Using count data models to determine the factors affecting farmers' quantity decisions of precision farming technology adoption
Computers and Electronics in Agriculture, vol.62, no.2, pp.231-242, 2008 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 62 Issue: 2
- Publication Date: 2008
- Doi Number: 10.1016/j.compag.2008.01.004
- Journal Name: Computers and Electronics in Agriculture
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.231-242
- Keywords: Adoption intensity, Precision farming technologies, Zero-inflated Poisson and Negative Binomial models
- Bilecik Şeyh Edebali University Affiliated: No
Abstract
The following study investigates the adoption of various precision farming technologies in terms of both the probability and the use intensity of technology components implemented. Zero-inflated Poisson and Negative Binomial count data model regressions were used to determine factors influencing farmers' decision to adopt greater number of precision technologies. Results from the count data analysis of a random sample of Ohio farm operators demonstrate that several factors were significantly associated with the adoption intensity and probability of precision farming technologies, including farm size, farmer demographics, soil quality, urban influences, farmer status of indebtedness, and location of the farm within the state. © 2008 Elsevier B.V. All rights reserved.