Impact of Technological Innovation on Performance in Dairy Sheep Farms in Spain

Document Type : Original Research

Authors
C. de-Pablos-Heredero 1
J. L. Montes-Botella 2
A. Garcia 3
1 ESIC Business and Marketing School and Department of Business Administration and Applied Economics II, Rey Juan Carlos University, 28072 Madrid, Spain.
2 Department of Applied Economics I, Rey Juan Carlos University, 28072 Madrid, Spain.
3 Department of Animal Science, University of Córdoba, Campus de Rabanales, 14071 Córdoba, Spain.
Abstract
The objective of this study was to evaluate the causal relationship between technological innovation and sheep farm’s results, based on a Structural Equation Modeling Approach (SEM) in dairy sheep systems in the center of Spain. Different from traditional multiple-trait models, SEM analysis allows assessment of potential causal interrelationships among outcomes and can effectively discriminate effects. Information from 157 dairy sheep farms in Castilla La Mancha was used. The questionnaires included 38 technological innovations and 188 questions on productive, economic and social data. Four hypotheses were formulated oriented to understand how the farm's technological innovation will affect the productive structure and farm's performance. The results derived from the SEM analysis showed a positive relationship between the technological indicator and the farm’s structure, productivity, and economic results. The variable technological adoption could be regarded as a predictable measure of structure, productivity, and economic performance. Technology is associated with the productive structure. Independent of sheep farms’ size, dairy sheep farms can be positioned in the growing returns area as a consequence of a proper use of it. SEM approach to observational data in the context of dairy sheep system suggests that there is not a single optimal structure. The model built constitutes a tool of great utility to make decisions, as it allows predicting the impact of technologies on final results ex-ante.

Keywords

Subjects

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Journal of Agricultural Science and Technology
Volume 22, Issue 3
March and April 2020
Pages 597-610