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Scientific and public interest in epidemiology and mathematical modelling of disease spread has increased significantly due to the current COVID-19 pandemic. Political action is influenced by forecasts and evaluations of such models and the whole society is affected by the corresponding countermeasures for containment. But how are these models structured?
Which methods can be used to apply them to the respective regions, based on real data sets? These questions are certainly not new. Mathematical modelling in epidemiology using differential equations has been researched for quite some time now and can be carried out mainly by means of numerical computer simulations. These models are constantly being refinded and adapted to corresponding diseases. However, it should be noted that the more complex a model is, the more unknown parameters are included. A meaningful data adaptation thus becomes very diffcult. The goal of this thesis is to design applicable models using the examples of COVID-19 and dengue, to adapt them adequately to real data sets and thus to perform numerical simulations. For this purpose, first the mathematical foundations are presented and a theoretical outline of ordinary differential equations and optimization is provided. The parameter estimations shall be performed by means of adjoint functions. This procedure represents a combination of static and dynamical optimization. The objective function corresponds to a least squares method with L2 norm which depends on the searched parameters. This objective function is coupled to constraints in the form of ordinary differential equations and numerically minimized, using Pontryagin's maximum (minimum) principle and optimal control theory. In the case of dengue, due to the transmission path via mosquitoes, a model reduction of an SIRUV model to an SIR model with time-dependent transmission rate is performed by means of time-scale separation. The SIRUV model includes uninfected (U) and infected (V ) mosquito compartments in addition to the susceptible (S), infected (I) and recovered (R) human compartments, known from the SIR model. The unknwon parameters of the reduced SIR model are estimated using data sets from Colombo (Sri Lanka) and Jakarta (Indonesia). Based on this parameter estimation the predictive power of the model is checked and evaluated. In the case of Jakarta, the model is additionally provided with a mobility component between the individual city districts, based on commuter data. The transmission rates of the SIR models are also dependent on meteorological data as correlations between these and dengue outbreaks have been demonstrated in previous data analyses. For the modelling of COVID-19 we use several SEIRD models which in comparison to the SIR model also take into account the latency period and the number of deaths via exposed (E) and deaths (D) compartments. Based on these models a parameter estimation with adjoint functions is performed for the location Germany. This is possible because since the beginning of the pandemic, the cumulative number of infected persons and deaths
are published daily by Johns Hopkins University and the Robert-Koch-Institute. Here, a SEIRD model with a time delay regarding the deaths proves to be particularly suitable. In the next step, this model is used to compare the parameter estimation via adjoint functions with a Metropolis algorithm. Analytical effort, accuracy and calculation speed are taken into account. In all data fittings, one parameter each is determined to assess the estimated number of unreported cases.
Mathematical models of species dispersal and the resilience of metapopulations against habitat loss
(2021)
Habitat loss and fragmentation due to climate and land-use change are among the biggest threats to biodiversity, as the survival of species relies on suitable habitat area and the possibility to disperse between different patches of habitat. To predict and mitigate the effects of habitat loss, a better understanding of species dispersal is needed. Graph theory provides powerful tools to model metapopulations in changing landscapes with the help of habitat networks, where nodes represent habitat patches and links indicate the possible dispersal pathways between patches.
This thesis adapts tools from graph theory and optimisation to study species dispersal on habitat networks as well as the structure of habitat networks and the effects of habitat loss. In chapter 1, I will give an introduction to the thesis and the different topics presented in this thesis. Chapter 2 will then give a brief summary of tools used in the thesis.
In chapter 3, I present our model on possible range shifts for a generic species. Based on a graph-based dispersal model for a generic aquatic invertebrate with a terrestrial life stage, we developed an optimisation model that models dispersal directed to predefined habitat patches and yields a minimum time until these patches are colonised with respect to the given landscape structure and species dispersal capabilities. We created a time-expanded network based on the original habitat network and solved a mixed integer program to obtain the minimum colonisation time. The results provide maximum possible range shifts, and can be used to estimate how fast newly formed habitat patches can be colonised. Although being specific for this simulation model, the general idea of deriving a surrogate can in principle be adapted to other simulation models.
Next, in chapter 4, I present our model to evaluate the robustness of metapopulations. Based on a variety of habitat networks and different generic species characterised by their dispersal traits and habitat demands, we modeled the permanent loss of habitat patches and subsequent metapopulation dynamics. The results show that species with short dispersal ranges and high local-extinction risks are particularly vulnerable to the loss of habitat across all types of networks. On this basis, we then investigated how well different graph-theoretic metrics of habitat networks can serve as indicators of metapopulation robustness against habitat loss. We identified the clustering coefficient of a network as the only good proxy for metapopulation robustness across all types of species, networks, and habitat loss scenarios.
Finally, in chapter 5, I utilise the results obtained in chapter 4 to identify the areas in a network that should be improved in terms of restoration to maximise the metapopulation robustness under limited resources. More specifically, we exploit our findings that a network’s clustering coefficient is a good indicator for metapopulation robustness and develop two heuristics, a Greedy algorithm and a deducted Lazy Greedy algorithm, that aim at maximising the clustering coefficient of a network. Both algorithms can be applied to any network and are not specific to habitat networks only.
In chapter 6, I will summarize the main findings of this thesis, discuss their limitations and give an outlook of future research topics.
Overall this thesis develops frameworks to study the behaviour of habitat networks and introduces mathematical tools to ecology and thus narrows the gap between mathematics and ecology. While all models in this thesis were developed with a focus on aquatic invertebrates, they can easily be adapted to other metapopulations.
Previous research concerned with early science education revealed that guided play can support young children’s knowledge acquisition. However, the questions whether guided play maintains other important prerequisites such as children’s science self-concept and how guided play should be implemented remain unanswered. The present dissertation encompasses three research articles that investigated 5- to 6-year-old children’s science knowledge, science theories, and science self-concept in the stability domain and their relation to interindividual prerequisites. Moreover, the articles examined whether children’s science knowledge, science theories, and science self-concept can be supported by different play forms, i.e., guided play with material and verbal scaffolds, guided play with material scaffolds, and free play. The general introduction of the present dissertation first highlights children’s cognitive development, their science self-concept, and interindividual prerequisites, i.e., fluid and crystallised intelligence, mental rotation ability, and interest in block play. These prerequisites are applied to possible ways of supporting children during play. The first article focused on the measurement of 5-to-6-year-old children’s stability knowledge and its relation to interindividual prerequisites. Results suggested that children’s stability knowledge could be measured reliably and validly, and was related to their fluid and crystallised intelligence. The second article was concerned with the development of children’s intuitive stability theories over three points of measurement and the effects of guided and free play, children’s prior theories as well as their intelligence on these intuitive theories. Results implied that guided play with material and verbal scaffolds supported children’s stability theories more than the other two play forms, i.e., guided play with material scaffolds and free play. Moreover, consistency of children’s prior theories, their fluid and crystallised intelligence were related to children’s theory adaptation after the intervention. The third article focused on the effect of the playful interventions on children’s stability knowledge and science self-concept over three points of measurement. Furthermore, the reciprocal effects between knowledge acquisition and science self-concept were investigated. Results implied that guided play supported knowledge acquisition and maintained children’s science self-concept. Free play did not support children’s stability knowledge and decreased children’s science self-concept. No evidence for reciprocal effects between children’s stability knowledge and their science self-concept was found. Last, in a general discussion, the findings of the three articles are combined and reflected amidst children’s cognitive development. Summarising, the present dissertation shows that children’s science knowledge, science theories, and science self-concept can be supported through guided play that considers children’s cognitive development.
Ray tracing acceleration through dedicated data structures has long been an important topic in computer graphics. In general, two different approaches are proposed: spatial and directional acceleration structures. The thesis at hand presents an innovative combined approach of these two areas, which enables a further acceleration of the tracing process of rays. State-of-the-art spatial data structures are used as base structures and enhanced by precomputed directional visibility information based on a sophisticated abstraction concept of shafts within an original structure, the Line Space.
In the course of the work, novel approaches for the precomputed visibility information are proposed: a binary value that indicates whether a shaft is empty or non-empty as well as a single candidate approximating the actual surface as a representative candidate. It is shown how the binary value is used in a simple but effective empty space skipping technique, which allows a performance gain in ray tracing of up to 40% compared to the pure base data structure, regardless of the spatial structure that is actually used. In addition, it is shown that this binary visibility information provides a fast technique for calculating soft shadows and ambient occlusion based on blocker approximations. Although the results contain a certain inaccuracy error, which is also presented and discussed, it is shown that a further tracing acceleration of up to 300% compared to the base structure is achieved. As an extension of this approach, the representative candidate precomputation is demonstrated, which is used to accelerate the indirect lighting computation, resulting in a significant performance gain at the expense of image errors. Finally, techniques based on two-stage structures and a usage heuristic are proposed and evaluated. These reduce memory consumption and approximation errors while maintaining the performance gain and also enabling further possibilities with object instancing and rigid transformations.
All performance and memory values as well as the approximation errors are measured, presented and discussed. Overall, the Line Space is shown to result in a considerate improvement in ray tracing performance at the cost of higher memory consumption and possible approximation errors. The presented findings thus demonstrate the capability of the combined approach and enable further possibilities for future work.
The sediments of surface waters are temporary or final depository of many chemical compounds, including trace metals and metalloids (metal(loid)s) from natural and anthropogenic sources. Whether they act as a source or sink of metal(loid)s depends strongly on the dynamics of the biogeochemical processes that take place at the sediment-water interface (SWI). Important information on biogeochemical processes as well as on the exposure, the fate and the transport of pollutants at the SWI can be obtained by determining chemical concentration profiles in the sediment pore water. A major challenge is to conduct experiments with a spatial resolution, which allows to adequately record existing gradients and to log all the parameters needed, to describe and better understand the complex processes at the SWIs. At the same time, it is from major importance to prevent the formation of any artifacts during sampling, which may occur due to the labile nature of the SWIs and the very steep biogeochemical gradients.
In this context, in the first part of this work, a system was developed and tested that enables the automated, minimal invasive sampling of sediment pore water of undisturbed or manipulated sediments while simultaneously recording parameters such as redox potential, oxygen content and pH value. In an incubation experiment the impact of acidification and mechanical disturbance (re-suspension) on the mobility of 13 metal(loid)s was investigated using a triple quadrupole inductively coupled plasma-mass spectrometry (ICP-QQQ-MS) multi-element approach. Most metals were released as consequence of sulfide weathering whereas mechanical disturbance had a major impact on the mobility of the oxide forming elements As, Mo, Sb, U and V. Additionally, options were demonstrated to address with the system the size fractionation of metal(loid)s in pore water samples and the speciation of As(III/V) and Sb(III/V).
In the second part, the focus, with a similar experimental design, was placed on the processes leading to the release of metal(loid)s. For this purpose, two incubation experiments with different oxygen supply were conducted in parallel. For the first time the nonmetals carbon, phosphorus and sulfur were analyzed simultaneous to 13 metal(loid)s in sediment pore water by ICP-QQQ-MS. Throughout the experiment metal(loid) size fractionation was monitored. It was confirmed that resuspension promotes the mobility of metalloids such as As, Sb and V, while the release of most metals was largely attributed to pyrite weathering. The colloidal (0.45-16 μm) contribution in terms of mobilization was only relevant for a few elements.
Finally, the sampling system was used as part of a new approach to sediment risk assessment. Undisturbed sediment cores from differently contaminated positions in the Trave estuary were examined, considering 16 metal(loid)s, the non-metals C, P and S and the ions NH4+, PO43- and SO42-. By the first in-depth comparison with in-situ dialysis-based pore water sampling the ability of the suction-based approach to represent field conditions was proven. The pore water studies together with supplementing resuspension experiments in bio-geochemical microcosms and sequential extraction identified the most “pristine” sediment of the study area as posing the greatest risk of metal(loid) release. However, the potentially released amounts per kg of sediment are only a few parts per thousand of the average daily loads of the Trave river.
Enterprise Collaboration Systems (ECS) have become substantial for computer-mediated communication and collaboration among employees in organisations. As ECS combine features from social media and traditional groupware, a growing number of organisations implement ECS to facilitate collaboration among employees. Consequently, ECS form the core of the digital workplace. Thus, the activity logs of ECS are particularly valuable since they provide a unique opportunity for observing and analysing collaboration in the digital workplace.
Evidence from academia and practice demonstrates that there is no standardised approach for the analysis of ECS logs and that practitioners struggle with various barriers. Because current ECS analytics tools only provide basic features, academics and practitioners cannot leverage the full potential of the activity logs. As ECS activity logs are a valuable source for understanding collaboration in the digital workplace, new methods and metrics for their analysis are required. This dissertation develops Social Collaboration Analytics (SCA) as a method for measuring and analysing collaboration activities in ECS. To address the existing limitations in academia and practice and to contribute a method and structures for applying SCA in practice, this dissertation aims to answer two main research questions:
1. What are the current practices for measuring collaboration activities in Enterprise Collaboration Systems?
2. How can Social Collaboration Analytics be implemented in practice?
By answering the research questions, this dissertation seeks to (1) establish a broad thematic understanding of the research field of SCA and (2) to develop SCA as a structured method for analysing ac-tivity logs of ECS. As part of the first research question, this dissertation documents the status quo of SCA in the academic literature and practice. By answering the second research question, this dissertation contributes the SCA framework (SCAF), which guides the practical application of SCA. SCAF is the main contribution of this dissertation. The framework was developed based on findings from an analysis of 86 SCA studies, results from 6 focus groups and results from a survey among 27 ECS user companies. The phases of SCAF were derived from a comparison of established process models for data mining and business intelligence. The eight phases of the framework contain detailed descriptions, working steps, and guiding questions, which provide a step by step guide for the application of SCA in practice. Thus, academics and practitioners can benefit from using the framework.
The constant evaluation of the research outcomes in focus groups ensures both rigour and relevance. This dissertation employs a qualitative-dominant mixed-methods approach. As part of the university-industry collaboration initiative IndustryConnect, this research has access to more than 30 leading ECS user companies. Being built on a key case study and a series of advanced focus groups with representatives of user companies, this dissertation can draw from unique insights from practice as well as rich data with a longitudinal perspective.
We are living in a world where environmental crises come to a head. To curb aggravation of these problems, a socio-ecological transformation within society is needed, going along with human behavior change. How to encourage such behavior changes on an individual level is the core issue of this dissertation. It takes a closer look at the role of individuals as consumers resulting in purchase decisions with more or less harmful impact on the environment. By using the example of plastic pollution, it takes up a current environmental problem and focuses on an understudied behavioral response to this problem, namely reduction behavior. More concrete, this dissertation examines which psychological factors can encourage the mitigation of plastic packaging consumption. Plastic packaging accounts for the biggest amount of current plastic production and is associated with products of daily relevance. Despite growing awareness of plastic pollution in society, behavioral responses do not follow accordingly and plastic consumption is still very high. As habits are often a pitfall when implementing more resource-saving behavior, this dissertation further examines if periods of discontinuity can open a ’window of opportunity’ to break old habits and facilitate behavior change. Four manuscripts approach this matter from the gross to the subtle. Starting with a literature review, a summary of 187 studies addresses the topic of plastic pollution and human behavior from a societal-scientific perspective. Based on this, a cross-sectional study (N = 648) examines the deter-minants of plastic-free behavior intentions in the private-sphere and public-sphere by structural equation modeling. Two experimental studies in pre-post design build upon this, by integrating the determinants in intervention studies. In addition, it was evaluated if the intervention presented during Lent (N = 140) or an action month of ‘Plastic Free July’ (N = 366) can create a ‘window of opportunity’ to mitigate plastic packaging consumption. The literature review emphasized the need for research on behavioral solutions to reduce plastic consumption. The empirical results revealed moral and control beliefs to be the main determinants of reduction behavior. Furthermore, the time point of an intervention influenced the likelihood to try out the new behavior. The studies gave first evidence that a ‘window of opportunity’ can facilitate change towards pro-environmental behavior within the application field of plastic consumption. Theoretical and practical implications of creating the right opportunity for individuals to contribute to a socio-ecological transformation are finally discussed.
Graph-based data formats are flexible in representing data. In particular semantic data models, where the schema is part of the data, gained traction and commercial success in recent years. Semantic data models are also the basis for the Semantic Web - a Web of data governed by open standards in which computer programs can freely access the provided data. This thesis is concerned with the correctness of programs that access semantic data. While the flexibility of semantic data models is one of their biggest strengths, it can easily lead to programmers accidentally not accounting for unintuitive edge cases. Often, such exceptions surface during program execution as run-time errors or unintended side-effects. Depending on the exact condition, a program may run for a long time before the error occurs and the program crashes.
This thesis defines type systems that can detect and avoid such run-time errors based on schema languages available for the Semantic Web. In particular, this thesis uses the Web Ontology Language (OWL) and its theoretic underpinnings, i.e., description logics, as well as the Shapes Constraint Language (SHACL) to define type systems that provide type-safe data access to semantic data graphs. Providing a safe type system is an established methodology for proving the absence of run-time errors in programs without requiring execution. Both schema languages are based on possible world semantics but differ in the treatment of incomplete knowledge. While OWL allows for modelling incomplete knowledge through an open-world semantics, SHACL relies on a fixed domain and closed-world semantics. We provide the formal underpinnings for type systems based on each of the two schema languages. In particular, we base our notion of types on sets of values which allows us to specify a subtype relation based on subset semantics. In case of description logics, subsumption is a routine problem. For
the type system based on SHACL, we are able to translate it into a description
logic subsumption problem.
Water scarcity is already an omnipresent problem in many parts of the world, especially in sub-Saharan Africa. The dry years 2018 and 2019 showed that also in Germany water resources are finite. Projections and predictions for the next decades indicate that renewal rates of existing water resources will decline due the growing influence of climate change, but that water extraction rates will increase due to population growth. It is therefore important to find alternative and sustainable methods to make optimal use of the water resources currently available. For this reason, the reuse of treated wastewater for irrigation and recharge purposes has become one focus of scientific research in this field. However, it must be taken into account that wastewater contains so-called micropollutants, i.e., substances of anthropogenic origin. These are, e.g., pharmaceuticals, pesticides and industrial chemicals which enter the wastewater, but also metabolites that are formed in the human body from pharmaceuticals or personal care products. Through the treatment in wastewater treatment plants (WWTPs) as well as through chemical, biological and physical processes in the soil passage during the reuse of water, these micropollutants are transformed to new substances, known as transformation products (TPs), which further broaden the number of contaminants that can be detected within the whole water cycle.
Despite the fact that the presence of human metabolites and environmental TPs in untreated and treated wastewater has been known for a many years, they are rarely included in common routine analysis methods. Therefore, a first goal of this thesis was the development of an analysis method based on liquid chromatography - tandem mass spectrometry (LC-MS/MS) that contains a broad spectrum of frequently detected micropollutants including their known metabolites and TPs. The developed multi-residue analysis method contained a total of 80 precursor micropollutants and 74 metabolites and TPs of different substance classes. The method was validated for the analysis of different water matrices (WWTP influent and effluent, surface water and groundwater from a bank filtration site). The influence of the MS parameters on the quality of the analysis data was studied. Despite the high number of analytes, a sufficient number of datapoints per peak was maintained, ensuring a high sensitivity and precision as well as a good recovery for all matrices. The selection of the analytes proved to be relevant as 95% of the selected micropollutants were detected in at least one sample. Several micropollutants were quantified that were not in the focus of other current multi-residue analysis methods (e.g. oxypurinol). The relevance of including metabolites and TPs was demonstrated by the frequent detection of, e.g., clopidogrel acid and valsartan acid at higher concentrations than their precursors, the latter even being detected in samples of bank filtrate water.
By the integration of metabolites, which are produced in the body by biological processes, and biological and chemical TPs, the multi-residue analysis method is also suitable for elucidating degradation mechanisms in treatment systems for water reuse that, e.g., use a soil passage for further treatment. In the second part of the thesis, samples from two treatment systems based on natural processes were analysed: a pilot-scale above-ground sequential biofiltration system (SBF) and a full-scale soil aquifer treatment (SAT) site. In the SBF system mainly biological degradation was observed, which was clearly demonstrated by the detection of biological TPs after the treatment. The efficiency of the degradation was improved by an intermediate aeration, which created oxic conditions in the upper layer of the following soil passage. In the SAT system a combination of biodegradation and sorption processes occurred. By the different behaviour of some biodegradable micropollutants compared to the SBF system, the influence of redox conditions and microbial community was observed. An advantage of the SAT system over the SBF system was found in the sorption capacity of the natural soil. Especially positively charged micropollutants showed attenuation due to ionic interactions with negatively charged soil particles. Based on the physicochemical properties at ambient pH, the degree of removal in the investigated systems and the occurrence in the source water, a selection of process-based indicator substances was proposed.
Within the first two parts of this thesis a micropollutant was frequently detected at elevated concentrations in WWTPs effluents, which was not previously in the focus of environmental research: the antidiabetic drug sitagliptin (STG). STG showed low degradability in biological systems and thus it was investigated to what extend chemical treatment by ozonation can ensure attenuation of it. STG contains an aliphatic primary amine as the principal point of attack for the ozone molecule. There is only limited information about the behaviour of this functional group during ozonation and thus, STG served as an example for other micropollutants containing aliphatic primary amines. A pH-dependent degradation kinetic was observed due to the protonation of the primary amine at lower pH values. At pH values in the range 6 - 8, which is typical for the environment and in WWTPs, STG showed degradation kinetics in the range of 103 M-1s-1 and thus belongs to the group of readily degradable substances. However, complete degradation can only be expected at significantly higher pH values (> 9). The transformation of the primary amine moiety into a nitro group was observed as the major degradation mechanism for STG during ozonation. Other mechanisms involved the formation of a diketone, bond breakages and the formation of trifluoroacetic acid (TFA). Investigations at a pilot-scale ozonation plant using the effluent of a biological degradation of a municipal WWTP as source water confirmed the results of the laboratory studies: STG could not be removed completely even at high ozone doses and the nitro compound was formed as the main TP and remained stable during further ozonation and subsequent biological treatment. It can therefore be assumed that under realistic conditions both a residual concentration of STG and the formed main TP as well as other stable TPs such as TFA can be detected in the effluents of a WWTP consisting of conventional biological treatment followed by ozonation and subsequent biological polishing steps.
Successful export sectors in manufacturing and agribusiness are important drivers of structural transformation in Sub-Sahara African countries. Backed by industrial policies and active state involvement, a small number of successful productive export sectors has emerged in Sub-Saharan Africa. This thesis asks the question: How do politics shape the promotion of export-driven industrialisation and firm-level upgrading in Sub-Saharan Africa? It exemplifies this question with an in-depth, qualitative study of the cashew processing industry in Mozambique in the period from 1991 until 2019. Mozambique used to be one of the world’s largest producers and processors of cashew nuts in the 1960s and 1970s. At the end of the 20th century, the cashew processing industry broke down completely but has re-emerged as one of the country’s few successful agro-processing exports.
The thesis draws on theoretical approaches from the fields of political science, notably the political settlements framework, global value chain analysis and the research on technological capabilities to explore why the Mozambican Government supported the cashew processing industry and how Mozambican cashew processors acquired the technological capabilities needed to access the global cashew value chain and to upgrade. It makes an important theoretical contribution by linking the political settlements framework and the literature on upgrading in global value chains to study how politics shaped productive sector promotion and upgrading in the Mozambican cashew processing industry. The findings of the thesis are based on extensive primary data, including 58 expert interviews and 10 firm surveys, that was collected in Mozambique in 2018 as well as a broad base of secondary literature.
The thesis argues that the Mozambican Government supported the cashew processing industry because it became important for the Government’s political survival. Promoting the cashew sector formed part of an electoral strategy for the ruling FRELIMO coalition and a means to keep FRELIMO factions united by offering economic opportunities to key constituencies. In 1999, it adopted a protectionist cashew law that created strong incentives for cashew processing in Mozambique. This not only facilitated the re-emergence of the cashew processing industry after its breakdown. The law and the active involvement of the National Cashew Institute (INCAJU) also affected the governance of the local cashew value chain, the creation of backward linkages, and the upgrading paths of cashew processors. The findings of the thesis suggest that the cashew law reduced the pressure on the cashew processing industry to upgrade. The law further created opportunities for formal and informal rent creation for members of the political elite and lower level FRELIMO officials that prevented a far-reaching reform of the law. The thesis shows that international buyers do not promote upgrading among Sub-Sahara African firms in global value chains with market-based or modular governance. Moreover, firms that operate in countries where industrial policies are not enforced effectively cannot draw on the support of government institutions to enhance their capabilities and to upgrade. Firms therefore mainly depended on costly learning channels at firm level, e.g. learning by doing or hiring skilled labour, and/or on technical assistance from donors to build the technological capabilities needed to access global value chains and to remain competitive.
The findings of the thesis suggest that researchers, governments, development practitioners and consultants need to rethink their understanding of upgrading in GVCs in four ways. First, they need to move away from understanding upgrading in terms of moving towards more complex, higher value-added activities in GVCs (functional upgrading). Instead, it is important to consider the potential of other, more realistic types of upgrading for firms in low-income countries, such reducing risks by diversifying suppliers and buyers or increasing rewards by making production processes more efficient. Second, they need to replace an overly positive view on upgrading that neglects possible side-effects at sector and/or country level. Third, GVC participation on its own does not promote upgrading among local supplier firms in Sub-Saharan Africa. The interests of lead firms and Sub-Sahara African supplier firms may not be aligned or even conflicting. Targeted industrial policies and the creation of institutions that effectively promote capability building among firms therefore become even more important. Finally, upgrading needs to be understood as a process that is not only shaped by interactions between firms, but also by local domestic politics.
The findings of the thesis are highly relevant for scholars from the fields of political science, development studies, and economics. Its practical implications and tools, e.g. a technological capabilities matrix for the cashew industry, are of interest for development practitioners, members of public institutions in Sub-Sahara African countries, local entrepreneurs, and representatives of local business associations that are involved in promoting export sectors and upgrading among local firms.