Wael Jabr
Associate Professor of Information Systems
Department Supply Chain & Information Systems
Office Address 447 Business Building
Phone Number
814-865-0379
Email Address
wjabr@psu.edu
Wael Jabr
Associate Professor of Information Systems
Department Supply Chain & Information Systems
Office Address 447 Business Building
Phone Number
814-865-0379
Email Address
wjabr@psu.edu
I am an Associate Professor of Supply Chain and Information Systems at the Smeal College of Business, Pennsylvania State University. I earned my PhD in Management Science from the Information Systems and Operation Management department at the University of Texas at Dallas’ Jindal School of Management.
Expertise
Every time a judge weighs an algorithm's recommendation before sentencing, or a shopper reads reviews before buying, a decision that used to belong to a person alone is now being shaped by a system someone else designed. That interaction — between people and the digital systems now embedded in how firms operate — is what my research is about. As platforms and, increasingly, AI take on a growing role in how decisions get made, they're not just changing what businesses do; they're changing how individuals decide, what they pay attention to, and how they treat each other. My research examines this evolving relationship through two themes: A) human–algorithm interactions, and B) information-rich platforms.
A) Human–Algorithm Interactions: As algorithms take on a larger role in firms' decisions, how people actually respond to them — behaviorally and perceptually — has become critical, especially where algorithmic input complements, and sometimes overrides, human judgment. My work pays particular attention to how these effects vary across demographic lines. In the judicial system, I find that algorithmic sentencing recommendations produce uneven impacts by race and gender, with real consequences for public safety. In peer-production systems, I find that algorithmic agents can disrupt workflows and reduce efficiency when they override experienced human contributors. My ongoing work extends this theme to how firms integrate AI into operational decision-making more broadly.
B) Information-Rich Platforms: Digital transformations have also made platforms central to everyday decision-making. An app store, for example, doesn't just connect developers with users — it surfaces the reviews that guide what people buy, turning the platform into an infomediary. My research examines this role: how much information platforms should surface before it degrades decision quality, how reputation-system design shapes user contributions, and how the interplay between recommendations and reviews influences consumer choice. I've extended this work to online trading platforms, studying how visible social signals shape behavioral biases in financial decisions. On the social side, I study how platforms' information flows push users toward more polarized messaging, and how greater transparency in public data can drive real behavioral change in firms.
Education
Ph.D., Information Systems, The University of Texas at Dallas, 2011
Master of Business Administration, The University of Texas at Dallas, 2010
Courses Taught
BA 840 – BUS DATA MGMT (3)
Business Data Management will enable students to use various database designs to acquire the information needed to make effective business decisions. Successful students will be able to design, create, and implement a relational database and be able to write SQL statements to obtain information from a database. In addition, students will investigate the next generation approaches for storing, manipulating, and managing web data in unstructured formats. Students will gain an understanding of the advantages and disadvantages among XML, NoSQL, NewSQL, and Relational databases. After successfully completing this course, students will have the knowledge, skills, and abilities to:- structure a database, configure it, perform analysis within it, and report from it- have adequate understanding of SQL to retrieve data from a database using SQL query language- design a database system including an ER Model and a UML class diagram, and implement the design in an enterprise databaseapplication- understand NoSQL databases, XML native databases, NewSQL databases, and the advantages and disadvantages of thesedatabases.