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DETERMINATION OF THE STRESS INDUCED DAMAGE INITIATION THRESHOLDS FOR SOME SELECTED ROCK TYPES
(Nazarbayev University School of Mining and Geosciences, 2024-04) Akhmedya, Madyar
Underground mining operations result in a shift of the initial stress field, leading to the formation of large stress concentrations and relaxation resulting in rock failures. The current failure criteria are insufficient in completely describing the damage caused by stress in excavations, making it difficult to evaluate excavation performance and avoid accidents. The parameter s in the Hoek-Brown failure criterion indicates the cohesive strength of the rock. Typically, its value is entirely determined by the quality of the rock mass at a large scale in the field. In the modified failure criterion known as the brittle Hoek-Brown damage initiation criterion, the parameter s is equal to 0.11. Recent findings indicate that the Hoek-Brown parameter, s, varies across different types of hard, strong, brittle, moderate to massive rock masses, and is influenced by the specific rock composition. This thesis highlights the need to revise the existing relationships by determining the brittle Hoek-Brown parameter s for certain chosen rock types in Kazakhstan.
The primary goal of the thesis is to determine the stress damage thresholds for eventual estimation of the Hoek-Brown brittle material parameter s for different rock types utilizing uniaxial compression tests (UCS) instrumented with acoustic emission (AE) sensors. The damage initiation stress threshold is the stress level at which cracks begin to occur in a rock under compressive load. For silica-rich rock types, this threshold is shown to be more than 0.8, however according to Martin (1999) it is indicated to be 0.33 for all rock types. The data obtained further demonstrate that the brittle Hoek-Brown parameter s is not the same for all rock types and depends on the genesis of the rock type and mineralogical composition. The analysis also included the impact of grain size and mineralogical composition on the unconfined compressive strength (UCS) and the thresholds for damage initiation. The results indicated that the thresholds for damaging stress and uniaxial compressive strength drop as the grain size increases. Furthermore, more experiments need to be done in order to verify and enhance the database used to determine s values for different kinds of rocks.
MARKET RESEARCH ON BACHELOR OF BUSINESS ADMINISTRATION DUAL DEGREE LAUNCH AT NAZARBAYEV UNIVERSITY GRADUATE SCHOOL OF BUSINESS
(Nazarbayev University Graduate School of Business, 2024-12) Temirkhanova, Aruzhan; Sybanbayeva, Aruzhan; Tilesheva, Ainur; Flores, Wendoly B.
The research was conducted to analyze the demand for the Bachelor of Business Administration dual degree at Nazarbayev University Graduate School of Business (NUGSB) in partnership with the Hong Kong University of Science and Technology. It aimed to identify the target market, understand the program demand, and develop possible marketing solutions to enhance its communication with customers.
Key findings included the university's choice and decision-making process and the program’s appeal. However, the affordability and novelty of the program were seen as the main challenges. The recommendations included digital marketing enhancement, the establishment of partnerships with companies and counselors, and higher student engagement.
Ultimately, the target market (high-achieving students from financially sustainable families in Astana, Almaty, Shymkent, and Aktau) and the level of demand (low with the potential to increase) were defined.
DIVIDEND POLICY AND STOCK PRICE PERFORMANCE: EVIDENCE FROM THE KAZAKHSTAN STOCK EXCHANGE
(Nazarbayev University Graduate School of Business, 2024-12-12) Shynatay, Zhassulan
Theoretically, the publication of dividends does not have any impact on the
financial position of the company, since capitalization and resources remain
unchanged. Nevertheless, world practice shows that the market reacts to stock
publications about the payment of dividends. This study performed an analysis of
the impact of the publication of payments and the payment of dividends by
Kazakhstani companies on the KASE and LSE trading exchanges. The study found
that for financial companies an announcement of dividend increase positively
impacts the stock prices and investors experience positive abnormal returns.
However, for non-financial companies increase in the amount of dividends lead to
negative abnormal returns which means drop in the price of stocks. Overall the
market reacts negatively to the announcement of dividends.
INCORPORATING GOOGLE TRENDS AS BIG DATA FOR ENHANCED INFLATION FORECASTING: EVIDENCE FROM KAZAKHSTAN
(Nazarbayev University Graduate School of Business, 2024-12-11) Beisenbek, Rakhat
Accurate inflation forecasting is essential for policymakers and businesses, allowing for informed decision-making and economic stability. Most historical forecasting methods are based on a few key macroeconomic factors while leaving a wide variety of more detailed data from the big data sources unused. This paper aims to analyze the performance of using Google Trends data on improving the inflation forecast of Kazakhstan and compare the result with the traditional macroeconomic models.
The research develops two primary models: a baseline model that includes conventional macroeconomic indicators such as GDP growth, oil prices, NEER, and inflation expectations, and an enhanced model that integrates Google Trends data for key terms like "inflation," "GDP," and "exchange rate." These data are preprocessed with standardization, lagging, and percentage change transformations. Machine learning techniques, specifically random forest and gradient boosting regressors, are applied to evaluate model performance. Statistical validation includes Likelihood Ratio tests for out-of-sample density forecast accuracy, as well as the Mean Squared Error (MSE), Mean Absolute Error (MAE) evaluation metrics calculation, Mincer-Zarnowitz regression for bias, and the Diebold-Mariano test for forecasting accuracy.
Findings show that incorporating the set of variables of Google trends improves the forecasting accuracy of the enhanced model by making relatively small MSE and MAE compared to the baseline. The Likelihood Ratio test supports the improvement of the models for density forecasting, and in terms of feature importance, Google Trends data turn out to be critical for the enhanced model. While the result of the Diebold-Mariano test turned out to show the marginal significance, extending the dataset period and applying advanced techniques further maintained the robustness of the enhanced model.
This research proves that Google Trends as a big data contributes to enhancing the accuracy of the inflation forecasts for developing economies.Although sentiment analysis was initially considered, it was excluded from the study due to data limitations in Google news and the absence of an access tokens for media sources like Facebook.
TOTAL FACTOR PRODUCTIVITY IN KAZAKHSTAN'S SMALL AND MEDIUM ENTERPRISES (SME) SECTOR
(Nazarbayev University Graduate School of Business, 2024-12) Nuraliyeva, Mizhgona
This study investigates the key drivers of Total Factor Productivity (TFP) in small and medium enterprises (SMEs) in Kazakhstan, focusing on a combination of firm-level data (2011–2023) and advanced econometric methods. TFP, which is a measure of efficiency and innovation, is analyzed using Olley-Pakes (OP), Levinsohn-Petrin (LP), Ackerberg-Caves-Frazer (ACF), and kernel-based learning techniques (KLT) in this paper.
Exchange rate shocks serve as instrumental variables to address endogeneity concerns and explore the impact of materials, capital wage bill, energy costs, firm size, and other inputs on productivity. The results reveal that firm size and wage bills positively influence TFP under specific conditions, whereas inappropriate use of energy and capital can have negative influence on productivity.
The use of each method helps to analyze the estimation approaches properly, providing a clear understanding of TFP dynamics. To be able to proceed with practical policy recommendations, counterfactual simulations of wage bill reductions were created.
This research contributes to the existing literature by focusing on advanced methodologies to estimate TFP and providing practical policy recommendations to enhance SME productivity in Kazakhstan.