Analytics, Information and Operations Management research

The Analytics, Information and Operations Management (AIO) academic area includes faculty who are experts in topics such as business analytics, information systems and supply chain management, as well as former industry professionals whose experience supplements our curriculum.

AIO faculty regularly publish in leading academic journals and lend their expertise to regional and national media. Their intellectual contributions generate new knowledge and understanding, particularly as industries continue to rely more heavily on data-driven decision making.

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Area directors

Degree programs

Research topics

Data mining
Machine learning
Information security
Supply chain management
Healthcare information systems

In the Media

Disruptor Daily
What is the future of supply chain management? 16 experts share insights
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Inbound Logistics
What's the difference between supply chain visibility and transparency?
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Academic Minute
Mazhar Arikan, University of Kansas, talks baggage fees
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Recent research & news

Professor named co-editor-in-chief of journal

KU professor Andrew Chen has been appointed co-editor-in-chief of Decision Support Systems, an academic journal covering theoretical and technical issues in the support of enhanced decision making.

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Artificial intelligence expert originates new theory for decision-making

How should people make decisions when the outcomes of their choices are uncertain, and the uncertainty is described by probability theory? That’s the question faced by Prakash Shenoy, the Ronald G. Harper Distinguished Professor of Artificial Intelligence at the University of Kansas School of Business.

New study advocates updating approach to teaching supply chain curriculum

“Nobody worries about the supply chain until something goes wrong,” said Joe Walden, the assistant area director in analytics, information and operations management at the University of Kansas.

Time holds the key in best approach to multistage-bidding process, study finds

A team's new research led by a University of Kansas School of Business professor will help companies determine the best way to solicit bids from suppliers in a multistage reverse auction.