In Dutch higher education institutions, IT outsourcing (ITO) is becoming more common. New applications nowadays are executed from the ‘cloud’. But what to do with on premise applications? Can they also be outsourced? If so, what factors does a higher education institution have to consider when making the ITO decision of their on-premise applications? This research starts with finding the factors that are already known in existing ITO literature (in different contexts). Then, these decision factors are validated in four explorative interviews before surveying the factors within a higher education context. In total, fourteen factors are deemed to be important for Dutch higher education institutions. Based upon the survey responses by Dutch IT decision makers, a hierarchy exist in these fourteen factors. Also, this research suggest a relationship between outsourcing decision factors and the sourcing models. Additionally, outsourcing objectives seem to influence this relationship.
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This thesis studies the factors that influence physical distribution structure design. Distribution Structure Design (DSD) concerns the spatial layout of the distribution channel as well as the location(s) of logistics facilities. Despite the frequent treatment of DSD in supply chain handbooks, an empirically validated conceptual framework of factors is still lacking. This thesis studies DSD in multiple industry sectors (Fashion, Consumer Electronics, Online Retail) and proposes a conceptual framework.
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Spatial decisions on distribution channel layout involve the layout of the transport and storage system between production and consumption as well as the selection of distribution centre locations. Both are strategic company decisions to meet logistics challenges, i.e. delivering the right product at the right location on time. In this paper we study the main factors and sub factors that drive spatial decisions on distribution channel layout. The current literature has a strong focus on normative approach and lacks descriptive research into these factors. In the second part of the study, we investigated the importance of the factors. Best-Worst Method (BWM) has been used to calculate the factor weights. BWM provides consistent results and requires fewer comparisons than ‘matrix based’ methods. An online survey was used to collect the data. According to total sample of respondents, the most important factors are ‘Logistics costs’, ‘Service level’ and ‘Demand level’. Logistics costs being the most important factor is in line with Supply Chain Management literature. Logistics experts consider ‘Customer demand’ as the second most important factor, whereas decision makers consider ‘Service level’ the second most important factor. A limitation of the research is that the majority of respondents are from Europe and the USA. For future research we suggest to test how respondents from non-Western countries value the importance of several factors.
