Aylanma kapital bilan ishlashda samaradorlikni oshirish: korxona moliya siyosatini takomillashtirish yo‘nalishlarida data science yondashuvlari.
DOI:
https://doi.org/10.5281/zenodo.15776872Keywords:
aylanma kapital, Data Science, moliyaviy boshqaruv, likvidlik, mashinaviy o‘rganish, rentabellik, pul oqimi, regressiya, prognozlash, kredit riski, ishlab chiqarish sikli, avtomatlashtirilgan qarorlar, aktivlar samaradorligi, klasterni aniqlash, vaqt qatorlari, tahliliy tizimlar, moliyaviy monitoringAbstract
Maqolada korxonalar moliyaviy siyosatining muhim elementi bo‘lgan aylanma kapitalni boshqarishda Data
Science (ma’lumotlar fanlari) yondashuvlaridan foydalanish orqali samaradorlikni oshirish imkoniyatlari o‘rganiladi.
Aylanma kapitalning aylanish tezligi, likvidlik darajasi va moliyaviy oqimlarga ta’siri real vaqtli tahlil, prognoz modellar va
mashinaviy o‘rganish algoritmlari asosida baholanadi. Tadqiqotda zamonaviy statistik metodlar yordamida O‘zbekiston
korxonalarining moliyaviy ko‘rsatkichlari tahlil qilinib, ishlab chiqarish siklini optimallashtirish, kredit riskini kamaytirish,
qaror qabul qilishni avtomatlashtirish bo‘yicha ilmiy asoslangan takliflar ishlab chiqiladi. Yondashuvlar O‘zbekiston
Prezidentining raqamli iqtisodiyotni jadallashtirishga doir farmonlarida belgilangan vazifalar bilan bevosita bog‘liq bo‘lib,
real sektorni raqamlashtirish orqali korxonalarda moliyaviy barqarorlikni mustahkamlashga xizmat qiladi.
References
Axmedov Sh. “Moliyaviy menejment asoslari”. – Toshkent, 2018.
Hakimov Z. “Bank faoliyatida moliyaviy monitoring”. – Toshkent, 2021.
O‘ralov T. “Korxona aktivlaridan samarali foydalanish”. – Samarqand, 2019.
Yusupova M. “Moliyaviy tahlil va ishlab chiqarish sikli”. – Buxoro, 2020.
Davenport T. “Competing on Analytics”. – Harvard Business Review, 2010.
Manyika J. “Big Data: The next frontier for innovation”. – McKinsey Global Institute, 2013.
Weißbach H.-J. “Machine Learning im Mittelstand”. – Berlin, 2020.
Trevor J. “Rethinking Strategy”. – Oxford University Press, 2021.
Shimizu K. “AI in Financial Risk Management”. – Tokyo, 2019.
Kolmakov A. “Digital Finance in Industrial Companies”. – Moscow, 2021.
Marr B. “Data Strategy: How to Profit from a World of Big Data”. – Wiley, 2017.
Mamajonov F. “Debitorlik qarzlarini boshqarish mexanizmlari”. – Farg‘ona, 2022.
G‘aniyev N. “Korxona likvidligini baholash usullari”. – Qarshi, 2021.
Mirzayeva L. “Aylanma mablag‘lar va ularning aylanishi”. – Toshkent, 2020.
Kungratov Ilmurod Kuzibay ugli. (2024). SECURING TRAVEL EXPERIENCES: THE IMPACT OF TRANSLATION ON
TOURISM INSURANCE ACCESSIBILITY. Insurance Market of Uzbekistan, 1(11), 36–38. https://doi.org/10.55439/
INS/vol1_iss11/219
Abdullaev Munis Kurbonovich, & Kungratov Ilmurod Kuzibay ugli. (2025). THE IMPORTANCE OF DATA SCIENCE IN
THE DIGITAL TRANSFORMATION OF THE UZBEKISTAN ECONOMY: EMPIRICAL ANALYSIS AND SCIENTIFIC
APPROACHES. Economics and Innovative Technologies, 13(1), 83–90. https://doi.org/10.55439/EIT/vol13_iss1/645
Kungratov, I. (2024). DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE IN UZBEKISTAN:
CHALLENGES, INNOVATIONS, AND FUTURE TRENDS. DTAI – 2024, 1(DTAI). Retrieved from https://dtai.tsue.uz/
index.php/DTAI2024/article/view/314
Шохрух Бобокулов, & Ильмурод Кунгратов. (2025). Бизнес-анализ и оптимизация механизма коммерциализации
научно-инновационных разработок организации. Muhandislik Va Iqtisodiyot, 3(1), 7–12. https://doi.org/10.5281/
zenodo.14837564
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 YASHIL IQTISODIYOT VA TARAQQIYOT
This work is licensed under a Creative Commons Attribution 4.0 International License.