Property Loss Estimation for Wind and Earthquake Perils

This article describes the development of a generic loss assessment methodology, which is applicable to earthquake and windstorm perils worldwide. The latest information regarding hazard estimation is first integrated with the parameters that best describe the intensity of the action of both windstorms and earthquakes on building structures, for events with defined average return periods or recurrence intervals. The subsequent evaluation of building vulnerability (damageability) under the action of both earthquake and windstorm loadings utilizes information on damage and loss from past events, along with an assessment of the key building properties (including age and quality of design and construction), to assess information about the ability of buildings to withstand such loadings and hence to assign a building type to the particular risk or portfolio of risks. This predicted damage information is then translated into risk-specific mathematical vulnerability functions, which enable numerical evaluation of the probability of building damage arising at various defined levels. By assigning cost factors to the defined damage levels, the associated computation of total loss at a given level of hazard may be achieved. This developed methodology is universal in the sense that it may be applied successfully to buildings situated in a variety of earthquake and windstorm environments, ranging from very low to extreme levels of hazard. As a loss prediction tool, it enables accurate estimation of losses from potential scenario events linked to defined return periods and, hence, can greatly assist risk assessment and planning.     

Innovation Management as a Post-Modern Phenomenon: The Outsourcing of Pharmaceutical R&D

The institutionalization of R&D by large, modern organizations is regarded as one of the most significant social and economic factors of the twentieth century. In recent years post-modern organizations have begun to replace bureaucratic control with market control. This approach is particularly attractive in the case of R&D employees who have been relatively successful in resisting direct managerial control. Government statistics are used to demonstrate that external R&D increased from 5% to 16% of internal R&D expenditure between 1989 and 1995. This trend is examined in the context of consolidation within the UK pharmaceutical industry, which has considerable implications for the sustainability of high-technology industry in the UK.     

Capturing hearts and minds: The influence of relational identification with the leader on followers' mobilization and cardiovascular reactivity

The influence of relational identification (RI) on leadership processes and the effects of social identity leadership on followers' responses to stress have received scant theoretical and research attention. The present research advances theoretical understanding by testing the assertion that high RI with the leader drives follower mobilization of effort and psychophysiological responses to stress. Two experimental scenario studies (Study 1 and Study 2) support the hypothesis that being led by an individual with whom followers perceive high RI increases follower intentional mobilization. Study 2 additionally showed that high (vs. low) RI increases follower resource appraisals and cognitive task performance. A laboratory experiment (Study 3) assessing cardiovascular (CV) reactivity showed that, compared to neutral (i.e., non-affiliated) leadership, being led by an individual with whom participants felt low RI elicited a maladaptive (i.e., threat) response to a pressurized task. In addition, relative to the low RI and neutral conditions, high RI with the leader did not engender greater challenge or threat reactivity. In conclusion, advancing social identity leadership and challenge and threat theory, findings suggest that leaders should be mindful of the deleterious effects (i.e., reduced mobilization and greater threat state) of low RI to optimize follower mobilization of effort and psychophysiological responses to stress.     

Risks of Mortality and Morbidity from Worldwide Terrorism: 1968–2004

Worldwide data on terrorist incidents between 1968 and 2004 gathered by the RAND Corporation and the Oklahoma City National Memorial Institute for the Prevention of Terrorism (MIPT) were assessed for patterns and trends in morbidity/mortality. Adjusted data analyzed involve a total of 19,828 events, 7,401 "adverse" events (each causing >or= 1 victim), and 86,568 "casualties" (injuries), of which 25,408 were fatal. Most terror-related adverse events, casualties, and deaths involved bombs and guns. Weapon-specific patterns and terror-related risk levels in Israel (IS) have differed markedly from those of all other regions combined (OR). IS had a fatal fraction of casualties about half that of OR, but has experienced relatively constant lifetime terror-related casualty risks on the order of 0.5%--a level 2 to 3 orders of magnitude more than those experienced in OR that increased approximately 100-fold over the same period. Individual event fatality has increased steadily, the median increasing from 14% to 50%. Lorenz curves obtained indicate substantial dispersion among victim/event rates: about half of all victims were caused by the top 2.5% (or 10%) of harm-ranked events in OR (or IS). Extreme values of victim/event rates were approximated fairly well by generalized Pareto models (typically used to fit to data on forest fires, sea levels, earthquakes, etc.). These results were in turn used to forecast maximum OR- and IS-specific victims/event rates through 2080, illustrating empirically-based methods that could be applied to improve strategies to assess, prevent, and manage terror-related risks and consequences.     

An interactive three-stage model for mutual funds portfolio selection

The aim of this work is to be a useful instrument for helping finance practitioners on the selection of suitable mutual fund portfolios. The portfolio selection problem is characterized by imprecision and/or vagueness inherent in the required data and more generally, in the context where investors have to make decisions. In order to mitigate these problems, a three stage model has been proposed based on a multi-index model and considering several market scenarios described in an imprecise way by an expert. The proposed fuzzy model allows the Decision Maker to select, by means of an outranking method, a suitable portfolio taking into account the uncertainty related to the market scenarios and the imprecision and/or vagueness associated with the model data.     

The State of the Field in UK Management Research: Reflections of the Research Assessment Exercise (RAE) Panel

This paper reviews the state of the field of the sub-disciplines within UK management research, based upon the submissions of 94 UK higher education institutions to the Business and Management Studies Panel in the UK's 2001 Research Assessment Exercise (RAE). It offers observations on the UK model of the assessment of quality in, and funding of, research conducted in publicly funded higher education institutions.     

Data envelopment analysis in the presence of measurement error: case study from the National Database of Nursing Quality Indicators® (NDNQI®)

Data envelopment analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency [B. Hollingsworth, The measurement of efficiency and productivity of health care delivery. Health Economics 17(10) (2008), pp. 1107–1128], but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized [B.J. Gajewski, R. Lee, M. Bott, U. Piamjariyakul, and R.L. Taunton, On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process. Journal of Applied Statistics 36(9) (2009), pp. 933–944; J. Ruggiero, Data envelopment analysis with stochastic data. Journal of the Operational Research Society 55 (2004), pp. 1008–1012]. We propose to address measurement error systematically using a Bayesian method (Bayesian DEA). We will apply Bayesian DEA to data from the National Database of Nursing Quality Indicators^® to estimate nursing units’ efficiency. Several external reliability studies inform the posterior distribution of the measurement error on the DEA variables. We will discuss the case of generalizing the approach to situations where an external reliability study is not feasible.     

Statistical approaches for conducting network meta-analysis in drug development

We introduce health technology assessment and evidence synthesis briefly, and then concentrate on the statistical approaches used for conducting network meta-analysis (NMA) in the development and approval of new health technologies. NMA is an extension of standard meta-analysis where indirect as well as direct information is combined and can be seen as similar to the analysis of incomplete-block designs. We illustrate it with an example involving three treatments, using fixed-effects and random-effects models, and using frequentist and Bayesian approaches. As most statisticians in the pharmaceutical industry are familiar with SAS? software for analyzing clinical trials, we provide example code for each of the methods we illustrate. One issue that has been overlooked in the literature is the choice of constraints applied to random effects, and we show how this affects the estimates and standard errors and propose a symmetric set of constraints that is equivalent to most current practice. Finally, we discuss the role of statisticians in planning and carrying out NMAs and the strategy for dealing with important issues such as heterogeneity.