The quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multi-criteria decision making because it produces inadequate management of processes and activities in various spheres.

One of the most common tools for achieving optimization and adequate production process management is linear programming (LP) in various forms. However, there are specific cases of the application of linear programming when production optimization implies several potential solutions instead of one. Exactly such a problem is solved in this paper, which integrates linear programming and a Multi-Criteria Decision-Making (MCDM) model. First, linear programming was applied to optimize production and several potential solutions lying on the line segment AB were obtained. A list of criteria was created and evaluated using the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA). To obtain the final solution, a novel Rough compromise ranking of alternatives from distance to ideal solution (R-CRADIS) method was developed and verified through comparative analysis. The results show that the integration of linear programming and a Fuzzy-Rough MCDM model can be an exceptional solution for solving specific optimization problems.

The modern world is at a new historical turning point (transition from industrial to post-industrial or information society). Today, this is most often referred to as a transitional or transitional period. However, this process is often reduced as the transition of the planned economies of the former socialist countries to market economies and the transition of their authoritarian social systems to democratic societies. The modern transitional period represents the period of the realization of the third scientific and technological revolution (biotechnology, robotics, informatics, new materials, conquest of space and sea for production purposes), which changes both production forces and production relations. Namely, all this leads to a new organization of production, a new type and carrier of production management, changes the importance and role of ownership, factors of production, the nature of distribution, and thus suggests the creation of a new type of social relations. The process of socialization, humanization, new integration is being realized, new technologies are being developed, but also a new quality of life. It is reflected in the transformation of the capitalist and real-socialist mode of production into a new mode of production. We call this transitional stage the modern transitional or transitional period.

A quality corporate governance system is a basic prerequisite for a sustainable growth economy, more easily increasing the efficiency of the economic system and guaranteeing access to external sources of capital. The level of quality of corporate governance can be defined as the degree of fulfillment of set standards of corporate governance defined at the international and national institutional level. In the new, modern business conditions, with strong dynamic changes in the social and business environment, modern corporate companies, ie their management bodies, are taking on new characteristics, adapting to new requirements and challenges. In this sense, the new demanding business conditions require continuous improvement of corporate governance potential. Based on previous theoretical and empirical knowledge, Bosnia and Herzegovina has the characteristics of a closed corporate governance system in both entities, so, as a basis for developing models for measuring the level of corporate governance, selected models that measure corporate governance in countries with typical closed corporate governance systems. A significant number of studies show that corporations that achieve higher standards and better corporate governance practices also have better business performance results and thus greater value in the capital market. This means that corporations with a higher level of corporate governance also have better financial operating results, easier access to financial capital, and greater value in the capital market. The main purpose of the research is to determine the level of influence of the quality of corporate governance on business performance, ie to determine whether corporations that had good corporate governance had higher business liquidity and vice versa. The main goal of the research is to establish the link and relationship between quality and corporate performance management indicators of the corporation's business.