Teaching and Educational Methods

Using Data Analytics and Decision-Making Tools for Agribusiness Education

Matthew S. Elliott(a) and Lisa M. Elliott(a)
(a)South Dakota State University

JEL Codes: A22, A29, Q13
Keywords: Agribusiness, data analytics

Publish Date: March 26, 2020
Volume 2, Issue 2

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Abstract

The agriculture sector has entered a new era wherein every stage of the supply chain involves gathering an increasing amount of data. Most of these data are generated in real-time and require rapid analysis that can support optimal decision making for agribusinesses to remain competitive. Consequently, employers desire that students gain data analysis skills in agribusiness classes to best inform optimal decision making. This paper discusses how data analytics have been incorporated into an agribusiness management course.

About the Author: Matthew S. Elliott is an Assistant Professor in the Ness School of Management and Economics at South Dakota State University (corresponding author email: matthew.eliott@sdstate.edu). Lisa M. Elliott is an Assistant Professor in the Ness School of Management and Economics at South Dakota State University. Acknowledgement: This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch project under 1017800 and No. 1006890.

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