究构建了一个概念框架，为AI创新的组织模式提供了新的范式。本研究通过阐明AI创新与其他IT创新的对比差异，并提出一套基于实证的企业AI创新方案，为AI创新领域的学术研究与实践应用作出了贡献。
10.The Complementor’s Dilemma: Navigating Growth Ambitions and the Dependency on Focal Actors in Platform Ecosystems
互补者困境：平台生态系统中非核心参与者的野心增长与其对核心参与者的依赖
作者：Shiyuan Liu, Ola Henfridsson, Jochem T. Hummel和Joe Nandhakumar
Abstract: The literature on platform ecosystems increasingly recognizes that nonfocal actors such as complementors may have growth ambitions. Such ambitions, if successfully advanced, may even elevate the complementor’s position in the platform ecosystem to that of a focal actor. However, transitioning from nonfocal actor to focal actor is challenging. Along the way, the nonfocal actor may need to choose between the seemingly unfavorable alternatives of acting on its growth ambitions—risking losing the focal actors’ support needed for that growth—or relinquishing its ambitions to ensure the support of the focal actors continues. Referring to this phenomenon as the complementor’s dilemma, we unpack the process whereby a nonfocal actor can pursue growth ambitions while successfully managing relationships with the focal platforms in the ecosystem. To address this research problem, we conducted an in-depth, embedded case study of a Chinese short-form video platform, Douyin (known as TikTok outside of China), from its inception as a complement in 2016 to its establishment as a focal actor in 2018. During this two-year period, Douyin grew spectacularly from 0.75 million to 208.28 million users. We examined the process through which Douyin navigated the complementor’s dilemma multiple times within the confines of its dependency on Weibo and WeChat, the focal actors in China’s social network platform ecosystem. We contribute to the platform ecosystem literature by offering a process perspective that conceptualizes the complementor’s dilemma and theorizes how to navigate the dilemma when transitioning from a nonfocal actor to a focal actor in a platform ecosystem.
摘要：平台生态系统研究日益认识到，互补者等非核心参与者可能怀有成长抱负。若这些抱负得以成功实现，甚至可能将互补者在平台生态系统中的地位提升至核心参与者水平。然而，从非核心参与者向核心参与者转型面临诸多挑战。在此过程中，非核心参与者往往面临两难抉择：要么践行成长抱负，却需承担失去实现该增长所必需的核心参与者支持的风险；要么放弃抱负，以确保核心参与者的持续支持。本研究将这一现象定义为“互补者困境”，深入剖析了非核心参与者在追求成长抱负的同时，如何成功维系与生态系统中核心平台间关系的过程。为解决这一研究问题，本研究对中国短视频平台抖音（海外版为TikTok）进行了深度嵌入式案例研究，追踪其自2016年作为互补者起步，至2018年确立为核心参与者的历程。在这两年间，抖音的用户规模实现爆发式增长，从75万增至2.0828亿。研究重点考察了抖音在在中国社交网络平台生态系统中，依赖核心参与者微博与微信的背景下，多次成功化解互补者困境的具体过程。本研究通过提供过程视角，对互补者困境进行了概念化阐述，并理论化了平台生态系统中非核心参与者向核心参与者转型过程中应对该困境的策略，从而丰富了平台生态系统文献。
11.Does Ransomware Make Investors “WannaCry”? On Investors’ Divergent Reactions to Ransomware Hits and Near Misses
勒索软件会让投资者“想哭”吗？投资者对勒索软件攻击与未遂事件的差异化反应
作者：Sebastian W. Schuetz, Yan Chen, Jens Forderer和Yusi Ma
Abstract: In recent years, ransomware has become one of the most dangerous cyber threats, with successful attacks causing severe operational disruptions and staggering damages. Rationally speaking, investors should react negatively to firms’ ransomware disclosures, but this may not always be the case. Based on norm theory, we describe a paradoxical phenomenon wherein investors exhibit negative reactions to ransomware hits (i.e., events that led to operational disruptions) but positive reactions to near misses (i.e., events in which operational disruptions were narrowly avoided). The positive reactions occur due to an outcome bias in which near-miss events—events that are objectively negative but less severe than expected—are viewed positively instead of negatively. We tested these predictions by reporting on an investigation of stock market reactions to disclosures of ransomware hits vs. near misses. To do so, we assembled a comprehensive dataset of ransomware incidents disclosed by U.S. public firms. Using the event study method, we estimated abnormal stock market returns and found evidence in support of our predictions. First, in line with expectations, ransomware hits that led to the expected severe impact resulted in stock price drops of -4.40%. However, near misses, where disruptions were avoided, were rewarded with gains of 2.87%, confirming positive instead of negative reactions. This offers new insights into investors’ biased responses to certain cybersecurity incidents. These positive reactions, however, represent a call for caution because, albeit seemingly favorable, they mask underlying risks.
摘要：近年来，勒索软件已成为最危险的网络威胁之一，成功的攻击会导致严重的运营中断和巨额损失。从理性角度而言，投资者应对企业披露的勒索软件事件做出负面反应，但实际情况并非总是如此。基于规范理论，本研究揭示了一种悖论现象：投资者对勒索软件攻击事件（即导致运营中断的事件）表现出负面反应，而对勒索软件未遂事件（即侥幸避免运营中断的事件）却表现出正面反应。这种正面反应源于结果偏差——勒索软件未遂事件虽本质上属于负面事件，但其严重程度低于预期，因此被投资者赋予正面而非负面评价。为验证上述预测，本研究考察了股市对披露勒索软件攻击事件与未遂事件披露的反应。研究首先收集了美国上市公司披露的勒索软件事件综合数据集，随后采用事件研究法估算股市异常收益率，所得结果支持了研究假设。首先，造成严重影响的勒索软件攻击事件导致股价下跌4.40%；而成功避免运营中断的勒索软件未遂事件则使股价上涨2.87%，证实了投资者的正面反应。该研究为理解投资者对特定网络安全事件的认知偏差提供了新见解。然而，这种正面反应可能掩盖了潜在风险，尽管表面上对企业有利，实则值得高度警觉。
12.The Interplay Between Healthcare Information Technologies and Denied Claims
医疗信息技术与理赔拒付之间的相互作用机制
作者：Sezgin Ayabakan, Hilal Atasoy和Min-Seok Pang
Abstract: This study investigates the role of health information technology (HIT) in reducing claim denials, which are a significant burden for healthcare providers in the U.S. We theorize the impacts of electronic health records (EHRs) on claim denials, starting with an examination of EHR adoption and followed by a deeper assessment of how EHRs are sourced both within a hospital and across hospitals in the same health system. We propose that while EHR adoption reduces the likelihood of claim denials by improving the accuracy and completeness of information processing, it can also increase claim denials if EHR applications are sourced from multiple vendors within a hospital or different vendors across hospitals. Using a large-scale dataset of claim records from the state of Maryland from 2012-2016, we found that the greater the EHR adoption by care providers, the less likely a claim is denied. In addition, our findings suggest that EHRs are more effective in preventing denials when a hospital sources EHR applications from a single vendor and when a group of hospitals in the same health system sources EHRs from the same vendor. Additionally, we observed a decrease in claim denials when physicians previously worked in hospitals utilizing EHR applications from the same vendor. This study provides significant theoretical insights into the information systems literature on HIT and offers practical implications for healthcare providers by uncovering the multifaceted roles of EHRs in information processing and compliance.
摘要：本研究探讨医疗信息技术（Health information technology）在降低理赔拒付率中的作用——理赔拒付是美国医疗服务提供者面临的长期困扰。研究围绕电子健康记录（Electronic health records，EHRs）对理赔拒付的影响展开理论分析：首先考察EHR的采用情况，进而深入评估医院内部及同一医疗体系内不同医院的EHR采购模式。研究提出，EHR的采用虽能通过提升信息处理的准确性与完整性降低理赔拒付概率，但若医院内部从多个供应商采购EHR应用程序，或同一医疗体系内不同医院从不同供应商采购EHR，则可能增加理赔拒付风险。研究采用美国马里兰州2012-2016年的大规模理赔记录数据集，结果显示：医疗服务提供者的EHR采用程度越高，理赔被拒的概率越低。此外，研究发现，当医院从单一供应商采购EHR应用程序，或同一医疗体系内的多家医院从同一供应商采购EHR时，EHR在预防理赔拒付方面的效果更显著。同时，若医生此前曾在使用同一供应商EHR应用程序的医院工作，理赔拒付率也会有所下降。本研究为医疗信息技术领域的信息系统文献提供了重要理论洞见，同时通过揭示EHR在信息处理与合规方面的多重作用，为医疗服务提供者提供了实践启示。
13.Find the Good. Seek the Unity: A Hidden Markov Model of Human-AI Delegation Dynamics
寻善求同：人机委托动态中的隐马尔可夫模型
作者：Junming Liu, Wei Thoo Yue, Alvin Chung Man Leung和Xin Zhang
Abstract: As AI becomes integral to enterprise decision-making, this study explores the collaborative dynamics between managers and AI systems, focusing on human willingness to delegate tasks to AI. Grounded in the “agentic” systems delegation framework and instance-based learning theory, we employed a hidden Markov model in a longitudinal study of the dynamic delegation decision-making process involving 875 store managers. We found that there is a potential polarization in managers’ delegation willingness, with managers who recognize the capability of AI exhibiting high delegation willingness and fostering increased collaboration with AI over time—in contrast to their counterparts who are inclined to reduce AI’s involvement. During human-AI interactions, managers’ continuous performance appraisal of AI shapes their dynamic delegation willingness, which in turn affects their assessment of AI capability. This process forms a delegation feedback loop that drives the dynamics of delegation behaviors. Our study indicates that managers with a high willingness to delegate tend to outperform their counterparts and offers valuable insights for human-AI collaborative intelligence in organizational settings.
摘要：随着人工智能（AI）成为企业决策的重要组成部分，本研究基于能动性系统委托框架与实例学习理论，探讨管理者与AI系统间的协作动态，重点关注人类向AI委托任务的意愿。通过对875名门店管理者展开纵向研究，我们采用隐马尔可夫模型（hidden Markov model）分析动态委托决策过程。结果表明，管理者的委托意愿可能存在两极分化趋势：认可AI能力的管理者展现出较高的委托意愿，且随着时间推移会深化与AI的协作；而不认可AI能力的管理者则倾向于减少AI的参与。在人机互动过程中，管理者对AI的持续绩效评估会影响其动态委托意愿，进而影响其对AI能力的评价，由此形成推动委托行为动态发展的"委托反馈循环"。研究还发现，高委托意愿的管理者往往比低委托意愿的管理者表现更优，该结论为组织场景下的人机协作智能提供了重要启示。
14.An Empirical Study of Strategic Opacity in Crowdsourced Evaluations
众包评价中战略模糊性的实证研究
作者：Linli Xu, Qi Xie和Gordon Burtch
Abstract: Crowd-voting mechanisms are commonly used to implement scalable evaluations of crowdsourced creative submissions. Unfortunately, the use of crowd-voting also raises the potential for gaming and manipulation. Manipulation is problematic because (1) submitters’ motivation depends on their belief that the system is meritocratic, and (2) manipulated feedback may undermine learning, as submitters seek to learn from received evaluations and those of peers. In this work, we consider a design approach to addressing the issue, focusing on the notion of strategic opacity, i.e., purposefully obfuscating evaluation procedures. On the one hand, opacity may reduce the incentive and thus the prevalence of vote manipulation, and submitters may instead dedicate that time and effort to improving their submission quantity or quality. On the other hand, because opacity makes it difficult for submitters to discern the returns to legitimate effort, submitters may also reduce their submission effort or simply exit the market. We explored this tension via a multimethod study employing field experiments at 99designs and a controlled experiment on Amazon Mechanical Turk. We observed consistent results across all experiments: opacity leads to reductions in gaming in these crowdsourcing contests and significant increases in the allocation of effort toward legitimate vs. illegitimate activities, with no discernible influence on contest participation. We discuss boundary conditions and the implications for contest organizers and contest platform operators.
摘要：群体投票机制常用于对众包创意提交作品进行规模化评价。然而，群体投票的使用也带来了潜在的作弊与操纵风险。这类操纵行为存在问题，原因在于：（1）提交者的参与动机依赖于其对系统择优机制的信任；（2）被操纵的反馈可能阻碍提交者的学习过程——毕竟提交者本希望从自身及同行获得的评价中汲取经验。本研究采用设计科学方法应对该问题，聚焦于战略模糊性（strategic opacity）这一概念，即有意模糊评价流程。一方面，模糊性可能降低投票操纵的动机，进而减少操纵行为的发生，促使提交者将时间精力用于提升作品数量与质量；另一方面，由于模糊性使提交者难以判断“合规努力”所能带来的回报，他们也可能降低创作投入，甚至直接退出该市场。为探究这种矛盾关系，本研究采用混合方法开展研究（包括在99designs平台开展的田野实验和在Amazon Mechanical Turk平台上实施的受控实验）。所有实验均呈现一致结果：在这些众包竞赛中，模糊性不仅众包竞赛中的策略性操纵行为，促使参与者将更多精力投入正当而非违规活动，且对竞赛参与度无明显影响。研究还探讨了该策略的边界条件以及对竞赛主办方和竞赛平台运营者的启示。
15.Information Technology Firms and Revenue Stall, 1950-2015: Theory and Empirical Evidence
1950-2015年信息技术企业收入停滞现象：理论与实证证据
作者：Terence J. V. Saldanha, Sunil Mithas和Raveesh Mayya
Abstract: A slowdown in revenue growth, referred to as revenue stall in this study, is a key concern for any firm. We examine how information technology-producing firms (i.e., IT firms) differ from non-IT firms in experiencing revenue stall and in benefiting from R&D investments in terms of reduced revenue stall. We hypothesize that whereas IT firms experience more revenue stall than non-IT firms, R&D investments reduce revenue stall to a greater extent in IT firms than in non-IT firms. Our empirical analyses of a longitudinal dataset of more than 1,400 large public firms in the United States from 1950 to 2015 broadly support our hypotheses. Consistent with the theoretical arguments underlying our hypotheses, we also find that IT firms experience higher competition, dynamism, and turbulence, and have higher intangible assets than non-IT firms.
摘要：收入增长放缓（又称营收停滞）是所有企业关注的核心问题。本研究探讨了信息技术生产企业（即IT企业）与非IT企业在遭遇收入停滞方面的差异，以及二者通过研发投资缓解收入停滞的效果有何不同。研究提出假设：一方面，IT企业比非IT企业更易经历营收停滞；另一方面，研发投入对营收停滞的缓解作用在IT企业中比在非IT企业中更为显著。通过对1950-2015年美国1400余家大型上市企业的纵向数据分析，实证结果基本支持了上述假设。与假设背后的理论观点一致，研究还发现，相较于非IT企业，IT企业面临的竞争更激烈、环境动态性与不确定性更高，且拥有更多无形资产。
16.Editor’s Comments: Rebalancing Novelty with Rigor and Relevance in Information Systems Research
主编寄语：在信息系统研究中平衡新颖性、严谨性与相关性
作者：Heshan Sun, Wen Wen, Jason Bennett Thatcher, Michael Chau和Susan Brown
Abstract: This editorial is inspired by a growing concern within the information systems (IS) community that novelty has become a dominant criterion for publication, despite being unevenly interpreted and poorly specified. In our editorial experience, when authors are told that their papers lack novelty, they often receive little concrete guidance on what precisely counts as novelty, how it varies across paradigms, or how it should be balanced with rigor and relevance.
摘要：本期的主编寄语，源于信息系统（IS）学界日益增长的关切：尽管新颖性（novelty）的定义既不统一、界定也不清晰，但其已成为论文发表的核心评判标准。根据我们的编辑经验，当作者被告知其论文缺乏创新性时，往往难以获得具体指导——包括何为新颖性的精确界定、不同研究范式下的评判差异，以及如何与严谨性和相关性实现平衡。
原文链接：https://misq.umn.edu/contents-49-3
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