The European Innovation Partnership (EIP) is considered to be a new phenomenon signalling political will, highly relevant issue in contemporary domain of discussions among practitioners and researchers. While practitioners lack experience, researchers make attempts to identify the factors that influence effectiveness of an innovation partnership, explore the indicators and techniques to determine and evaluate its effectiveness. Aim of the study presented in the article is to determine the external and internal factors that influence effectiveness of the European Innovation Partnership by analysing the operating conditions of an operational group of the European Innovation Partnership in Agriculture (EIP-AGRI). Expert evaluation was carried out by experts who have scientific and practical experience: scientists, policy makers, innovators, developing an innovation partnership. The force field analysis has shown that the number of negative factors of EIP effectiveness exceeds the number of positive factors, and the factors analysed and evaluated allow to identify potential negative consequences in a timely manner and provide the opportunity to predict effectiveness of the EIP-based projects.

The European Innovation Partnership in Agriculture (EIP-AGRI) was initiated by the European Commission for social benefits and the modernization of the overall economy through innovation. Better and faster results are expectingby fostering collaboration between scientists, agricultural advisors and farmers. The main problem is how to evaluate the effectiveness of innovation partnership projects in agriculture, with what indicators to define and measure it? To address this problem, a methodology for evaluating the effectiveness of innovation partnerships in agriculture hasneeded. This article presents the methodology of evaluation of the effectiveness of innovation partnership in agriculture, which details the selected evaluation indicators, determines their significance, and provides guidelines for the interpretation of the results of efficiency evaluation. The developed evaluation methodology has tested using the project data of EIP groups operating in Lithuania. The methodology for evaluating the effectiveness of innovation partnerships in agriculture is relevant fromboth a scientific and practical point of view.

The social (public) water management projects implement the goals of national sustainable development - improve the living and working conditions for people in rural areas, protect the environment. The mentioned projects don’t generate net income, but create social benefit for the public. The social benefit associated with the expected impact of the project. The social benefit not measured in monetary units, but in various quantitative and qualitative metrics. The research problem follows from the diversity of social benefit indicators and the need of complex assessment of these indicators. Multicriteria evaluation methods allow complex assessment of social benefit indicators, social benefit of social (public) projects can be evaluated and the project alternatives can be ranked and compared. The article analyzed and assessed possibilities and weaknesses of the multicriteria methods for social (public) project social benefit evaluation, the methodic for multicriterial evaluation of social benefit of water management project is consisted and the complex assessment of social benefit of water management project alternatives are carried out.

From the technical and agro-technical point of view, the reclaimed land of poor condition covers 222.4 thousand ha. More than 15.0 thousand ha of drained agricultural land turned into a swamp, more than 67.3 thousand ha overgrew with bushes and forest. The average depreciation of buildings reached 59.1 percent. When drainage structures are worn down, there is a need to overhaul or, in many cases, to reconstruct them. The economic situation in the country and farming agricultural conditions change, therefore it is appropriate to assess drainage systems from the economic viability and payback time of the projects viewpoints, using a variety of partial drainage and surface water drainage ways, depending on land use. Drainage systems should be reconstructed in areas, which are used in agricultural production, therefore agricultural output prices, state and EU subsidies as well as profits per unit of area are key indicators that determine economic viability of the drainage system reconstruction project. Drainage system reconstruction clients are municipalities, land reclamation business associations and, in rare cases, farmers or other individuals, their goal - to get the maximum profit at the lowest possible cost. Considering the expected activity, simple solutions are often enough, therefore, the reconstruction of drainage systems should be designed allowing a wider choice of cost-effective technical solutions.

The main idea of this paper is that innovation is contributing to the efficiency and sustainability of investment. The main question is how to measure and assess efficiency of investment in innovation for the project benefit. The main objectives of this paper are: a) to analyse the concept and theoretical models of innovation, and b) to establish the criteria and select model for further assessing the efficiency of investment in innovation project. The research was based on analytical and expert methods and included theoretical analysis of literature sources, analytical, expert and comparison analysis. This paper discusses the definition of innovation of different authors, as well as the role of innovation for the efficiency of investment, and defines various criteria for measuring the efficiency of investment in innovation project. Paper suggests these criteria allocated to five groups related to product, process, finance, market and management. The comparison of three models (CBA, DEA and MCA) presented in this paper concluded that all three models in principle are suitable for assessing efficiency of investment in innovation project. However, the management aspect, which is hardly measurable but important in innovation efficiency performance analysis, suggests proceeding further modelling with MCA using it as complement to CBA.