The 7th International Conference on Modern Management based on Big Data (MMBD 2026)

Special session proposals should include the title, aim and scope (including a list of main topics), and the names of the organizers of the special session, together with a short biography of all organizers. A list of potential contributors will be helpful.

Special session proposals will be evaluated based on the timeliness, uniqueness of the topic and qualifications of the proposers. The proposers are expected to have a PhD degree and have a good publication track record in the proposed area. After review, a decision on whether the proposal will be accepted will be sent to the proposers within two weeks after receipt of the proposals. Accepted special sessions will be listed on the website. However, it is likely that an accepted proposal will be combined with another one to avoid multiple special sessions covering a similar topic.

Please send us the proposal via email: mmbd@academicconf.com

1. Aims of the Session

This special session aims to address the multifaceted impacts of big data, digitalization, and AI on socio-economic systems and the natural environment amid global efforts toward sustainability. It seeks to bring together diverse academic perspectives to clarify how these technologies shape critical areas such as employment, energy transition, environmental conservation, and social equity. By facilitating the exchange of cutting-edge research and insights, the session intends to resolve emerging conflicts—such as the trade-off between AI-driven development and environmental protection, or between environmental regulations and economic equality—and explore actionable pathways to steer society toward inclusive, sustainable growth aligned with the Sustainable Development Goals (SDGs). Ultimately, it aims to build a shared understanding of how to leverage big data, digitalization, and AI to advance a balanced, resilient sustainable economy.

2. Targets and Contributors

The session targets scholars, researchers, and practitioners across multiple disciplines who focus on the intersection of technology, economy, society, and sustainability. Key contributors include academics specializing in macroeconomics, management, environmental economics, energy studies, and digital governance; industry experts from technology firms, financial institutions, and sustainability-focused enterprises; and policymakers involved in shaping digital transformation, environmental regulation, and SDG implementation. It also welcomes researchers from emerging and developing economies, whose insights on issues like gender equality, energy access, and socio-economic inequality are vital to addressing global sustainability challenges.

3. Main Topics

Tentative topics related to Big Data and AI

• New management systems enabled by big data and AI
• Employment dynamics: Job creation and unemployment risks driven by big data and AI
• Environmental impacts and sustainability of big data and AI applications
• Big data, AI, and their implications for gender equality and public health
• Next-generation energy systems powered by AI and big data (e.g., smart grids)
• Disciplinary approaches: Economic and management perspectives on big data and AI
• Sustainable development through big data and AI
• Applications of big data and AI in ESG finance
• Big data, AI, and the future of globalization

Tentative topics related to Digitalization

• International-level digitalization: Impacts on global trade, economic partnerships, and SDGs
• Country-level digitalization: Opportunities, challenges, and macroeconomic performance; digitalization’s role in mitigating internal and external shocks; and its influence on inter-country relationships
• Sectoral and industry-level digitalization: Transformations in finance, manufacturing, agriculture, higher education, banking, tourism, and healthcare
• Firm-level digitalization: Effects on business performance, management activities, strategic decision-making, customer experience, marketing processes, and competitive advantage

Submission Deadlines for this Special Session:

First Round Submission Deadline for Full Papers: March 20, 2026
Final Submission Deadline for Full Papers: May 20, 2026
Submission Deadline for Abstracts (without full paper publication in conference proceeding or related journals): June 10, 2026

This special session is now open for submission and registration. Please submit your abstract/full paper via the Submission System and choose the option of "Special Session on The Potential of Big Data, Digitalization and AI in a Sustainable Economy". After that, you can make the conference registration directly via the Registration Page or the conference secretary will contact you for further information.

Session Chair and Committee Profiles

Session Chair:

Prof. Yoshihiro Hamaguchi
Professor of Macroeconomics at Hannan University, Osaka, Japan

Organizing Committee

Dr. Xuan-Hoa Nghiem
Head of the Economics Department, Faculty of Economics and Management, International School, Vietnam National University, Hanoi, Vietnam.

If you would like to join the Organizing Committee of this special session, please contact the conference secretary Ms. Cindy Shen via email: mmbd@academicconf.com and upload a copy of your latest short bio and recent photo as email attachments for further evaluation.

Description:

This is an applied-education and applied-research track. This track focuses on using AI, Data Science, and Web 6.0 technologies to create novel learning content and environment to learners, and novel business applications in business, finance, healthcare, entrepreneurship, etc. Technical papers, business applications and case studies are welcome. Some papers will be nominated to submit to a journal after revision. All posters, student papers, academic papers and industrial papers are welcome.

Notes: The Track will set four best papers that will be selected by the track chair and the chair will deliver the certificates to the winners at the end of the track.

(1) Best applied research paper award
- research originality (literature review) and link the theory and concepts to the market or industry
- scientific research method, with critical thinking and logical thinking to support its argumentation (literature review and discussion)
- well document the experimental results, well paper organisation, layout and presentation
- with innovation and impact

(2) Most impact paper award
- solved existing industrial problems
- the invention with long run impact to the companies, industry, society, or community (number of company and/or people)
- with company case currently used its invention of the paper

(3) Most innovative paper award
- point out the research gaps of two fields in market and/or research
- novel method or approach to solve it that no one does before
- experimental proof the innovation when comparing existing methods in different fields

(4) Most industrial practical paper award
- Address the need of the company or society, - Not a conceptual idea but is an application or tool or a well-document format
- In live application already or a company case used it

Topics include, but not limited to:

Submission Deadline for Full Papers: May 8, 2026
Submission Deadline for Abstracts (without full paper publication in conference proceeding or related journals): June 6, 2026

This track is now open for submission and registration. Please submit your abstract/full paper via the Submission System and choose the option of Track on "Applied-education and applied-research in AI, Data Science, and Web6.0". After that, you can make the conference registration directly via the Registration Page or the conference secretary will contact you for further information.

Dr. Adela Lau is the Deputy Director of HKU SAAS Data Science Lab, Division of Statistics and Actuarial Science, School of Computing and Data Science of the University of Hong Kong. Dr. Lau published over 60 journal and conference papers and funded over 50 research and industrial collaboration and consultancy projects in the area of machine learning, business intelligence, text analysis, network analysis, social media and big data analytics, AI and Mixed Reality in metaverse, intelligence applications, risk management, information system adoption, ontology/taxonomy building, business process re-engineering, portal design, knowledge management, e-learning, public/community health studies, healthcare systems and nursing clinical quality control & assessment. She gained several awards including NANDA Foundation Research Grant Award (USA), Faculty Merit Award in Services (HK), and Inaugural Teaching and Learning Showcase Award (HK). She was the former director of Center for Business Development at Madonna University in USA, and the co-director of the Center for Integrative Digital Health at Hong Kong Polytechnic University (PolyU) and leaded the IT team for healthcare product innovation. Dr. Lau was an active committee member of Knowledge Management Research Center at PolyU and Data Science Center at Hong Kong University of Science and Technology (HKUST), in which she initiated and developed industrial applied-research consultancy projects. She was also the UG coordinator of the Risk Management and Business Intelligence Program at HKUST, and was responsible to lead, execute, and coordinate the program works including curriculum design, enrichment programs, and administration across three schools of business, science, and engineering.