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A business strategy proposal for the Manufaktura brand with zero waste philosophy
Ročková, Veronika ; Koudelková, Petra (advisor) ; Rosenfeldová, Jana (referee)
The bachelor's thesis "A business strategy proposal for the Manufaktura brand with zero waste philosophy" deals with an analysis of the problem of waste material from the field of the cosmetics industry and offers one of the many possible solutions to this problem for the Czech cosmetics company Manufaktura. In the theoretical part of the thesis, the basic terms connected to the zero-waste lifestyle are explained, the Manufaktura brand is presented, as are its values and history and examples of functioning alternatives on the field of sustainable caring cosmetics are shown. The theoretical part of the thesis also explains the importance of a sales and a marketing strategy and of strategy planning overall. The practical part of the thesis brings forth a draft of a business strategy aimed at implementing a draught cosmetics programme for several caring cosmetics products. Based on the findings from the performed qualitative marketing research, it brings forth a suitable approach for implementing this type of a sales practice and also brings solutions to the arisen pitfalls connected to it.
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Nonnegative time series
Ročková, Veronika ; Anděl, Jiří (advisor) ; Štěpán, Josef (referee)
Models for non-negative time series nd their usefulness in many diverse areas of applications (hydrology, medicine, nance). The non-negative nature of the observations has been utilized for deriving estimators with superior asymptotic properties. For the purposes of estimation, it is necessary to recognize the situations when the estimated model indeed de nes a non-negative time series. Such non-negativity conditions can then be used as a basis for constrained optimization. The main thrust of this work is to review the non-negativity conditions currently available for ARMA models and, more importantly, to generalize the existing results for some models for which the explicit result was missing. We center our discussion mainly on univariate models. However, we note that the pursued ideas are directly applicable also for multivariate time series. This observation enables determination of some readily obtainable conditions for lower order vector valued Autoregressive Moving Average models.
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Nonnegative time series
Ročková, Veronika ; Anděl, Jiří (advisor) ; Štěpán, Josef (referee)
Models for non-negative time series nd their usefulness in many diverse areas of applications (hydrology, medicine, nance). The non-negative nature of the observations has been utilized for deriving estimators with superior asymptotic properties. For the purposes of estimation, it is necessary to recognize the situations when the estimated model indeed de nes a non-negative time series. Such non-negativity conditions can then be used as a basis for constrained optimization. The main thrust of this work is to review the non-negativity conditions currently available for ARMA models and, more importantly, to generalize the existing results for some models for which the explicit result was missing. We center our discussion mainly on univariate models. However, we note that the pursued ideas are directly applicable also for multivariate time series. This observation enables determination of some readily obtainable conditions for lower order vector valued Autoregressive Moving Average models.
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