Information Systems Research最新文献_第3页

Preparedness and Response in the Century of Disasters: Overview of Information Systems Research Frontiers 灾难世纪中的准备和响应：信息系统研究前沿概述

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-07-01 DOI: 10.1287/isre.2024.intro.v35.n2

Ahmed Abbasi, Robin Dillon, H. Raghav Rao, Olivia R. Liu Sheng

{"title":"Preparedness and Response in the Century of Disasters: Overview of Information Systems Research Frontiers","authors":"Ahmed Abbasi, Robin Dillon, H. Raghav Rao, Olivia R. Liu Sheng","doi":"10.1287/isre.2024.intro.v35.n2","DOIUrl":"https://doi.org/10.1287/isre.2024.intro.v35.n2","url":null,"abstract":"“The Century of Disasters” refers to the increased frequency, complexity, and magnitude of natural and man-made disasters witnessed in the 21st century: the impact of such disasters is exacerbated by infrastructure vulnerabilities, population growth/urbanization, and a challenging policy landscape. Technology-enabled disaster management (TDM) has an important role to play in the Century of Disasters. We highlight four important trends related to TDM, smart technologies and resilience, digital humanitarianism, integrated decision-support and agility, and artificial intelligence–enabled early warning systems, and how the confluence of these trends lead to four research frontiers for information systems researchers. We describe these frontiers, namely the technology-preparedness paradox, socio-technical crisis communication, predicting and prescribing under uncertainty, and fair pipelines, and discuss how the eight articles in the special section are helping us learn about these frontiers.History: Senior editor, Suprateek Sarker.Funding: This study was funded by the National Science Foundation (NSF) [Grants 2240347 and IIS-2039915]. H. R. Rao is also supported in part by the NSF [Grant 2020252]. The usual disclaimer applies.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141503754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Impact of Geographic and Social Proximity on Physicians: Evidence from the Adoption of an Online Health Community 地理和社会距离对医生的影响：采用在线健康社区的证据

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-14 DOI: 10.1287/isre.2020.0663

Panpan Wang, Liuyi He, Jifeng Luo, Zhiyan Wu, Han Zhang

{"title":"The Impact of Geographic and Social Proximity on Physicians: Evidence from the Adoption of an Online Health Community","authors":"Panpan Wang, Liuyi He, Jifeng Luo, Zhiyan Wu, Han Zhang","doi":"10.1287/isre.2020.0663","DOIUrl":"https://doi.org/10.1287/isre.2020.0663","url":null,"abstract":"Despite the increasing popularity of telehealth, the diffusion of online health communities lags behind because of the limited physician participation. The low adoption levels of telehealth could be attributed to the social environment rather than a baseline reluctance to adopt. By utilizing a panel data set of physicians’ adoption over eight years, we empirically investigate the impacts of geographically and socially close adopters and examined the interaction of proximity influences and competition in adoption. Our results suggest that positive effects of both geographic and social proximity influence on adoption when local competition among physicians on OHCs is low. The positive impact of socially close prior adopters increases with local competition, whereas that of geographically close prior adopters decreases with local competition. Therefore, online health communities could leverage proximity influence by incorporating information cues such as the cumulative adoption rates of close peers to facilitate physician adoption. However, the framing of information cues should consider interactions of competition and proximity influence. Platform managers need to balance the direct crowding-in effect of competition and the adverse moderating effect by which it diminishes the influence of geographic proximity, especially for low-title physicians. For high-title physicians, who are more independent, emphasize the usefulness of online platforms.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141343951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning Personalized Privacy Preference from Public Data 从公共数据中学习个性化隐私偏好

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-13 DOI: 10.1287/isre.2023.0318

Wen Wang, Beibei Li

{"title":"Learning Personalized Privacy Preference from Public Data","authors":"Wen Wang, Beibei Li","doi":"10.1287/isre.2023.0318","DOIUrl":"https://doi.org/10.1287/isre.2023.0318","url":null,"abstract":"In the era of digital transformation, understanding personalized privacy preferences is essential for firms and policymakers to build trust and ensure compliance. Traditional methods rely on private data and explicit user input, which can be invasive and impractical. This paper introduces a novel framework that leverages public data, specifically social media posts, to predict individual privacy preferences. By employing deep learning and natural language processing, the framework extracts psychosocial traits such as lifestyle, risk preferences, and emotional states from public data, offering a nonintrusive and scalable approach. Findings reveal that psychosocial traits derived from social media provide greater predictive power than traditional private data. This model aids businesses and policymakers by offering a deeper understanding of user privacy concerns, enabling the development of effective privacy policies and practices. This innovative approach not only enhances consumer privacy control and trust but also optimizes data management for platforms and informs better regulatory decisions, showcasing the practical implications of utilizing public data for privacy preference prediction.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141345057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Monitoring and Home Bias in Global Hiring: Evidence from an Online Labor Platform 全球招聘中的监督和家庭偏见：来自在线劳务平台的证据

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-12 DOI: 10.1287/isre.2021.0526

Chen Liang, Yili Hong, Bin Gu

{"title":"Monitoring and Home Bias in Global Hiring: Evidence from an Online Labor Platform","authors":"Chen Liang, Yili Hong, Bin Gu","doi":"10.1287/isre.2021.0526","DOIUrl":"https://doi.org/10.1287/isre.2021.0526","url":null,"abstract":"Online labor platforms increasingly use monitoring systems to manage remote workers. This study assesses whether and how these systems mitigate employer bias in hiring foreign versus domestic workers. Leveraging the exogenous introduction of a monitoring system for time-based projects on a leading online labor platform, we employ a difference-in-differences model to estimate the impact of monitoring systems on mitigating employers’ tendency to bias against hiring foreign workers (home bias). Results indicate a significant reduction in home bias, along with a 15% increase in the hiring of foreign workers following the introduction of the monitoring system. The mitigation effect is notably stronger in high-routine projects or when employers lack prior positive experiences with foreign workers, two scenarios characterized by low external uncertainty and high internal uncertainty, respectively. Moreover, employers no longer exhibit a stronger home bias in scenarios of lower moral hazard risk or coordination costs. These findings lend support to the effectiveness of monitoring systems in mitigating employers’ home bias through facilitating contractual control and coordination. Our study offers important implications for the design of online labor platforms and policymaking.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141350606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time to Stop? An Empirical Investigation on the Consequences of Canceling Monetary Incentives on a Digital Platform 该停止了吗？关于取消数字平台货币激励后果的实证调查

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-11 DOI: 10.1287/isre.2022.0017

Dongcheng Zhang, Hanchen Jiang, M. Qiang, Kunpeng Zhang, Liangfei Qiu

{"title":"Time to Stop? An Empirical Investigation on the Consequences of Canceling Monetary Incentives on a Digital Platform","authors":"Dongcheng Zhang, Hanchen Jiang, M. Qiang, Kunpeng Zhang, Liangfei Qiu","doi":"10.1287/isre.2022.0017","DOIUrl":"https://doi.org/10.1287/isre.2022.0017","url":null,"abstract":"Practice- and Policy-Oriented Abstract Digital platforms commonly use monetary incentives to motivate users to perform specific tasks. Existing studies have shown the effects of introducing such monetary rewards on task participation and performance on public platforms. However, little is known about the impact of canceling rewards, and particularly less attention is paid to corporate platforms. Our study examines the impact of canceling monetary incentives using quasi-natural experiments on a corporate platform. We find that canceling monetary incentives is not simply the reverse process of their introduction. Specifically, compared with the increase in task participation when rewards were initially introduced, canceling these rewards leads to a sharper decrease in participation. Additionally, although introducing rewards has no significant effect on task performance, canceling rewards causes a significant decline in performance. These results suggest that canceling monetary rewards has a net negative impact on task participation and performance. Furthermore, we examine the heterogeneity of this impact concerning user motivation types and working competency levels. We also discuss the similarities and differences between corporate and public platforms in the impact of monetary incentives. Our results provide important practical implications for enterprise information systems and general information systems regarding their design of incentive strategies.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141356345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving Students’ Argumentation Skills Using Dynamic Machine-Learning–Based Modeling 利用基于机器学习的动态建模提高学生的论证能力

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-10 DOI: 10.1287/isre.2021.0615

Thiemo Wambsganss, Andreas Janson, Matthias Söllner, Ken Koedinger, J. Leimeister

{"title":"Improving Students’ Argumentation Skills Using Dynamic Machine-Learning–Based Modeling","authors":"Thiemo Wambsganss, Andreas Janson, Matthias Söllner, Ken Koedinger, J. Leimeister","doi":"10.1287/isre.2021.0615","DOIUrl":"https://doi.org/10.1287/isre.2021.0615","url":null,"abstract":"This study explores the potential of dynamic, machine learning (ML)-based modeling to enhance students’ argumentation skills—a crucial component in education and professional success. Traditional educational tools often rely on static modeling, which does not adapt to individual learner needs or provide real-time feedback. In contrast, our research introduces an innovative ML-based system designed to offer dynamic, personalized feedback on argumentation skills. We conducted three empirical studies comparing this system against traditional methods such as scripted and adaptive support modeling. Our results show that dynamic behavioral modeling significantly improves learners’ objective argumentation skills across domains, outperforming all established methods. The results further indicate that, compared with adaptive support, the effect of the dynamic modeling approach holds across complex (large effect) and simple tasks (medium effect) and supports learners with lower and higher expertise alike. This research has important implications for educational policy and practice; incorporating such dynamic systems could transform learning environments by providing scalable, individualized support. This would not only foster essential skills but also cater to diverse learner profiles, potentially reducing educational disparities. Our work suggests a shift toward integrating more adaptive technologies in educational settings to better prepare students for the demands of the modern workforce.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Effect of Popularity Cues and Peer Endorsements on Assertive Social Media Ads 人气线索和同行认可对自信型社交媒体广告的影响

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-07 DOI: 10.1287/isre.2021.0606

Ashish Agarwal, Shun-Yang Lee, Andrew B. Whinston

{"title":"The Effect of Popularity Cues and Peer Endorsements on Assertive Social Media Ads","authors":"Ashish Agarwal, Shun-Yang Lee, Andrew B. Whinston","doi":"10.1287/isre.2021.0606","DOIUrl":"https://doi.org/10.1287/isre.2021.0606","url":null,"abstract":"Social media platforms, like Facebook, often display assertive call-to-action (CTA) ads that encourage direct purchases or app installs. These ads can show popularity cues (e.g., number of “likes”) and peer endorsements (e.g., friends who “liked” the ad). Although such signals can positively influence user engagement for informational ads, our research reveals they can backfire for assertive CTA ads. Through field tests on Facebook and incentive-compatible experiments, we find that popularity cues do not improve and that peer endorsements actually harm click performance on assertive CTA ads. The negative effect of peer endorsements is amplified when they come from dissimilar friends. Underlying this effect is users’ persuasion knowledge getting activated; they view these signals as manipulative advertising tactics for the assertive CTAs, resulting in psychological reactance. However, the detrimental impact is mitigated when peer endorsements come from friends with similar preferences. For advertisers, our findings suggest discounting popularity and peer endorsement metrics when evaluating assertive CTA ad performance. Platforms, like Facebook, should also consider making these signals optional for such ads. Overall, exercising discretion with these social proof signals for assertive purchase/install messaging can improve advertising outcomes.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141374862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of the General Data Protection Regulation on the Global Mobile App Market: Digital Trade Implications of Data Protection and Privacy Regulations 通用数据保护条例》对全球移动应用市场的影响：数据保护和隐私法规对数字贸易的影响

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-06-07 DOI: 10.1287/isre.2022.0421

Ziru Li, Gunwoong Lee, T. S. Raghu, Zhan (Michael) Shi

{"title":"Impact of the General Data Protection Regulation on the Global Mobile App Market: Digital Trade Implications of Data Protection and Privacy Regulations","authors":"Ziru Li, Gunwoong Lee, T. S. Raghu, Zhan (Michael) Shi","doi":"10.1287/isre.2022.0421","DOIUrl":"https://doi.org/10.1287/isre.2022.0421","url":null,"abstract":"Although regional data protection and privacy regimes are often cited as major barriers to crossborder digital trade, mitigating consumer privacy concerns through regulations can potentially increase the demand for foreign digital products or services. This study delves into this by assessing the impact of the General Data Protection Regulation (GDPR) on the global mobile app market. Contrary to the belief that such regulations hinder digital trade, our data show a notable post-GDPR increase in top foreign apps in European Union countries, suggesting that the GDPR may alleviate privacy concerns and encourage the adoption of foreign digital products. This finding is crucial for policymakers dealing with data and privacy issues as it indicates the potential of these regulations to balance economic growth with privacy and security protection. The study suggests that data and privacy regulations can address data concerns without significantly harming digital trade. Additionally, it uncovers an opportunity for multinational companies. Although compliance costs are higher, clear privacy regulations could lessen consumer domestic bias, opening doors to international markets. Therefore, evaluating privacy regulations’ impact on global markets means considering both their benefits for demand and their costs for suppliers.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

KETCH: A Knowledge-Enhanced Transformer-Based Approach to Suicidal Ideation Detection from Social Media Content KETCH：基于知识增强变换器的社交媒体内容自杀意念检测方法

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-05-31 DOI: 10.1287/isre.2021.0619

Dongsong Zhang, Lina Zhou, Jie Tao, Tingshao Zhue, Guodong (Gordon) Gao

{"title":"KETCH: A Knowledge-Enhanced Transformer-Based Approach to Suicidal Ideation Detection from Social Media Content","authors":"Dongsong Zhang, Lina Zhou, Jie Tao, Tingshao Zhue, Guodong (Gordon) Gao","doi":"10.1287/isre.2021.0619","DOIUrl":"https://doi.org/10.1287/isre.2021.0619","url":null,"abstract":"Suicide is a major cause of death among 15- to 29-year-olds globally, claiming more than 50,000 lives in the United States in 2023 alone. Despite governmental efforts to provide support, many individuals experiencing suicidal thoughts do not seek help but are increasingly turning to social media to express their feelings. This trend offers a critical opportunity for timely detection and intervention of suicidal ideation. We develop an innovative transformer-based model for suicidal ideation detection (SID) that combines domain knowledge with dynamic embedding and lexicon-based enhancements. Our model, which is tested on social media data in two languages from different platforms, outperforms existing state-of-the-art models for SID. We have also explored its applicability to detecting depression and its practical implementation in real-world scenarios. Our research contributes significantly to the field, offering new methods for timely and proactive intervention in suicidal ideation, with potential wide-reaching effects on public health, economics, and society. Methodologically, our approach advances the integration of human expertise into AI models to enhance their effectiveness.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Addressing Online Users’ Suspicion of Sponsored Search Results: Effects of Informational Cues 消除网络用户对赞助商搜索结果的疑虑：信息线索的影响

IF 4.9 3区管理学

Information Systems Research Pub Date : 2024-05-30 DOI: 10.1287/isre.2021.0364

Honglin Deng, Weiquan Wang, Kai H. Lim

{"title":"Addressing Online Users’ Suspicion of Sponsored Search Results: Effects of Informational Cues","authors":"Honglin Deng, Weiquan Wang, Kai H. Lim","doi":"10.1287/isre.2021.0364","DOIUrl":"https://doi.org/10.1287/isre.2021.0364","url":null,"abstract":"Online searches are often accompanied by sponsored content (e.g., targeted ads), which sometimes seem irrelevant but could be good alternatives to expand users’ consideration space. The sponsored search results (SSRs) often trigger suspicions among users. This study examines the potential of customer ratings and reviews of the SSRs to mitigate such suspicion and enhance user engagement with the SSRs. The research reveals that when SSRs for well-known brands are paired with positive customer ratings, users’ suspicion toward the SSRs can be reduced. However, for lesser-known brands, only ads with high ratings can effectively reduce users’ suspicion. This study further reveals that addressing users’ uncertainty in evaluating SSRs and concerns about the platform’s intentions in providing them is paramount to minimizing users’ suspicion. Our study holds significant practical implications for online platforms seeking to optimize the presentation of SSRs either with famous or unknown brands alongside organic search results. The findings underscore the importance of strategically integrating user-generated content and ratings to reduce the suspicion of users navigating SSRs. It offers actionable insights for e-commerce platforms aiming to enhance users’ decision-making processes by better utilizing SSRs with positive customer ratings.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0