Multiple scales analysis of nonlinear oscillations of a portal frame foundation for several machines

An analytical study of the nonlinear vibrations of a multiple machines portal frame foundation is presented. Two unbalanced rotating machines are considered, none of them resonant with the lower natural frequencies of the supporting structure. Their combined frequencies is set in such a way as to excite, due to nonlinear behavior of the frame, either the first anti-symmetrical mode (sway) or the first symmetrical mode. The physical and geometrical characteristics of the frame are chosen to tune the natural frequencies of these two modes into a 1:2 internal resonance. The problem is reduced to a two degrees of freedom model and its nonlinear equations of motions are derived via a Lagrangian approach. Asymptotic perturbation solutions of these equations are obtained via the Multiple Scales Method.

Machine vision methods for process measurements in pulping

The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

Roles of leadership in complex environments : Enhancing Knowledge Flows in Organisational Constellations through Practice-Based Innovation Processes

Global challenges, complexity and continuous uncertainty demand development of leadership approaches, employees and multi-organisation constellations. Current leadership theories do not sufficiently address the needs of complex business environments. First of all, before successful leadership models can be applied in practice, leadership needs to shift from the industrial age to the knowledge era. Many leadership models still view leadership solely through the perspective of linear process thinking. In addition, there is not enough knowledge or experience in applying these newer models in practice. Leadership theories continue to be based on the assumption that leaders possess or have access to all the relevant knowledge and capabilities to decide future directions without external advice. In many companies, however, the workforce consists of skilled professionals whose work and related interfaces are so challenging that the leaders cannot grasp all the linked viewpoints and cross-impacts alone. One of the main objectives of this study is to understand how to support participants in organisations and their stakeholders to, through practice-based innovation processes, confront various environments. Another aim is to find effective ways of recognising and reacting to diverse contexts, so companies and other stakeholders are better able to link to knowledge flows and shared value creation processes in advancing joint value to their customers. The main research question of this dissertation is, then, to seek understanding of how to enhance leadership in complex environments. The dissertation can, on the whole, be characterised as a qualitative multiple-case study. The research questions and objectives were investigated through six studies published in international scientific journals. The main methods applied were interviews, action research and a survey. The empirical focus was on Finnish companies, and the research questions were examined in various organisations at the top levels (leaders and managers) and bottom levels (employees) in the context of collaboration between organisations and cooperation between case companies and their client organisations. However, the emphasis of the analysis is the internal and external aspects of organisations, which are conducted in practice-based innovation processes. The results of this study suggest that the Cynefin framework, complexity leadership theory and transformational leadership represent theoretical models applicable to developing leadership through practice-based innovation. In and of themselves, they all support confronting contemporary challenges, but an implementable method for organisations may be constructed by assimilating them into practice-based innovation processes. Recognition of diverse environments, their various contexts and roles in the activities and collaboration of organisations and their interest groups is ever-more important to achieving better interaction in which a strategic or formal status may be bypassed. In innovation processes, it is not necessarily the leader who is in possession of the essential knowledge; thus, it is the role of leadership to offer methods and arenas where different actors may generate advances. Enabling and supporting continuous interaction and integrated knowledge flows is of crucial importance, to achieve emergence of innovations in the activities of organisations and various forms of collaboration. The main contribution of this dissertation relates to applying these new conceptual models in practice. Empirical evidence on the relevance of different leadership roles in practice-based innovation processes in Finnish companies is another valuable contribution. Finally, the dissertation sheds light on the significance of combining complexity science with leadership and innovation theories in research.

Validation and Selection of Transportation Cost Drivers with Advanced Methods

In today's logistics environment, there is a tremendous need for accurate cost information and cost allocation. Companies searching for the proper solution often come across with activity-based costing (ABC) or one of its variations which utilizes cost drivers to allocate the costs of activities to cost objects. In order to allocate the costs accurately and reliably, the selection of appropriate cost drivers is essential in order to get the benefits of the costing system. The purpose of this study is to validate the transportation cost drivers of a Finnish wholesaler company and ultimately select the best possible driver alternatives for the company. The use of cost driver combinations as an alternative is also studied. The study is conducted as a part of case company's applied ABC-project using the statistical research as the main research method supported by a theoretical, literature based method. The main research tools featured in the study include simple and multiple regression analyses, which together with the literature and observations based practicality analysis forms the basis for the advanced methods. The results suggest that the most appropriate cost driver alternatives are the delivery drops and internal delivery weight. The possibility of using cost driver combinations is not suggested as their use doesn't provide substantially better results while increasing the measurement costs, complexity and load of use at the same time. The use of internal freight cost drivers is also questionable as the results indicate weakening trend in the cost allocation capabilities towards the end of the period. Therefore more research towards internal freight cost drivers should be conducted before taking them in use.

A Model-Based Development and Verification Framework for Distributed System-on-Chip Architecture

The capabilities and thus, design complexity of VLSI-based embedded systems have increased tremendously in recent years, riding the wave of Moore’s law. The time-to-market requirements are also shrinking, imposing challenges to the designers, which in turn, seek to adopt new design methods to increase their productivity. As an answer to these new pressures, modern day systems have moved towards on-chip multiprocessing technologies. New architectures have emerged in on-chip multiprocessing in order to utilize the tremendous advances of fabrication technology. Platform-based design is a possible solution in addressing these challenges. The principle behind the approach is to separate the functionality of an application from the organization and communication architecture of hardware platform at several levels of abstraction. The existing design methodologies pertaining to platform-based design approach don’t provide full automation at every level of the design processes, and sometimes, the co-design of platform-based systems lead to sub-optimal systems. In addition, the design productivity gap in multiprocessor systems remain a key challenge due to existing design methodologies. This thesis addresses the aforementioned challenges and discusses the creation of a development framework for a platform-based system design, in the context of the SegBus platform - a distributed communication architecture. This research aims to provide automated procedures for platform design and application mapping. Structural verification support is also featured thus ensuring correct-by-design platforms. The solution is based on a model-based process. Both the platform and the application are modeled using the Unified Modeling Language. This thesis develops a Domain Specific Language to support platform modeling based on a corresponding UML profile. Object Constraint Language constraints are used to support structurally correct platform construction. An emulator is thus introduced to allow as much as possible accurate performance estimation of the solution, at high abstraction levels. VHDL code is automatically generated, in the form of “snippets” to be employed in the arbiter modules of the platform, as required by the application. The resulting framework is applied in building an actual design solution for an MP3 stereo audio decoder application.

Creating an open-books implementation framework for a maintenance-related value-based life-cycle model

This study is a qualitative action research by its nature with elements of personal design in the form of a tangible model implementation framework construction. Utilized empirical data has been gathered via two questionnaires in relation to the arranged four workshop events with twelve individual participants. Five of them represented maintenance customers, three maintenance service providers and four equipment providers respectively. Further, there are two main research objectives in proportion to the two complementary focusing areas of this thesis. Firstly, the value-based life-cycle model, which first version has already been developed prior to this thesis, requires updating in order to increase its real-life applicability as an inter-firm decision-making tool in industrial maintenance. This first research objective is fulfilled by improving appearance, intelligibility and usability of the above-mentioned model. In addition, certain new features are also added. The workshop participants from the collaborating companies were reasonably pleased with made changes, although further attention will be required in future on the model’s intelligibility in particular as main results, charts and values were all reckoned as slightly hard to understand. Moreover, upgraded model’s appearance and added new features satisfied them the most. Secondly and more importantly, the premises of the model’s possible inter-firm implementation process need to be considered. This second research objective is delivered in two consecutive steps. At first, a bipartite open-books supported implementation framework is created and its different characteristics discussed in theory. Afterwards, the prerequisites and the pitfalls of increasing inter-organizational information transparency are studied in empirical context. One of the main findings was that the organizations are not yet prepared for network-wide information disclosure as dyadic collaboration was favored instead. However, they would be willing to share information bilaterally at least. Another major result was that the present state of companies’ cost accounting systems will definitely need implementation-wise enhancing in future since accurate and sufficiently detailed maintenance data is not available. Further, it will also be crucial to create supporting and mutually agreed network infrastructure. There are hardly any collaborative models, methods or tools currently in usage. Lastly, the essential questions about mutual trust and predominant purchasing strategies are cooperation-wise important. If inter-organizational activities are expanded, a more relational approach should be favored in this regard. Mutual trust was also recognized as a significant cooperation factor, but it is hard to measure in reality.

Modular framework for outlier detection

Outlier detection is an important form of data analysis because outliers in several cases contain the interesting and important pieces of information. In the recent years, many different outlier detection algorithms have been devised for finding different kinds of outliers in varying contexts and environments. Some effort has been put to study how to effectively combine different outlier detection methods. The combination of outlier detection algorithms as an ensemble was studied in this thesis by designing a modular framework for outlier detection, which combines arbitrary outlier detection techniques. This work resulted in an example implementation of the framework. Outlier detection capability of the ensemble method was validated using datasets and methods found in outlier detection research. The framework achieved better results than the individual outlier algorithms. Future research includes how to handle large datasets effectively and the possibilities for real-time outlier monitoring.

The European Union and Assembling Biofuel Development – topological investigations concerning the associations between law, policy and space

Biofuels for transport are a renewable source of energy that were once heralded as a solution to multiple problems associated with poor urban air quality, the overproduction of agricultural commodities, the energy security of the European Union (EU) and climate change. It was only after the Union had implemented an incentivizing framework of legal and political instruments for the production, trade and consumption of biofuels that the problems of weakening food security, environmental degradation and increasing greenhouse gases through land-use changes began to unfold. In other words, the difference between political aims for why biofuels are promoted and their consequences has grown – which is also recognized by the EU policy-makers. Therefore, the global networks of producing, trading and consuming biofuels may face a complete restructure if the European Commission accomplishes its pursuit to sideline crop-based biofuels after 2020. My aim with this dissertation is not only to trace the manifold evolutions of the instruments used by the Union to govern biofuels but also to reveal how this evolution has influenced the dynamics of biofuel development. Therefore, I study the ways the EU’s legal and political instruments of steering biofuels are coconstitutive with the globalized spaces of biofuel development. My analytical strategy can be outlined through three concepts. I use the term ‘assemblage’ to approach the operations of the loose entity of actors and non-human elements that are the constituents of multi-scalar and -sectorial biofuel development. ‘Topology’ refers to the spatiality of this European biofuel assemblage and its parts whose evolving relations are treated as the active constituents of space, instead of simply being located in space. I apply the concept of ‘nomosphere’ to characterize the framework of policies, laws and other instruments that the EU applies and construes while attempting to govern biofuels. Even though both the materials and methods vary in the independent articles, these three concepts characterize my analytical strategy that allows me to study law, policy and space associated with each other. The results of my examinations underscore the importance of the instruments of governance of the EU constituting and stabilizing the spaces of producing and, on the other hand, how topological ruptures in biofuel development have enforced the need to reform policies. This analysis maps the vast scope of actors that are influenced by the mechanism of EU biofuel governance and, what is more, shows how they are actively engaging in the Union’s institutional policy formulation. By examining the consequences of fast biofuel development that are spatially dislocated from the established spaces of producing, trading and consuming biofuels such as indirect land use changes, I unfold the processes not tackled by the instruments of the EU. Indeed, it is these spatially dislocated processes that have pushed the Commission construing a new type of governing biofuels: transferring the instruments of climate change mitigation to land-use policies. Although efficient in mitigating these dislocated consequences, these instruments have also created peculiar ontological scaffolding for governing biofuels. According to this mode of governance, the spatiality of biofuel development appears to be already determined and the agency that could dampen the negative consequences originating from land-use practices is treated as irrelevant.

Multiple sclerosis and pregnancy: clinical and immunological aspects

Background: Multiple Sclerosis (MS) is an autoimmune disease of the central nervous system that affects most commonly young women in their childbearing age. Previous studies have shown that MS relapse rate usually reduces during pregnancy and increases again after delivery. Patients with MS and their treating physicians are interested to know more about the risks the disease can cause to pregnancy and how pregnancy affects the disease. The reasons for increased relapse rate after delivery are not entirely clear, but loss of pregnancy related immune tolerance and changes in the hormonal status at the time of delivery seem to be of relevance. Aims and methods: The aims of this study were to follow the natural course of MS during and after pregnancy, evaluate pregnancy related risks among MS patients, follow the inflammatory response of MS patients during and after pregnancy and clarify the risk of relevant co-morbidities known to affect other autoimmune diseases after pregnancy and compare these results to healthy controls. This study was a part of a prospective nation-wide follow-up study of 60 Finnish MS patients. All eligible MS patients were enrolled in the study during the years 2003-2005. A prospective followup continued from early pregnancy until six months postpartum. MS relapses, EDSS scores and obstetric details were recorded. Blood samples were obtained from the patients at early, middle, and late pregnancy, after delivery and one month, three months and six months postpartum. Results: MS patients were no more likely to experience pregnancy or delivery complications than the Finnish mothers in general. The need of instrumental assistance, however, was higher among mothers with MS. Disease activity followed the course seen in previous studies. The majority of mothers (90.2%) breastfed their babies. Contrary to previous results, breastfeeding did not protect MS patients from disease worsening after delivery in present study. Mothers with active pre-pregnancy disease chose to breastfeed less frequently and started medication instead. MS patients presented with higher prevalence of elevated thyroid autoantibodies postpartum than healthy controls, but the rate of thyroid hormonal dysfunction was similar as that of healthy controls. The mode of delivery nor the higher rate of tissue damage assessed with C-reactive protein concentration were not predictive of postpartum relapses. The prevalence of gestational diabetes was slightly higher among mothers with MS compared to Finnish mothers in general, but postpartum depression was observed in similar rates. MS patients presented with significantly lower serum concentrations of vitamin D during pregnancy and postpartum than healthy controls. Conclusions: Childbearing can be regarded as safe for mothers with MS as it is for healthy mothers in general. Breastfeeding can be recommended, but it should be done only after careful evaluation of the individual risk for postpartum disease activation. Considering MS patients tend to develop thyroid antibody positivity after delivery more often than healthy controls and that certain treatments can predispose MS patients to thyroid hormonal dysfunction, we recommend MS mothers to be screened for thyroid abnormalities during pregnancy and after delivery. Increased risk for gestational diabetes should be kept in mind when following MS mothers and glucose tolerance test in early pregnancy should be considered. Adequate vitamin D supplementation is essential for MS mothers also during pregnancy and postpartum period.

Mathematical modeling and optimal control of malaria

Malaria continues to infect millions and kill hundreds of thousands of people worldwide each year, despite over a century of research and attempts to control and eliminate this infectious disease. Challenges such as the development and spread of drug resistant malaria parasites, insecticide resistance to mosquitoes, climate change, the presence of individuals with subpatent malaria infections which normally are asymptomatic and behavioral plasticity in the mosquito hinder the prospects of malaria control and elimination. In this thesis, mathematical models of malaria transmission and control that address the role of drug resistance, immunity, iron supplementation and anemia, immigration and visitation, and the presence of asymptomatic carriers in malaria transmission are developed. A within-host mathematical model of severe Plasmodium falciparum malaria is also developed. First, a deterministic mathematical model for transmission of antimalarial drug resistance parasites with superinfection is developed and analyzed. The possibility of increase in the risk of superinfection due to iron supplementation and fortification in malaria endemic areas is discussed. The model results calls upon stakeholders to weigh the pros and cons of iron supplementation to individuals living in malaria endemic regions. Second, a deterministic model of transmission of drug resistant malaria parasites, including the inflow of infective immigrants, is presented and analyzed. The optimal control theory is applied to this model to study the impact of various malaria and vector control strategies, such as screening of immigrants, treatment of drug-sensitive infections, treatment of drug-resistant infections, and the use of insecticide-treated bed nets and indoor spraying of mosquitoes. The results of the model emphasize the importance of using a combination of all four controls tools for effective malaria intervention. Next, a two-age-class mathematical model for malaria transmission with asymptomatic carriers is developed and analyzed. In development of this model, four possible control measures are analyzed: the use of long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic, and screening and treatment of asymptomatic individuals. The numerical results show that a disease-free equilibrium can be attained if all four control measures are used. A common pitfall for most epidemiological models is the absence of real data; model-based conclusions have to be drawn based on uncertain parameter values. In this thesis, an approach to study the robustness of optimal control solutions under such parameter uncertainty is presented. Numerical analysis of the optimal control problem in the presence of parameter uncertainty demonstrate the robustness of the optimal control approach that: when a comprehensive control strategy is used the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the design of cost-effective strategies for disease control with multiple interventions, even under considerable uncertainty of model parameters. Finally, a separate work modeling the within-host Plasmodium falciparum infection in humans is presented. The developed model allows re-infection of already-infected red blood cells. The model hypothesizes that in severe malaria due to parasite quest for survival and rapid multiplication, the Plasmodium falciparum can be absorbed in the already-infected red blood cells which accelerates the rupture rate and consequently cause anemia. Analysis of the model and parameter identifiability using Markov chain Monte Carlo methods is presented.

Supplier segmentation and development in project business

The purpose of this study was to expand the applicability of supplier segmentation and development approaches to the project-driven construction industry. These practices are less exploited and not well documented in this operational environment compared to the process-centric manufacturing industry. At first, portfolio models to supply base segmentation and various supplier development efforts were investigated in literature review. A step-wise framework was structured for the empirical research. The empirical study employed multiple research methods in three case studies in a large Finnish construction company. The first study categorized the construction item classes into the purchasing portfolio and positioned suppliers to the power matrix by investigating buyer-supplier relations. Using statistical tests, the study also identified factors that affect suppliers’ performance. The final case study identified improvement areas of the interface between a main contractor and one if its largest suppliers. The final results indicate that only by assessing the supply base in a holistic manner and the power circumstances in it, buyers comprehend how to best establish appropriate supplier development strategies in the project environment.

Framework for Regional Heating Energy Efficiency Assessment

The aim of this project was to develop general framework for systematic assessment of energy efficiency of heating on regional level in Russia. The framework created during this project includes two main instruments, namely: general regional heating energy efficiency assessment model (REEMod) and general regional heating energy efficiency assessment criteria for housing areas (REECrit). Framework pays extreme attention to realization of energy saving, overall cost efficiency and comfortable indoor climate. Life-cycle ideology was applied during creation of the framework. Application of the framework can provide decision-making process with systematically collected and processed information on current state of areas energy efficiency. Such information will help decision makers to evaluate current situation of the whole energy chain, to compare different development scenarios and to identify the most efficient improvement methods, thus supporting realization of regions efficient energy management. Simultaneous pursuit of energy savings, cost efficiency and indoor air quality can contribute to development of sustainable community. Presented instruments should be continuously developed further as an iterative process based on knew experience, development of technology and overall understanding of energy efficiency issues.

Imaging Neuroinflammation in Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system CNS), where inflammation and neurodegeneration lead to irreversible neuronal damage. In MS, a dysfunctional immune system causes auto‐reactive lymphocytes to migrate into CNS where they initiate an inflammatory cascade leading to focal demyelination, axonal degeneration and neuronal loss. One of the hallmarks of neuronal injury and neuroinflammation is the activation of microglia. Activated microglia are found not only in the focal inflammatory lesions, but also diffusely in the normal‐appearing white matter (NAWM), especially in progressive MS. The purine base, adenosine is a ubiquitous neuromodulator in the CNS and also participates in the regulation of inflammation. The effect of adenosine mediated via adenosine A2A receptors has been linked to microglial activation, whereas modulating A2A receptors may exert neuroprotective effects. In the majority of patients, MS presents with a relapsing disease course, later advancing to a progressive phase characterised by a worsening, irreversible disability. Disease modifying treatments can reduce the severity and progression in relapsing MS, but no efficient treatment exists for progressive MS. The aim of this research was to investigate the prevalence of adenosine A2A receptors and activated microglia in progressive MS by using in vivo positron emission tomography (PET) imaging and [11C]TMSX and [11C](R)‐PK11195 radioligands. Magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) was performed to evaluate structural brain damage. Non‐invasive input function methods were also developed for the analyses of [11C]TMSX PET data. Finally, histopathological correlates of [11C](R)‐PK11195 radioligand binding related to chronic MS lesions were investigated in post‐mortem samples of progressive MS brain using autoradiography and immunohistochemistry. [11C]TMSX binding to A2A receptors was increased in NAWM of secondary progressive MS (SPMS) patients when compared to healthy controls, and this correlated to more severe atrophy in MRI and white matter disintegration (reduced fractional anisotropy, FA) in DTI. The non‐invasive input function methods appeared as feasible options for brain [11C]TMSX images obviating arterial blood sampling. [11C](R)‐PK11195 uptake was increased in the NAWM of SPMS patients when compared to patients with relapsing MS and healthy controls. Higher [11C](R)‐PK11195 binding in NAWM and total perilesional area of T1 hypointense lesions was associated with more severe clinical disability, increased brain atrophy, higher lesion load and reduced FA in NAWM in the MS patients. In autoradiography, increased perilesional [11C](R)‐PK11195 uptake was associated with increased microglial activation identified using immunohistochemistry. In conclusion, brain [11C]TMSX PET imaging holds promise in the evaluation of diffuse neuroinflammation in progressive MS. Being a marker of microglial activation, [11C](R)‐ PK11195 PET imaging could possibly be used as a surrogate biomarker in the evaluation of the neuroinflammatory burden and clinical disease severity in progressive MS.

Phenotypic and genotypic variant of MDR-Mycobacterium tuberculosis multiple isolates in the same tuberculosis episode, Rio de Janeiro, Brazil

Assuming that the IS6110-restriction fragment length polymorphism (RFLP) changes at a constant rate of 3.2 years, this methodology was applied to demonstrate, for the first time, variant patterns of Mycobacterium tuberculosis (MTB) in multiple isolates obtained at short time intervals from sputum and blood of an HIV+ patient with multiple admissions to the Emergency Room and to the multidrug-resistant tuberculosis (MDR-TB) Reference Center of a secondary-care hospital in Rio de Janeiro, Brazil. In sputum, the IS6110-RFLP appeared in isolates with two variant patterns with 10 and 13 IS6110 copies. However, blood presented only the pattern corresponding to 10 copies, suggesting compartmentalization. With regard to the exact match of 10 of 13 bands, this may be a subpopulation with the same clonal origin and this may be related to the IS6110 transposition. A susceptibility test demonstrated an MDR profile (INH R, RIF R, SM R, and EMB R), with the sputum isolate also exhibiting EMB S (R = resistant; S = sensitive). A gene mutation confirmed resistance only to streptomycin. There was agreement between the results of the phenotypic test and the clinical response to MDR-TB treatment, suggesting serious implications with regard to treatment administration based exclusively on molecular methods, and calling attention to the fact that more effective control strategies against the emergence of MDR strains must be implemented by the TB control program to prevent transmission of MDR-MTB strains at health facilities in areas highly endemic for TB.

The role of collective intelligence in crowdsourcing innovation

Social insects are known for their ability to display swarm intelligence, where the cognitive capabilities of the collective surpass those of the individuals forming it by orders of magnitude. The rise of crowdsourcing in recent years has sparked speculation as to whether something similar might be taking place on crowdsourcing sites, where hundreds or thousands of people interact with each other. The phenomenon has been dubbed collective intelligence. This thesis focuses on exploring the role of collective intelligence in crowdsourcing innovations. The task is approached through three research questions: 1) what is collective intelligence; 2) how is collective intelligence manifested in websites involved in crowdsourcing innovation; and 3) how important is collective intelligence for the functioning of the crowdsourcing sites. After developing a theoretical framework for collective intelligence, a multiple case study is conducted using an ethnographic data collection approach for the most part. A variety of qualitative, quantitative and simulation modelling methods are used to analyse the complex phenomenon from several theoretical viewpoints or ‘lenses’. Two possible manifestations of collective intelligence are identified: discussion, typical of web forums; and the wisdom of crowds in evaluating crowd submissions to websites. However, neither of these appears to be specific to crowdsourcing or critical for the functioning of the sites. Collective intelligence appears to play only a minor role in the cases investigated here. In addition, this thesis shows that feedback loops, which are found in all the cases investigated, reduce the accuracy of the crowd’s evaluations when a count of votes is used for aggregation.