This special issue seeks to generate novel insights that deepen scholarly understanding while informing practical policy and strategy across diverse economic, social, and geographic contexts.
Guest editors:
Dr. Abbas Tarhini,
Lebanese American University, Department of Information Technology & Operations
Management, Lebanon
Email: abbas.tarhini@lau.edu.lb, ORCID iD: https://orcid.org/0000-0002-9441-1649
Dr. Wissal Ben Arfi,
Associate Professor in Innovation and Entrepreneurship, and Chair of the Marketing Department at Paris School of Business
Email: w.benarfi@psbedu.paris, ORCID iD: https://orcid.org/0000-0002-4076-1731
Dr. Ina Kayser,
IST-Hochschule für Management, Germany,
Email: ikayser@ist-hochschule.de, ORCID iD: https://orcid.org/0000-0001-7521-7886
Special issue information:
Background and Motivation
The convergence of artificial intelligence (AI), Artificial General Intelligence (AGI), blockchain,Internet of Things (IoT), FinTech, and emerging data infrastructures is fundamentally transforming both regional socio-economic structures and organizational knowledge practices across the globe (Tarhini, et al., 2022). As digital transformation accelerates, organizations and societies alike are grappling with how best to integrate these technologies to foster sustainable development, improve governance, and enhance knowledge creation.
From a global perspective, AI is being recognized not just as an automation tool but as an augmentation force that significantly enhances human decision-making, knowledge creation, and value generation within organizations (Brynjolfsson & Mitchell, 2017; Grover et al., 2020). The role of AI in augmenting human intelligence is particularly relevant in knowledge-intensive environments where decision support systems, AI-driven hiring tools, and human-machine collaboration are becoming more prevalent (Lebovitz et al., 2021; Harfouche et al., 2023). However, significant challenges remain, including ensuring fairness, managing human-AI collaboration, and bridging the gap between tacit (know-how) and explicit (know-what) knowledge (Teodorescu et al., 2021; Wijnhoven et al., 2023).
Recent studies have highlighted the transformative potential of emerging technologies in driving innovation-driven growth and sustainability across different regions and sectors (Dabbous et al., 2024; Hao et al., 2024; Saunila, 2020).). AI-enabled solutions, in particular, are being integrated across healthcare, education, urban planning, and governance, creating new modes of value creation and knowledge transfer (Van Hoang, 2024; Mikhaylov et al., 2018). However, successful implementation requires contextual adaptation, especially in emerging and developing regions where institutional readiness, infrastructure maturity, and socio-cultural dynamics vary significantly (Dennehy et al., 2023; Wamba Taguimdje et al., 2020).
Globally, AI's ability to analyze vast amounts of data, recognize patterns, and generate insights enables new forms of knowledge generation that go beyond traditional human cognitive capabilities (Schwartz & Te'eni, 2024). However, the effectiveness of AI in knowledge work depends on how well it is integrated with human expertise and intuition, balancing machine-driven insights with human-centric practices (Lebovitz et al., 2021; Revilla et al., 2023). Ethical governance frameworks are crucial to guiding responsible AI use,particularly in balancing innovation promotion with safeguarding individual and societal rights (De Almeida, 2021; Gianni, 2022; Ferreira et al., 2019).
Digital transformation presents a unique opportunity across both developed and emerging economies, where it intersects with pressing socio-economic challenges such as digital inequality, governance gaps, and uneven access to infrastructure. As nations and organizations pivot toward knowledge-based models, AI and advanced analytics are increasingly leveraged to enhance evidence-based decision-making, improve public sector
responsiveness, and foster inclusive innovation ecosystems (Neupane, 2024; Carayannis et al., 2024). However, persistent disparities in digital infrastructure, gender inclusion, and digital literacy remain significant barriers to achieving equitable and sustainable transformation on a global scale.
By integrating both macro-level digital strategies and micro-level organizational practices, this special issue aims to offer a comprehensive platform for scholarly discourse on the evolving role of AI in global digital transformation. Contributions from diverse disciplines—including information systems, knowledge management, cognitive science, organizational learning, and AI ethics—are particularly encouraged. This special issue seeks to generate novel insights that deepen scholarly understanding while informing practical policy and strategy across diverse economic, social, and geographic contexts.
Topics and Research QuestionsWe invite researchers aimed at investigating the following topics:
1. AI for Regional and Socio-Economic Development:
• Digital transformation through AI and emerging technologies
• AI-driven decision-making in public and private sector governance
• FinTech innovations and their impact on financial inclusion and regional economies
• Blockchain and IoT applications beyond finance (e.g., healthcare, supply chains,
energy systems)
• Smart cities and sustainable urban planning
• Circular economy models and AI for sustainability
2. AI in Knowledge Transformation and Organizational Learning:
• Human-AI collaboration in decision-making and knowledge creation
• AI-driven decision support and augmentation of human intelligence
• AI's role in capturing and using tacit vs. explicit knowledge
• AI in organizational learning and knowledge augmentation frameworks
3. Ethical AI and Governance Frameworks:
• Governance frameworks for AGI and emerging technologies in global contexts
• Ethical AI, privacy, and data protection in evolving digital ecosystems
• Fairness, bias, and accountability in AI-driven knowledge processes
• Transparency and governance challenges in AI-generated knowledge
4. Human-Centric and Inclusive AI Applications:
• Cultural adaptation and technology acceptance in digital transformation initiatives
• Bridging the digital divide through improved digital infrastructure and accessibility
• Gender and digital inclusion: Empowering women through technology
• Information systems for promoting social inclusion and economic development
5. AI-Augmented Intelligence and Human Expertise:
• The interplay between human expertise and AI systems
• Augmentation vs. automation: when should humans remain in the loop?
• Unintended consequences of AI-driven decision-making in knowledge-intensive
tasks
• Chatbots and conversational AI in customer service and knowledge work
Manuscript submission information:
The timeline of this special issue is as follows:
Submission dates:
From To
Submission Deadline July 1, 2025 December 30, 2025
First Round of Reviews January 1, 2026 February 8, 2026
Revised Papers Due February 9, 2026 March 31, 2026
Second Round of Reviews April 1, 2026 April 21, 2026
Revised Papers Due (2nd round) April 22, 2026 May 24, 2026
Third Round of Reviews (if applicable) May 25, 2026 June 7, 2026
Final Decision Publication (copyediting and adjusting the paper to the JIK style guidelines) from June 8, 2026 to July 12, 2026
Publication: This is a VSI; accepted papers will be published online immediately once accepted and will be included in the next available issue of the journal.
Before submitting a manuscript, please read carefully the Journal of Innovation & Knowledge Guide for authors
In particular, authors should disclose in their manuscript the use of AI and AI-assisted technologies and a statement will appear in the published work. Declaring the use of these technologies supports transparency and trust between authors, readers, reviewers, editors, and contributors and facilitates compliance with the terms of use of the relevant tool or technology. Plagiarism in all its forms constitutes unethical behaviour and is unacceptable.
More information can be found at the following link:
https://www.sciencedirect.com/journal/journal-of-innovation-and-knowledge/publish/guide-for-authors
Short Special Issue Name: VSI: AI & Digital Futures
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References:
Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358: 1530–1534.
Carayannis, E. G., Askounis, D., Andoutropoulou, M., & Zotas, N. (2024). Leveraging AI for Enhanced eGovernment: Optimizing the Use of Open Governmental Data. Journal of the Knowledge Economy, 1-36.
Dabbous, A., Barakat, K. A., & Tarhini, A. (2024). Digitalization, crowdfunding, eco-innovation and financial development for sustainability transitions and sustainable competitiveness: Insights from complexity theory. Journal of Innovation & Knowledge, 9(1), 100460.
De Almeida, P. G. R., dos Santos, C. D., & Farias, J. S. (2021). Artificial intelligence regulation: a framework for governance. Ethics and Information Technology, 23(3), 505-525.
Dennehy, D., Griva, A., Pouloudi, N., Dwivedi, Y. K., Mäntymäki, M., & Pappas, I. O. (2023). Artificial intelligence (AI) and information systems: perspectives to responsible AI. Information Systems Frontiers, 25(1), 1-7.
Ferreira, J. J., & Teixeira, A. A. (2019). Open innovation and knowledge for fostering business ecosystems. Journal of Innovation & Knowledge, 4(4), 253-255.
Gianni, R., Lehtinen, S., & Nieminen, M. (2022). Governance of responsible AI: From ethical guidelines to cooperative policies. Frontiers in Computer Science, 4, 873437.
Grover, P., Kar, A. K., and Dwivedi, Y. K. (2020). “Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions,” Annals of Operations Research, pp. 1-37.
Harfouche, A., Quinio, B., Saba, M., & Bou Saba, P. (2023). The recursive theory of knowledge augmentation: Integrating human intuition and knowledge in artificial intelligence to augment organizational knowledge. Information Systems Frontiers. 25, 55–70 (2023). https://doi.org/10.1007/s10796-022-10352-8
Hao, X., Liang, Y., Yang, C., Wu, H., & Hao, Y. (2024). Can industrial digitalization promote regional green technology innovation?. Journal of Innovation & Knowledge, 9(1), 100463.
Lebovitz, S., Levina, N., & Lifshitz-Assaf, H. (2021). Is AI ground truth really true? The dangers of training and evaluating AI tools based on experts’ know-what. MIS Quarterly, 45(3), 1501-1525. https://doi.org/10.25300/MISQ/2021/16564
Mikhaylov, S. J., Esteve, M., & Campion, A. (2018). Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration. Philosophical transactions of the royal society a: mathematical, physical and engineering sciences, 376(2128), 20170357.
Neupane, B. (2024). Artificial Intelligence and Big Data Technologies to Optimize Government Decision-Making Processes in Cloud-Based Environments. Journal of Artificial Intelligence and Machine Learning in Cloud Computing Systems, 8(11), 1-12.
Revilla, E., Saenz, M. J., Seifter, M., & Ma, Y. (2023). Human–artificial intelligence collaboration in prediction: A field experiment in the retail industry. Journal of Management Information Systems, 40(4), 1071–1098.
https://doi.org/10.1080/07421222.2023.2267317
Saunila, M. (2020). Innovation capability in SMEs: A systematic review of the literature. Journal of Innovation & knowledge, 5(4), 260-265.
Schwartz, D., & Te'eni, D. (2024). AI for knowledge creation, curation, and consumption in context. Journal of the Association for Information Systems, 25(1), 37-47.
Tarhini, A., Harfouche, A., & De Marco, M. (2022). Artificial intelligence-based digital transformation for sustainable societies: the prevailing effect of COVID-19 crises. Pacific Asia Journal of the Association for Information Systems, 14(2), 1.
Teodorescu, M. H. M., Morse, L., Awwad, Y., & Kane, G. C. (2021). Failures of fairness in automation require a deeper understanding of human-ML augmentation. MIS Quarterly, 45(3), XX-XX. https://doi.org/10.25300/MISQ/2021/16535
Van Hoang, T. (2024). Impact of integrated artificial intelligence and internet of things technologies on smart city transformation. Journal of Technical Education Science, 19(Special Issue 01), 64-73.
Wamba-Taguimdje, S. L., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business process management journal, 26(7), 1893-1924.
Wijnhoven, F., Hoffmann, P., Bemthuis, R., & Boksebeld, J. (2023). Using process mining for workarounds analysis in context: Learning from a small and medium-sized company
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