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modeling. The aim of the thesis is to identify and quantify the mechanisms through which the characteristics of the sound environment—in particular the tempo, frequency, tonality, and intensity of music
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of corporate responsibility and performance and their empirical application in modeling the relationships between constructs based on data from a sample of companies. The expected output will be a model
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and regression and/or choice models to identify the determinants of private label acceptance and their relationship to sustainable consumption and waste. The output of the work will be a model of the
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‑ making in the beer market to support effective strategic management of a brewery. It starts from the premise that traditional economic models of consumer behaviour do not sufficiently capture real decision
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groups of households, and policy settings must respond to the different needs of households. We will use econometric modelling, timeseries econometric analysis, and microeconomic analysis to compute
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, and machine learning methods. Using regression analysis and vector autoregression (VAR) models, the study examines the relationship between macroeconomic variables and the performance of various
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of an adaptive audio stimulation model that will enable personalized setting of stimulation protocols. The results of the work will be applicable in the development of intelligent mental ergonomics systems
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supply chain restructuring as geopolitical volatility, trade disruptions and regulatory uncertainty challenge long established globalised production models. This dissertation investigates how
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industry of large breweries. Attention will be paid to comparing the strategic models of small and large breweries, with large concerns primarily using large production scale, investment power and stability
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is therefore essential for stringent comparisons between experimental data and modern theoretical approaches, including beyond-mean-field and shell-model calculations. To address these questions, a