Pub Date : 2025-12-26DOI: 10.1007/s10796-025-10671-6
Tanmay Chakraborty, Marion Koelle, Jörg Schlötterer, Nadine Schlicker, Christian Wirth, Christin Seifert
{"title":"Explanation Format does not Matter; but Explanations do - An Eggsbert study on explaining Bayesian Optimization tasks","authors":"Tanmay Chakraborty, Marion Koelle, Jörg Schlötterer, Nadine Schlicker, Christian Wirth, Christin Seifert","doi":"10.1007/s10796-025-10671-6","DOIUrl":"https://doi.org/10.1007/s10796-025-10671-6","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"6 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145829919","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}
Pub Date : 2025-12-22DOI: 10.1007/s10796-025-10668-1
Marilyn Bello, Rafael Bello, María-Matilde García, Ann Nowé, Iván Sevillano-García, Francisco Herrera
{"title":"A Three-level Framework for LLM-enhanced Explainable AI: From Technical Explanations to Natural Language","authors":"Marilyn Bello, Rafael Bello, María-Matilde García, Ann Nowé, Iván Sevillano-García, Francisco Herrera","doi":"10.1007/s10796-025-10668-1","DOIUrl":"https://doi.org/10.1007/s10796-025-10668-1","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"21 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145807378","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}
Pub Date : 2025-12-22DOI: 10.1007/s10796-025-10681-4
Zainab Al-Lataifeh, Mark A. Harris, James Smith, Amita Goyal Chin
Generative AI Health Assistants (GAIHAs) are transforming patient engagement in modern healthcare by providing personalized support and medical information. Despite the rapid growth in the number of GAIHAs and the technologies that integrate them, patient adoption remains uncertain. This uncertainty highlights the need for a deeper exploration of the factors influencing their acceptance and adoption as well as the barriers that limit widespread use. Traditional models, like the Technology Acceptance Model (TAM), primarily emphasize adoption drivers such as usefulness and ease of use while overlooking barriers such as privacy concerns and resistance to change. Other models such as the Unified Theory of Acceptance and Use of Technology (UTAUT) include social influence but limit scope to workplace expectations, neglecting broader social dynamics that are relevant in consumer-driven contexts like healthcare. This study investigates the drivers of GAIHA adoption through a new framework, EVF-DOI-IB, which integrates the Extended Valence Framework (EVF), the Diffusion of Innovation (DOI) theory, and Innovation Barriers (IB). The proposed framework builds on the core constructs of trust, risk, benefit, and intention from EVF, and extends them with additional antecedents. The new framework also incorporates innovation drivers from the DOI perspective, namely relative advantage, trialability, and interpersonal communication. Finally, the new framework includes the innovation barriers resistance to change and privacy concerns. The results from a quantitative analysis of our survey data reveal that trust and perceived benefits strongly predict adoption intentions while resistance to change and privacy concerns heighten perceived risks. The findings also show that interpersonal communication and relative advantages play vital roles in reinforcing trust. Our research contributes to the body of knowledge in that it expands EVF’s application to the domain of healthcare AI technologies and provides actionable recommendations for developers and healthcare providers.
{"title":"Generative AI Health Assistants in Modern Healthcare: Drivers and Barriers to Adoption","authors":"Zainab Al-Lataifeh, Mark A. Harris, James Smith, Amita Goyal Chin","doi":"10.1007/s10796-025-10681-4","DOIUrl":"https://doi.org/10.1007/s10796-025-10681-4","url":null,"abstract":"Generative AI Health Assistants (GAIHAs) are transforming patient engagement in modern healthcare by providing personalized support and medical information. Despite the rapid growth in the number of GAIHAs and the technologies that integrate them, patient adoption remains uncertain. This uncertainty highlights the need for a deeper exploration of the factors influencing their acceptance and adoption as well as the barriers that limit widespread use. Traditional models, like the Technology Acceptance Model (TAM), primarily emphasize adoption drivers such as usefulness and ease of use while overlooking barriers such as privacy concerns and resistance to change. Other models such as the Unified Theory of Acceptance and Use of Technology (UTAUT) include social influence but limit scope to workplace expectations, neglecting broader social dynamics that are relevant in consumer-driven contexts like healthcare. This study investigates the drivers of GAIHA adoption through a new framework, EVF-DOI-IB, which integrates the Extended Valence Framework (EVF), the Diffusion of Innovation (DOI) theory, and Innovation Barriers (IB). The proposed framework builds on the core constructs of trust, risk, benefit, and intention from EVF, and extends them with additional antecedents. The new framework also incorporates innovation drivers from the DOI perspective, namely relative advantage, trialability, and interpersonal communication. Finally, the new framework includes the innovation barriers resistance to change and privacy concerns. The results from a quantitative analysis of our survey data reveal that trust and perceived benefits strongly predict adoption intentions while resistance to change and privacy concerns heighten perceived risks. The findings also show that interpersonal communication and relative advantages play vital roles in reinforcing trust. Our research contributes to the body of knowledge in that it expands EVF’s application to the domain of healthcare AI technologies and provides actionable recommendations for developers and healthcare providers.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"2 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145807716","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}
Pub Date : 2025-12-22DOI: 10.1007/s10796-025-10678-z
Jules SADEFO KAMDEM, Danielle Selambi Kapsa
{"title":"CyberRisk Prediction using Machine Learning and Extreme Value Theory","authors":"Jules SADEFO KAMDEM, Danielle Selambi Kapsa","doi":"10.1007/s10796-025-10678-z","DOIUrl":"https://doi.org/10.1007/s10796-025-10678-z","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"45 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145807379","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}
Pub Date : 2025-12-19DOI: 10.1007/s10796-025-10686-z
Dawen Yan, Manran Zhang
{"title":"Correction to: Prediction of Financial Distress for Chinese Listed Manufacturing Companies given Uncertain Financial Accounting Data Environments","authors":"Dawen Yan, Manran Zhang","doi":"10.1007/s10796-025-10686-z","DOIUrl":"https://doi.org/10.1007/s10796-025-10686-z","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"151 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796211","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}
Pub Date : 2025-12-13DOI: 10.1007/s10796-025-10653-8
Jingjing Li, Haiyang Feng, Nan Feng, Nan Yuan
{"title":"Optimal Data Collection Levels for Two-Sided Software Platforms: Considering User Privacy Concerns","authors":"Jingjing Li, Haiyang Feng, Nan Feng, Nan Yuan","doi":"10.1007/s10796-025-10653-8","DOIUrl":"https://doi.org/10.1007/s10796-025-10653-8","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"10 3 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145752825","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}
Pub Date : 2025-12-12DOI: 10.1007/s10796-025-10666-3
Navid Aghakhani, Chia-Wei Joy Lin, Hamid Reza Nikkhah, Michelle Carter
{"title":"Social Media Engagement and Consumer Patronage: The Moderating Role of Business Operation and Competition Intensity","authors":"Navid Aghakhani, Chia-Wei Joy Lin, Hamid Reza Nikkhah, Michelle Carter","doi":"10.1007/s10796-025-10666-3","DOIUrl":"https://doi.org/10.1007/s10796-025-10666-3","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"32 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145752826","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}
Pub Date : 2025-12-12DOI: 10.1007/s10796-025-10663-6
Rajat Subhra Chatterjee, Tomas Kliestik, Deepak Kumar Singh, Uthayasankar Sivarajah, Sheshadri Chatterjee
{"title":"Ethical and Structural Determinants of Generative AI-Driven Healthcare Data Sharing for Financial Analysis","authors":"Rajat Subhra Chatterjee, Tomas Kliestik, Deepak Kumar Singh, Uthayasankar Sivarajah, Sheshadri Chatterjee","doi":"10.1007/s10796-025-10663-6","DOIUrl":"https://doi.org/10.1007/s10796-025-10663-6","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"362 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753181","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}
Pub Date : 2025-12-08DOI: 10.1007/s10796-025-10656-5
Luis Ibañez-Lissen, Lorena González-Manzano, José M. de Fuentes, Joaquin Garcia-Alfaro
{"title":"Characterizing Cross-Contamination on Multitask Multimodal Large Language Models","authors":"Luis Ibañez-Lissen, Lorena González-Manzano, José M. de Fuentes, Joaquin Garcia-Alfaro","doi":"10.1007/s10796-025-10656-5","DOIUrl":"https://doi.org/10.1007/s10796-025-10656-5","url":null,"abstract":"","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"20 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697024","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}
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