Context: The amount of software in solutions provided in various domains is continuously growing. These solutions are a mix of hardware and software solutions, often referred to as software-intensive systems. Companies seek alternatives to improve the software development process to avoid delays or cost overruns related to software development. Component origins such as in-house, outsourcing, Components OffThe-Shelf (COTS) or Open Source Software (OSS) are gaining popularity, therefore, leading to the decision to choose among component origins. Objective: The overall goal of this thesis is to support decisionmaking for selecting component origins. Following a decision-making process including all the key decision-making activities is crucial in making decisions. Therefore, the objective of the thesis is to support the decision-makers to create a decision-making process based on their context. In addition, the objective is to improve the decision-making process by incorporating research results and decision-makers’ opinion and knowledge in practice. Method: We identified the factors that influence the choice to select among different component origins through a systematic literature review using an Snowballing (SB) strategy and a Database (DB) search. We extended the investigation and conducted a case survey of 22 cases. Using design science, we developed solutions including a process-line to support decision-makers, a Bayesian synthesis process to integrate the evidence from literature into practice and a Knowledge Translation (KT) framework to facilitate the implementation of research results in practice. Results: In-house development and alternative component origins (outsourcing, COTS, and OSS) are being used for software development. Several factors such as time, cost and license implications influence the selection of component origins. Solutions have been proposed to support the decision-making. However, these solutions consider only a subset of factors identified in the literature. According to the case survey, the solutions proposed in literature are not aligned with practice.Inpractice,thedecisionsaremostlybasedonopinions.Thedesign objective to support decision-makers with the decision-making process is identified. Therefore, we propose a process-line to address the designobjective.Inaddition,tomakethedecision-makingmoreinformediwe propose a KT framework incorporating Bayesian synthesis to help decision-makers make evidence-informed decisions. Conclusions: The decision to choose among component origins is case dependent. To support the decision-making process, the flexibility and customization of the solution based on the context are important. Therefore, the process-line proposed in the thesis is not prescriptive rather it is customizable to the context. In addition, to facilitate evidence-based decision-making, we provide an application of the KT framework that allows decision-makers to consider research results in addition to their own opinions and knowledge.