Announcements Calls for Papers Transactions on Engineering Management

IEEE Transactions on Engineering Management Call for Submissions for Special Issue on “AI 2 AI Business Platforms: An Emerging Agenda for Organizational Studies”

Guest Editors

Dr Yashar Salamzadeh
Senior Lecturer in Digital Business, Faculty of Business, Law
and Tourism, University of Sunderland, Sunderland, UK

Prof. Nadja Damij, PhD
Faculty of Business, Law and Tourism, University of Sunderland, Sunderland, UK

Dr Pardis Moslemzadeh Tehrani
Faculty of Business, Law and Tourism, University of Sunderland, Sunderland, UK

Dr Dolores Modic
Associate Professor in Innovation and Management
Nord University Business School, Nord University, Norway

Dr Thomas Rashford
Lecturer in Business and Management
Faculty of Business, Law and Tourism, University of Sunderland, Sunderland, UK

Prof. Tsan-Ming (Jason) Choi, PhD
Chair in Operations and Supply Chain Management
Management School, University of Liverpool, UK

Aims and Objectives
For years, business model design, business model innovation and business model transformation
were trending topics for researchers and practitioners (Massa and Tucci, 2013; Spieth et al., 2014;
Chesbrough, 2010; Pieroni et al., 2019; Kraus et al., 2022; Mostaghel et al., 2022; Andreini et al.,
2022; Damij & Damij, 2014). However, the business model transformation idea is not stopping
just on simple innovations, and some radical transformations based on industrial revolutions and
for our days, the IR 4.0 is playing this role (Li et al., 2022; Favoretto et al., 2022; Salamzadeh,

With the expansion of the idea of using artificial intelligence in various aspects of businesses, we
see many new technologies, tools, services, and business ideas developed on the strengths of AI
(Artificial Intelligence) (Enholm et al., 2022; Feuerriegel et al., 2022; Weber et al., 2022; Damij
& Bhattacharya, 2022; Hafner et al., 2022; Olan et al., 2022). This application ranges from AI in
marketing to AI in HRM (Human Resource Management) and to AI in strategic management. We
can easily see that AI is almost everywhere in our organizational systems, from design to customer
service and it is becoming a cradle-to-cradle tool for many products and services. Many businesses
have started using AI as a tool [to streamline their operations] such as finding the best supplier
(Cui et al., 2022), the best employee performance (Kelly, 2022), the best manager (Soleimani et
al., 2022), the best-selling opportunity (Kopalle et al., 2022), the best market to enter (Cao, 2022),
customer relationship management (Ledro et al., 2022), etc.

One of the potential applications of the AI can be the scenario of AI2AI business platforms, which
have started to emerge. Programmers and business practitioners can design an AI tool to find the
best price for them, while suppliers can also develop AI tools to negotiate with potential customers
on prices and quantities of their orders. As it can be seen from this simplified example, it will be
highly possible to see these two AI tools make a deal and do this purchase task for their businesses.
Similar examples can be shared on how AI tools can hire a talented employee, propose a new
strategy based on business intelligence or invest in a new financial opportunity.

In order to manage these types of business practices performed and/or managed and/or made
decision on, using AI tools on both sides of the transaction, we need to start conceptualizing the
AI-to-AI business platforms and to make the role of human clear in this process.

As this is an emerging topic with really rare academic research on, this research idea is proposed
and we try to achieve to as many as possible of conceptual frameworks on human, technologic,
social, organizational, financial, and entrepreneurial sides of these AI2AI business platforms. This
is the reason we accept qualitative, quantitative, and mixed method papers to share different
narratives about this emerging concept with different stakeholders. Therefore, investigating and
conceptualizing both dark and light sides of this scenario seems an urgent topic of discussion for
academia and for practitioners.

The topics of the papers for this special issue are related/but not limited to the below items:

  • AI-AI business platforms, conceptual models
  • AI-AI business platforms, and their impact on human resources (employees and managers)
  • AI-AI business platforms, and their impact on organizational systems
  • AI-AI business platforms, and their impact on entrepreneurial activities in business ecosystems
  • AI-AI business platforms, and their impact on human-machine interaction approaches
  • AI-AI business platforms, and technologies incorporated in them.
  • AI-AI business platforms, and their social impact (quality of life, equality, justice, happiness and…)
  • AI-AI business platforms, and relevant business model innovations
  • AI-AI business platforms, and the philosophical aspects of this paradigm shift
  • AI-AI business platforms, and circular economy
  • AI-AI business platforms and the new generations (Gen Z and Gen Alpha)
  • AI-AI business platforms and Policy Governance
  • AI-AI business platforms and regulatory frameworks
  • Ethical implications of AI-AI business platforms in different industries
  • Regulatory and Policy Governance on high-risk AI systems
  • Future scenarios of AI-AI business platforms

    Notes for Prospective Authors:

    Submitted papers should not have been previously published nor be currently under consideration
    for publication elsewhere.

    Conference papers are only be submitted if the paper has been completely re-written and if
    appropriate written permissions have been obtained from any copyright holders of the original

    Manuscripts should be submitted through the publisher’s online system. Submissions will be
    reviewed according to the journal’s rigorous standards and procedures through double-blind peer
    review by at least two qualified reviewers.

Submission Process

Please prepare the manuscript according to IEEE-TEM’s guidelines ( and submit to the journal’s Manuscript Central site ( Please upload the paper on the IEEE TEM Editorial Manager clearly indicating it is submission for the IEEE TEM Special Issue on AI2AI Business Platforms.

Schedule for the Special Issue:

  • 31 December 2025 – Full paper submission deadline for the review process.
  • 30 April 2026– First round of reviews sent to authors
  • 30 September 2026– Second round of reviews sent to authors
  • 31 December 2026 – Expected publication, however, note that: each accepted paper’s online
    version will become available at the journal’s website as soon as accepted.

Selected References

  • Andreini, D., Bettinelli, C., Foss, N. J., & Mismetti, M. (2022). Business model innovation: a review of the
    process-based literature. Journal of Management and Governance, 26(4), 1089-1121.
  • Cao, L. (2022). Ai in finance: challenges, techniques, and opportunities. ACM Computing Surveys (CSUR),
    55(3), 1-38.
  • Atkins, S., Badrie, I., & van Otterloo, S. (2021). Applying Ethical AI Frameworks in practice: Evaluating
    conversational AI chatbot solutions. Computers and Society Research Journal.
  • Chesbrough, H. (2010). Business model innovation: opportunities and barriers. Long range planning, 43(2-
    3), 354-363.
  • Cui, R., Li, M., & Zhang, S. (2022). AI and Procurement. Manufacturing & Service Operations Management,
    24(2), 691-706.
  • Damij, N., Damij, T. (2014). Business Process Approaches. In: Process Management. Progress in IS.
    Springer, Berlin, Heidelberg.
  • Damij, N. and Bhattacharya, S. (2022). The Role of AI Chatbots in Mental Health Related Public Services
    in a (Post)Pandemic World: A Review and Future Research Agenda,” 2022 IEEE Technology and
    Engineering Management Conference (TEMSCON EUROPE), Izmir, Turkey, pp. 152-159, doi:
  • Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business
    value: A literature review. Information Systems Frontiers, 24(5), 1709-1734.
  • Favoretto, C., Mendes, G. H. D. S., Filho, M. G., Gouvea de Oliveira, M., & Ganga, G. M. D. (2022). Digital
    transformation of business model in manufacturing companies: challenges and research agenda. Journal of
    Business & Industrial Marketing, 37(4), 748-767.
  • Feuerriegel, S., Shrestha, Y. R., von Krogh, G., & Zhang, C. (2022). Bringing artificial intelligence to
    business management. Nature Machine Intelligence, 4(7), 611-613.
  • Hafner, A., Damij, N. and D. Modic (2022). Augmented intelligence for state-of-the-art patent search, 2022
    IEEE Technology and Engineering Management Conference (TEMSCON EUROPE), Izmir, Turkey,
    pp. 61-66, doi: 10.1109/TEMSCONEUROPE54743.2022.9801959.
  • Kelley, S. (2022). Employee perceptions of the effective adoption of AI principles. Journal of Business
    Ethics, 178(4), 871-893.
  • Kiseleva, A., Kotzinos, D., & De Hert, P. (2022). Transparency of AI in healthcare as a multilayered system
    of accountabilities: between legal requirements and technical limitations. Frontiers in Artificial Intelligence,
    5, 879603.
  • Kopalle, P. K., Gangwar, M., Kaplan, A., Ramachandran, D., Reinartz, W., & Rindfleisch, A. (2022).
    Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future
    research opportunities. International Journal of Research in Marketing, 39(2), 522-540.
  • Kraus, S., Kanbach, D. K., Krysta, P. M., Steinhoff, M. M., & Tomini, N. (2022). Facebook and the creation
    of the metaverse: radical business model innovation or incremental transformation? International Journal of
    Entrepreneurial Behavior & Research, 28(9), 52-77.
  • Ledro, C., Nosella, A., & Vinelli, A. (2022). Artificial intelligence in customer relationship management:
    literature review and future research directions. Journal of Business & Industrial Marketing, 37(13), 48-63.
  • Li, H., Hu, Q., Zhao, G., & Li, B. (2022). The co-evolution of knowledge management and business model
    transformation in the post-COVID-19 era: insights based on Chinese e-commerce companies. Journal of
    Knowledge Management, 26(5), 1113-1123.
  • Massa, L., & Tucci, C. L. (2013). Business model innovation. The Oxford handbook of innovation
    management, 20(18), 420-441.
  • Mostaghel, R., Oghazi, P., Parida, V., & Sohrabpour, V. (2022). Digitalization driven retail business model
    innovation: Evaluation of past and avenues for future research trends. Journal of Business Research, 146,
  • Olan, F., Arakpogun, E. O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial
    intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business
    Research, 145, 605-615.
  • Pieroni, M. P., McAloone, T. C., & Pigosso, D. C. (2019). Business model innovation for circular economy
    and sustainability: A review of approaches. Journal of cleaner production, 215, 198-216.
  • Salamzadeh, Y. (Ed.). (2022). Digital Transformation: A Human-Centric Approach. Efe Akademi Yayınları.
  • Soleimani, M., Intezari, A., & Pauleen, D. J. (2022). Mitigating cognitive biases in developing AI-assisted
    recruitment systems: A knowledge-sharing approach. International Journal of Knowledge Management
    (IJKM), 18(1), 1-18.
  • Truby, J., Brown, R. D., Ibrahim, I. A., & Parellada, O. C. (2022). A Sandbox Approach to Regulating High-
    Risk Artificial Intelligence Applications. European Journal of Risk Regulation, 13(2), 270-294.
  • Spieth, P., Schneckenberg, D., & Ricart, J. E. (2014). Business model innovation–state of the art and future
    challenges for the field. R&d Management, 44(3), 237-247.
  • Weber, M., Beutter, M., Weking, J., Böhm, M., & Krcmar, H. (2022). AI Startup Business Models: Key
    Characteristics and Directions for Entrepreneurship Research. Business & Information Systems Engineering,
    64(1), 91-109.
  • Yazdanpanah, V., Gerding, E. H., Stein, S., Dastani, M., Jonker, C. M., Norman, T. J., & Ramchurn, S. D.
    (2022). Reasoning about responsibility in autonomous systems: challenges and opportunities. AI &
    SOCIETY, 1-12.

Guest Editor Bios

Dr. Yashar Salamzadeh
Yashar is a senior lecturer in digital business at the University of Sunderland, UK. As an active
researcher, he has published over 150 papers in a wide range of academic journals and conferences
and received over 2400 citations on his academic works. He is serving more than 35 journals as a
reviewer, review board member and editorial board member. Having around 14 years of
experience in academia, in various parts of the world ranging from Middle east to Southeast Asia
and Europe, he has an active background in consultancy projects and helping businesses. He has
developed different MBA courses and modules on digitalization such as MBA in digital leadership
at Universiti Sains Malaysia and Digital Enterprise and innovation module at University of
Sunderland. His main research interests are digital business, digital leadership, digital
transformation, digital HRM, digital competencies and corporate digital responsibility. He can be
contacted at

Prof. Nadja Damij
Nadja is a Professor in Business and Management and a Director of Research Centre for Business
and Management as well as experienced academic manager (former Head of Subject, Chair of
Research Interest Group, Programme Director, and Dean) and researcher in digital business and
digital innovation with a PhD in Business Information Management. She has been engaged in high-level research as a principal investigator of national and international project consortiums
with a combined budget of £4.4m. She is a member of the Advisory Board of Digital Future
Challenge Based Learning in Higher Education International Project Consortium, as well as a
Guest Editor for (1) IEEE TEMs journal (AJG 3) on re-thinking information technologies and information systems: from informing pandemic preparedness to managing business disruptions and endemic responses and (2) International Journal of Entrepreneurial Behaviour and Research (AJG 3) on Emerging Issues in Digital Entrepreneurship: Challenges and Opportunities. Nadja
published the top 25% most downloaded eBook in the Process Management eBook collection in
2018 by Springer and has been awarded the Excellence in Leadership Award by International
Institute for Applied Knowledge Management, USA in 2017.

Dr. Pardis Moslemzadeh Tehrani
Pardis Moslemzadeh Tehrani serves as the Associate Head of the Law School at the University of
Sunderland. Prior to joining Sunderland University, she held the positions of Senior Lecturer and
Visiting Associate Professor at the Faculty of Law, University of Malaya. She has authored and
co-authored over 70 research outputs published by highly reputable publishers. Pardis has played
a significant role in numerous international research grants, serving as both a principal investigator
and co-researcher in collaborative projects supported by the Ministry of Higher Education,
spanning China, Malaysia, and the United Kingdom. She has collaborated with various
international bodies, including the ICRC, ASEAN University Network, the Institute of Human
Rights and Peace Studies (IHRP), the Norwegian Centre for Human Rights, and other human rights
organizations. Her editorial and reviewing roles are extensive, with involvement in multiple
Editorial Review Boards, such as the Journal of International Migration (Wiley), Journal of Jus
Cogens (Springer), International Journal of Digital Crime and Forensics, and as a book editor for
World Scientific Publishing. Pardis’s achievements have been celebrated with numerous honours,
including the University of Malaya Excellent Service Certificates Award, as well as scholarships
from the German-Southeast Asian Center of Excellence for Public Policy and Good Governance,
and ASEAN-European Academic University Network (ASEA-UNINET). In recognition of her
outstanding contributions, she was bestowed with the University of Malaya Excellence Award in
the category of Book Publication, specifically for her book titled “Cyber Terrorism: The Legal and
Enforcement Issues” in 2019. It is noteworthy that this book has been acknowledged as one of the
most downloaded eBooks from World Scientific Publishers in 2020.

Dr. Dolores Modic
Dolores Modic is an Associate Professor in Innovation and Management at Nord University
Business School, Steinkjer, Norway, in the Innovation and Entrepreneurship division. She is also
a Senior Research Fellow at Rudolfovo – scientific and technological centre Novo Mesto, where
she is the leader of the research group Center for technology transfer and intellectual property.
Previously, she has been a Fulbright Scholar in the US at UNC Chapel Hill (2015), and the JSPS
Research Fellow at Kyushu University in Japan (2016-2018). She has participated in more than 15
projects (sponsored by agencies in Europe, USA and Asia), with various roles (authoring, PI, WP leader, etc.), including on projects related to intellectual property, university technology transfer,
digital innovation, circular economy and patent informatics. Dolores has published in leading
scientific journals in innovation and management (including journals like Research Policy – AJG
4*). She is also an ad hoc reviewer for several top tier journals such as Journal of Technology
Transfer, and Journal of Business Research.

Dr. Thomas Rashford
Growing up in Western Canada, Thomas’s academic journey began at some of the region’s most
prestigious institutions. He not only attended but also later taught at esteemed universities and
colleges in Alberta, including the Southern Alberta Institute of Technology (SAIT), Mount Royal
University, Athabasca University, and the University of Lethbridge. His deep-rooted connection
to the local academic landscape has allowed him to forge invaluable relationships with scholars
and industry professionals in Western Canada over the past eight years. Thomas possesses an
inspiring academic background, holding a Bachelor of Arts in Applied Linguistics (BA), a
Bachelor of Business Management (B.Mgt), a Master of Arts in Education (MA), and a Master of
Business Administration (MBA). Additionally, he has earned a Postgraduate Certificate in
Advanced Research Methods (PGC), distinguishing himself as a relentless pursuer of knowledge
and expertise. His commitment to professional development is further underscored by his
certifications as a Project Management Professional, a Certified Canadian Instructor, and a
Certified Microsoft AI Professional. These certifications exemplify his dedication to staying at the
forefront of emerging trends and technologies in the business and AI domains. He has spent the
last five years collaborating with academics and industry professionals in Western Canada,
developing guidelines and frameworks that harness the power of AI and machine learning to
address complex real-world challenges for, Alberta’s premier artificial intelligence lab.
In this capacity, he works alongside government officials, post-secondary students, and graduates
to create intelligent solutions that drive innovation and solve pressing societal issues. Prior to
joining the University of Sunderland, Thomas played a pivotal role in shaping the academic
landscape at the University of Strathclyde Business School (SBS) in Glasgow, Scotland. He
designed and coordinated a series of modules that have left an indelible mark on business education
in the region.

Prof. Tsan-Ming (Jason) Choi
Professor Tsan-Ming CHOI (Jason) is a management scientist, operations researcher and systems
engineer. He is now Chair in Operations and Supply Chain Management, and Director of the
Centre for Supply Chain Research at University of Liverpool Management School (ULMS). He
has published extensively in leading journals in the fields of operations management, engineering
management, logistics, and supply chain management. His recent research has been funded by
many external funding bodies such as Research Grants Council (HK), University Grants Council (HK), M.O.E. (TW), and M.O.S.T. (TW). He is also serving the academic community as the Co-
Editor-in-Chief of Transportation Research Part E: Logistics and Transportation Review, a Senior Editor of Production and Operations Management, and Decision Support Systems, a Department Editor of IEEE Transactions on Engineering Management, and an Associate Editor of Decision
Sciences, and IEEE TSMC-Systems. He is currently an external member of the engineering panel,
Research Grants Council (HK) and he mainly handles projects in OR/OM/Engineering
Management. Over the past two decades, he served as an officer/exco member/secretary/treasurer
of professional societies such as Production and Operations Management Society (HK), IEEE
SMC Society (HK), and IEEE TEM Society (HK). He is listed as a Highly Cited Researcher by
Clarivate (Web of Science) and a Top 2% scientist by Stanford University. Before joining ULMS,
he taught at The Chinese University of Hong Kong (CUHK), The Hong Kong Polytechnic
University (PolyU) and National Taiwan University (NTU), altogether for over two decades. In
particular, he was honoured as a Yushan Fellow Professor at NTU, a President’s Award Winning
Professor at PolyU, and a distinguished alumnus of CUHK’s Faculty of Engineering.

ISSN: 0018-9391
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Publisher: IEEE

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