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While the global production of wind energy is increasing, there exists a significant gap in the academic and practice literature regarding the analysis of wind turbine accidents. Our paper presents the results obtained from the analysis of 240 wind turbine accidents from around the world. The main focus of our paper is revealing the associations between several factors and deaths and injuries in wind turbine accidents. Specifically, the associations of death and injuries with the stage of the wind turbine's life cycle (transportation, construction, operation, and maintenance) and the main cause factor categories (human, system/equipment, and nature) were studied. To this end, we conducted a detailed investigation that integrates exploratory and statistical data analysis and data mining methods. The paper presents a multitude of insights regarding the accidents and discusses implications for wind turbine manufacturers, engineering and insurance companies, and government organizations.

In a single period framework, we develop a supply portfolio risk assessment tool for raw material procurement in the presence of supply risk (owing to contract breaches), demand risk and the spot price risk. Contract breaches are operational risk events that are classified under the "Clients, Products and Business Practices" category of the Basel II framework. We allow for the negative financial impact of intentional long-term fixed price contract breaches to be mitigated by using the spot market. The manufacturer uses the spot market to procure their need in the presence of a contract breach as well as to handle the shortfall/excess in customer demand. We use the CreditRisk + framework, well known in finance literature, to extend the single supplier model to a portfolio of suppliers. This extension enables us to obtain, in the context of supply risk, the entire loss distribution at the portfolio level. In particular, akin to the value-at-risk statistic in finance, one can easily obtain a simple yet effective quantile measure of supply risk, coined as supply-at-risk, for a portfolio of long-term fixed price supply contracts. 1 Furthermore, 29% of the respondents counted the commodity shortages and price fluctuations as an important supply chain risk.

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A copula-based simulation model for supply portfolio risk in the presence of dependent breaches of contracts is introduced in this paper. We demonstrate our method for a supply-chain contract portfolio of commodity metals traded at the London Metal Exchange (LME). The analysis of spot price data on six LME commodity metals leads us to use a t-copula dependence structure with t-marginals and generalized hyperbolic marginals for the log returns. We also provide efficient simulation algorithms using importance sampling for the normal and tcopula dependence structure to quantify risk measures, supply-at-risk and conditional supply-at-risk. Numerical examples on a portfolio of six commodity metals demonstrate that our proposed method succeeds in decreasing the variance of the simulations. A numerical sensitivity analysis for the choice of the copula function is also provided. To the best of our knowledge, this is the first paper proposing efficient simulation algorithms on a supply-chain contract portfolio that has a copula-based dependence structure with generalized hyperbolic marginals.