Purpose: The main reason for developing the model was to fulfil the gap in the scope of synthetic/aggregate measure of corporate innovativeness in terms of company’s results in this area and their impact on its performance. Design/methodology/approach: In the proposed concept two aspects have been considered: quantitative and qualitative results of company’s innovation activity (i) and impact of this results on financial performance of company and its efficiency (ii). Due to the fact, that access to information on innovative activities results of companies is highly diversified, proposed model provides two versions to use: one, more general, based on public sources of data (Public Data Approach) and one, more detailed, based on data which should be collected through survey research (Survey Data Approach). The basis for corporate resultant innovativeness model creation was an assumption, that the ultimate market success of the company is not determined by how many innovative solutions it implements and introduces to the market and with what force it does it, but how these solutions will be accepted by the market and what economic benefits the company will receive due to them. Findings: Proposed methodology of innovativeness assessment gives a chance to eliminate several key shortcomings of the so far used methods and concepts of corporate innovativeness measurement and assessment. Research limitations/implications: Input data accessibility, development of knowledge (rules) bases needed to perform fuzzy inference. Practical implications: Presented model gives an opportunity to assess and compare enterprises in terms of their resultant innovativeness and then to assess the impact of this innovativeness on their performance. Social implications: Assessments generated by presented model can be basis for managerial decisions inside the assessed enterprise or investment decisions of investors in the capital market. Originality/value: Original approach for aggregate corporate resultant innovativeness assessment that eliminates several weaknesses of methods used so far.
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