## 1 Introduction
According to [6], the strategic objectives are created in tandem with the statement of vision and provide an answer to the question \"where do we want to be in the future?\". However, the vision of the strategy created in this way does not answer the question of _why_ we select specific strategic goals. The adoption of vision statements and the definition of the objectives of the strategy is a decision-making process. [PERSON] [14] analyzed systems and processes for planning and decision support. The authors' research supports the design of information systems capable of coping with the needs and fundamental limits of improved judgment. [PERSON] [14] discussed and described the following: (1) the cognitive styles of decision makers; (2) individual human information processing in decision situations and biases in the acquisition, analysis, and interpretation of information; (3) decision rules for individual decision situations; (4) contingency task structural models of decision situations; and (5) decision-making frameworks, organizational settings, and information processing in group and organizational decision situations. [PERSON] [15] stated that the success and survival of an organization depend on its ability to adapt to specific contingencies. This has led to investment in systems for information management and decisions in the planning function. [PERSON] et al. [16] proposed an integrated decision support system for use in environmental planning. The purpose of developing an integrated decision support system is to systematically support a series of tasks from systems analysis to policy analysis with the aid of these systems science methodologies and by integrating the knowledge or judgment of experts with the available numerical data. According to the rational model of decision-making, the decision-making process can be divided into six steps, as described in [17]:  
1. Identifying the problem;
2. Generating alternatives;
3. Evaluating an alternative;
4. Choosing an alternative;
5. Implementing a decision;
6. Evaluating decision effectiveness. After identifying the problem, alternatives for its solving should be generated. These alternatives are evaluated, and the best alternative is selected for implementation. The selected alternative is then assessed over time to ensure the effectiveness of the decisions. After this assessment, the whole process may be restarted to achieve better outcomes. In this study, we suggest a novel approach to defining strategic goals and objectives. Our approach is based on the need to integrate business intelligence tools into a strategic planning process. For this purpose, we propose an ontology-driven simulation method for assessing the economic impacts that should be implemented as a decision support tool for choosing the best strategy goals and objectives. The proposed ontological model semantically describes the strategic planning process and is used as a basis for ontology-driven simulation methods for assessing the economic impact of the chosen strategy. [PERSON] [18] presents three common dichotomies: reference vs. application ontologies, description logics vs. resource description framework (RDF)-based semantics, and ontological vs. conceptual models. Ontology is annotated with a semantic representation of input-output multipliers obtained from the economic impact analysis of the analyzed region. Economic impact analysis provides a rule-based and transparent measure of economic activity, jobs, wages, and tax revenues [5]. According to the author of [5], the results of the economic impact analysis can be seen through the increase/decrease of the following indicators:  
1. The operating result (or sales volume);
2. Additional value (or gross regional product);
3. Wealth (including property values);
4. The personal income, tax (salary);
5. New jobs. Improvement of the above-listed indicators is the main objective of most development strategies. Economic impacts can be classified as follows [5]:  
1.