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Analyzing destination country risk profiles in business study abroad programs: a neural network approach

Rick L. Brattin (Department of Information Technology and Cybersecurity, College of Business, Missouri State University, Springfield, Missouri, USA)
Randall S. Sexton (Department of Information Technology and Cybersecurity, College of Business, Missouri State University, Springfield, Missouri, USA)
Rebekah E. Austin (Department of Information Technology and Cybersecurity, College of Business, Missouri State University, Springfield, Missouri, USA)
Xiang Guo (Department of Information Technology and Cybersecurity, College of Business, Missouri State University, Springfield, Missouri, USA)
Erica M. Scarmeas (Department of Information Technology and Cybersecurity, College of Business, Missouri State University, Springfield, Missouri, USA)
Michelle J. Hulett (International Business Programs, College of Business, Missouri State University, Springfield, Missouri, USA)

Journal of International Education in Business

ISSN: 2046-469X

Article publication date: 28 November 2023

Issue publication date: 15 January 2024

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Abstract

Purpose

This study aims to identify how objective indicators of destination country risk differentiate business study abroad programs from those in other academic disciplines.

Design/methodology/approach

The authors trained a neural network model on six years of student-initiated inquiries about study abroad programs at a large US university. The model classified business versus nonbusiness study abroad programs using objective measures of destination country risk as the primary inputs.

Findings

The model correctly classifies business and nonbusiness study abroad programs with over 70% accuracy. Business programs were found to be 20% less likely to include destinations where the Centers for Disease Control and Prevention recommend nonroutine vaccinations and favor countries with higher Global Peace Index scores.

Practical implications

These results underscore the need to consider destination country risk in the design and administration of study abroad programs. An understanding of student preferences for lower risk destinations can contribute to improved planning, execution and student experiences in these programs.

Social implications

Better planning and management of study abroad programs based on understanding of destination country risk can lead to enhanced student safety and experiences.

Originality/value

This study offers a unique perspective on understanding study abroad programs by focusing on objective measures of destination country risk rather than risk perceptions. It also is, to the best of the authors’ knowledge, the first to use a neural network to classify study abroad programs as business versus nonbusiness using objective measures of country-specify risk indicators.

Keywords

Citation

Brattin, R.L., Sexton, R.S., Austin, R.E., Guo, X., Scarmeas, E.M. and Hulett, M.J. (2024), "Analyzing destination country risk profiles in business study abroad programs: a neural network approach", Journal of International Education in Business, Vol. 17 No. 1, pp. 133-147. https://doi.org/10.1108/JIEB-05-2023-0029

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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