Search

Focusing on sustainability, the new Common Agricultural Policy (2023–2027) sets ambitious goals for water management, as reducing irrigation water use is a vital issue. Cooperation among farmers, relevant authorities, and researchers plays a significant role in achieving these objectives. Therefore, this study applies a multicriteria mathematical programming model to optimize land use, considering water use, profit, labor, and cost. The model was applied to three farmer groups located in Greece and proved to be valuable in the implementation of irrigation water use. Using the same methodology, two additional cases of farmer groups that utilize drylands are presented in complementary ways to investigate how the new CAP affects non-irrigated land uses. Regarding the irrigated case, reducing water usage involves decreasing the land dedicated to crops characterized by high water demand, such as rice, corn, vetch, and clover. This adjustment stems from the necessity to replace irrigated land with non-irrigated land because climate change demands low water consumption for crops and underscores the importance of the new policy framework to promote sustainable agriculture. As for the non-irrigated case, achieving optimal farm planning entails reducing the cultivated areas of vetch, grassland, and sunflower. This result is driven by the need to increase crops receiving primary subsidies, highlighting the necessity for non-irrigated farms to enhance their profitability through the benefits provided by the Common Agricultural Policy. Lastly, it is important to note that this study significantly contributes to guiding decision-makers in achieving alternative agricultural land uses and farm plans while also aiding in the comprehension of the new cross-compliance rules. [ABSTRACT FROM AUTHOR]

This study aims to change land use by implementing a Decision Support Model (DMS) with the goal of reducing water and fertilizer use. The problem is solved by deriving the necessary results of a set of selected pilot fields that belong to a farmer group located in the region of Central Macedonia. In order to define the pilot farms, the necessary data are collected and then processed using multicriteria weighted goal programming in order to develop a Decision Support Model that is related to the reduction of water and fertilizer use. [ABSTRACT FROM AUTHOR]

The aim of this study is to change land use by applying a decision support model that will contribute to the assimilation of the new cross-compliance rules, to optimal water management, and to the enhancement of the effectiveness and profitability of the farms. The research objective will be achieved by establishing 50-acre pilot fields for five farmer groups through the optimal allocation of limited economic and land resources. The result extracted will lead to the gradual incorporation of the new directives to reduce production costs and recognize the new cross-compliance rules. [ABSTRACT FROM AUTHOR]

The digitalization of farming is considered the fourth revolution in agriculture. The necessity of providing decision support tools and electronic platforms to help Greek farmers in their work is becoming increasingly evident. For this reason, this article presents the electronic platform called "FarmEconomicMonitoring" to monitor the operations of farms to control production costs and improve efficiency. With the use of the electronic platform by the farmer–entrepreneurs, their easy adaptation to the new technologies concerning decision-making and farm management systems becomes achieved. [ABSTRACT FROM AUTHOR]

Agricultural digitalization is gaining momentum, urging a transition from process-driven to technology-enhanced and data-driven agriculture. To support such a transition and help farmers derive benefits from digital technologies, also avoiding the potential threats associated with digitalization, future advisors need a variety of competencies, ranging from pure technocentric skills to more complex capabilities, such as impact forecasting and transition facilitation. Do Greek students who study to become advisors have these competencies? In this study, we attempted to answer this question following a quantitative approach. The results indicate that participants possess low levels in all the examined sets of competencies and, as a result, have limited overall competency in dealing with digital agriculture. These findings suggest the need for agricultural universities to reset competence-related targets and design strategies to supply future farm advisors with the competencies needed to act as facilitators of agricultural digitalization. [ABSTRACT FROM AUTHOR]

In this study a linear programming model was applied and the main structural and economic characteristics of the optimal organization of Greek goat farms were analyzed. The analysis was based on farm accounting data collected from 96 goat farms in northern Greece, through face-to-face interviews with farmers. The farm size in terms of does was used as a classification criterion and three farm size groups were formulated (small/medium/large size farms). Based on technical and economic data calculated for the surveyed farms and on specific indicators defined by livestock experts, a linear programming model was implemented for each of the three size groups of farms and the optimal plans under which farms maximize their gross margin were estimated. The optimal plans reveal the main structural characteristics of the farms and indicate the adjustments required to fully exploit the available technology. The results show that under the optimal plan all farms should increase the number of animals they rear. Small farms make full use of the available grazing land, while there is a small reduction in the use of grazing land in medium and large size farms. The farms under the optimal plans recommend to reduce production of feed on-farm and procure feed from the market, and produce cheese on-farm. The optimal structure indicates that goat farming should return to its traditional features and become a purely livestock farming activity operating under extensive production systems, making use of pastures of mountainous/disadvantaged areas, and avoiding excessive use of fodder. Under the production pattern, the farms will reduce production costs and improve their resilience and sustainability. [ABSTRACT FROM AUTHOR]

Measuring efficiency and determining factors that may influence it are very important steps to improve the businesses' competitive position, growth, and sustainability. This paper aims to investigate the efficiency of small accommodation businesses located in Greek non-coastal areas and to determine a set of factors that may affect it, from the perspective of the three dimensions of family businesses (family, business, ownership). The method adopted, in order for the research objective aim to be fulfilled, is the two-stage Data Envelopment Analysis model. In the first stage, the efficiency was estimated from a sample of 150 businesses. In the second stage, the influence of various factors on the examined efficiency was investigated by implementing a Bootstrap Truncated regression. The results showed that the majority of the examined businesses presented a low level of efficiency. Regarding the determination of the factors, it occurred that the manager's age, ownership form, and business type influenced the relative efficiency level in contrast to the factors of the business's age, the manager's sex and education level, the state of succession, as well as the manager's agricultural employment. By fulfilling the aim of this study, a significant contribution to the relative literature and especially to the hospitality field is offered. [ABSTRACT FROM AUTHOR]