Mis Quarterly最新文献

{"title":"Clashing Climates: How (In)Congruence Between an Information Security Climate and Other Organizational Climates Affects Security Policy Compliance","authors":"Ali Vedadi,Akmal Mirsadikov","doi":"10.25300/misq/2025/18613","DOIUrl":"https://doi.org/10.25300/misq/2025/18613","url":null,"abstract":"Securing information assets against cyberattacks requires organizations to bolster employees’ security behaviors, including compliance with information security policies (ISPs). A strong information security climate (ISC) has been found to be a powerful determinant of such behaviors. However, the ISC does not exist in isolation, and its effect on ISP compliance can be impacted by other (in)congruent organizational climates that coexist within an organization, as simultaneously perceived by employees. Drawing on the competing values framework, this research investigates the joint influences of the ISC and coexisting climates on ISP compliance. Specifically, we analyze the interplay between the ISC and other coexisting climates, considering their complementary or competing nature, and the extent to which employees perceive these climates to have similar (i.e., aligned) or discrepant (i.e., misaligned) magnitudes of intensity within the organization. Using polynomial regression and response surface analysis, we examine how each (mis)aligned condition is associated with ISP compliance. The results highlight the interplay of the ISC with coexisting climates and provide nuanced insights into complex and nonlinear relationships among these climates.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"14 1","pages":"1033-1058"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond Slacktivism: Unraveling the Power of Peripheral Mobilization Through Social Media Talk and Ties","authors":"Romilla Syed,Leiser O. Silva,Oyebisi Oladeji","doi":"10.25300/misq/2025/18103","DOIUrl":"https://doi.org/10.25300/misq/2025/18103","url":null,"abstract":"Building on theories of social movements and social networks, this study examines how participants at the core and periphery of a network mobilize a social movement across different temporal stages. To explore the mobilization potential of participants in terms of their network activity (the number of messages sent by core or peripheral participants) and network reach (the number of potential users a participant can expose to messages through their connections), we used the case of the 2017 Women’s March and adopted a computational theory construction (CTC) approach to identify the emergent patterns in network activity and network reach of core and peripheral participants before, during, and after the protest. Our results challenge the notion of “slacktivism” associated with peripheral participants and suggest that peripheral participants make meaningful contributions to social movements by generating and exposing distinct meanings and keeping the movement momentum alive, especially when core participation wanes. Based on empirical results and theoretical assumptions, we formulated a set of propositions to explain the dynamics of peripheral mobilization. This study contributes to the digital activism literature, which has thus far underestimated the mobilization potential of peripheral participants. At the practical level, our findings can help organizers strategize framing appropriate movement messages and activating the critical periphery to increase the audience of their messages. Finally, our research approach may be of interest to other scholars interested in the CTC paradigm.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"11 1","pages":"1001-1032"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Taste vs. Stats: Investigating Racial Discrimination in Online Donation and Investment Crowdfunding","authors":"Qianqian Ben Liu,Xuechen Luo","doi":"10.25300/misq/2025/18542","DOIUrl":"https://doi.org/10.25300/misq/2025/18542","url":null,"abstract":"Racial discrimination in crowdfunding is a significant barrier to equitable access to capital, as racial minorities face greater challenges in achieving their fundraising goals. While prior research has documented discriminatory patterns in crowdfunding outcomes, the underlying mechanisms driving this discrimination remain unclear. This is a critical gap that must be addressed to develop effective interventions. Drawing on economic theories of taste-based and statistical discrimination, we examine how discrimination mechanisms vary across crowdfunding types. We posit that donation crowdfunding primarily exhibits taste-based discrimination, while investment crowdfunding manifests statistical discrimination. We tested these predictions through three preregistered randomized experiments. Confirming our prediction, the first experiment revealed taste-based discrimination against Black fundraisers in donation crowdfunding. The second experiment demonstrated statistical discrimination in investment crowdfunding. However, contrary to prior research showing negative discrimination against minorities, our second experiment revealed positive statistical discrimination toward Asian fundraisers. We posit that this positive discrimination is due to the decision frame participants adopt, and this explanation is supported by Experiment 3: The direction of discrimination is reversed when task instructions are modified to elicit a negative decision frame. Our research advances both the crowdfunding and the racial discrimination literatures while providing insights for platform design and debiasing interventions.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"37 1","pages":"1157-1182"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Chain-of-Preference: A Novel Deep Learning Method for Mixed-Grained Recommendation","authors":"Gang Chen,Tan Cheng,Jianxiong Wang,Shuaiyong Xiao,Huimin Zhao","doi":"10.25300/misq/2025/19311","DOIUrl":"https://doi.org/10.25300/misq/2025/19311","url":null,"abstract":"The trade-off between recommending specific versus diverse information to users has long been a challenging issue in recommendation systems. In this study, we probe into a novel problem—mixed-grained recommendation (MGR)—to address this challenge. MGR involves determining the optimal recommendation granularity that aligns with users’ needs for item exploitation and exploration. To this end, we propose a novel deep chain-of-preference learning strategy to infer a user’s choice across mixed-grained categories and items, based on category-aware demand-perception alignment in a top-down manner. Specifically, we design a chain-of-preference-empowered deep learning method (CoPDL) that can infer a user’s (1) dynamic and interrelated mixed-grained demands along a multigranularity item tree, (2) self-adapted perception along the item tree, and (3) choice regarding mixed-grained nodes in the item tree by virtue of top-down category-aware inference. Empirical evaluation results demonstrate the superior performance of CoPDL over state-of-the-art deep learning alternatives for fine-grained, coarse-grained, and mixed-grained recommendations. Further explanatory investigations provide insights into how CoPDL fulfills MGR in effectively balancing the trade-off between recommendation specificity and diversity.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"51 1","pages":"1117-1156"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of In-house and Wire Content Mix on Online Newspaper Subscriptions","authors":"Xiaoli Yang,Nachiketa Sahoo,Timothy Simcoe","doi":"10.25300/misq/2025/18870","DOIUrl":"https://doi.org/10.25300/misq/2025/18870","url":null,"abstract":"Declining circulation and advertising revenue have led many newspapers to cut costs by reducing in-house staff and relying more on wire content. In-house production provides unique content, while wire (non-exclusive) content offers broad coverage at a lower cost. Using data from a regional U.S. newspaper, we examined how the mix of in-house and wire content affects subscription decisions. To address reader-side selection bias, we used local precipitation as an excluded variable to indirectly randomize readers’ exposure to the content mix. We found that a 1-percentage-point increase in the share of in-house articles raised daily subscriptions by 0.024 percentage points (≈9% of baseline) and by another 0.009 percentage points (≈4% of baseline) under a paywall. Against this overall trend, wire business and sports articles also increased conversion, suggesting opportunities for selective sourcing. Effects were weaker for local readers and for visitors from social media. Finally, readers from aggregators responded to in-house content and paywalls much like direct visitors, indicating that differentiation and paywalls remain effective even as readers turn to aggregators to discover news.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"1 1","pages":"1217-1232"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What Happens When Machines Become Smarter? An Empirical Investigation of AI Opponents in Online Gaming","authors":"Haoyu Yuan,Qinglai He,Lingli Wang,Ni Huang,Qiang Wei,Jiayin Zhang","doi":"10.25300/misq/2025/18603","DOIUrl":"https://doi.org/10.25300/misq/2025/18603","url":null,"abstract":"The online gaming industry increasingly incorporates virtual agents to enhance player experiences. Although prior literature has explored the provision of virtual agents in gaming, research on technological advancements remains limited. In this study, we investigate how introducing artificial intelligence (AI) powered agents as virtual opponents (versus rule-based opponents) influences human players’ engagement and performance. Leveraging a large-scale quasi-field experiment in a multiplayer online racing game, we employed difference-in-differences analyses with matching strategies. We show that the introduction of AI opponents can have “discouragement effects” on players, resulting in reduced player engagement and decreased performance. In addition, our mechanism exploration revealed that introducing AI opponents increases competition intensity and immersion in the game, and these two factors exhibit opposing influences on players’ subsequent behavior. Specifically, heightened competition hinders players’ further engagement and performance progression, whereas a more immersive experience encourages more gaming participation and better performance. Further, we found that the effects of AI opponents on player engagement and performance vary by player motivation and skill levels, such that competition-oriented and highly skilled players are more receptive to AI opponents. Moreover, our findings indicate that optimal engagement and performance outcomes occur when players compete against opponents with comparable and low competence levels, respectively. Lastly, we observed an inverted U-shaped relationship between the proportion of AI opponents and players’ engagement and performance. Our study contributes to the literature on human-AI interactions by offering novel empirical evidence on the impact of AI opponents on human players’ experiential and instrumental outcomes and disentangling the underlying mechanisms. This work also offers practical implications for game designers and policymakers regarding the design of AI-integrated competitive environments.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 1","pages":"971-1000"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FAIR: A Design Theory for Artificial Intelligence Fairness","authors":"Arun Rai,Jing Tian,Ling Xue","doi":"10.25300/misq/2026/17971","DOIUrl":"https://doi.org/10.25300/misq/2026/17971","url":null,"abstract":"Artificial intelligence (AI)-automated decision systems encounter persistent, interdependent, and dynamic fairness tensions that traditional one-off interventions cannot resolve. Because these tensions persist due to interdependence and dynamic interaction, organizations require both a theory of the problem to explain their persistence and a theory of the solution to prescribe how they can be managed. Our design theory, FAIR (fairness adaptation through AI-augmented responsiveness), provides a theory of the problem by reframing AI fairness as a sociotechnical paradox constituted within AI artifacts that automate decision tasks, through interdependent organizational, technical, and governance choices and their interaction with regulatory mandates and societal norms. Synthesizing four fairness perspectives (ethics, organizational justice, economic fairness, and Rawlsian justice), we identify three metatheoretical dimensions (principles, goals, foci) and show that the interdependence within and among these dimensions is the root, endogenous source that constitutes paradoxical fairness tensions. Building on this diagnosis, FAIR provides a theory of the solution by specifying an organizational capability grounded in three design foundations. First, the paradox lens motivates iterative adaptive cycles (surfacing and resolving) to continually surface and resolve AI fairness tensions. Second, design science in information systems and computer science distinguishes AI artifacts (the “what”) from the actors (the “who”) responsible for adapting them, establishing the basis for complementary human-AI agent collaboration in the adaptive cycles: AI agents execute monitoring to surface and refinement to resolve tensions, whereas human agents specify objectives, adjudicate trade-offs, and exercise contextual judgment and oversight. Third, the managing-with-AI literature informs how this human-AI agent collaboration should be governed. These foundations yield two reinforcing mechanisms: (1) artifact-level adaptation, achieved through structured human-AI agent collaboration, within and across the layers of the AI decision pipeline—representation (data), learning (model), and calibration (decision); and (2) portfolio-level, risk-tiered federated governance that structures how human-AI agent collaboration scales across tasks and artifacts, balancing process standardization with configuration choices and human control with AI autonomy based on task risk. Enabled by organizational “fairness complements”—namely, human skills to work with AI agents and structured stakeholder feedback—this sociotechnical design provides organizations with a sustained capability to harmonize global coherence and local flexibility in the responsive adaptation of AI fairness.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"10 1","pages":"817-850"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Consultation Success on Online Health Platforms Using Dynamic Knowledge Networks and Multimodal Data Fusion","authors":"Shuang Geng,Wenli Zhang,Jiaheng Xie,Gemin Liang,Ben Niu,Sudha Ram","doi":"10.25300/misq/2025/19444","DOIUrl":"https://doi.org/10.25300/misq/2025/19444","url":null,"abstract":"Online healthcare consultation in virtual health is an emerging industry marked by innovation and fierce competition. Accurate and early prediction of healthcare consultation success can help online platforms proactively address patient concerns and improve retention rates. However, this prediction task is inherently challenging due to several factors: Patients’ needs often remain unclear until they explicitly articulate them, and their questions may evolve throughout the consultation process. Additionally, the task involves processing multimodal input information, including consultation dialogues and the complex network of various stakeholders in a patient’s healthcare journey. To address these issues, we propose the “dynamic knowledge network and multimodal data fusion” framework with a dynamic knowledge graph and multimodal data fusion, which enhances the predictive power of online healthcare consultations. Our work has important implications for new business models where specific and detailed online communication processes are stored in the IT database, and at the same time, latent information with predictive power is embedded in the network formed by stakeholders’ digital traces. It can be extended to diverse industries and domains, where the virtual or hybrid model (e.g., integration of online and offline services) is emerging as a prevailing trend.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"62 1","pages":"909-940"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategic Participation on Tokenized Platforms: Balancing Investment and Labor Intensities","authors":"Tianyi Li,Xiaoquan (Michael) Zhang","doi":"10.25300/misq/2025/19441","DOIUrl":"https://doi.org/10.25300/misq/2025/19441","url":null,"abstract":"Participants on tokenized platforms (i.e., platforms with blockchain implementation) can simultaneously take multiple roles, such as user, investor, and laborer, and draw income from the last two roles. Unlike traditional markets that typically prioritize one means of profitable participation, participants on such platforms need to allocate their efforts on the platform to increase revenue. We developed a decision framework for determining participants’ strategic participation on tokenized platforms to maximize earnings from investment and labor. Individual participants were distinguished from the platform-average participant, and decision-making is cast into two subproblems: (1) ignoring individual actions’ impact on platform state, we constructed strategies based on metrics that characterized model projections of future platform development and derived the metrics from Monte Carlo ensembles; (2) considering individuals’ actions as explicitly influencing the platform state, we formulated the control problem as a Markov decision process and solved it via reinforcement learning (RL). The framework addresses parameter uncertainty from model estimation, system uncertainty in model projection, and input uncertainty during participant-platform interaction. We compared metric-based and RL strategies from the two solution approaches using historical token price series; the results suggest good performance of our decision framework.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"28 1","pages":"941-970"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stimulating Feedback Contributions Using Digital Nudges: A Field Experiment in a Real-Time Mobile Feedback Platform","authors":"Michael Rivera,Xue Guo,Guohou Shan,Liangfei Qiu","doi":"10.25300/misq/2025/18920","DOIUrl":"https://doi.org/10.25300/misq/2025/18920","url":null,"abstract":"As more organizations recognize the importance of providing real-time feedback to enhance performance, a common challenge arises: Employees often lack the incentive to contribute enough high-quality feedback to their colleagues. Our study examines the use of digital nudges to encourage employees’ active participation in feedback applications. Building on cognitive load theory and job characteristics theory, we designed two key dimensions to enhance the effectiveness of digital nudges: timing of delivery and task significance messaging. We propose that the timing of digital nudges (morning vs. afternoon) influences employees’ cognitive load, while task significance messaging enhances motivation by emphasizing the meaningfulness of the task. Through a field experiment, we examined the effects of these two dimensions, individually and in combination, on feedback quantity and quality using a real-time feedback application. Our results show that digital nudges with task significance result in more feedback contributions and higher-quality feedback than generic message prompts. Moreover, timing amplifies these effects by lowering cognitive load, but only when task significance messaging is present. Through a follow-up randomized online experiment, we unpacked the mechanisms associated with the various digital nudge impacts. We found that timing reduces employees’ intrinsic and germane load while task significance increases employees’ germane load and external motivation. These findings indicate that while task significance serves as the primary motivator for feedback contribution, optimal timing enhances its effectiveness. We also found that nudge effectiveness varies with employees’ roles (i.e., managers vs. associates) as feedback givers and receivers. This study provides valuable theoretical insights and practical implications.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"16 1","pages":"1199-1216"},"PeriodicalIF":7.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}