Prof. J. Alberto Aragon-Correa, University of Granada, Spain
J. Alberto
Aragon-Correa is
Professor of
Management and the
T-Systems –
University of
Granada Chair of
Innovation in
Digital
Sustainability at
the University of
Granada (Spain).
Furthermore, he is
also the current
Director of the
Talent Incubator.
Previously,
Aragon-Correa was an
Honorary Professor
of Management and
Professor of
International
Business at the
University of Surrey
(United Kingdom). He
was also a guest
visiting scholar at
University of
California, Los
Angeles (USA),
University of
California, Berkeley
(USA), and ETH
Zurich
(Switzerland).
Aragon-Correa's
research examines
firms’ business
strategies,
especially the
connections between
innovation,
governance, and
sustainability in
multinational firms.
Aragon-Correa's work
have been published
in many of the most
prestigious journal
in the field of
management, such as
Academy of
Management Review,
Academy of
Management Journal,
Journal of
Management, Academy
of Management
Annals, Journal of
International
Business Studies,
Academy of
Management
Perspectives,
California
Management Review,
among others.
Aragon-Correa has
been awarded with
the Academy of
Management «ONE
Distinguished
Scholar Award», a
distinction designed
to recognize
scholars who have
provided top
inspirational
academic leadership.
His research has
gained recognition,
featuring in the
“List of Top Two
Percent Scientists
in the World”
published by Prof.
Ioannidis (Stanford
University) and
colleagues. As of
May 2024, his works
have received more
than 14400 citations
(h-index=41)
according to Google
Scholar.
He is the incoming
Editor in Chief of
the Business
Research Quarterly
(BRQ), the journal
of the Spanish
Academy of
Management (ACEDE).
Furthermore, he
currently holds the
position of
Co-Editor for the
Cambridge University
Press book series
titled
″Organizations and
the Natural
Environment”.
Aragon-Correa also
serves as a
Consulting Editor
for Organization &
Environment, a
journal focusing on
sustainability and
management published
by SAGE Publishing.
Abstract:
Sustainability is
crucial for ensuring
the long-term health
of our planet, and
management research
on sustainability
has grown
exponentially in the
last decade. In the
dynamic landscape of
business
sustainability, the
methods used to
evaluate
environmental
strategies and
performance within
firms have
significantly
evolved. This
keynote presentation
will delve into the
historical
trajectory of these
measurement systems,
critically examining
the strengths and
limitations of both
traditional and
contemporary
approaches. We will
explore the
transition from
anecdotal
assessments to more
sophisticated,
quantitative methods
that leverage
advancements in big
data analytics.
Our discussion will
highlight the
pressing need for
emergent approaches
that harness big
data to provide more
accurate insights
into the actual
environmental impact
of firms.
Additionally, we
will describe an
initiative designed
by the speaker and
his academic team,
the TERAIN database.
This innovative
platform integrates
comprehensive
analytics from the
European Pollutant
Release and Transfer
Register (EPRTR) and
its counterpart in
the USA, offering a
robust tool for
scholars,
practitioners, and
investors.
Attendees will gain
a vivid
understanding of how
appropriate
methodological
approaches can
improve the
measurement of
environmental
performance in the
context of firms.
Prof. Lin Xiu, University of Minnesota – Duluth, USA
Dr. Lin Xiu received her PhD in Industrial Relations and Human Resources from the University of Toronto in 2010. Currently, she holds a professorship within the Department of Management Studies at the University of Minnesota – Duluth. Her research encompasses a range of subjects including labor market dynamics, HR analytics, compensation frameworks, as well as the nexus between leadership and employee well-being. Dr. Xiu has made significant scholarly contributions to her field, evidenced by the recognition of her work in prominent journals such as the British Journal of Industrial Relations, the Journal of Total Rewards, the International Journal of Manpower, the Leadership & Organization Development Journal, the Journal of Economic Psychology, and Personnel Review. Her academic impact extends to leading special issues, evaluating substantial research funding applications, and managing multiple research grants. Through her consultancy efforts, Dr. Xiu has exerted a notable influence on organizational practices (e.g., wellness programs) and labor market policy development (e.g. Paid Family and Medical Leave policies). She currently serves as an Associate Editor for the International Journal of Manpower (IJM).
Abstract: Artificial Intelligence (AI) introduces
a transformative shift in the nature of work.
This study explores this shift through a
holistic framework that moves beyond traditional
views of automation, revealing AI’s extensive
influence on the facets of work design, conduct,
and measurement. AI fundamentally
reconceptualizes the very essence of work,
necessitating a paradigmatic shift in work
design methodologies that underscore
flexibility, adaptability, and innovative
problem-solving. Through the development and
deployment of HR Analytics and Talent
Intelligence, organizations attain unprecedented
granularity in understanding workforce dynamics,
thereby revolutionizing recruitment processes
and talent management strategies. Concurrently,
labor platforms emerge as pivotal conduits for
the provisioning of work, reshaping the contours
of work execution. With AI’s ascendancy,
conventional performance metrics undergo a
metamorphic evolution, compelling a reassessment
of entrenched notions of productivity and
efficiency. Ethical considerations loom large in
this landscape, prompting a critical examination
of AI’s impacts on workforce dynamics, privacy,
and fairness. By understanding these issues,
organizations can make better decisions about
how to use AI to improve work processes, drive
innovation, and ensure fairness and inclusivity
for all.
Prof. Xu Chen, University of Electronic Science and Technology of China, China
Dr. Xu Chen is Professor of operations and supply chain management at School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, China. His current research interests include coopetition management, supply chain management, and operations management. His publications have appeared in Production and Operations Management, IISE Transactions, IIE Transactions, European Journal of Operational Research, OMEGA-International Journal of Management Science, Journal of Business Research, IEEE Transactions on Engineering Management, IEEE Transactions on Systems Man and Cybernetics: Systems, International Journal of Production Economics, International Journal of Production Research, Journal of the Operational Research Society, Annals of Operations Research, and other journals. His research has been supported by grants from the National Sciences Foundation of China (NSFC), Major Program of National Social Science Foundation of China (NSSFC), and National Key R&D Program of China.
Abstract: Applications of blockchain in supply chain management (SCM) have received extensive attention among academics and industrial practitioners. Most current blockchain-related review papers focus on the values, methodologies, barriers, trends, and challenges of blockchain applications in the supply chain (SC) context. Despite some papers discussing blockchain’s role in SCs from a specific perspective, the existing review papers mainly concentrate on blockchain’s influence on one of the three critical SC flows. Hence, this study comprehensively reviews 251 academic papers to capture the precise impacts of blockchain on the material, information, and money flows in SCM. Following the above analyses, a conceptual framework is put forward to accentuate blockchain’s influence on SCM. By unveiling a comprehensive research landscape, this study offers valuable viewpoints and vital information for scholars and practitioners to better identify research frontiers and themes of blockchain applications in SCM.