Kala Seal, Ph.D.
Professor of Information Systems and Business Analytics, College of Business Administration | Loyola Marymount University
Los Angeles, CA, UNITED STATES
Chair, Department of Information Systems and Business Analytics and Director, Comparative Management Systems (CMS) Program
Biography
You can contact Kala Seal at Kala.Seal@lmu.edu.
Kala Seal is chair of the Department of Information Systems and Business Analytics and director of the Comparative Management Systems (CMS) program at Loyola Marymount University. Professor Seal has been a member of the College of Business Administration faculty since 1990.
Prior to joining LMU, he worked as an assistant executive engineer for the largest oil and natural gas corporation in India. Along with his teaching and research at LMU, Professor Seal also has worked as faculty consultant for Jet Propulsion Laboratory and Mattel Inc. Professor Seal is an active researcher with publications in many of the leading journals in his area (e.g. Interfaces, International Journal of Mobile Marketing, INFORMS Transactions on Education, and many others). He regularly serves as a reviewer for many journals in his area. As a faculty and the director of the Comparative Management Systems program, Professor Seal has traveled to 40+ countries to conduct and guide research of multiple groups of MBA students on e-commerce and business use of mobile phones. He has been honored with the Faculty of the Year - MBA Program at LMU. He is also recipient of an NSF grant and was awarded a Fulbright Research Scholar award in 2010 for conducting research on business use of mobile phones by small and micro entrepreneurs in India. Professor Seal is a member of the INFORMS and Association of Indian Management Scholars.
Education (3)
University of Texas at Dallas: Ph.D., Information Systems and Management Science 1990
University of Texas at Dallas: M.S., Computer Science 1989
Indian Institute of Technology, India : B.Tech, Mechanical Engineering 1985
Areas of Expertise (4)
Mobile Commerce
Mobile Payments
Decision Modeling in Excel
Information System Strategies
Industry Expertise (3)
Research
Training and Development
Education/Learning
Accomplishments (1)
AIMS-NMIMS Outstanding Paper Award (professional)
2015-12-22
Dr. Kala Seal and MBA students Kiera Carvalho, Jennifer Evans, Heather Toll, Taylor Walker, Paul Prisco, Mailan Bui and James Frakes received the AIMS-NMIMS Outstanding Paper Award awarded by The Association of Indian Management Scholars at the AIMS International Conference on Management in Bangalore, India. The paper was titled “A Value Framework for Mobile Payment with Examples from Selected Asian Countries.”
Articles (4)
How Levels of Interactivity in Tutorials Affect Students’ Learning of Modeling Transportation Problems in a Spreadsheet
Decision Sciences Journal of Innovative Education2014-07-29
Do students learn to model OR/MS problems better by using computer-based interactive tutorials and, if so, does increased interactivity in the tutorials lead to better learning?
Mobile Brand Interaction in Southeast Asia: A Comparative Study
International Journal of Mobile Marketing2013-12-03
The rapid adoption of mobile technology in Southeast Asia has provided local and international brands with new opportunities to interact with consumers. Embracing the unique aspects of mobile has enabled a region that was once lacking in consumer understanding of technology to rapidly approach parity with consumers in more developed countries.
How CEOs of Real Estate Companies Like to Learn
Journal of Real Estate Practice and Education2007-01-06
In the past ten years, many executive education programs have been developed at universities to assist leaders in learning new skills and proficiencies. However, there is little published literature that examines specifically how CEOs have learned needed new skills in the past or on the learning preferences of CEOs.
"Understanding Cardiovascular Disease Progression Behavior from Patient Cohort Data using Markov Chain Model
ICIS2020Arin Brahma, Samir Chatterjee, Kala Chand Seal
2020-11-09
Cardiovascular Diseases (CVDs) are the number one cause of deaths worldwide and management of these highly chronic diseases is a major concern to healthcare providers. Progression of CVDs often involves several comorbidities, multi-morbidities, and multiple episodic occurrences, involving recur-ring hospitalization over a period of time. Using longitudinal data of 4839 CVD episodes of 1274 real patients and continuous-time Markov model as the kernel theory, this research finds the CVD progression paths and transition probabilities. The resultant probability data and the transition paths open the door for building simulation models and tools which can help the hospital administrators to improve resource and capacity planning. Practitioners can compare a patient’s disease progression trend against the pattern revealed by the model. Results are actionable and can influence treatment and intervention strategies in overall CVD progression management by clinicians and providers. The framework developed is repeatable, reusable, and extensible to other diseases and populations.
