Browsing by Subject "Agent-based modeling"

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Agent-based simulation modeling for analysis and support of rural producer organizations in agriculture
(2014) Latynskiy, Evgeny; Berger, Thomas
Development of smallholder agriculture is widely recognized as an important pathway to poverty reduction in rural areas, particularly in Sub-Saharan Africa. Many researchers propose collective action of smallholder farmers by means of rural producer organizations (RPO) as a promising opportunity to improve commercialization and market access of small farms, which in turn will result in improvement of rural livelihoods. However, little is known about the determinants of RPO success. Currently, there is a broad demand for detailed analyses of RPO performance and for ex-ante assessments of the developmental interventions and policies of RPO support. This thesis focuses on the provision of high-resolution quantitative data for the design of such interventions using a case study of coffee producers in the lake-shore Uganda and their RPO. This work demonstrates the effective ways to increase farmers’ welfare through the network of RPO and analyzes the associated risks and opportunities. This work applies agent-based computer simulation to analyze the RPO. Designed virtual simulation experiments assess the broad portfolio of development interventions and economic scenarios that are challenging to investigate by means of real-world empirical research. The agent-based nature of the model allows for a holistic integration of several modeling concepts in the developed model application. This leads to the inclusion into the model of a number of important aspects of the bio-economic system of coffee production in Uganda. The first aspect is the heterogeneity among farming households, reflected by differences in natural conditions, resource endowments, production and market constraints, time and consumption preferences. The second aspect is the inseparability of decisions that are taken on the farm (i.e. investment, production, consumption and marketing) from one another. The third aspect is human-environment interaction cycles and the dynamics of the bio-economic system, including interactions across levels of hierarchy (here: individual farmers and RPO). The constructed model is parameterized, calibrated and validated using the empirical data from project and country-level surveys. The set-up of the model and the results of simulation experiments are further complemented by (i) a detailed review of relevant literature, (ii) community-based participatory research with members of RPO and (iii) interviews with key informants. Results of simulation experiments indicate that RPO activities can cause significant increases in members’ sales revenues and consequently can improve their household incomes. The posvitive impacts of RPO can be amplified through external assistance. Recommended RPO-level interventions include (i) on-the-spot payments for RPO members’ transactions and (ii) support for group certification. Both are expected to have high cost efficiency and a low risk of failure. In addition, results of this thesis suggest that improvement of agricultural productivity through the provision of quality planting material and the promotion of good agricultural practices is likely to be highly beneficial for the rural households. In order to stream the related development policies to smallholder farmers it is recommended to use RPO networks. Findings of the participatory research in Ugandan RPO indicate that the establishment of transparent rules of reception of RPO services and allocation of earned benefits, together with frequent and formal reporting of RPO administration might increase members’ cooperation within an RPO. This thesis also shows the vulnerability of coffee producing households and their RPO to the risks imposed by the volatility of agricultural prices. The role of development policy is, therefore, to provide price risk insurance for smallholder farmers and to facilitate the formation of accurate price expectations. However, viable and sustainable models of smallholder risk insurance are yet to be found.
Assessing alternative options to improve farming systems and to promote the adoption of low-carbon agriculture in Mato Grosso, Brazil
(2018) Carauta, Marcelo; Berger, Thomas
Currently, our society faces a significant challenge to eradicate hunger and poverty while preserving natural resources and reducing greenhouse gas (GHG) emissions. In this context, Brazil plays an important role since it is one of the most significant players in global food production and hosts a variety of ecosystems and a significant share of the Earths biodiversity. The federal state of Mato Grosso (MT) is located at the most dynamic agricultural frontier in the Cerrado-Amazon transition zone and leads the national production of grain, fiber, and meat. The need to balance agricultural production and environmental protection shifted the focus of Brazilian land-use policy toward sustainable agriculture. The federal government pledged to reduce its GHG emissions and implemented policies to enforce it. Brazils low-carbon agricultural plan offers credit with low-interest rate to farmers who want to implement sustainable agriculture practices. These include the restoration of degraded pasture, adoption of integrated systems, no-till agriculture, biological nitrogen fixation, commercial forests, treatment of animal wastes, and climate change adaptation. The present thesis contributed to the CARBIOCIAL project (“Carbon-optimized land management strategies for southern Amazonia”), a German-Brazilian cooperation to investigate viable carbon-optimized land management strategies maintaining ecosystem services under changing climate conditions in the Southern Amazon. In this context, this thesis examines options to improve farming systems in MT and evaluates policy measures that could promote the adoption of low-carbon agricultural systems. The work is divided into three parts: The first part is subdivided into three chapters (chapters 1, 2 and 3) and offers an overview on land use change in Brazil and explores land use decisions of farmers in MT, where highly dynamic double-crop systems currently prevail. The second part is subdivided into two chapters (chapters 4 and 5) and is dedicated to evaluating alternative options to improve farming systems in MT. The third part is subdivided into three chapters (chapters 6, 7 and 8) and investigates factors that may influence farmers to adopt IAPS, evaluates policy measures to promote the adoption of low-carbon agricultural systems, and provides a detailed quantification of individual GHG emissions of a large variety of agricultural practices and the aggregate emissions resulting from their current use in MT. To this end, this thesis develops an Integrated Assessment (IA) approach that simulates farm-level decision-making and agricultural land use change. It introduces a novel approach to evaluate the full distribution of GHG emissions related to the agricultural land-use change in MT. Our IA approach integrates three software packages: MPMAS (Mathematical Programming-based Multi-Agent Systems), MONICA (Model for Nitrogen and Carbon in Agro-ecosystems) and CANDY (Carbon and Nitrogen Dynamics). Data to parameterize the model was gathered from several sources, such as field experiments, statistical offices, farm level surveys from private consultancies, life-cycle inventory databases, extension services, expert interviews, and literature. This thesis presents the first extensive study on crop yield response in MT by simulating yields in response to different climatic conditions, soil types, sowing dates, crop rotation schemes, fertilization amounts, and macro-regions. The simulation results show that biophysical constraints still play a crucial role on yield gaps in MT whereas socio-economic constraints have a slight yield-increasing effect. This thesis further examines alternative ways to improve the farming systems in MT by investigating the role of sunflower adoption in increasing farm income. We have found a substantial potential for sunflower cultivation in MT with positive impacts on both farm and regional level. Additionally, we identified bottlenecks for sunflower diffusion such as the distance from farm gate to processing facility. Regarding Brazilian agricultural policy, we have found that the Brazilian low-carbon agricultural program contributed to the adoption of integrated systems. However, we observed different adoption rates through macro-regions and types of integrated systems. Furthermore, our simulations additionally show that the ABC program also contributed to the adoption of less GHG-emitting practices, but its performance is subjected to agent expectations on prices and yields
R&D and knowledge dynamics in university-industry relationships in biotech and pharmaceuticals : an agent-based model
(2011) Pyka, Andreas; Scholz, Ramon; Triulzi, Giorgio
In the last two decades, University-Industry Relationships have played an outstanding role in shaping innovation activities in Biotechnology and Pharmaceuticals. Despite the growing importance and the considerable scope of these relationships, there still is an intensive and open debate on their short and long term effects on the research system in life sciences. So far, the extensive literature on this topic has not been able to provide a widely accepted answer. This work introduces a new way to analyse University-Industry Relationships (UIRs) which makes use of an agent-based simulation model. With the help of simulation experiments and the comparison of different scenario results, new insights on the effects of these relationships on the innovativeness of the research system can be gained. In particular, focusing on knowledge interactions among heterogeneous actors, we show that: (i) universities tend to shift from a basic to an applied research orientation as a consequence of relationships with industry, (ii) universities? innovative capabilities benefit from industry financial resources but not so much from cognitive resources of the companies, (iii) biotech companies? innovative capabilities largely benefit from the knowledge interaction with universities and (iv) adequate policies in terms of public basic research funding can contrast the negative effects of UIRs on university research orientation.
Simulation of the sustainability of farming systems in Northern Thailand
(2008) Potchanasin, Chakrit; Zeddies, Jürgen
Introduction Due to an increase in environmental problems and resource degradation, economic development should be pursued with consideration of environmental functions and the supply and quality of natural resources. Monitoring and assessment of whether the development approaches a sustainable path are required to provide information for policy development. This becomes increasingly important ? especially for marginal areas where the environment and natural resources are sensitive. The study area is located in the mountainous area of Northern Thailand with abundant natural resources and a healthy ecological environment. However, population growth, land limitation, and external factors ? such as market forces ? are inducing change and pressure on resource utilization. The resources are intensively used and farming systems are changing to more commercial practices. Therefore, the region?s long term sustainability needs investigation. Objectives This study aims at assessing the sustainability of the farming systems in the study area under the sustainability concept, farming systems approach and Multi-Agent Systems (MAS) approach. The first objective of this study is to describe the characteristics of the farming systems in the study area. The second objective is to develop and use a MAS model to evaluate sustainability of the study area. The last objective is to use the model to present sustainability of farming systems under different scenarios based on changes of significant factors and policy intervention. In addition, the ability of the systems to cope with and recover themselves from these changes is examined. Methodology The sustainability of the farming systems in the study area was assessed through defined indicators representing three conditions: the economic, social and environmental condition. The indicators were defined based on the framework of indicator determination to serve the objectives and methodology of this study. The selected indicators for this study are: household income, net farm income, household capital, household saving, food security, top-soil erosion and fallow period. For these indicators the following sustainability classes were defined: Sustained (S), Conditional sustained (C), and Non-sustained (N) class. Evaluation of sustainability was carried out at two levels: the household and the village level. At the household level the sustainability situation was evaluated based on the individual farm household performance corresponding to each indicator. The sustainability at village level was assessed through the Sustainability index (SI) when single indicators are considered and the Performance index (PI) in which a group of indicators is regarded. The dynamics of the sustainability situation at household and village level were extrapolated over 15 years (2003 ? 2017) in order to examine the sustainability of the study area?s farming systems. The MAS model was developed and named CatchScapeFS. The model structure relies on descriptions of the farming systems in the study area. The MAS approach was applied in order to capture the complexity and extrapolate the long-term sustainability situation in the study area. The model composes of two components: a biophysical and a socioeconomic component. The biophysical component is based on the CatchScape3 model. It consists of biophysical models: a hydrological model, a crop model, a water balance model and a soil erosion model, which are embedded in the landscape model of the study area (represented in spatial grid cells as plots of one rai or 0.16 ha). The socioeconomic component is composed of farm household agents and other social elements. The farm household samples were classified based on the similarity of characteristics and behaviour into the market, subsistence, and partnership oriented group. The Monte Carlo technique was applied to generate farm agents out of the existing farm household samples. The CatchScapeFS model was designed according to the object-oriented modelling approach. The CORMAS platform was selected as a capable tool to facilitate modelling and simulation. During a simulation time step covering 10 days, activities in six principal phases including activities in eight phases of farm agent household activities are executed. The model was validated and tested for its stability. Validation was conducted by social validation and statistic data comparison validation. The results of the model validation and stability test showed the reliability of using the model to serve the study objectives. Main results Sustainability of study area at the household level The results show unsustainability over time in the study area. The number of households in the Sustained class (S) decreases whereas the number in the Non-sustained (N) and Conditional sustained class (C) tend to increase. For the economic condition, unsustained aspects occurred because of rising private household expenditure and decreasing capital products on the farm. For the social condition, the results show an increase of the households? rice deficit and rice acquisition in the long run which enhances the area?s unsustainability. For the environmental condition, erosion and shortening fallow aspects induce the area?s unsustainability. The area?s erosion is severe and increases over time. For the fallow aspect, the average fallow period is shortening because of intensive land use in order to produce for consumption ? which potentially induces land degradation in the long run. Sustainability of the study area at village level Similar to the results at household level, the findings show that farming systems in the study area are not sustainable. Unsustainability was observed by a declining Performance index (PI) and declining Sustainability indexes (SIs) of all indicators in the long term. By considering PI values with the trends, the area?s sustainability in economic condition is better than the social and especially environmental condition. This can be explained by relative high SI values for the economic indicators compared to the SIs of the social and environmental indicators. By considering all SIs and their dynamic trend, sustainability issues can be ranked to determine the sustainability issues which need to be improved. Food security is the most unsustained issue followed by the issues of household saving, household capital, top-soil erosion, household income, fallow period, and net farm income respectively. Scenario analysis The scenarios were the implementation of a policy to improve sustainability and occurrence of unexpected events through changes of biophysical and economic factors. The scenario of the sustainability improving policy is defined as introduction of a high yield variety of upland rice and maize including introduction of mango to the households who currently only produce annual crops. Unexpected events due to the change of biophysical factors were simulated with a drought and rain increasing scenario. A decreasing crop price scenario represented an unexpected event due to the change of an economic factor. Implementation of proposed sustainability improvement policy The results show that the sustainability in the study area is obviously improved; represented by an increase of the PI value with a positive trend over time. In addition, the SIs of many indicators increase in this scenario, except the SI of household saving, which was rather constant. The PI of economic indicators improves with a higher number of households in the sustainable class when considering the household income, net farm income and household capital indicators. For the social condition, PI and SI values of food security increase because of a reduced rice deficit. For the environmental condition, the PI value of the environmental indicators increases because of a reduction of soil erosion and a longer fallow periods. It can be concluded that this scenario provides a policy option which potentially leads to an improvement of the sustainability situation in the study area. Drought scenario The results show that the study area was still unsustainable similar to the baseline scenario. However, the results show a slightly better PI during drought with a higher value and a slower decrease over time. These are the effects of the trade-offs between the indicators. The top-soil erosion indicator (influenced by decreasing rain) becomes better. This positive effect compensates for the negative effects regarding household savings, food security and fallow period indicators ? which all declined. In addition, the simulation results presented the adaptation and reaction of farm agents to drought. Drought is perceived and causes a delay in planting to avoid damage. This induced a variation of the planted area. However, the variation becomes lower because of adaptation as the farm households learn from their experiences. During drought, an increase in the rice and maize deficiency occurred. The average amount of borrowed rice increased over time and the rice acquisition of the farm agents is performed by borrowing from the village rice bank and neighbours In addition, the farm agents acquire maize by collecting wild vegetables to feed their animals. Furthermore, the results indicate the ability of the farm households to cope with and to recover to some extent from a drought. Rain increasing scenario In this scenario, the study area was still unsustainable, similar to the baseline. However, for this scenario, the top-soil erosion is worse because of the increasing rainfall. The PI of economic indicators slightly increased in the first year with increasing rain because of the rising income from livestock production. However, this was caused by random effects influencing the model?s initial stage. For the social condition, there are only small random changes compared to the baseline scenario. For the environmental condition, the PI and SIs of environmental indicators become worse due to an increase of top-soil erosion. Price decreasing scenario The results show that the area?s sustainability is worse compared to the baseline. A reduction of the crop price directly affects household income and cash ? which consequently generates a cash deficit problem. However, due to the area characteristics and household behaviour, there is no effect on resource use because prices do not influence the farm agents? decision making. The PI of this scenario declines faster than in the baseline. This was affected by the decrease of the SIs of the economic indicators which decreased during the periods of the price fall. The households are confronted with a decline in cash which results in a deficiency of cash. Cash acquisition of the households is performed by selling livestock and borrowing from the village fund and neighbours. For the social and environmental condition, there are only small changes due to random effects. Policy recommendations Based on the study results, policies to improve sustainability of the study area farming systems are recommended. Firstly, to improve the area?s sustainability, the introduction of high yield variety of upland rice and maize with conservation practices as well as the introduction of mango to the farm households who currently produce only annual crops is recommended. Secondly, diverting research efforts to develop cash crop alternatives is required in order to improve household cash income. Thirdly, the promotion and support for raising livestock and off-farm activities, such as weaving and the development of tourism, should be performed in order to increase household cash income. Fourthly, awareness raising measures for stakeholders concerning environmental and resource protection have to be executed and achieved. For this, the CatchScapeFS model can be used as a tool to promote a common view between stakeholders. Fifthly, the introduction of birth control in this area is also necessary. Simultaneously, an understanding of households? regarding the effects of population growth should be created in order to obtain the villagers? cooperation without cultural conflicts. Recommendations for further research Guidelines for further studies and applications are recommended. Firstly, development of the model to be more realistic could be undertaken by representing more details of the systems, for example, introducing a nutrient soil dynamic model. However, this should be based on the considered research question (s) and should consider both the marginal benefits and marginal costs of development. Secondly, application of the CatchScapeFS model to other study areas would need to consider the compatibility of the model components and structure of the characteristics in the new study area. In addition, if applied to new areas the indicators to represent sustainability of the study area should be revised. Thirdly, applications following this study framework can be extended to different sustainability approaches ? such as sustainable rural livelihood or sustainable land management. However, the compatibility and relationship of the indicators with the study framework should be considered. Fourthly, a framework through application of object-oriented modelling is recommended as an alternative for further studies to investigate the consequences of policy interventions. However, resource requirements for any research application should be taken into account. Fifthly, the CatchScapeFS model can be used as a tool to test and monitor the effects of potential policies which can be implemented into Bor Krai village. Also, the model can be used as a tool to promote a common view of the overall village systems as well as to support collective decision making managed by stakeholders of the systems. Recommendations for newcomers to MAS application research Suggestions from the present study for newcomers have been proposed. The first recommendation to deal with the MAS application research is that newcomers have to learn the computer programs and programming. Learning programming with advice of programming experts at the beginning period and attention of newcomers to apply the code in different circumstances are highly recommended. Secondly, development of an integrated model in multidisciplinary research requires learning the academic knowledge from other disciplines. Therefore, determining the study objectives within the possible extent, introducing assumptions to simplify the additional disciplines, and consulting specialists to learn the required knowledge within a short time frame are suggested. Lastly, the development of integrated model requires a huge amount of data. Therefore, in the case which required data cannot be obtained, introducing assumptions based on theory and literature is recommended.
Smallholder adaptation through agroforestry : agent-based simulation of climate and price variability in Ethiopia
(2021) Yismaw, Habtamu Demilew; Berger, Thomas
Climate variability has been posing formidable policy challenges in Ethiopia by deteriorating rural livelihoods. Climate variability-induced shocks have a profound impact on smallholder farmers welfare both in the short run via reducing production and increasing output prices and in the long run by depleting productive farm assets and leading them to a poverty trap. However, the impact of shocks on smallholders welfare depends on their choice of adaptation and coping measures to deal with them, which are in turn farmer-specific. This thesis applied an integrated econometric analysis and farm-level simulations to assess smallholder farmers adaptation and coping measures under extreme climate and price variability in Ethiopia. The thesis provides a special focus on the role of investment in small-scale agroforestry to curb the adverse effects of shocks. Drought, hailstorms, pests, and crop diseases are identified as the most frequent and intense climate variability-induced shocks in Ethiopia. Smallholders dominant adaptation and coping measures for each shock are identified using logistic principal component analysis (LPCA). The application of dimensionality reduction of binary data using LPCA to select smallholder farmers dominant adaptation and coping measures is unique to this study. Results show that planting stress-resistant crops and varieties, early planting, increasing seed rate, and soil and water conservation practices are the dominant ex-ante adaptation measures. Whereas selling livestock, selling assets, reducing consumption, borrowing and replanting are the dominant ex-post coping measures. In what follows, household-specific drivers of smallholder farmers choice of adaptation and coping measures are disentangled using multivariate probit regression (MVP) for each shock. Gender, knowledge and experience, participation in rural institutions, social networks, resource endowments, and their shock experience and expectation are the significant drivers of farmers choices of ex-ante adaptation and ex-post coping measures. Results suggest that smallholder farmers choice of measures to deal with climate variability-induced shocks is highly distinctive and depends on their socioeconomic settings, experience and knowledge, and their interactions with the environment. Correlation analysis both in LPCA and MVP results show that most of the measures farmers choose are complementary, which implies that no single measure is robust and works best for all farmers. Farmers invest more on ex-post measures than ex-ante measures. Those who invest on tree perennials as ex-ante drought measures are less likely to use severe measures such as selling livestock and other assets in the aftershock. The econometric analysis in the first part of the thesis establishes a descriptive analysis of smallholder farmers behavioral responses to climate variability-induced covariate shocks. This captures the behavior of farmers in the status quo. However, it does not tell us much about how farmers would behave in different future circumstances, especially with extreme climate and price variability. This requires a prescriptive and descriptive approach with a detailed investigation of farmers behavior down to the plot level. To achieve this objective, the second part of the thesis applies household-level micro-simulation to analyze ex-ante planning and ex-post responses to future climate and price variability, focusing on the role of smallholder farmers’ investment in woodlot perennials to their livelihoods. The agent-based simulation package - Mathematical Programming-based Multi-Agent Systems (MPMAS) is used for this purpose to capture investment, production, and consumption decisions at the farm household level. A farm decision model representing smallholder farmers in the Upper Nile Basin in Ethiopia is developed accordingly. The farmers in the area are known for their integrated crop-livestock system, and a unique Acacia Dicurrens based emph{taungya} system in the country. This thesis shows a first-time use of an agent-based modeling approach representing the acacia-based emph{taungya} system in the Upper Nile Basin in Ethiopia, which is another contribution of this study. The farm decision model is validated using empirical data and interactive sessions with experts. Another methodological novelty of this study is developing and using interactive web applications to validate the farm decision model with experts remotely due to the COVID-19 pandemic. Interactive model validation is not new in agent-based modeling using MPMAS. However, the web-based R Shiny app and an integrated web-based expert survey questionnaire app is an original contribution of this study. The study also uses Zoom virtual conferencing to record all interactive validation sessions with experts. Two simulation experiments were designed to quantify the effects of shocks and price variability on agents livelihoods. The High-Performance Computing platform in Baden Wurttemberg (bwHPC) is used to run simulation experiments for this study. The first simulation experiment aims at measuring the effects of shocks on agents livelihoods and the effectiveness of ex-ante planning to curb the adverse effects of these shocks. The application of model features on agents ex-ante preparation for the possible occurrence of shocks within the farm decision model is a new development in this study. Accordingly, the frequent and intense crop and tree diseases in the area - potato late blight and acacia seedling disease are introduced as shocks in the model. Simulation results show that both potato late blight and acacia seedling disease reduce annual per capita discretionary income significantly and forcing some poor resource agents to fail to fulfill minimum non-food expenditure. The trade-off in agents land-use decisions between trees and crops by agents shows that they prefer to plant trees than crops as an ex-ante planning strategy for shocks. The second simulation experiment aims at examining the effect of long-run expected price changes, mainly on land-use decisions of agents in the model. Four future price scenarios are designed, and the results are compared with the baseline to examine the effect on agents discretionary income and land-use decisions. The purpose of this simulation experiment is to see if there is a deviance from croplands to woodlots and vise versa based on long-run changes in expected prices. Simulation results show that agents are highly responsive to changes in expected prices in the long run, except for the expected price of bamboo. In cases where there is a decrease in the expected price of acacia charcoal or an increase in the expected price of crops or both, results show that agents will go back to potatoes and wheat-dominated production systems instead of the acacia-dominated production system . This study suggests that supporting farmer adaptation to climate variability-induced shocks should focus on policy interventions related to crop and land management activities. Policy interventions should also focus on building the household asset base to boost farmers coping ability and resilience to shocks. Moreover, results suggest that robust climate adaptation and mitigation interventions should take the heterogeneity of farmers into account. Furthermore, both econometrics and farm-level simulation analyses show the importance of planting trees as a crucial adaptation strategy. Findings suggest that investment in woodlot perennials is an essential adaptation strategy for smallholder farmers with scarce resource settings and should be promoted and scaled to a broader area in the region.
United we stand, divided we fall : essays on knowledge and its diffusion in innovation networks
(2019) Bogner, Kristina; Pyka, Andreas
Knowledge is a key resource, allowing firms to innovate and keep pace with national and international competitors. Therefore, the management of this resource within firms and innovation networks is of utmost importance. As the collection and generation of (new) knowledge gives such competitive advantage, there is a strong interest of firms and policy makers on how to foster the creation and diffusion of new knowledge. Within four studies, this doctoral thesis aims at extending the literature on knowledge diffusion performance by focussing on the effect of different network structures on diffusion performance as well as on knowledge types besides mere techno-economic knowledge. Study 1 analyses the effect of different structural disparities on knowledge diffusion by using an agent-based simulation model. It focuses on how different network structures influence knowledge diffusion performance. This study especially emphasizes the effect of an asymmetric degree distribution on knowledge diffusion performance. Study 1 complements previous research on knowledge diffusion by showing that (i) besides or even instead of the average path length and the average clustering coefficient, the (symmetry of) degree distribution influences knowledge diffusion. In addition, (ii) especially small, inadequately embedded agents seem to be a bottleneck for knowledge diffusion in this setting, and iii) the identified rather negative network structures on the macro level seem to result from the myopic linking strategies of the actors at the micro level, indicating a trade-off between ‘optimal’ structures at the network and at the actor level. Study 2 uses an agent-based simulation model to analyse the effect of different network properties on knowledge diffusion performance. In contrast to study 1, this study analyses this relationship in a setting in which knowledge is diffusing freely throughout an empirical formal R&D network as well as through four benchmark networks. In addition, the concept of cognitive distance and differences in learning between agents in the network are taken into account. Study 2 complements study 1 and further previous research on knowledge diffusion by showing that (i) the (asymmetry of) degree distribution and the distribution of links between actors in the network indeed influence knowledge diffusion performance to a large extend. In addition, (ii) the extent to which a skewed degree distribution dominates other network characteristics varies depending on the respective cognitive distance between agents. Study 3 analyses how so called dedicated knowledge can contribute to the transformation towards a sustainable, knowledge-based Bioeconomy. In this study, the concept of dedicated knowledge, i.e. besides mere-techno economic knowledge also systems knowledge, normative knowledge and transformative knowledge, is first introduced. Moreover, the characteristics of dedicated knowledge which are influencing knowledge diffusion performance are analysed and evaluated according to their importance and potential role for knowledge diffusion. In addition, it is analysed if and how current Bioeconomy innovation policies actually account for dedicated knowledge. This study complements previous research by taking a strong focus on different types of knowledge besides techno-economic knowledge (often overemphasized in policy approaches). It shows, that i) different types of knowledge necessarily need to be taken into account when creating policies for knowledge creation and diffusion, and ii) that especially systems knowledge so far has been insufficiently considered by current Bioeconomy policy approaches. Study 4 analyses the effect of different structural disparities on knowledge diffusion by deducing from theoretical considerations on network structures and diffusion performance. The study tries to answer whether the artificially generated network structures seem favourable for the diffusion of both mere techno-economic knowledge as well as dedicated knowledge. Study 4 especially complements previous research on knowledge diffusion by (i) analysing an empirical network over a long period of time, and (ii) by indicating a potential trade-off between structures favourable for the diffusion of mere techno-economic knowledge and those for the diffusion of other types of dedicated knowledge. Summing up, it is impossible to make general statements that allow for valid policy recommendations on network structures ‘optimal’ for knowledge diffusion. Without knowing the exact structures and context, politicians will hardly be able to influence network structures. Especially if we call for knowledge enabling transformations as the transformation towards a sustainable knowledge-based Bioeconomy, creating structures for the creation and diffusion of this knowledge is quite challenging and needs for the inclusion and close cooperation of many different actors on multiple levels.