Abstract
The current PhD thesis aims to contribute to new methodological approaches concerning the optimization of inputs use efficiency, under the prism of sustainable development (economy, society, and environment) in the agricultural sector. For this reason, a brief introduction is provided, outlining the rationale on which the benchmarking of agricultural systems is imperative, based on the guidelines given at the global level by the United Nations (UN), while there is also a more specific description of Data Envelopment Analysis (DEA), which is also the methodology assessed in this thesis. Chapter 2 outlines the research questions that emerged from the analysis of 120 articles in the field of optimization in the agricultural sector. More specifically, there is a need: 1) to introduce social factors into the overall assessment process, so that decisions can be made that cover all 3 pillars of sustainable development, 2) to create farm specific databases that show a high degree of accuracy 3 ...
The current PhD thesis aims to contribute to new methodological approaches concerning the optimization of inputs use efficiency, under the prism of sustainable development (economy, society, and environment) in the agricultural sector. For this reason, a brief introduction is provided, outlining the rationale on which the benchmarking of agricultural systems is imperative, based on the guidelines given at the global level by the United Nations (UN), while there is also a more specific description of Data Envelopment Analysis (DEA), which is also the methodology assessed in this thesis. Chapter 2 outlines the research questions that emerged from the analysis of 120 articles in the field of optimization in the agricultural sector. More specifically, there is a need: 1) to introduce social factors into the overall assessment process, so that decisions can be made that cover all 3 pillars of sustainable development, 2) to create farm specific databases that show a high degree of accuracy 3) to use more complex methodological approaches, such as those applied in other sectors of operational research. In Chapter 3, a combination of DEA with the multi-criteria decision-making method TOPSIS is applied, to derive results that also include the social dimension, focusing on the first literature gap. The research carried out concerned 107 cotton producers in Thessaly and Central Macedonia regions. Final results show that there is a well-established production protocol, while there are few producers that perform under a low degree of efficiency. Regarding the combination of DEA and TOPSIS, it seems to be particularly useful not only for the integration of social characteristics, but also for cases where it is difficult to have accurate field data. Chapter 4 refers to a case study where the inputs’ use efficiency of producers in Greece and Italy is studied through the network of GD.NET, a decision-making system for the cultivation of durum wheat, which has derived from the collaboration of HORTA and Barilla. In this case, differences resulting from the application of the Agricultural Decision Support System (ADSS) provided by GD.NET on a local and national level, were highlighted. More specifically, it seems that Italian farmers have a clear tendency to reduce their inputs, while Greek durum wheat producers do not apply the production protocol under the same consistency. Nevertheless, this chapter promotes the way of how modern agriculture should be applied, collecting and processing field data with the use of ADSS, aiming at increasing efficiency and mitigating negative environmental externalities. Chapter 5 presents the application of DEA using time series data of the agricultural sectors of the European Union members. The methodological interest of this research is focusing on the impact of appropriate window width selection, which corresponds to the time interval based on which the impact of technology change is considered as insignificant. In this case, the ideal window width appeared to be of 7 years, which corresponds to programming periods of the Common Agricultural Policy (CAP).In the last chapter, a summary of all chapters is being presented, as well as the challenges that accompany the application of DEA on a business and academic perspective, to comply with the general directions of the UN, to achieve sustainable development until the year 2050.
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