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Modern transformations in the socioeconomic sphere begin to demonstrate the growing role of intangible factors of production to an increasing extent every year. The most important of them are reputation capital, which reflects the efficiency and growth potential, and hence the prospects for the future development of environmental management, economic agents, territories, states. The central purpose of the study is to build and solve a crucial methodological problem, such as determining the relationship between the reputation capital of a region and the parameters of the development of environmental management and economic sectors. It should be noted that despite the fast-growing interest of world economic science in this issue, there is no generally accepted systemic solution to it thus far. In this vein, based on the generalization and systematization of methodological approaches to building the reputation capital of territories, as well as based on the experience and testing of previously obtained results on this topic, the authors tried to carry out a statistical analysis of the sought correlations between the index of reputation capital of the region and the environmental management sector in the studied regional types of economic activity. The research focuses on relations concerning the activation of investment processes in the sectors of environmental management and economic activity based on increasing the reputation capital of the region. The Republic of Tatarstan is treated as the object of the research. [ABSTRACT FROM AUTHOR]

In a competitive environment, it is crucial for organizations to know how efficiently and effectively they are operating compared to similar organizations. The challenge is to somehow draw helpful insights from all these numbers that will lead to improvements in the performance of the organization. Efficiency measurement is one aspect of organizational performance. Data Envelopment Analysis (DEA) technique is considered the most appropriate tool for evaluating the performance of a set of comparable homogenous organizations under some predefined conditions. In real-life problems, values for input and/or output variables include uncertainty, this uncertainty may be randomness or vagueness in nature. The purpose of this study is the using of some theoretical results to develop a unified DEA model to handle different uncertainty types, the developed model allows various natures of variables (vagueness, randomness and deterministic) depending on the nature of uncertainty in the variables. Implementation of the model was presented through some cases to illustrate the model functionality. In addition, the results are compared with three other different DEA models; a Combined fuzzy/deterministic model, a Combined stochastic/deterministic model, and a deterministic model. Managers can rely on the developed model to assess relative efficiency in business complex systems associated with different uncertainty natures. [ABSTRACT FROM AUTHOR]

In a competitive environment, it is crucial for organizations to know how efficiently and effectively they are operating compared to similar organizations. The challenge is to somehow draw helpful insights from all these numbers that will lead to improvements in the performance of the organization. Efficiency measurement is one aspect of organizational performance. Data Envelopment Analysis (DEA) technique is considered the most appropriate tool for evaluating the performance of a set of comparable homogenous organizations under some predefined conditions. In real-life problems, values for input and/or output variables include uncertainty, this uncertainty may be randomness or vagueness in nature. The purpose of this study is the using of some theoretical results to develop a unified DEA model to handle different uncertainty types, the developed model allows various natures of variables (vagueness, randomness and deterministic) depending on the nature of uncertainty in the variables. Implementation of the model was presented through some cases to illustrate the model functionality. In addition, the results are compared with three other different DEA models; a Combined fuzzy/deterministic model, a Combined stochastic/deterministic model, and a deterministic model. Managers can rely on the developed model to assess relative efficiency in business complex systems associated with different uncertainty natures. [ABSTRACT FROM AUTHOR]

In a competitive environment, it is crucial for organizations to know how efficiently and effectively they are operating compared to similar organizations. The challenge is to somehow draw helpful insights from all these numbers that will lead to improvements in the performance of the organization. Efficiency measurement is one aspect of organizational performance. Data Envelopment Analysis (DEA) technique is considered the most appropriate tool for evaluating the performance of a set of comparable homogenous organizations under some predefined conditions. In real-life problems, values for input and/or output variables include uncertainty, this uncertainty may be randomness or vagueness in nature. The purpose of this study is the using of some theoretical results to develop a unified DEA model to handle different uncertainty types, the developed model allows various natures of variables (vagueness, randomness and deterministic) depending on the nature of uncertainty in the variables. Implementation of the model was presented through some cases to illustrate the model functionality. In addition, the results are compared with three other different DEA models; a Combined fuzzy/deterministic model, a Combined stochastic/deterministic model, and a deterministic model. Managers can rely on the developed model to assess relative efficiency in business complex systems associated with different uncertainty natures. [ABSTRACT FROM AUTHOR]

In a competitive environment, it is crucial for organizations to know how efficiently and effectively they are operating compared to similar organizations. The challenge is to somehow draw helpful insights from all these numbers that will lead to improvements in the performance of the organization. Efficiency measurement is one aspect of organizational performance. Data Envelopment Analysis (DEA) technique is considered the most appropriate tool for evaluating the performance of a set of comparable homogenous organizations under some predefined conditions. In real-life problems, values for input and/or output variables include uncertainty, this uncertainty may be randomness or vagueness in nature. The purpose of this study is the using of some theoretical results to develop a unified DEA model to handle different uncertainty types, the developed model allows various natures of variables (vagueness, randomness and deterministic) depending on the nature of uncertainty in the variables. Implementation of the model was presented through some cases to illustrate the model functionality. In addition, the results are compared with three other different DEA models; a Combined fuzzy/deterministic model, a Combined stochastic/deterministic model, and a deterministic model. Managers can rely on the developed model to assess relative efficiency in business complex systems associated with different uncertainty natures. [ABSTRACT FROM AUTHOR]

The article argues in favor of an integrated indicator of quality of services of higher education institutions. This indicator is calculated relying on the balanced scorecard methodological tools modified to be suited to higher education. The integrated indicator which has been developed incorporates interrelated sets of criteria used to ensure the quality of higher education services such as academic performance and research activity among students, the way in which the quality of educational services is assessed by the market, financial indicators and human resources characteristics. The development of the system of higher education, the effectiveness of modern higher education institutions directly depends on the quality and consistency of quantitative evaluation of their services. It should be noted that there is no universally accepted approach to this assessment in the modern Russian Federation. The mechanism for selecting specific indicators of the effectiveness of the quality of educational services, or a way to bring different dimensions of indicators to a single coordinate system. This article discusses a comprehensive system of key indicators characterizing the quality of educational services in the higher education system of Russia. [ABSTRACT FROM AUTHOR]

Due to the increase in competition and innovation, the importance of quality of service and performance evaluation to improve the provider's customer satisfaction have been taken into consideration more than ever. Performance management helps to check the performance of the chain, and indications of individual network elements or services that are forming the overall quality of service system. In that sense, this study focuses on efficiency measurement modeling for service systems. Additionally, the initial model was built to measure the efficiency of the units in a chain. We implemented the model on the artificial data of several coffeeshop chains using satisfaction factors while connecting to the financial aspect to determine the potential improvements that will help the operator enhance their services by learning from best practices. Data Envelopment Analysis (DEA) is used as a method, and the performance matrix will be adopted as a second stage analysis. DEA aims to find the Decision Making Units (DMUs) that produce high output outcomes using the low input resources compared with their peers. The paper provides recommendations to improve the productivity and efficiency of the inefficient units in a chain and develop a decision model to enable better best practices decision making. [ABSTRACT FROM AUTHOR]