Theses and Dissertations

ORCID

0009-0008-0651-5925

Advisor

Li, Xiaofei

Committee Member

Canales, Elizabeth

Committee Member

Thompson, Diego

Date of Degree

8-12-2026

Original embargo terms

Visible MSU Only 1 year

Document Type

Graduate Thesis - Campus Access Only

Major

Agriculture (Agricultual Economics)

Degree Name

Master of Science (M.S.)

College

College of Agriculture and Life Sciences

Department

Department of Agricultural Economics

Abstract

Despite the rapid advancement of agricultural autonomy in recent decades, most autonomous technologies are designed for large-scale farms, leaving smaller farms relatively overlooked. While farm size is frequently cited as a substantial factor in agricultural autonomy adoption, little empirical work has examined this relationship for fully autonomous tractors. This study applied a logistic regression model, supplemented by random forests for cross-method validation, to identify whether farm size shapes farmers' adoption intention toward fully autonomous tractors. Findings show that farm size affects adoption intention through a threshold mechanism. In addition, prior experience with semi-autonomous or precision agriculture technologies emerges as the strongest predictor of adoption intention of fully autonomous tractor across all analytical methods. These results indicate that current fully autonomous tractors are indeed disproportionately oriented toward large-scale operations, suggesting a structural technology gap for small-scale and medium-scale farms.

Sponsorship (Optional)

USDA National Institute of Food and Agriculture (Award Number: 2023-67023-40458).

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