MILLIY TURISTIK XIZMATLAR BOZORI SAMARADORLIGINI STOXASTIK CHEGARAVIY TAHLIL USULIDA BAHOLASH

MILLIY TURISTIK XIZMATLAR BOZORI SAMARADORLIGINI STOXASTIK CHEGARAVIY TAHLIL USULIDA BAHOLASH

Authors

  • Bekzot Janzakov “Ipak yo‘li” turizm va madaniy meros xalqaro universitet dotsenti, PhD.

DOI:

https://doi.org/10.54613/ku.v16i.1312

Keywords:

Stoxastik chegaraviy tahlil, kiruvchi o‘zgaruvchi, chiquvchi o‘zgaruvchi, turizm bozori, texnik samaradorlik.

Abstract

Ushbu maqolada O‘zbekiston Respublikasi milliy turizm bozori miqyosida kiruvchi o‘zgaruvchilar: xonalar soni, xizmat ko‘rsatuvchilar soni va turistik transport vositalari soni asosida turistik xizmatlar eksporti natijaviy o‘zgaruvchi sifatida 2016-yildan 2024-yilgacha bo‘lgan davrda texnik samaradorlik ko‘rsatkichlari stoxastik chegaraviy tahlil usuli asosida hisoblandi va shu asosda samaradorlikni oshirish bo‘yicha ilmiy tavsiyalar ishlab chiqildi. Ushbu maqolada O‘zbekiston turizm sanoatida texnik samaradorlikni baholash uchun stoxastik chegara tahlili (SCHT) metodologiyasi qo‘llanilgan. Kobb–Duglas turidagi ishlab chiqarish funksiyasi asosida 2016–2024 yillar kesimida turizm eksporti, xonalar soni, xizmat ko‘rsatuvchi korxonalar soni va transport imkoniyatlari o‘rtasidagi iqtisodiy bog‘liqlik empirik tahlil qilingan. Natijalar transport omilining statistik jihatdan ahamiyatli ta’sir ko‘rsatmasligini, binobarin, sektor samaradorligiga bevosita hissa qo‘shmasligini ko‘rsatdi. Model diagnostikasi samaradorliksiz komponentning yuqori ulushga egaligini tasdiqlab, ishlab chiqarish parametrlaridagi tafovutlarning deyarli to‘liq ichki samarasizlik omillari bilan izohlanishini aniqladi. Texnik samaradorlik indekslari pandemiya yillarida keskin pasayib, keyingi davrda tiklanish tendensiyasini namoyon etdi. Tadqiqot natijalari turizm infratuzilmasi rivoji, boshqaruv sifatini oshirish va resurslardan samarali foydalanish bo‘yicha siyosiy qarorlar qabul qilishda amaliy ahamiyatga ega.

Foydalanilgan adabiyotlar:

Debreu, G. (1983a). Mathematical economics: Twenty papers of Gerard Debreu. Cambridge University Press.

2. Koopmans, T. C. (1951). Activity analysis of production and allocation. Wiley.

3. Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253–290.

4. Macedo, P., Madaleno, M., & Moutinho, V. (2023). Stochastic frontier analysis with maximum entropy estimation. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 251–270). Springer.

5. Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50(6), 1393–1414

6. Chambers, R. G., Chung, Y., & Färe, R. (1996). Benefit and distance functions. Journal of Economic Theory, 70(2), 407–419

7. Kapelko, M., Oude Lansink, A., & Stefanou, S. E. (2023). Multidirectional dynamic inefficiency analysis: An extension to include corporate social responsibility. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 113–130). Springer.

8. Jradi, S., & Ruggiero, J. (2023). Stochastic MQT. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 131–142). Springer.

9. Aigner, D., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37.

10. Amsler, C., Chen, Y. Y., Schmidt, P., & Wang, H. J. (2023). A hierarchical panel data model for the estimation of stochastic metafrontiers: Computational issues and an empirical application. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 183–196). Springer.

11. Parmeter, C. F., & Kumbhakar, S. C. (2023). Recent advances in the construction of nonparametric stochastic frontier models. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 165–182). Springer.

12. Stead, A. D., Wheat, P., & Greene, W. H. (2023). Robustness in stochastic frontier analysis. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 197–228). Springer.

13. Macedo, P., Madaleno, M., & Moutinho, V. (2023). Stochastic frontier analysis with maximum entropy estimation. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Advanced mathematical methods for economic efficiency analysis: Theory and empirical applications (pp. 251–270). Springer.

14. Bosetti, V., Cassinelli, M., & Lanza, A. (2007). Benchmarking in tourism destinations; Keeping in mind the sustainable paradigm. In Á. Matias, P. Nijkamp, & P. Neto (Eds.), Advances in modern tourism research: Economic perspectives (pp. 165–179). Springer

15. Mirzaev, K., & Janzakov, B. (2020). The determinants of international tourism (in the example of CIS countries). European Journal of Molecular & Clinical Medicine, 7(2), 2020.

16. Djanzakovich, M. (2022). Ogli JBK The analysis of impact of factors influencing leadership abilities. 湖南大学学报 (自然科学版), 49(09).

17. Mirzaev, K. (2011). Approaches and issues for developing livestock services in Uzbekistan. Perspectives of Innovations, Economics and Business, PIEB, 8(2), 23-25.

18. Safarov, B., Mirzaev, K., Janzakov, B., & Ruzibayev, O. (2022). A Study on the Impact of Distance and Income on Potential Gastrotourists’ Decision-Making Process. African Journal of Hospitality, Tourism and Leisure, 11(6), 2052-2062.

Published

2025-11-10

Iqtiboslik olish

Janzakov, B. (2025). MILLIY TURISTIK XIZMATLAR BOZORI SAMARADORLIGINI STOXASTIK CHEGARAVIY TAHLIL USULIDA BAHOLASH. QO‘QON UNIVERSITETI XABARNOMASI, 16, 92–96. https://doi.org/10.54613/ku.v16i.1312
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