This thesis project studied the demand planning process of Cargill Global Edible Oil Solutions (GEOS) in the EMEA region and had the objective of developing a demand forecast model for the Retail Food Services customers to improve their satisfaction levels. The scope of this covered the commercial and contractual relationships, for the delivery of the bottle oil ready for distribution at the retail market; the procurement and production processes, as well as the Sales and Operation Planning (S&OP) process in detail. For the S&OP, Cargill relies on the Make to Forecast (MTF) production strategy, which has two main mechanisms for demand management and production planning. The first one is the use of a demand forecast and the second is the management of safety stocks. The demand forecast helps to guide the production planning to meet the upcoming weekly demand until it becomes available 7 days before the delivery time. While the safety stocks help to compensate for forecast errors and deviations, as well as for production setbacks that may occur. Unfortunately, for Cargill GEOS the automatic demand forecast has an accuracy of 42%, and the safety stock levels rose considerably and were managed on a constant level all year round to compensate. This impeded Cargill to meet the customer demand on time and in full according to the contracted service levels. The main challenges in this situation were the limited data availability and the demand data fragmentation due to changes in the product specifications. Which required the development of specific procedures and frameworks to align the fragmented data and to obtain a weekly demand forecast. For the development of the forecast model, 3 statistical seasonal forecasting models were considered to maintain the transparency of the process, the ARIMA model, the ETS exponential smoothing, and the STL+ETS. Due to the limited data availability, the chosen model was the STL+ETS model as this was the one that was able to replicate the observed demand, with an average weighted accuracy of 76%. The insights obtained from the seasonal forecast allowed to improve the safety stocks management, from a fixed level all year round to a seasonal management according to the expected demand and its variability throughout the year. The solutions developed in this thesis project were not limited to the demand forecast development but they aimed to improve the demand management process in different aspects. Which will allow Cargill GEOS to improve considerably their service levels without considerable additional costs, such as the increase of the production or warehouse capacity.

Policy reforms in response to the crisis were initially expected to dampen future house price increases. Instead, the Dutch owner-occupied housing market has overheated not even five years after its recovery. As this could indicate a structural change in the housing demand of households, models were estimated using logistic regression analysis to examine how household mobility has changed following the crisis and position these changes in the context of macroeconomic and institutional developments. Based on the macroeconomic developments, the demand for owner-occupancy was expected to increase after the crisis. For one, the economy was gaining momentum rather than losing it, offering much better prospects for the near future. In addition, house prices were still relatively low and credit cheaper than ever, which greatly increased the accessibility of the owner-occupied sector for lower income households and offered interesting investment opportunities. Regarding institutional developments, the various reforms following the crisis are believed to cause an increase in the demand for affordable owner-occupied housing as a result of the tightened lending criteria in combination with the restricted accessibility of the social rental sector. In addition, the reforms are also expected to polarise households by widening the gap between the rental and owner-occupied sector through equity requirements. The results of the empirical analyses reveal a significant quantitative increase in demand with the intention to move nearly doubling from 21% in 2002 to 39% in 2015. The preference for homeownership itself, on the other hand, remained relatively stable. The most surprising development over time is the convergence of households from different income categories with respect to the intention to move, the preferred tenure, and desired purchase price. It is therefore believed that favourable macroeconomic conditions shortly after the crisis temporarily ameliorated the negative effects of the institutional changes. Further research is necessary to confirm whether the surge in the intention to move is merely a temporary effect of the crisis or an indication of a growing mismatch between housing demand and supply.

Fall prevention programs hold great promise to improve quality of life among older adults and to decrease healthcare expenditures. However, there are substantial barriers for entrepreneurs working in the elderly care to set up fall prevention programs, due to the size of the investments required, the uncertainty of the parties about the potential benefits from the reduction in healthcare expenditures and the divergence of interests within our fragmented healthcare system. Hence, a method to assess the effect of fall prevention programs is needed, and, if these programs indeed appear to have a positive effect on the healthcare costs, there might be possibilities to use an innovative financing structure, such as a Health Impact Bond (HIB), to encourage the implementation. A HIB is a performance-based instrument by which the financial risk shifts from local implementers to investors. During this research, a python tool was developed to determine the effect of fall prevention programs using hospital data. By doing a case study in Dordrecht, the economic feasibility of a HIB for fall prevention programs was assessed. A Difference-in-Differences design was used to determine the effect of the fall prevention programs on both the number of injurious fall incidents and healthcare costs. Other barriers for setting up these programs using a HIB regarding governance and law were identified.

Driven by a quest for efficiency, many Western countries have witnessed merger waves across the entire breadth of their public sectors. The underlying assumption is that economies of scale exist in public service delivery; the idea that the average cost of public services decreases as the size of public organizations increases. The analysis of economies of scale in public service delivery and the related quest for the optimal size of public organizations has attracted a great deal of attention from researchers across disciplines. Nonetheless, despite its size, the literature on economies of scale in public service delivery has been characterized as inconclusive and inconsistent in many areas. As a result, it has proven difficult for researchers to provide policy makers and public managers with consistent recommendations regarding the optimal scale of public organizations and, more generally, the extent to which public services can expect to benefit from economies of scale. The analysis of economies of scale is subject to several methodological challenges. This dissertation focuses on one specific methodological concern: it departs from the observation that a troublesome factor in the analysis of economies of scale is the conceptual complexity of ’scale’. In essence, complexity here refers to the notion that there is more to the scale of public service delivery than simply the administrative size of the organizations that deliver those services. Typically, economies of scale are investigated by comparing the (average) cost of homogeneous organizations - such as hospitals, local governments or schools - to measures of size, in which the administrative, overall organization is the unit under investigation. However, large organizations may be organised into many smaller units and vice versa, or some services such as ICT may be subject to more economies of scale than others. @en