期刊追踪 |MIS Quarterly: Management Information Systems: 2025年第49卷3期

MIS Quarterly: Management Information Systems（MIS Quarterly）是全球公认的UT DALLAS 商学院24种国际顶级期刊（UTD24）之一，也是金融时报（Financial Times）认定的50种经管类顶级期刊（FT50）之一。MISQ2024年的影响因子是6.0，是信息管理科学领域排名第一的期刊。MIS Quarterly 主要关注信息系统领域，特别是与管理信息系统相关的主题。它涵盖了广泛的主题，包括信息技术的采用、组织信息系统、信息系统管理、电子商务、信息系统战略、数据分析等等。

摘要：个人通常无法评估新闻报道的真实性——尤其是在社交媒体平台上。最近的研究表明，表明规范性信号的干预措施，如标记虚假主张，并不总是有效的。我们提出了一种方法，在该方法中，为用户提供了在确定声明的真实性时要考虑的推理证据，而不是依赖于标准的真或假标志。我们进行了一系列实验来探索不同形式的推理证据对个人判断新闻报道真实性的影响。我们发现提供这样的证据可以显著提高个人对真假新闻的判断——当然也有一些警告。提供具有高证据强度的推理证据会导致准确性判断的普遍提高。包含证据强度较低的项目的推理证据可能会改变可信度，从而提高对真假主张的判断，但降低对其他主张的判断。我们还确定了真假说法之间的重要不对称，发现如果人们处于更具批判性的心态，一些证据的效果可能会得到改善——例如，通过引导他们思考真理和谎言的概念。综上所述，这些结果扩展了关于假新闻问题的知识，并可能提出有效的方法来解决这个问题，而不减少对真实新闻的关注。

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：本研究探讨了短视频平台TikTok上流行的“标签舞蹈挑战”（HDCs）现象，如何帮助音乐艺人在数字音乐市场获得关注。标签舞蹈挑战将音乐与舞蹈巧妙结合，旨在吸引用户参与并实现病毒式传播，从而让其背景音乐所属的艺人从中受益。数字音乐行业虽以多样性为特点，但在性别包容性方面仍面临挑战，因此本研究重点关注标签舞蹈挑战对女性艺人与男性艺人成功的助力差异。本研究运用角色一致性理论提出假设：相较于男性艺人，女性艺人更易从标签舞蹈挑战的曝光中获益，尤其是在性别一致的情况下 —— 即挑战创作者与艺人均为女性时。研究以主流音乐流媒体平台Spotify上艺人粉丝数量的日变化为指标，衡量标签舞蹈挑战带来的收益，并利用从Spotify和TikTok收集的歌曲及艺人层面数据对假设进行验证。研究发现，与未参与标签舞蹈挑战的同类艺人相比，参与新标签舞蹈挑战的艺人在Spotify上的粉丝数量显著增加。此外，研究还观察到，女性创作者是这一效应的关键驱动因素：她们能使女性艺人在Spotify上的粉丝日增长率额外提升约3%，这一结果凸显了性别一致的价值。本研究揭示了短视频（尤其是通过标签舞蹈挑战这一形式）在推动女性艺人发展方面的作用，同时也为促进数字音乐行业内的包容性提供了参考。

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：这项研究考察了数字平台如何影响非约束性合同的履行。许多具有高度不确定性的行业，如卡车货运和建筑，同时使用不具约束力的合同和现货市场，前者对拒绝交易没有法律制裁，后者有利于以市场决定的价格进行实时、灵活的交易。理解非约束性合同履行的条件是这些行业的主要关注点。利用亚马逊货运平台在卡车货运行业的进入，我们证明了增加一个数字平台支持的现货市场可以提高非约束性合同的性能。我们确定了几个驱动这种效应的机制:(1)扩大承运人的运输能力，(2)降低现货市场价格，以及(3)减少托运人对非约束性合同的依赖。此外，数字平台对提高非约束性合同绩效的影响在需求波动和运输时间较短的市场中尤为明显。这项研究有助于理解数字平台在同时使用非约束性合约和现货市场的高度不确定性行业中的影响。我们的发现为决策者和企业管理者提供了在高度不确定的行业中利用数字平台提高运营效率的启示。

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：激励决定用户贡献的成败。虽然提供介绍性激励以吸引新用户在在线社区中越来越受欢迎，但它们对用户贡献的影响在很大程度上仍不为人知。利用一项将支付给领先在线健康社区医生的激励增加一倍的政策变化，我们研究了此类介绍性激励的启动和终止对医生贡献(就患者咨询而言)的影响，以及这些影响如何根据医生的在线和离线收入而变化。我们发现，尽管在政策窗口期间医生的贡献有所增加，但在政策窗口结束后，介绍性激励无意中减少了医生的贡献。此外，医生倾向于使用他们的在线收入而不是线下收入作为参考点来锚定他们的贡献，这表明心理会计在起作用。我们的发现为使用介绍性激励的意外后果提供了一个警示性的视角，并揭示了当用户对在线社区做出贡献(或不做出贡献)时心理账户的相关机制。这些发现为在线社区的激励设计和用户参与提供了重要的启示。

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：对在线社会运动的研究通常得出的结论是，集体认同，即运动中个体抗议者共享的自我意识，不仅难以实现，而且可有可无，尽管它被视为传统运动的一个定义特征。在本文中，我们探讨了这些发现的边界条件之一，即抗议行为的风险性。通过分析高风险的社会运动“我的秘密自由”(My secretive Freedom)，该运动以一种混合了线上和线下抗议实践的方式对伊朗的强制头巾进行了质疑，我们表明，集体意识可以在在线社会运动中体现出来，为什么它对高风险行动主义的成功至关重要，以及它是如何(再)产生的。比较和对比MySF的三个实例，其中每一个都是在不同的社交媒体平台上制定的，我们开发了一个理论模型，说明集体主义的感觉是如何在高风险的在线行动主义中制定的。除了为需要集体认同的在线运动提供指导之外，我们的研究还通过理论化体现的作用、情感以及活动家个人和运动的集体认同之间的辩证关系，挑战了先前关于在线行动主义的研究。

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：增强现实(AR)正在迅速成为一种变革性的显示技术，将计算机生成的内容与现实世界的环境实时融合在一起。利用分散注意力理论，本研究调查了不同的信息传递渠道(即AR与手机)和信息的性质(即对特定物理环境和复杂性的依赖)如何影响工作绩效。一项在飞机维修背景下的现场实验表明，通过AR和手机提供信息对工作绩效的影响是由工作注意力调节的。研究结果表明，当信息高度依赖于特定的物理环境时，增强现实的有效性尤其明显，但当信息复杂度高时，增强现实的有效性就会降低。这项研究加深了我们对直接在用户眼前呈现信息(即通过AR)如何影响他们的注意力管理和工作表现的理解。这些发现对于企业如何利用AR来提高工业环境中的工作绩效具有重要意义。

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：对于消费者来说，在其他分心的事物中，例如在家看电视、在商场购物或参加音乐会，在他们的个人设备上从事各种任务变得越来越普遍。虽然这种注意力的分散带来了挑战，但它也为广告商提供了宝贵的机会，可以根据用户环境的信息有策略地推送有针对性的广告。通过使用为本研究开发的定制应用程序的一系列受控实验室实验，我们展示了营销人员如何在令人分心的环境中优化消费者个人设备上的弹出广告。在这样做的过程中，我们扩展了双任务干扰研究的传统观点，这些研究以前只关注孤立的相应任务，而不考虑来自环境的任何刺激。我们的结果表明，在存在来自环境的额外刺激的情况下，对任务的关注和打断任务的弹出广告的有效性之间存在促进关系。然而，这种关系受到来自环境的注意力扩散程度的调节。随着任务和环境之间的距离增加，消费者对任务的注意力更加分散，导致弹出广告的编码较差。至关重要的是，根据环境内容优化弹出广告的内容和时机可以显著提高其有效性。我们的研究结果对于帮助营销人员在注意力分散的环境中开发可操作的移动广告策略具有重要意义。

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：许多现实世界的过程自动化环境充斥着高专业知识和有限的标记数据。我们提出了一个计算设计科学工件来在这样的环境中自动进行系统评审。SR是一个手动过程，从医学文献中收集和综合数据，以告知医学决策和改善临床实践。现有的用于SR自动化的机器学习解决方案存在缺乏标记数据和对高专业知识手动过程的错误描述的问题。受人类从有限示例中学习的惊人能力的激励，我们提出了一个原则性和可推广的少量学习框架——FastSR——以使用最少的训练数据来自动化多步骤、专业密集型的SR过程。FastSR通过SR专家的注释逻辑，扩展了传统的少量学习框架，包括(1)各种表示以说明不同的SR知识，(2)注意机制以反映医学文本片段的语义对应，以及(3)共享表示以共同学习相关的任务(即，句子分类和序列标记)。我们在三个测试床上实例化和评估了FastSR:来自Wilson disease (WD)和新冠肺炎的全文文章，以及包含广泛疾病的临床试验摘要的公共数据集(EBM-NLP)。我们的实验表明，FastSR明显优于几个基准测试解决方案，并将SR项目加速了65%。与其他ML和手动SR解决方案相比，我们严格检查了SR结果和FastSR的实际优势，并提出了一种新的FastSR增强协议。总的来说，我们多方面的定量和定性评估强调了FastSR在加速软件无线电方面的有效性和适用性。我们的结果对于在高专业知识、低标签环境中设计自动化/增强流程的计算工件具有重要意义。

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：尽管人工智能（AI）创新的普及率不断提升，但企业在开发和实施AI创新项目时，仍频繁报告失败与挫折。许多AI项目失败的一个常见原因在于，它们的组织方式与其他信息技术（IT）创新项目完全一致。为阐明AI创新与IT创新的开展为何需要、以及如何通过不同方式管理，本研究基于熊彼特理论框架的两个关键维度——创新的形式（产品创新vs.流程创新）与程度（突破性创新vs.渐进式创新），对这两类创新进行了对比分析。通过对一组匹配的AI专利与IT专利样本展开研究，我们发现了稳健证据：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，我们构建了一个概念框架，为AI创新的组织方式提供了新的思路。本研究通过揭示AI创新与其他IT创新的对比差异，并提出一系列基于实证的命题（探讨企业如何更好地管理其AI创新活动），为AI创新领域的学术研究与实践应用做出了贡献。

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.

出品/浙江工商大学数字创新与全球价值链升级研究中心

供稿/张靖雯

排版/李健钊

审稿/罗海贝