R&D and private investment: How to conserve indigenous fruit biodiversity of Southern Africa

Indigenous fruits contribute widely to rural incomes in Southern Africa but their availability is declining. A domestication program aims to increase farm-household income and conserve biodiversity through farmer-led tree planting. Planting domesticated indigenous fruit trees is an uncertain, irreversible but flexible investment. Our analysis applies the real option approach using contingent claims analysis, which allows solving the discounting problem. The article analyses (1) to what level fruit collection cost and/or (2) the necessary technical change, i.e. breeding progress, have to rise in order to render tree planting economical, using data from income portfolios of rural households in Zimbabwe. Results currently show that collecting indigenous fruits is more profitable than planting the trees. A combination of technical change and decrease in resource abundance can provide incentives for farmer-led planting of domesticated trees and biodiversity conservation. However, breeding progress must be significant for investment in tree planting to be economically attractive. --indigenous fruits,real option,technology adoption,uncertainty,ex ante impact assessment,Zimbabwe

Design flexibility in complex engineering systems under multiple uncertainties

Master'sMASTER OF ENGINEERIN

Quantitative and Qualitative Models for Managing Risk Interdependencies in Supply Chain

The interdependent nature of supply chain elements and events requires risk systems must be assessed as an interrelated framework to optimize their management and integrate effectively with other decision-making tools in uncertain environments. This research shows a synthesis and analysis of the main qualitative/quantitative methods that have been used in the literature considering the treatment of event dependencies in supply chain risk management in the period 2003– 2018. The results revealed that the integration with disruption analysis tools and artificial intelligence methods are the most common types adopted, with increasing trend and effectiveness of Bayesian and fuzzy theory approache

Robust adaptation decision-making under uncertainty: Real Options Analysis for water storage

Planning for climate change adaptation is challenging due to the inherent uncertainty associated with future climate changes. Although we have a range of climate projections, even these cannot provide a definitive picture of the future, with little certainty regarding the timing, magnitude and location of change. As a result there is increasing interest in approaches that can accommodate uncertainty better. A range of approaches exist and are being developed across several disciplines. Each has advantages and disadvantages and is suited for different types of decisions. In this study we focus on one of these approaches, Real Options Analysis (ROA), and chose water storage for irrigation as an example to demonstrate its use in uncertain futures

Best Practices and Methodological Guidelines for Conducting Gas Risk Assessments

The EC Regulation concerning measures to safeguard security of gas supply (EC/994/2010) requires member states to make a full assessment of the risks affecting the security of gas supply. According to Article 9, this risk assessment must: (a) use the infrastructure and supply standards (articles 6 and 8); (b) take into account all relevant national and regional circumstances; (c) run various disruption scenarios; (d) identify the interaction and correlation of risks with other Member States. (e) take into account the maximal interconnection capacity of each border entry and exit point. The objective of this report is to provide guidance and advice for performing risk assessments. It will do so by first providing a literature review, and then by proposing a basic structure for undertaking a gas security risk assessment, in accordance with best practices and standard procedures found in risk management.JRC.F.3-Energy securit

Automatic generation of high-throughput systolic tree-based solvers for modern FPGAs

Tree-based models are a class of numerical methods widely used in financial option pricing, which have a computational complexity that is quadratic with respect to the solution accuracy. Previous research has employed reconfigurable computing with small degrees of parallelism to provide faster hardware solutions compared with general-purpose processing software designs. However, due to the nature of their vector hardware architectures, they cannot scale their compute resources efficiently, leaving them with pricing latency figures which are quadratic with respect to the problem size, and hence to the solution accuracy. Also, their solutions are not productive as they require hardware engineering effort, and can only solve one type of tree problems, known as the standard American option. This thesis presents a novel methodology in the form of a high-level design framework which can capture any common tree-based problem, and automatically generates high-throughput field-programmable gate array (FPGA) solvers based on proposed scalable hardware architectures. The thesis has made three main contributions. First, systolic architectures were proposed for solving binomial and trinomial trees, which due to their custom systolic data-movement mechanisms, can scale their compute resources efficiently to provide linear latency scaling for medium-size trees and improved quadratic latency scaling for large trees. Using the proposed systolic architectures, throughput speed-ups of up to 5.6X and 12X were achieved for modern FPGAs, compared to previous vector designs, for medium and large trees, respectively. Second, a productive high-level design framework was proposed, that can capture any common binomial and trinomial tree problem, and a methodology was suggested to generate high-throughput systolic solvers with custom data precision, where the methodology requires no hardware design effort from the end user. Third, a fully-automated tool-chain methodology was proposed that, compared to previous tree-based solvers, improves user productivity by removing the manual engineering effort of applying the design framework to option pricing problems. Using the productive design framework, high-throughput systolic FPGA solvers have been automatically generated from simple end-user C descriptions for several tree problems, such as American, Bermudan, and barrier options.Open Acces

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Investment and Time to Plan: A Comparison of Structures vs. Equipment in a Panel of Italian Firms

“Time to build” models of investment expenditures play an important role in many traditional and modern theories of the business cycle, especially for explaining the dynamic propagation of shocks. We estimate the structural parameters of a time-to-build model using firm-level investment data on equipment and structures. For equipment expenditures, we find no evidence of time-to-build effects beyond one period. For structures, by contrast, there is clear evidence of time to build in the range of 2-3 years. The contrast between equipment and structures is intuitively reasonable and consistent with previous results. The estimates for structures also indicate that initial-period expenditures are low, and increase as projects near completion. These results provide empirical support for including “time to plan” effects for investment in structures. More generally, these results suggest a potential source of specification error for Q models of investment and production-based asset pricing models that ignore the time required to plan, build and install new capital.Investment expenditures, Panel data, Italian firms, Time to build