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An economic crisis can be measured from different perspectives. A very commonly used measure is that of a country’s economic growth. When growth is lower than desired, the economy is assumed to be near stagnation or in an economic recession. This paper connects entrepreneurship and economic growth in decision-making problems assessed with modern aggregation systems. Aggregation techniques can represent information more comprehensively in uncertain and imprecise environments. This paper suggests several practical aggregation operators for this purpose, such as the ordered weighted average and the probabilistic ordered weighted averaging weighted average. Other aggregation systems based on macroeconomic theory are also introduced. The paper concludes with an application in an entrepreneurial uncertain multi-criteria multi-person decision-making problem regarding the selection of optimal markets for creating a new company. This approach is based on the use of economic growth as the fundamental variable for determining the preferred solution.
This paper has presented a new approach for dealing with entrepreneurship under uncertain environments that can be assessed by a country’s economic growth. A main assumption is that positive economic growth is very helpful for entrepreneurial activities because it indicates that the market is expanding. The approach proposed relates the concepts of entrepreneurship and economic growth in decision-making processes where entrepreneurs look for the optimal market and it is important to detect countries in which a higher economic growth is expected. Since the information is uncertain and nobody knows exactly what the future will bring, several methods have been presented for forecasting economic growthusing a wide range of aggregationsystems. A key method for doing this is by using the classical methods available in macroeconomic theory. The main formulation compares GDP in one year with the previous year in order to calculate economic growth. It has been demonstrated that decomposing GDP into its main variables can provide a new framework for assessment with aggregation systems. Several aggregation methods have been presented including a wide range of POWAWA operators. Their main advantage is that they include as particular cases the classical methods based on the arithmetic mean and the weighted average. Therefore, the new methods presented in this study can always be reduced to the classical framework if the problem considered is simple. However, in complex environments with a lot of uncertainties,this approach is more complete than the classical ones because it can represent the information in a more complete way.