Browsing by Subject "supply chain"
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(2020)Sales forecasting is crucial for run any retail business efficiently. Profits are maximized if popular products are available to fulfill the demand. It is also important to minimize the loss caused by unsold stock. Fashion retailers face certain challenges which make sales forecasting difficult for the products. Some of these challenges are the short life cycle of products and introduction of new products all around the year. The goal of this thesis is to study forecasting methods for fashion. We use the product attributes for products in a season to build a model that can forecast sales for all the products in the next season. Sales for different attributes are analysed for three years. Sales for different variables vary for values which indicate that a model fitted on product attributes may be used for forecasting sales. A series of experiments are conducted with multiple variants of the datasets. We implemented multiple machine learning models and compared them against each other. Empirical results are reported along with the baseline comparisons to answer research questions. Results from first experiment indicate that machine learning models are almost doing as good as the baseline model that uses mean values as predictions. The results may improve in the upcoming years when more data is available for training. The second experiment shows that models built for specific product groups are better than the generic models that are used to predict sales for all kinds of products. Since we observed a heavy tail in the data, a third experiment was conducted to use logarithmic sales for predictions, and the results do not improve much as compared to results from previous methods. The conclusion of the thesis is that machine learning methods can be used for attribute-based sales forecasting in fashion industry but more data is needed, and modeling specific groups of products bring better results.
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(2022)Achieving goals set for sustainable development and a prosperous life for future generations requires a collective effort, including from people on a private level, national governments, and private organizations alike. Sustainable development is often divided into three pillars, the environmental, economic and social pillars. One sector at the center of this is the agri-food sector, where social sustainability appears to be receiving little attention along its value chains. Oats, a staple product for Finland and Sweden, are considered a sustainable product from environmental and health perspectives, as well as potentially from an economic standpoint, but again social sustainability in the oats value chains is missing from the discussion. This thesis sets out to assess to which extent the social dimension of sustainability is addressed in these oats value chains. Using a mixed methods approach, the thesis explores the different measures used for assessing aspects of social sustainability. Measuring progress in sustainable development is often done through the use of indicators, which many of them are derived from the UN Sustainable Development Goals. Indicators are meant to reveal areas where progress has not been made and policy should be targeted for development. Large organizations are reporting their contributions in annually published sustainability reports. For this, sustainability aspects need to be measurable, which requires converting real-life phenomena into measurable indicators, often quantifiable numbers. This is especially difficult for some social aspects. There is a risk policymaking loses its focus of pursuing development beyond the indicators, but instead is only trying to answer to the indicators. The thesis is applying a qualitative mixed methods approach. First, published sustainability reports are assessed, followed by indepth, semi-structured expert interviews. The research material consists of two published sustainability reports, an unpublished sustainability report comparison document, as well as 11 interviews. The data was gathered in March, April and May 2022. The interviews were analyzed using a qualitative content analysis and divided into themes for analysis. From an objective general standpoint, the oats value chain stakeholders valued all three dimensions of sustainability equally, but through the use of examples of activities the same did not translate into the organizations’ daily activities. Actions and programs were more focused on environmental and economic aspects, and the absence of social sustainability examples in initial responses proposes a slight disregard toward the social dimension. Still, organizations introduced a variety of methods in place for assessing social issues, especially internally. Organizations in the oats value chain are looking to make an impact for a more sustainable future, but measuring performance presents challenges, especially on the social side. Categorizing aspects of social sustainability under different dimensions of sustainability is complicated.
Now showing items 1-2 of 2