The paper presents a new model for integration of circular economy strategies into the municipal solid waste management. The goals are to reduce the waste produced, recycle at the highest rate as possible (material recovery) and to use the resultant residual waste for energy recovery. Such a strategy utilizes both pricing and advertising principles in the mixed integer linear programming model while accounting two criterions-assessment of greenhouse gas (GHG) and cost minimization. The aim is to design the optimal waste management grid to suggest a sustainable economy with environmental concerns. The government, municipalities and/or authorized packaging company decide about the investments to the propagation of waste prevention and to advertising of waste recycling, while investors decide about new facility location and technological parameter. The availability of waste is projected in pricing method as well as in the location of the facility. The mathematical model will consider randomness in the form of waste production. The suggested non-linear functions of pricing and advertising are replaced by piecewise linear approximation to reduce computational complexity. The proposed multi-objective model is applied in a case study for the Czech Republic in the area of waste treatment infrastructure planning to support decision-making at the micro-regional level. The integration of circular economy principles, considering also the total amount of produced GHG, revealed the existing potential in waste prevention. On the other hand, the increase of recycling is limited, landfills are not supported and the energy recovery is preferred. However, the planning of the complex system relies on the decision-maker.
This paper presents the results of the research focused on the analysis of firm´s ability to forecast the behavior of external environment and its influence on firm's budgeting processes and its dependence on GDP fluctuations. The objective of the research was to verify whether the ability of firms to predict changes in business environment are influenced by the fluctuations of GDP. The authors have expected, that in case of higher fluctuations of GDP, the ability to predict changes in business environment will be lower. The authors have used the data obtained by means of questionnaire survey conducted in Czech Republic on the sample of 177 enterprises and other data obtained by the study performed in the USA and Canada. The study also presents empirical evidence on the capability of Czech enterprises to predict the behavior of primary budgetary elements, such as profits or sales volumes. The study shows the relatively high level of predictability of business environment changes indicated by Czech firms in comparison with the U.S. and Canadian companies, on the other hand, the study has not shown any significant dependence between GDP fluctuations and predictability level of the budgeting process.
Among the current trends in waste management and circular economy is the involvement of new fractions of waste for sorting and collection. One of them is fats and cooking oils, especially those coming from households. Now, the nascent fat waste recycling becomes promoted as regulations and waste recovery targets have been set in the European Union. The traditional manner of discarding household fat waste usually causes sewage problems. However, utilisation of this waste brings the potential for contributing to the energy supply and material recovery. This research presents a mathematical model for the optimal location of fat waste bins and containers in the given municipalities. The container network should comprise as few containers as possible, while the walking distance for the citizens towards the container is as short as possible. The objective of the proposed optimisation model is to minimise the total number of collection points (infrastructure cost). The collection points represent the citizens' addresses in a municipality. The average walking distance towards a container is a novel feature in the model, which is pertinent to waste fractions with low production per person. Cluster analysis describes the variability between municipalities, and further, it is possible to use regression analysis to model the number of containers for any municipality or region. The proposed general decision support tool estimates the total cost and number of bins needed for any region or a country. The region from the Czech Republic, which was used as a study area, revealed the requirement for 609 containers, with only EUR 30,000 of investment cost. There are around 950 inhabitants assigned to a single collection point on average.
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