The interdisciplinary interfaces of Information Systems (IS) are fast emerging as defining areas of research and development in IS. These developments are largely due to the transformation of Information Technology (IT) towards networked worlds and its effects on global communications and economies. While these developments are shaping the way information is used in all forms of human enterprise, they are also setting the tone and pace of information systems of the future. The major advances in IT such as client/server systems, the Internet and the desktop/multimedia computing revolution, for example, have led to numerous important vistas of research and development with considerable practical impact and academic significance. While the industry seeks to develop high performance IS/IT solutions to a variety of contemporary information support needs, academia looks to extend the reach of IS technology into new application domains. Information Systems Frontiers (ISF) aims to provide a common forum of dissemination of frontline industrial developments of substantial academic value and pioneering academic research of significant practical impact.  
  
Information Systems Frontiers will focus on research and development at the IS/IT interfaces in the academia and industry. The interfaces include the base disciplines of computer science, telecommunications, operations research, economics and cognitive sciences, for instance. Emerging areas that ISF will concentrate on in the next few years include, but are not limited to:

    enterprise modeling and integration
    emerging object/web technologies
    information economics
    IT integrated manufacturing
    medical informatics
    digital libraries
    mobile computing and electronic commerce.

The publication highlights of ISF are:

Focus

    Provide a forum for both academicians and industry specialists to explore the multiple frontiers of the IS/IT field
    Bring innovative research on all aspects of IS/IT interfaces from analytical, behavioral and technological perspectives 

Format

    Published bimonthly, with dedicated issues on a regular basis as well as a general issue per year
    Internet support with abstracts, fast track reviews, discussion groups and a variety of other services

Content

    Theories and models of IS/IT systems and solutions
    Pragmatic solutions to practical IS/IT problems
    Computational, empirical and system developmental studies
    Perspectives synthesizing recent developments in interface areas
    State-of-the-art, state-of-the-market, state-of-the-practice surveys
    Reviews of challenges, solutions and lessons learned in practice
    Management
    An Editorial Advisory Group and an Editorial Board both including outstanding individuals fro academia and industry
    Eminent guest editors for the dedicated issues,
    Editors of websites managing and maintaining the internet services. 

Special Issue on Innovative Applications and Ethical Implications of AI in the data sharing and financial analysis: Emerging Trends and Future Directions
截稿日期: 2025-11-30

Artificial Intelligence (AI) has profoundly impacted various sectors, including AI in data sharing and financial analysis; specifically in areas such as reporting, and access control (Papazafeiropoulou & Spanaki, 2016), 20. AI's capabilities in enhancing financial forecasting, risk management, investment strategies, and fraud detection are reshaping industries beyond financial services.This special issue aims to explore the latest advancements in AI applications across data sharing, financial analysis, and specifically for reporting, and access control purposes, while addressing ethical implications, adoption challenges, and data governance issues associated with these technologies (Jinasena et al. 2023). Implementing AI in these areas raises several ethical considerations related to transparency, fairness, accountability, data privacy, and regulatory compliance (Papazafeiropoulou & Spanaki, 2016; Spanaki et al. 2024),.

A primary ethical concern revolves around ensuring the transparency and explainability of AI algorithms used in decision-making processes. Organizations must design AI systems that minimize biases to avoid discriminatory practices (Parra Rodríguez, 2022). The integration of big data and AI in these sectors also raises significant concerns regarding data privacy and security, necessitating compliance with data protection laws and robust security measures (Aldboush, 2023, Spanaki et al 2023).

Establishing accountability through governance frameworks is essential to oversee the ethical deployment of AI and manage associated risks (Kurshan et al., 2021; Jinasena et al, 2023). Additionally, adherence to ethical standards and regulatory requirements through regular audits and updates is crucial to prevent misuse and ensure compliance (Ahmed, 2022).

This call for papers seeks to promote research exploring innovative uses of AI across AI data sharing, financial analysis and specifically on reporting, and access control purposes. The objective is to foster the development of ideas, methods, models, and solutions that leverage AI technologies to enhance decision-making, operational efficiency, and strategic planning across industries. Empirical and conceptual papers employing qualitative, quantitative, and mixed methodological approaches are invited. Topics of interest include transparency and explainability of AI algorithms, bias mitigation in AI-driven systems, data privacy and security, ethical governance frameworks, AI's impact on market stability and systemic risk, regulatory compliance, fairness and accountability in AI applications, customer trust in AI technologies, ethical implications of AI in automated systems, and balancing innovation with ethics in AI-driven products.

Researchers and practitioners are encouraged to submit papers that contribute to a deeper understanding of AI's multifaceted relationship with AI data sharing, financial analysis, reporting, and access control, aiming to inform practices and policies across various industries.

This special issue call is an open call for any submission relevant to the topic area, but also intends to publish papers presented at the conference titled "Innovative Applications and Ethical Implications of AI in AI Data Sharing, Financial Analysis, Reporting, and Access Control," scheduled in Heraklion, Crete, Greece, from September 19 to September 21, 2025. The Scientific Committee of the Conference will select papers for inclusion, advancing knowledge and practices in industry and society.

Submission Guidelines

Authors are invited to submit original research articles, reviews, case studies, and theoretical papers. All submissions will undergo a rigorous peer-review process to ensure the highest scientific quality and relevance standards.

Important Dates

• Submission Deadline: 30 November 2025
• Notification of Acceptance: 28 February 2026
• Final Manuscript Due:30 April 2026
• Publication Date: 30 June 2026

Special Issue on Leading and Managing in the Digital Era: Shaping the Future with AI and Data Analytics
截稿日期: 2025-12-01

The integration of Artificial Intelligence and Analytics (AI&A) is fundamentally transforming organizational leadership and management practices (Brynjolfsson & Mitchell, 2017; Raisch & Krakowski, 2021). As these technologies become increasingly sophisticated and pervasive, they are creating unprecedented challenges and opportunities for leaders and managers across all sectors (Dwivedi et al., 2021). The rapid advancement of Generative AI (GenAI) and large language models is accelerating this transformation, requiring new frameworks for understanding effective leadership and management in digitally-transformed organizations.

Alongside these advancements, ensuring ethical and accountable use of AI&A has become a critical concern (Dennehy et al., 2022). Leaders must address complex issues, including algorithmic bias, data privacy, transparency, explainability, and the societal impact of automation. Responsible leadership involves not only leveraging these technologies for innovation and efficiency but also embedding ethical principles into their design and implementation to build trust and develop sustainable organizational practices (Alshahrani et al., 2024; Floridi & Cowls, 2019). This responsibility is further compounded by the need to adapt traditional management theories and practices to address the complexities of leading AI&A-enabled organizations (Raj & Seamans, 2019). Leaders must now balance human-centric approaches with data-driven decision making, while addressing critical concerns around AI governance, ethics, and responsible innovation (Westerman et al., 2022). The emergence of GenAI tools is further challenging conventional notions of knowledge work and requiring new models of human-AI collaboration (Kolbjornsrud, 2024; Simon et al., 2024).

This special issue aims to advance our understanding of how leadership and management practices are evolving in response to digital transformation and AI&A adoption. While previous special issues in Information Systems Frontiers have examined various aspects of digital transformation and AI implementation (e.g., Pappas et al., 2023), or focused solely on AI and Responsibility (e.g., Dennehy et al., 2022), this issue specifically focuses on the changing nature of leadership and management in AI-enabled organizations. We seek contributions that examine both theoretical frameworks and empirical evidence for effective leadership in the digital era.

Topics of interest include, but are not limited to:

Leadership and Governance

• AI&A governance frameworks and responsible leadership
• Ethical considerations in AI-enabled decision making
• Managing AI-human teams and collaboration
• Digital leadership competencies and development
• Trust building in AI&A-enabled organizations
• The role of IS in enhancing responsible AI&A practices

Strategic Management

• AI&A strategy development and implementation
• Digital transformation leadership
• Innovation management in AI&A-enabled organizations
• Business model adaptation for the digital era
• Competitive dynamics in AI&A-intensive industries

Organizational Transformation

• Change management for AI&A adoption
• Cultural transformation in digital organizations
• Talent management for AI&A-enabled organizations
• Knowledge management in the age of GenAI
• New organizational forms and structures

Human Capital Development

• Leadership development for the digital era
• Building digital capabilities and competencies
• Managing hybrid human-AI workforces
• Upskilling and reskilling strategies
• Career development in AI-enabled organizations

Submission Guidelines

This special issue will consist of papers from two sources: (1) selected papers from the 2025 Leading and Managing in the Digital Era (LMDE) conference (lmde.net), and (2) submissions from an open call for papers. Papers from the LMDE conference must be substantially enhanced and will undergo the same rigorous peer review process as other submissions.

All submissions must follow the journal's standard formatting guidelines and be submitted through the editorial manager system: https://www.editorialmanager.com/isfi/default.aspx

Authors should aim for papers of approximately 25-30 pages (in submission format, 11 Font, 1.5 line spacing, including abstract, figures, tables, references and appendix).

Important Dates

• Submission deadline: December 1, 2025
• First round reviews: February 1, 2026
• Revised manuscripts due: April 1, 2026
• Second round reviews: June 1, 2026
• Final versions due: September 1, 2026
• Tentative publication date: November 15, 2026

Special Issue on Human- Centric and Generative AI for Information Access
截稿日期: 2025-12-15

The rapid growth of generative models and conversational AI is changing how we think about Information Systems (IS), especially in the area of information access (Shah, 2023; White, 2025). Tools like large language models (LLMs) and recommender systems (RS) are now central to how people search for, interact with, and consume information. As these technologies become more common, there is a growing need to design them in ways that are transparent, ethical, and focused on human needs (Mitra, 2025).

These AI systems are increasingly used in everyday contexts, like education, healthcare, law, and media (Storey, 2025). Because of this, research in IS must also pay attention to challenges such as bias, fairness, trust, and environmental impact. This is a key moment to rethink the future of information retrieval (IR) and recommendation research, putting people and ethical concerns at the center alongside technical performance (Stray, 2024; Bernard, 2025). At the same time, the variety of data available, from text and voice to images and user behavior, is opening up new ways to personalize and improve how we access information (Liu, 2024; Luo, 2024). This creates exciting opportunities for new ideas and practical solutions that combine IS, human-computer interaction, RS, and generative AI.

This special issue aims to explore how these human-centered and generative technologies can shape the future of information systems. We welcome research that offers new ideas, methods, or practical studies on how to design, build, and evaluate AI-powered systems for accessing information. These topics are closely aligned with the interests of Information Systems Frontiers and reflect current discussions in the AI and IS communities.

The emergence of large-scale generative models and conversational AI systems is reshaping the landscape of Information Systems (IS), especially in the domain of information access (Shah, 2023), (White, 2025). As human interaction with information becomes increasingly mediated by AI-driven technologies, ranging from large language models (LLMs) to adaptive recommender systems (RS), a new paradigm that prioritizes human-centricity, transparency, and ethical responsibility is taking shape in the design and deployment of IS solutions (Mitra, 2025).

Generative systems become embedded in everyday information interactions (across domains like education, healthcare, law, and media) (Storey, 2025) the need for responsible design principles becomes more pressing. Information Systems research is now expected also to address issues of bias, fairness, trust, and environmental impact. This moment presents a timely opportunity to redefine the paths of IR and RS research by foregrounding human values and ethical considerations alongside algorithmic performance (Stray, 2024) and (Bernard, 2025).

At the same time, the increasing availability of multimodal data streams (from voice and text to visual and behavioral) data offers vast potential to personalize and enrich information access experiences (Liu, 2024) and (Luo, 2024). This offers a unique opening for theoretical innovation and applied exploration at the intersection of IS, human-computer interaction, RS, and generative AI.

This special issue aims to collect research that advances our understanding of how generative and human-centric technologies can shape the next generation of information systems. It invites contributions that offer conceptual, empirical, and methodological insights into designing, deploying, and evaluating AI-powered systems for information access. This aligns well with the scope and readership of Information Systems Frontiers and contributes to contemporary conversations in AI-driven information systems.

We welcome submissions that address (but are not limited to) the following topics:

· Human-centric search, recommendation, and information filtering
· Generative AI for user interaction and information access
· Conversational IR, dialogue systems, and interactive agents
· Multimodal representation and retrieval
· Integration of LLMs in search and recommendation pipelines
· Fairness, transparency, and ethics in IR and RS
· Evaluation methodologies for interactive and generative systems
· Privacy-aware and responsible information access
· Application domains: education, healthcare, legal, cultural heritage
· Modeling user behavior and personalization
· Societal implications of AI-powered IR and RS
· Environmental sustainability of AI in IS and RS contexts
· Explainability, interpretability, and trust in generative systems

Special Issue on Interdisciplinary Research between IS and Tourism
截稿日期: 2025-12-31

The tourism industry has numerous examples of how smart technologies streamline Information System (IS) efforts and tourist experiences (Goo et al., 2022). As new business models emerge, a wave of technology-driven paradigms is transforming the tourism industry (Yang et al., 2024). Over the past two decades, the development of a tourism business ecosystem through various internet platforms and technological innovations has given rise to the concept of "smart tourism" (Gretzel et al., 2015). Now, the rise of AI is ushering smart tourism into a new era (Gupta et al., 2023). Tourism's rich history has produced extensive theoretical and practical implications across various disciplines, including marketing, management, branding, social network services, and online advertising. While IS in tourism remains a niche area in literature, its understanding continues to evolve. The field's momentum requires support from groundbreaking scholarly publications. With touristic products and experiences rapidly redefining the tourism industry through IS (Migliorini et al., 2024), this presents an optimal time to capitalize on this momentum in the era of Artificial Intelligence (AI).

The integration of IS research and tourism, coupled with vast data streams from devices, mobile phones, wearables, images, text, and voice inputs (Campbell et al., 2020; Kang et al., 2024) has only begun to tap into its full potential. Tourism practices can be significantly enhanced through IS applications, from elevating tourist experiences and refining destination marketing strategies to automating operations, streamlining customer support, optimizing targeted marketing, and extracting meaningful insights from tourist feedback (Koo et al., 2017, Verma et al., 2021). While these benefits make a compelling case for continued IS research, the pursuit of AIdriven opportunities in tourism development must be balanced against emerging concerns. Critical issues such as ethics, fairness, and data protection have become increasingly prominent (Vlačić et al., 2021). As tourists increasingly weave smartphones and AI into their travel experiences and daily routines, this early phase of AI development offers unique opportunities to expand both theoretical and practical understanding of IS in tourism. This special issue invites contributions that advance understanding of IS applications and methodologies within tourism contexts in the era of AI. We welcome research addressing the following areas, though submissions are not limited to these topics

• Smart tourism experience, smart tourism destination
• Smart business ecosystems and platform
• Psychological and behavioural reactions to IS developments in tourism products / services
• Cross-cultural differences and regional disparities in adoption of IS in tourism products / services
• AI-powered tourist experience
• Societal, cultural, and ethical issues related to AI-powered tourism marketing practices
• Assessment of the positive and negative implications of AI developments in tourism marketing
• Advanced and novel applications in tourism
• Advancing the machine learning methods for prediction and feature engineering in tourism
• IS for tourists’ decision making and choice modeling
• AI-powered service automation in tourism
• Big data and pattern recognition in tourism marketing
• Understanding tourists’ opinions using IS
• Ethical, privacy issue, security and data protection