INTEGRATED MULTI-LEVEL ASSESSMENT OF INNOVATION AND INVESTMENT EFFICIENCY IN SPORTS EQUIPMENT MANUFACTURING BASED ON EVIDENCE FROM UZBEKISTAN

Mualliflar

  • Ixtiyor Xamraqulov ##default.groups.name.author##

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innovation##common.commaListSeparator## investment##common.commaListSeparator## manufacturing##common.commaListSeparator## sports##common.commaListSeparator## entropy##common.commaListSeparator## hierarchy##common.commaListSeparator## technology##common.commaListSeparator## conformity##common.commaListSeparator## competitiveness##common.commaListSeparator## Uzbekistan

Annotatsiya

This article develops a decision-oriented, multilevel framework for assessing innovation and investment efficiency in Uzbekistan’s sports equipment manufacturing industry. The objective is to connect regional innovation conditions with enterprise technology readiness and competitiveness while explicitly accounting for safety testing, standards conformity, and digital traceability. Using 2024 official statistics for fourteen territorial units, seven indicators were normalized and aggregated with Shannon entropy weights. At the enterprise level, a five-block, nineteen-indicator techno-indicative matrix was applied to LB SPORT and MAGNA SPORT; a sixblock analytic hierarchy process (AHP) model was used to examine competitiveness priorities. Regional index values were 0.194 for Andijan, ranked sixth, and 0.020 for Fergana, ranked fourteenth. Innovation expenditure per capita received the highest entropy weight, 0.261, whereas fixed-capital investment per capita received 0.089. Calibrated enterprise technology scores were 0.551 and 0.497, respectively, with conditional targets of 0.737 and 0.673 by 2030. The AHP comparisons exhibited a consistency ratio near 0.003, while modeled competitiveness scores reached 61.6 and 52.5 points. The framework distinguishes external innovation constraints from internal organizational capabilities and links diagnostic gaps to investment priorities in digital production, product testing, and certification. Importantly, the baseline enterprise scores rely on public profiles and explicitly modeled parameters rather than audited operating records; the 2030 indicators are illustrative targets, not realized outcomes. The proposed method supports investment screening and managerial monitoring but requires subsequent validation using company-level records, independent expert judgments, and repeated observations over time. Its principal contribution is original sectorspecific integration rather than the invention of new weighting algorithms.

##submission.authorBiography##

  • Ixtiyor Xamraqulov

    PhD in Economics, Doctoral Researcher, Fergana State Technical University, Fergana, Uzbekistan 

##submission.citations##

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2026-10-20

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