Impact Assessment (IA) is an important process in order to help both researchers and policymakers to identify the vulnerable points of policies with final goal to improve them. For this reason, European Union introduced impact assessment, as a mandatory process in all new policies and directives. One of the main EU policies are the Rural Development Plans (RDPs), as a part of the second pillar of the Common Agricultural Policy (CAP), which are implemented in every member-state. The aim of this paper is to evaluate an impact assessment process for the rural development plan measures. This process was implemented as case study for a specific measure of the Greek RDP. The implementation of the impact assessment process refers to a sample of farms participating in the measure 121 “Modernization of agricultural holdings” in the region of Central Macedonia in Greece for the programming period of 2007–2013. From the evaluation of the IA process very useful conclusions were raised. The results will help the researchers and the policy makers to make improvements in every step of the impact assessment process.

Agricultural production and farm management are inextricable, since managerial aspects for safe and of high-quality food products have led to the development of successful production plans but multifaceted controversies as well. These controversies arise from the focus of policymakers, especially in the EU, to the environmental aspects of agricultural production, creating conflicting objectives for farmers. Energy from biomass derivatives could play a significant role in the dispute for economic and environmental sustainability in agriculture, along with the formulation of agro-energy districts. In this context, an MCDM model was developed integrating LCA data for the assessment of economic, environmental and energy sustainability regarding thirteen major crops in the Region of Central Macedonia in Greece. The model's objectives consist of maximization of farmers' gross income, minimization of emissions coming from farming practices and maximization of energy potentially coming from biomass. Furthermore, three different scenario-based directions allocate different weights to the respective objectives, creating different managerial strategies. The optimal production plan was the scenario in which the weights were allocated by goal programming. The optimal plan proposes the cultivation expansion of energy crops, tree crops, alfalfa and hard wheat to a higher degree. Moreover, a significant reduction to the cultivated areas of tobacco, rice, barley and soft wheat could lead to a potentially viable production plan.

The aim of this study is to analyse spatially the economic impacts of climate change on cereal yield in Greece. The paper employs the geographically weighted regression (GWR) method to determine the spatially varying relationships between geophysical, soil, climatic and social variables and their effects on crop yield based on both historical climate observations and a future climate emission scenario. In order to achieve this analysis, a high spatial analysis of 10 × 10 km grid cells is utilised. The results indicate that crop yield is influenced by several spatial agrophysical and climate variables. The future climate emission scenario, predicts an average decrease in rainfall, a rise in temperature and an increase in severe weather events. Moreover, these effects are highly region-specific.

In this study a Multicriteria Data Envelopment Analysis (MCDEA) model was implemented to the seven prefectures (DMUs) of Central Macedonia region in Northern Greece, in order to estimate the relative efficiency of agricultural production process. The model includes five inputs (land available, variable costs, labour, fertilizers, and number of tractors) and two outputs (total gross margin, and bioenergy produced from the biomass of crops residues), all of which are related to the three pillars of sustainable agricultural development i.e. economic, environmental and social. The MCDEA approach was selected to improve the efficiency discrimination of DMUs concerned since, due to small number of DMUs, the conventional DEA is not able to discriminate successfully the relative efficiency of DMUs compared. The model applied is the MCDEA-WGP-CCR and was solved by multiple objective linear programming (MOLP). The improved discrimination and ranking of the seven prefectures is evident from the empirical results. Only two prefectures were proved efficient and five inefficient. The achieved results were compared with those of the conventional DEA CCR model of input orientation. The suggested approach is proved capable to resolve the problem of the DEA CCR model related to small number of DMUs and the subsequent ranking of all DMUs with maximum efficiency.

Agricultural management has become an increasingly complex endeavor. As a result, there is the need to generate knowledge from information that can guide practice, and in that aspect, decision support systems (DSSs) can contribute to achieving this goal. A DSS can be defined as a computer-based information system that is used to support complex decision-making. The aim of this paper is to present such a DSS focused on the agricultural sector. Its purpose is to be used for the planning of agricultural production and better utilization of a region's available resources. The development of the DSS relies on the classic theory of such tools utilizing MCDM models, databases, and a user interfaces. The proposed DSS was applied in the prefecture of Larissa in Central Greece. The DSS is adaptable to different contexts, and applications of these capabilities are presented at the end of the paper, applied in different regions under additional objectives and/or constraints.

Agriculture is the main and, in some cases, the only, source of income and employment in rural areas. The change in the conditions under which agriculture is practiced has various effects on the agricultural economy but also on the social structure of rural areas. Climate change has multiple effects on agricultural production, necessitating the reorganization of agricultural production in some cases. These effects of climate change will also impact the economic and social aspects of farms in rural areas. This paper attempts to identify these effects by measuring the socioeconomic impacts of climate change in the region of Central Macedonia in Greece. For this reason, a multicriteria model was developed to simulate these impacts by estimating a set of seven social and economic indicators. The model was implemented to the average farm which was estimated from the main cultivations of the region. A scenario analysis was also used in combination with the multicriteria model. The multicriteria model suggests modifications are needed in the average farm crop plan of the region as a result of the climate change impact. The scenarios results show that climate change will negatively affect all the social and economic indicators and will continue to affect them over the years. These results can be used by policymakers to understand the economic and social impacts of climate change in the region to plan their future policies.

Existing pressure for the confrontation of a radically changing external environment has led many companies to invest in various Information Systems, such as Enterprise Resource Planning (ERP), in order to optimize their production processes and strategies. Despite the fact that ERP system is an important strategic tool, many companies fail to take advantage of its benefits due to their default in many aspects of management and implementation. This study aims to investigate the critical success factors of enterprise resource planning system implementation and build a categorization framework so as to create a theoretical base that enhances any further research approaches in various sectors of the economy. Therefore, 37 ERP critical success factors were identified by using Content Analysis method and classified into relative categories to the ERP orientations of implementation and the ERP life cycle phases. Finally, these two types of categorization were merged in order to examine the critical success factors' behavior during the ERP implementation. This paper and the multilateral theoretical framework it creates, sets out how critical success factors must be taken into account by companies and marks a beginning point that promises a sequence of further research approaches in particular economic sectors or in a set of them. By fulfilling the purpose of this study, a significant contribution to computer science literature and especially to the ERP field is offered.

The purpose of this study was to examine the implementation of Total Quality Management (TQM) as a business strategy in the Greek food and drink industry, along with the examination of the Information Technology (IT) adoption in the field. A research project was carried out in the sector companies based in Greece, using the questionnaire method. Findings showed a strong relation between IT implementation and impact of IT on TQM. Company size also seemed to affect TQM implementation, and the majority of IT implementation constructs, while company performance was not significant in terms of net profit margin and value added per employee.

Agriculture is highly affected by environmental conditions and the assessment of the agroclimatic potential is necessary for sustainability and productivity. The climate is among the most important factors that determine the agricultural potentialities of a region and the suitability of a region for a specific crop, whereas the yield is determined by weather conditions. In this chapter the first objective is to identify sustainable production zones in Thessaly by conducting contemporary agroclimatic classification based on remote sensing and GIS. The agroclimatic conditions of agricultural areas have to be assessed in order to achieve sustainable and efficient use of natural resources in combination with production optimization. Thus, a quantitative understanding of the climate of a region is essential for developing improved farming systems. The second objective derives from the first; it develops a decision support system (DSS) by using multi-criteria analysis combining different criteria to a utility function under a set of constraints concerning different categories of agroclimatic, social, cultural and economic conditions and so we can achieve an optimum agricultural production plan. In order to support the realization of the proposed production zoning and DSS in real-time, a Sensor Web service platform is proposed to be implemented based on the Sensor Web technologies, which extracts Real-time environmental and agronomic data.

The production of olives and olive oil in the Mediterranean region is one of the most important cultivations. The continuous changes imposed by the European Common Agricultural Policy (CAP) towards strengthening the influence of market forces have increased the necessity for the assessment of the efficiency of production protocols or patterns being implemented by the farmers. As regards olive trees cultivation, the efficiency of inputs utilization has not been studied in depth, despite the fact that this is a critical issue for both farmers and consumers. This study evaluates the efficiency rates of 100 Greek agricultural holdings specialized on olive trees cultivation by implementing a Data Envelopment Analysis (DEA) input oriented model. The inputs being used are land, fertilizers, agrochemicals, labour, and energy. The output being used is the revenue of each holding. The results quantify the significant variations of efficiency scores, providing evidence that there is space for restructuring the production process, in order to improve efficiency and thus decrease the production cost of inefficient farmers.

The simultaneous and increasing needs for safe and quality food products, along with the environmental and socio-economic sustainability, develop a multi-level problem with controversies and arbitrary assumptions for farmers and policy makers. In order to assess the aspect of sustainability in agricultural production, different impact assessment tools could be implemented. Although LCA gives the potential to develop alternative scenarios in order to achieve the optimal environmental performance, in the context of sustainability, at the same time subjective measures are developed which are difficult to quantify. Multi-criteria analysis (MCA) is the key to solve the current weakness, since it takes into account multiple criteria in a wide assortment of aspects and thus it could integrate sustainability elements. The purpose of this study is to outline the integration of LCA and MCA methodologies and develop a complete literature review regarding the sustainability of the agricultural sector through the above mentioned methodological merge. In this review we analyze scientific papers integrating LCA and different multi-criteria methodologies in agriculture. Through this analysis, we determine the connection between the methodologies through a variety of aspects regarding (a) the number and nature of multi-criteria methods integrated with LCA, (b) the way of integration between the methods in a technical perspective and (c) the benefits developed through the integration as well as the final conclusions which could only be elicited through this complex process. Studies which implemented LCA and MCA simultaneously illustrated positive economic and environmental results, since LCA focused on environmental sustainability and the multi-criteria modeling dealt with the subjective measures of LCA.

The formulation of bio-based industries constitutes a major goal for the generation of sustainable forms of energy globally. Nevertheless, the different bio-energy pathways depend on manifold conversion technologies and induce an assortment of environmental impacts. To this end, the evaluation tool of life cycle assessment (LCA) is thoroughly analysed for biomass exploitation systems, since it is acknowledged as the most advantageous methodological framework. Furthermore, specific critical points of LCA are identified through literature review and the four-step modular process is analysed. Moreover, a classification of 40 papers implementing LCA and biomass exploitation is conducted to investigate the direction of the scientific stimulus, as well as the fluctuation of funded projects after the bloom of relevant technological advancements. The majority of the papers assessed a complete biomass exploitation system 'from cradle to grave', while 65% describe systems in the European region. Finally, the increase of funded projects is prominent the last nine years and the number of researches regarding LCA and biomass is increasing as well.

The production of olives and olive oil in the Mediterranean region is one of the most important cultivation. The continuous changes of the European Common Agricultural Policy (CAP) towards strengthening the influence of market forces, has increased the necessity for assessing the efficiency of production protocols or patterns being implemented by the farmers. The case of olive trees cultivation, despite the fact that it is very important for both farmers and consumers, has not been in depth analyzed regarding the efficiency of inputs being used during the production process. This study evaluates the efficiency rates of 100 agricultural holding specialized on olive trees cultivation in Greece, by implementing a DEA input oriented model. The inputs being used are land, fertilizers, agrochemicals, labour, and energy. The output being used is the revenue of each holding. The results quantify the significant differentiation of efficiency scores, providing evidence that there is space for restructuring the production process, in order to improve efficiency and decrease by this way the production cost of inefficient farmers.

Blended learning is the combination of traditional and distance learning. It constitutes the natural evolution of e-learning through an integrated programme of multiple choices of means, implemented to solve a specific organizational problem using the best possible combination. It mainly resolves the problem of speed, classification and effectiveness and uses electronic education, where and when it is most appropriate, without imposing it when not necessary. The evaluation of blended learning and education is usually carried out as assessment of the framework and history, aims, results, activities and means, in order to draw useful conclusions for the design of new programmes and the guidance of future decisions relevant to the programmes of blended learning. It is actually a periodic review of efficiency, effectiveness, influence, viability and relevance of blended learningu0027s contribution to the broader context of predetermined aims. This paper identifies the specific characteristics, the advantages and technologies to support blended learning, and reports a framework for the use of appropriate criteria, procedures and methodological approaches for the evaluation of blended learning programmes.

This paper presents a multi-criteria model for agricultural production planning in agro-energy districts. The use of crop residues to produce thermal and electric energy promotes a sustainable environment. This is the reason that the formation of agro-energy districts and the increase of biomass energy production are among the main goals of the EU programming period 2014–2020. The model has two main objectives: income maximisation and maximisation of biomass energy produced by the crops' residues. The utility function of the multi-criteria model combines the two objectives and is maximised under a set of constraints. The model is applied in two prefectures of northern Greece, Imathia and Kilkis, located in the region of Central Macedonia. The two prefectures have different characteristics in relation to the main crops cultivated in their respective crops plans. In both prefectures, the optimum production plan achieves greater income and greater biomass energy production.

Abstract This paper aims to make a comparison between Greek and Bulgarian rural areas, in terms of social sustainability indicators. Social sustainability is related to social capital, social inclusion, social exclusion and social cohesion in rural economies, terms that can be measured by relevant social indicators. The paper focuses on the effects of farm household behaviour on social sustainability in regard to changes in employment, gender, migration and social capital. To this end two case study areas were selected; Macedonia and Thrace in Greece and South east Planning Region in Bulgaria. The data were collected by a survey carried out in the context of the European FP7 project entitled CAP-IRE (Assessing the multiple Impacts of the Common Agricultural Policy on Rural Economies). The survey included eleven case study areas in nine case study areas of the European Union. The paper also compares the results from the Greek and Bulgarian case study areas with the average results of the eleven European case study areas. Key words: social sustainability indicators, rural areas

The objectives of the European Union 2014–2020 programming period include increase of energy production from renewable sources through the creation of agro-energy districts. The utilization of residues of annual and perennial crops in agro-energy districts as a combustion product of the exploitation of biomass industry to produce heat and electricity, create a new sustainable environment. This paper focuses on optimizing the agricultural income and the biomass energy potential from crop residues in agricultural districts and especially in a case study in municipality of Almopia in Northern Greece. For this purpose, the optimal plan of agricultural production of the case study area arising from the development of a multi-criteria mathematical programming model that combines more than one conflicting criteria to a utility function that interprets the behavior of farmers and better approaches the rational decision making. The objective of the proposed model is to combine two criteria, namely the maximization of the total gross margin of the case study area and the maximization of electric or thermal power from biomass of crop residues, based on a set of constraints for land, labor, capital, Common Agricultural Policy rules, etc. The optimal production plan of the case study area achieves higher gross margin (3.6 %) and higher level of bioenergy (7.7 %) than the existent production plan. The optimal plan also presents better results than those achieved by the linear programming model when the only goal is to maximize either the gross margin or the production of bioenergy.