There are some specific features of the non-radial DEA (data envelopment analysis) models which cause some problems under the returns to scale measurement. In the scientific literature on DEA, some methods were suggested to deal with the returns to scale measurement in the non-radial DEA models. These methods are based on using StrongComplementary Slackness Conditions in the optimization theory. However, our investigation and computational experiments show that such methods increase computational complexity significantly and may generate "strange" results. In this paper, we propose and substantiate a direct method for the returns to scale measurement in the non-radial DEA models. Our computational experiments documented that the proposed method works reliably and efficiently on the real-life data sets.
The efficiency of the national innovation system (NIS) is widely considered to be the most important factor of innovation-based economic growth. Using the wide spectrum of different metrics for measuring the efficiency of NIS, modern studies focus mainly on high-income or upper-middle-income countries, while the effectiveness of the NIS in post-Soviet countries has not been studied enough. The post-socialist transformation has led to different models of economic development in these countries, which can be divided into three groups: a group with developed European institutions, a group with a focus on the European path of development, and, finally, a group of countries with an economic model of “state capitalism”. These models formed the trajectory of innovative development. The main purpose of this study is to compare the performance of NIS in post-Soviet countries and to find out whether differences between development institutions can help explain differences in the performance of NIS. The study applies the DEA methodology and considers NISs as homogeneous economic agents, which transform the same types of inputs (knowledge gained using human and financial resources) into the same types of positive outcomes (innovative products and services). The results of a study conducted on data for the period 2011–2018 show that there is no evidence to support the hypothesis that EU institutions or the type of economic model of the country directly relate to the effectiveness of the NIS. The example of Kazakhstan shows that NIS can be effective, even with strong state intervention in the economy. Taken together, the results of the paper suggest that the structure of R&D expenditures by sources of funding and types of research plays an important role in the formation of effective NIS.
The concept of eco-efficiency has recently become an issue of great importance due to the growing trend of environmental degradation, and many approaches based on Data Envelopment Analysis (DEA) are used in the literature to evaluate the environmental performance of economic systems. However, research to date has paid little attention to the possibility of extending the DEA approach to the problem of measuring the economic feasibility of eco-efficiency improvement. The main aim of this study is to evaluate the efficiency of investments focused on improving the eco-efficiency of the regional economy in Russia using the DEA approach. The various types of costs for environmental protection measures are considered as inputs and the annual decrease in specific environmental impacts of the regional economy are considered as outputs of DEA models. This is different from previous research, which generally focused on environmental efficiency only, omitting the integration of economic aspects in eco-efficiency measures. This study compares three different modifications of basic DEA models in the context of technical complexity and practical feasibility. The results show that the efficiency of regional environmental management in many Russian regions has a great potential for improvement. From a practical point of view, the Slack-Based Measure (SBM) model provides the most accurate results for policy applications. Unlike other ratings, the DEA-SBM model may stimulate an optimization of environmental protection spending and the introduction of technological and organizational eco-innovations.
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