Big data technology adoption in beef production

Abstract

The United States plays a fundamental role in meeting the global demand for beef. Environmental concerns and volatile weather conditions have increasingly impacted beef production in recent years. To mitigate these issues, the cattle industry has begun to integrate sophisticated technological solutions into production processes. Utilization of these technologies, known as precision livestock farming (PLF) include the use of sensors, robotics, and big data analytics. PLF can enhance production and reduce illness-related losses by providing real-time insights for whole farm operations through the integration and analysis of generated data. PLF technology is still in the early stages of development and implementation, thus little is known about the factors impacting producer adoption in beef production. The objective of this study is to examine factors affecting adoption of PFL, particularly big data technology, in beef cattle production. Results of a binary probit analysis indicate that herd size and prior adoption of sensor-based technology positively affected the adoption of big data technology by U.S. beef producers. It was also found that producer age negatively impacted big data technology adoption. Results of this study were consistent with similar adoption assessments conducted on beef producers, in which farm size and farmer age were found to be common factors affecting technology adoption.

Keywords

• Precision livestock farming
• big data technology
• sensors
• beef production
• technology adoption