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This paper reveals the computational library of the analytic models for the results of fuzzy arithmetic operations with fuzzy sets. In particular, the focus is on the synthesis of the universal inverse and direct models for maximum of triangular fuzzy numbers with different masks of their parameters. The results of the study verify the efficiency of the suggested computational library with soft computing models for fuzzy information processing in real-time control and decision making.

Several countries provide policy support to specific sectors in order to facilitate industry transitions. While industry-support policies stimulate the growth of their target sectors, little is known about how such policies engender heterogeneous international strategies. In this article, we investigate how industry-support policies influence foreign location choices. We argue that firms engage in jurisdiction shopping, choosing to invest in countries with more generous policy support, but that this tendency varies markedly across firms. Specifically, we suggest that firms’ nonmarket experience exacerbates the effect of policy support on location choice, whereas market experience has less of an impact. Further, we propose that some firms view generous policies more skeptically than others, depending on the nature of their nonmarket experience. We test and find support for our predictions using a longitudinal dataset of foreign investments of firms entering the solar energy industry in the European Union. Our findings indicate that supportive policies stimulate the energy transition, attracting in particular foreign entrants diversifying into renewables or having more policy experience. At the same time, they suggest that adverse policy changes in one country affect how firms assess policies in other countries, highlighting the need for policy coordination at a supranational level.

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