Print

Print


*2021 INFORMS/Data Mining Cluster*

*Big Data Applications in Global Operations and Management Session (VMC03)*



*Invitation to Attend*



*Date: Oct 25, 2021 11:00am-12:30pm (PDT, Pacific Time Zone) - Virtual, via
Zoom*



We invite you to attend the 2021 INFORMS session on “Big Data Applications
in Global Operations and Management,” organized by Industry Engineering,
Operations Management, and Strategic Management scholars.



Big data and machine learning applications, such as AI, bots,
Internet-of-Things, 5G, and blockchain, are revolutionizing how we live.
This INFORMS session is a cross-disciplinary enterprise devoted to
unpacking how big data and machine learning influence businesses and
society. Broadly speaking, we will attempt to understand the effect of big
data and machine learning on how businesses organize work, handle
digitization and large online communities, and formulate strategies.
Additionally, how big data helps us to develop new theories becomes a
pertinent question. We have a great panel of experts from Marketing,
Operations, Information and Decision Sciences, and Strategic Management,
who will share their valuable research insights on these critical
questions, providing much-needed directions to aspiring scholars who are
intending to incorporate big data and machine learning in their future work.



The session will feature exciting presentations from the following eminent
scholars:


[image: Xueming Luo.jpg]


*Professor Xueming Luo*
<https://www.fox.temple.edu/about-fox/directory/xueming-luo/> is Charles
Gilliland Chair Professor of Marketing, Professor of Strategic Management,
Professor of Management Information Systems.  He is the Founder/Director of
the Global Center for big data in mobile analytics in the Fox School of
Business at Temple University.
[image: Ravi Bapna.png]


*Professor Ravi Bapna* <https://carlsonschool.umn.edu/faculty/ravi-bapna>
is the Curtis L. Carlson Chair in Business Analytics and Information
Systems, Associate Dean for Executive Education and the Academic Director
of the Carlson Analytics Lab and the Analytics for Good Institute at the
University of Minnesota’s Carlson School of Management.
[image: Prithwiraj Choudhury.jpg]


*Professor Prithwiraj Choudhury*
<https://www.hbs.edu/faculty/Pages/profile.aspx?facId=327154> is the Lumry
Family Associate Professor at the Harvard Business School.




[image: Russell Funk.png]


*Professor Russell Funk*
<https://carlsonschool.umn.edu/faculty/russell-funk> is an assistant
professor in the Strategic Management and Entrepreneurship group at the
University of Minnesota’s Carlson School of Management.


Here is the link to the conference session: VMC03
<https://www.abstractsonline.com/pp8/?utm_campaign=2021%20Annual&utm_medium=email&_hsenc=p2ANqtz-8yOrpJrOUqqPqMJha3oCVeHwekVTtFCqXQx9cRN71uGmPFObViEcDmsLkwqoo0cp7AxMllOKf_tf-AOWX9kojrYdbQDg&_hsmi=155583759&utm_content=155583759&utm_source=hs_email&hsCtaTracking=76a3f7ff-51d5-4ec3-9afc-6681cc8dc243%7C1799fe6c-2007-47fc-9053-bd9abe03f130#!/10390/session/577>
.



We look forward to your attending this event.


Best Regards,



Xiaojin Liu <https://directory.business.vcu.edu/profile.php?urn=xliu22>,
Assistant Professor, Virginia Commonwealth University

Pankaj Kumar
<https://management.pamplin.vt.edu/faculty/directory/kumar-pankaj.html>,
Assistant Professor, Virginia Tech

Session Co-Chairs



Shouyi Wang <https://mentis.uta.edu/explore/profile/shouyi-wang>

Cluster-Chair INFORMS Data Mining Section

Associate Professor, Department of Industrial, Manufacturing & Systems
Engineering

The University of Texas at Arlington

-- 
Pankaj Kumar
Assistant Professor
Department of Management (mail code 0233), 2007 Pamplin Hall
Pamplin College of Business, Virginia Tech
880 West Campus Drive, Blacksburg, VA 24061

Phone: 540-231-6105
Email: [log in to unmask]
Office # 2-2104

____
AIB-L is brought to you by the Academy of International Business.
For information: http://aib.msu.edu/community/aib-l.asp
To post message: [log in to unmask]
For assistance:  [log in to unmask]
AIB-L is a moderated list.