Information Systems Frontiers最新文献_第2页

Human-Centric Auditing of AI-Powered Generative Search: When Citations Diverge from Rankings 以人为中心的人工智能生成搜索审计：当引用偏离排名时

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-09-10 DOI: 10.1007/s10796-026-10813-4

Chiang-Yu Cheng

引用次数: 0

Correction to: A Human-Centric Framework for Fair Job Recommendation Leveraging Generative AI and Data Augmentation 更正：利用生成式人工智能和数据增强的以人为中心的公平工作推荐框架

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-09-10 DOI: 10.1007/s10796-026-10817-0

Jianshan Sun,Jie shao,Kun Yuan,Dongyang Li

引用次数: 0

From Explainability to Actionability: a Tiered Adaptable Multi-Agent Framework with Agent Reasoning Tools for Collaborative Failure Recovery 从可解释性到可操作性：用于协同故障恢复的分层自适应多代理框架和代理推理工具

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-09-05 DOI: 10.1007/s10796-026-10815-2

Jie Tao,Lina Zhou

{"title":"From Explainability to Actionability: a Tiered Adaptable Multi-Agent Framework with Agent Reasoning Tools for Collaborative Failure Recovery","authors":"Jie Tao,Lina Zhou","doi":"10.1007/s10796-026-10815-2","DOIUrl":"https://doi.org/10.1007/s10796-026-10815-2","url":null,"abstract":"Abstract Effective human-AI collaboration, especially in failure scenarios, requires systems that function as active partners rather than static tools. This research addresses this requirement by introducing a tiered multi-agent architecture grounded in Human-Centered eXplainable AI principles. The architecture consists of three novel design artifacts: tiered reasoning that adapts explanation depth to failure severity, a traceable memory bus for auditability, and flexible reasoning tools for enhanced adaptability. These designs enable agents to not only perform evidence-based diagnoses of performance gaps but devise recovery strategies and propose actionable improvement plans as well. We empirically evaluate this architecture on an aspect term extraction task using hybrid methods that combine performance comparisons against state-of-the-art baselines, human expert user studies, and multi-role user simulations. The results demonstrate that our architecture significantly enhances both task performance and failure recovery diagnosis and plans. We then validate the generalizability of our architecture with a second task of comparable complexity. This research contributes an adaptable and generalizable framework and foundational artifacts for trustworthy AI teammates.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"179 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895957","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

Generative AI Labeling, Communication Style, and Perceived Emotional Support in Chatbot Interactions among International Students 国际学生聊天机器人互动中的生成式AI标签、沟通风格和感知情感支持

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-09-04 DOI: 10.1007/s10796-026-10814-3

Jian-Ren Hou, Maria Bellaniar Ismiati

引用次数: 0

Simulating the Future of Innovation: A Data-Grounded, Multi-Agent LLM Framework for R&D Collaboration Planning in Urban Mobility 模拟创新的未来：基于数据的城市交通研发协作规划的多智能体LLM框架

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-09-01 DOI: 10.1007/s10796-026-10797-1

Yong-Jae Lee

引用次数: 0

Emotional Resonance and Multimedia Presence: Unpacking Virality and Misinformation Risks in the Generative AI Era 情感共鸣和多媒体存在：在生成式人工智能时代，解开病毒式传播和错误信息的风险

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-09-01 DOI: 10.1007/s10796-026-10816-1

Venu Bhaskar Puthineedi, Ashish Kumar Jha

引用次数: 0

Explaining the Violation of Non-Disclosure Agreements by Software Developers 解释软件开发者违反保密协议的行为

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-08-29 DOI: 10.1007/s10796-026-10809-0

Gregory D. Moody, Mikko Siponen, Merrill Warkentin, Weijie Zhao

引用次数: 0

Neurosymbolic Large Language Models: A Survey of Symbolic Integration, Reasoning and Explainability 神经符号大语言模型：符号整合、推理和可解释性综述

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-08-28 DOI: 10.1007/s10796-026-10794-4

Maneeha Rani, Bhupesh Kumar Mishra, Dhavalkumar Thakker

{"title":"Neurosymbolic Large Language Models: A Survey of Symbolic Integration, Reasoning and Explainability","authors":"Maneeha Rani, Bhupesh Kumar Mishra, Dhavalkumar Thakker","doi":"10.1007/s10796-026-10794-4","DOIUrl":"https://doi.org/10.1007/s10796-026-10794-4","url":null,"abstract":"LLMs have demonstrated strong language-learning and human-like response-generation capabilities, and they are increasingly used to support decision-making in high-risk sectors. However, their internal decision processes remain difficult to interpret, and their responses may lack transparency. The literature has explored numerous approaches to address transparency challenges in LLMs, including Neurosymbolic AI (NeSy AI). NeSy AI approaches were primarily developed for conventional neural networks and may not transfer directly to the distinctive characteristics of LLMs. Consequently, there is a limited systematic understanding of how symbolic AI can be effectively integrated into LLMs. This paper aims to address this gap by first reviewing established NeSy AI methods and then proposing a novel taxonomy of symbolic integration in LLMs, along with a roadmap to merge symbolic techniques with LLMs. The taxonomy organises the literature across four dimensions: (1) the stage of LLM development at which symbolic information is integrated; (2) the coupling mechanism; (3) the architectural paradigm; and (4) the algorithm-level or application-level perspective. The review identifies commonly used benchmarks, recent advances and important research gaps, and uses these findings to outline directions for future research. By highlighting the latest developments and notable gaps in the literature, it offers practical insights for implementing frameworks for symbolic integration into LLMs to enhance transparency.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"38 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148842877","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

A Multi-Dimensional View of IS Discontinuance: Insights Using Socio-Technical Systems 信息系统停产的多维视角：使用社会技术系统的见解

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-08-28 DOI: 10.1007/s10796-026-10808-1

Smit Ghelani, Vidushi Pandey

引用次数: 0

Can Larger Language Models Always Perform Better? A Comparison of GPT, FinBERT, and Dictionaries in Evaluating Management Sentiment 更大的语言模型总是表现得更好吗？GPT、FinBERT和字典在评估管理情绪中的比较

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2026-08-25 DOI: 10.1007/s10796-026-10806-3

Xu Yang, Peng Liang, Indranil Bose, Nan Hu

引用次数: 0