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Improving product development is a complex task for many companies. One challenge is to avoid over-engineering and only include the functionality that customers are willing to pay for. Another challenge is to reduce costs in close co-operation with suppliers. This is a complex task because suppliers often have their own goals and are rarely located at the same physical place. Handling these two challenges is the domain of target costing. Emerging first from Japanese companies such as Toyota, Nissan and Olympus, target costing has become a critical element in achieving long-term profitability. Previous research on target costing has been paradoxical because even though it deals with product development, it has not incorporated the complexity of the product development process. More specifically, current models of target costing assume that the product development process can largely be planned and controlled by a single company. For complex multi-technology products, such as airplanes and industrial robots, this is far from true. By drawing on product development theories, and conducting an in-depth case study at ABB Robotics, this thesis explores target costing in the development of complex multi-technology products. The result is a framework that identifies challenges and problems in target costing processes, but also shows that target costing relies on both planning and improvisation to cope with tensions and contradictions in close customer and supplier relationships. / Diss. Stockholm : Handelshögskolan i Stockholm, 2011

Problems in the public policy decision-making environments are typically complex and continuously evolve. In a resource-constrained environment, several alternatives, criteria, and conflicting objectives must be considered. As a result, solutions to these types of problems cannot be modelled solely using single-criteria techniques. It has been observed that most techniques used to shape energy policy and planning either produce sub-optimal solutions or use strong assumptions about the preferences of decision-maker(s). This difficulty creates a compelling need to develop novel techniques that can handle several alternatives, multiple criteria and conflicting objectives to support public sector decision-making processes. First, the study presents a novel scenario-based multi-objective optimisation framework based on the augmented Chebychev goal programming (GP) technique linked to a value function for analysing a decision environment underlying energy choice among low-income households in isolated rural areas and informal urban settlements in South Africa. The framework developed includes a multi-objective optimisation technique that produced an approximation of a Pareto front linked to an a priori aggregation function and a value function to select the best alternatives. Second, the study used this model to demonstrate the benefits of applying the framework to a previously unknown subject in public policy: a dynamic multi-technology decision problem under uncertainty involving multiple stakeholders and conflicting objectives. The results obtained suggest that while it is cost-optimal to pursue electrification in conjunction with other short-term augmentation solutions to meet South Africa's universal electrification target, sustainable energy access rates among low-income households can be achieved by increasing the share of clean energy generation technologies in the energy mix. This study, therefore, challenges the South African government's position on pro-poor energy policies and an emphasis on grid-based electrification to increase energy access. Instead, the study calls for a portfolio-based intervention. The study advances interventions based on micro-grid electrification made up of solar photovoltaics (PV), solar with storage, combined cycle gas turbine (CCGT) and wind technologies combined with either bioethanol fuel or liquid petroleum gas (LPG). The study has demonstrated that the framework developed can benefit public sector decision-makers in providing a balanced regime of technical, financial, social, environmental, public health, political and economic aspects in the decision-making process for planning energy supply interventions for low-income households. The framework can be adapted to a wide range of energy access combinatorial problems and in countries grappling with similar energy access challenges.