This study links the dynamic capabilities (DCs) theory with performance in dairy sheep farms in Castilla La Mancha (central Spain). The approach is novel as it seeks to understand how best results can be achieved by deploying DCs in farms. The proposal is that dynamic capabilities are interrelated to each other and present a positive impact on the farm’s economic sustainability. A mixed methods approach (a combination of qualitative and quantitative methods of research) was utilized. First, 30 indicators of dynamic capabilities (8 of absorption, 11 of integration, 9 of innovation, and 2 of profits) were selected by applying Delphi’s methodology. Second, a structural equation model (SEM) was applied over a random sample of 157 dairy sheep farms to measure the relationship between DCs and the impact of each capability on farms’ final performance. The existence of positive relationships amongst absorption, integration, and innovation capabilities was evidenced. Absorption and integration capabilities exhibited positive influences on a farm’s final performance. The knowledge of the relationships amongst dynamic capabilities is a new orientation to increase farms’ viability. These findings reveal that the application of the dynamic capabilities theory can explain best farms’ economic sustainability.

La producción de leche de oveja en Castilla-La Mancha tiene una gran importancia, tanto a nivel económico como social. La oveja manchega juega un papel relevante en la conservación del medioambiente, dado que actúa de forma preventiva con respecto a los incendios y contribuye a la sostenibilidad de la población y el desarrollo de las zonas rurales. Al mismo tiempo, debe enfrentarse a un mundo globalizado con los gustos cambiantes de los consumidores. Esta investigación es una validación cualitativa de los elementos cuantitativos para la medición de capacidades que pueden encontrarse en el modelo publicado de capacidades dinámicas en el sector ovino lechero y, desde una perspectiva profesional, al someterlo a la opinión de personas expertas se aporta valoración profesional a este modelo. Se ha aplicado el método Delphi a un panel de 107 personas expertas en el ámbito de producción animal del sector ovino lechero manchego, siendo un requisito conocer profesionalmente las explotaciones de dicho sector en Castilla-La Mancha. Un 46 % de los expertos proceden del entorno académico con transferencia avalada en el sector, en un periodo de al menos cinco años y donde un 54 % son gerentes, trabajadores y profesionales que asesoran a este sector en un periodo similar. Además, se ha mantenido la equidad desde una perspectiva de género. Las personas consultadas ratificaron en un 56 % los indicadores identificados en el modelo y se encontró una explicación al 77 % de las diferencias identificadas. El estudio concluye con una evaluación favorable tras analizar las diferencias detectadas, donde además, este modelo avalado por expertos es de utilidad para establecer acciones tendentes a reforzar la posición competitiva de las explotaciones.

Familiar mixed dairy sheep farm is the most widespread system in the Mediterranean basin, in Latin America and in developing countries (85%). There is a strong lack of technological adoption in packages of feeding and land use in small-scale farms. To increase competitiveness, it would be of great interest to deepen the knowledge of how innovation was selected, adopted, and spread. The objective of this research was to select strategic feeding and land use technologies in familiar mixed dairy sheep systems and later assess dairy sheep farms in Spain. This objective was assessed by combining qualitative and quantitative methodologies. In the first stage, with the aim to identify and select the appropriate technologies, a panel of 107 experts in dairy sheep production was used. A questionnaire was applied to all of them with successive rounds using Delphi methodology. Later, these technologies were grouped by principal components analysis (PCA) and cluster analysis (CA). In a second stage the technological results from a random sample of 157 farms in the Center of Spain were collected. The technologies selected were linked to the technological adoption level of the farms in Castilla la Mancha by a multiple regression model. Ten technologies were selected by the 107 experts. Four factors were retained by PCA that explained at 67.11% of variance. The first factor is related to feeding strategies, the second to land use for livestock production, the third to efficient management of land resources or ecoefficiency and the fourth to by-products use. The expert evaluation was grouped in three clusters using the Ward’s method and the squared Euclidean distance measure, where the second showed higher values in the adoption level of each technology. The multiple regression model explained the relationship between the technologies and the technological level of the farms (R2 73.53%). The five technologies selected were: use of unifeed (1), supplemental feeding (5), grazing (6), raw materials production (7) and sustainable use of water and soil (10). These ten technologies identified can be directly extended to small-scale dairy farms from other countries in the Mediterranean basin and Latin America. This technological selection was supported from the broad and diverse panel of experts used. Besides, five technologies identified by the quantitative model will be able to be taken into account for the development of public innovation policies. They are direct technologies and easy to apply on the farm and seeking increased viability through innovation vs. intensification.