Bibliometric literature review in the era of Big Data: Challenges and opportunities
Date: TBD
Time: TBD
Bibliometric literature review stands as a fundamental aspect of research methodologies, providing a comprehensive overview of scholarly works and guiding future inquiry across various academic fields. Its importance transcends disciplinary boundaries, fuelling innovation and discovery. However, the rise of Big Data and artificial intelligence (AI) introduces both opportunities and complexities to literature review practices.
In the modern research landscape, scholars encounter a convergence of traditional methods and cutting-edge technology. Big Data and AI reshape how researchers approach literature reviews, offering new insights but also posing challenges in navigating vast amounts of information. Despite this, scholars can leverage advanced analytics and machine learning to uncover hidden trends and connections within the scholarly landscape.
AI-driven tools enable researchers to automate tasks like data extraction and citation analysis, streamlining the review process for more efficient knowledge discovery. Yet, ethical considerations must accompany these advancements to maintain academic integrity.
The fusion of bibliometric literature review with Big Data and AI represents a dynamic frontier where tradition meets innovation. Scholars are prompted to adapt their methodologies and embrace technological advancements while upholding scholarly principles. This transformative landscape holds the promise of unlocking new knowledge and fostering interdisciplinary collaboration to propel human understanding forward.
The workshop of two hour in total aims to explore the evolving impact of Big Data and AI on literature review, focusing specifically on bibliometric approaches. It will address the issues closely related to research design and advancing theory and practice.
Outline
This workshop will consist of two main agendas:
Addressing Research Design Considerations: The first agenda delves into how Big Data, AI, and related advancements influence research design. Topics include considerations for topic choice, keyword selection, data sources, criteria for selection, analysis tools, and techniques for result presentation and insights generation. This session, spanning an hour, will equip participants with practical strategies for leveraging these technologies in their literature review processes.
Exploring Implications for Theory and Practice: The second agenda examines the broader implications of incorporating Big Data and AI in literature review on theory and practice. Participants will explore how these factors drive and shape theory building, development, testing, and application. This session, also an hour in length, encourages participants to critically analyse the impact of technological advancements on advancing theoretical frameworks and practical applications in their respective fields.
Through interactive discussions and case studies, the workshop seeks to empower researchers to navigate the challenges and harness the opportunities presented by the integration of Big Data and AI in bibliometric literature review, ultimately enhancing the rigor and relevance of their research endeavours.
Target Audience
Researchers who are interested in bibliometric literature review and/or using Big Data and AI as approaches to empirical studies.
Presenters
Dr Lihong Zhang (University of Manchester) teaches core modules on Innovation Management, Applied Project Management and Planning & Control to the campus-based MSc/UG programmes, and Planning and Resource Management to Distance Learning Professional Development programmes. He served the Director of MSc Engineering Programmes for Project Management and Associate Editor to International Journal of Productivity and Performance Management.
Lihong has contributed to two UK national granted programs (i.e. CoPS and GRIPS) with a number of publications to top journals. His research broadly focuses on Complex Product-Service Systems, Green Supply Chain, Digital Transformation, and Project & Innovation Management (PIM). He as PI and his team has been awarded a KTP project (Knowledge Transfer Partnership) of £400k from UKRI, IAA (£9k, EPSRC), Industry co-funded projects (£30k) among other external incomes.
Dr Lihong Zhang has been Shortlisted “Project Professional of The Year” (2020), awarded Academic Advisor (Brilink, 2023), Senior Fellowship of HEA (2021) and Supervisor of the Year (FSE, 2022) for his outstanding achievement in EDIA (equality, diversity, inclusion and accessibility) initiatives, excellent contribution to PhD education and innovative approach to teaching and learning.
Dr Saeed Banihashemi (University of Canberra) is the Associate Professor of Construction Project Management, Founding Director of Digital Building & Built Environment Hub (BIM Hub) and Postgraduate Program Director of Building & Construction Information Management in the School of Design and Built Environment, Faculty of Arts and Design; University of Canberra (UC), Australia. Saeed’s research has embarked on an academic journey that intertwines the intricate complexities of project engineering and management practices with the transformative power of digital transformation and AI where his research has been globally recognized for its quality and promise.
Saeed has amassed over 80 publications, including 3 significant Routledge books and more than 60 Q1 journal articles, garnered over 2600 citations, H-index at 27, and more than $1.2 million in grant income. The recognition of his standing as an international researcher in the field is seen with my election as the Associate Editor of the Journal of Frontiers in Built Environment (Q2), Editorial Board Member of the journals of Smart & Sustainable Built Environment (Q1), Buildings (Q1) and PLOS One (Q1), and the guest editor for the Journal of Sustainability (Q1).